WO2025123698A1

WO2025123698A1 - Ai/ml enabled timing advance prediction

Info

Publication number: WO2025123698A1
Application number: PCT/CN2024/108898
Authority: WO
Inventors: Mingzeng Dai; Congchi ZHANG; Lianhai WU; Le Yan
Original assignee: Lenovo Beijing Ltd
Current assignee: Lenovo Beijing Ltd
Priority date: 2024-07-31
Filing date: 2024-07-31
Publication date: 2025-06-19
Anticipated expiration: 2027-01-31

Abstract

Various aspects of the present disclosure relate to AI/ML enabled TA prediction. In one aspect, a network entity obtains historical TA information. In turn, the network entity performs TA prediction to generate predicted TA information for UE based at least on the historical TA information. Then, the network entity transmits the predicted TA information to the UE.

Description

AI/ML ENABLED TIMING ADVANCE PREDICTION

TECHNICAL FIELD

The present disclosure relates to wireless communications, and more specifically to user equipment (UE) , network entities and methods supporting artificial intelligence (AI) or machine learning (ML) enabled timing advance (TA) prediction.

BACKGROUND

A wireless communications system may include one or multiple network communication devices, such as base stations, which may be otherwise known as an eNodeB (eNB) , a next-generation NodeB (gNB) , or other suitable terminology. Each network communication devices, such as a base station may support wireless communications for one or multiple user communication devices, which may be otherwise known as user equipment (UE) , or other suitable terminology. The wireless communications system may support wireless communications with one or multiple user communication devices by utilizing resources of the wireless communication system (e.g., time resources (e.g., symbols, slots, subframes, frames, or the like) or frequency resources (e.g., subcarriers, carriers) . Additionally, the wireless communications system may support wireless communications across various radio access technologies including third generation (3G) radio access technology, fourth generation (4G) radio access technology, fifth generation (5G) radio access technology, among other suitable radio access technologies beyond 5G (e.g., sixth generation (6G) ) .

In a wireless system, it is required to adjust the timing of an uplink frame in order to have alignment with a downlink frame in time domain. TA is a command sent by a base station to a UE to adjust its uplink transmission which means that the UE transmits UL symbols in advance for physical uplink shared channel (PUSCH) , physical uplink control channel (PUCCH) and sounding reference signal (SRS) transmission. The timing advance command (TAC) objective is to align the uplink transmission from all the UEs to the base station. TAC informs the UE the amount of time that it needs to advance the UL transmissions.

A TA value depends on the signal propagation delay from the base station to the UE, i.e. different UEs located at different location will have different TA values. TA will vary frequently, which will cause overhead of signalling to update TA by sending TAC media access control control element (MAC CE) .

The initial TA value relies on a random access procedure which makes the random access procedure is mandatorily performed in most of handover cases, which will cause handover delay.

SUMMARY

The present disclosure relates to UEs, network entities and methods that support AI/ML enabled TA prediction. With the UEs, network entities and methods, overhead caused by sending frequent TA command may be saved.

Some implementations of a network entity described herein may include a processor and a transceiver coupled to the processor, wherein the processor is configured to: obtain historical TA information; perform TA prediction to generate predicted TA information for a UE based at least on the historical TA information; and transmit the predicted TA information via the transceiver to the UE.

In some implementations, the processor is configured to obtain the historical TA information from the UE. In such implementations, the processor is further configured to transmit, via the transceiver to the UE, a first configuration for logging the historical TA information.

In some implementations, the network entity comprises a central unit (CU) and a distributed unit (DU) , and the CU obtains at least part of the historical TA information from the DU. In such implementations, the processor is further configured to transmit, via the transceiver from the CU to the DU, a first configuration for logging the historical TA information.

In some implementations, the network entity comprises a target network entity. In such implementations, the processor is configured to obtain the historical TA information from a source network entity.

In some implementations, the network entity comprises a source network entity. In such implementations, the processor is configured to obtain the historical TA information from a target network entity.

In some implementations, the processor is further configured to: obtain performance feedback of the predicted TA information from the target network entity.

In some implementations, the first configuration indicates at least one of the following: the historical TA information to be logged, a type of logging the historical TA information, at least one condition for reporting the logged historical TA information, an identity of data collection for the TA prediction, or identities of UEs, historical TA information of which is to be logged.

In some implementations, the historical TA information to be logged comprises at least one of the following: a historical TA value that is applied for uplink transmission, a time duration during which the UE applies the historical TA value, a remaining value of a time alignment timer, a location of the UE at the time of logging the historical TA value, measurements information at the time of logging the historical TA value, an identity of a serving cell of the UE at the time of logging the historical TA value, an identity of a beam that is applied by the UE at the time of logging the historical TA value, or time when the historical TA value is logged.

In some implementations, the type of logging the historical TA information comprises one of the following: periodical logging of the historical TA information, or logging the historical TA information based on at least one event.

In some implementations, the first configuration indicates the periodical logging of the historical TA information by indicating at least one of the following: time when the historical TA information starts to be logged, or a cycle of logging the historical TA information.

In some implementations, the at least one event comprises at least one of the following: the first configuration being received, the TA value that the UE is using being adjusted or changed, adjustment or change of the TA value that the UE is using being above a threshold, or a location of the UE where the TA value needs to be logged.

In some implementations, the at least one condition for reporting the logged historical TA information comprises at least one of the following: a first number of the logged historical TA information, a time duration associated with the logged historical TA information, or a request for the logged historical TA information from the network entity.

In some implementations, the predicted TA information comprises at least one of the following: a list of a predicted TA value and information about time when the predicted TA value is to be applied, a list of the predicted TA value and information about a location where the predicted TA value is to be applied, a predicted time alignment timer, or a prediction that a current TA will expire or the current TA will be invalid at first time.

In some implementations, the predicted TA value comprises one of the following: calculated time that is used by the UE to transmit uplink transmission in advance, or an index value indicating adjustment of a current TA value.

In some implementations, the processor is further configured to: transmit, via the transceiver to the UE, at least one condition for applying the predicted TA value.

In some implementations, the at least one condition for applying the predicted TA value comprises at least one of the following: a percentage of running time of a time alignment timer is greater than or equal to a first threshold, or the running time of the time alignment timer is greater than or equal to a second threshold.

In some implementations, the processor is configured to transmit the predicted TA information via a medium access control control element or a radio resource control message.

In some implementations, the processor is further configured to: transmit a first indication via the transceiver to the UE, wherein the first indication indicates whether the UE should apply the predicted TA information.

In some implementations, the processor is further configured to: transmit a second indication via the transceiver to the UE, wherein the second indication indicates the UE to start to apply the predicted TA information.

In some implementations, the processor is further configured to: transmit a third indication via the transceiver to the UE, wherein the third indication indicates the UE to stop applying the predicted TA information.

Some implementations of a UE described herein may include a processor and a transceiver coupled to the processor, wherein the processor is configured to: transmit historical TA information via the transceiver to a network entity; and receive predicted TA information via the transceiver from the network entity.

In some implementations, the processor is further configured to: receive, via the transceiver from the network entity, a first configuration for logging the historical TA information; and log the historical TA information based on the first configuration.

In some implementations, the processor is further configured to: receive, via the transceiver from the network entity, at least one condition for applying the predicted TA value.

In some implementations, the processor is configured to receive the predicted TA information via a medium access control control element or a radio resource control message.

In some implementations, the processor is further configured to: receive a first indication via the transceiver from the network entity, wherein the first indication indicates whether the UE should apply the predicted TA information.

In some implementations, the processor is further configured to: receive a second indication via the transceiver from the network entity, wherein the second indication indicates the UE to start to apply the predicted TA information.

In some implementations, the processor is further configured to: receive a third indication via the transceiver from the network entity, wherein the third indication indicates the UE to stop applying the predicted TA information.

Some implementations of a UE described herein may include a processor and a transceiver coupled to the processor, wherein the processor is configured to: receive a third configuration for TA prediction via the transceiver from a network entity; perform the TA prediction to generate predicted TA information based at least on the third configuration; and apply the predicted TA information.

In some implementations, the third configuration for TA prediction comprises at least one of the following: historical TA information, at least one model that is used for the TA prediction in the UE, at least one condition for starting or stopping the TA prediction in the UE, accuracy of the TA prediction, or a time duration during with a predicted TA value is to be applied.

In some implementations, the processor is further configured to: obtain historical TA information for the TA prediction by logging the historical TA information.

In some implementations, the historical TA information comprises at least one of the following: a historical TA value that is applied for uplink transmission, a time duration during which the UE applies the historical TA value, a location where the UE applies the historical TA value, measurements information when the UE applies the historical TA value, an identity of a serving cell of the UE when the UE applies the historical TA value, or location information about at least one serving transmission reception point (TRP) or a further network entity providing the serving cell.

In some implementations, the at least one condition for starting or stopping the TA prediction in the UE comprises a threshold for change of a path loss between the UE and the network entity.

In some implementations, the processor is further configured to: transmit capability information via the transceiver to the network entity, wherein the capability information indicates that the UE supports AI or ML functionality of the TA prediction or indicates that the UE supports AI/ML enabled TA prediction.

In some implementations, the processor is further configured to: transmit, via the transceiver to the network entity, information about at least one AI or ML model supported by the UE.

In some implementations, the processor is further configured to: receive a fourth configuration for applicability determination via the transceiver from the network entity; and determine whether the TA prediction is applicable for based on the fourth configuration.

In some implementations, the fourth configuration comprises at least one of the following: a location of a serving transmission reception point (TRP) or the network entity, a logical identity indicating the location of the TRP or the network entity, or network conditions.

In some implementations, the processor is further configured to: based on determining that the TA prediction is applicable, transmit a fourth indication via the transceiver to the network entity, wherein the fourth indication indicates the TA prediction is applicable.

In some implementations, the processor is further configured to: receive a fifth indication via the transceiver from the network entity, wherein the fifth indication indicates the UE to perform the TA prediction.

In some implementations, the predicted TA value comprises calculated time that is used by the UE to transmit uplink transmission in advance.

In some implementations, the processor is configured to apply the predicted TA value by: applying the calculated time to transmit the uplink transmission in advance.

In some implementations, the predicted TA value comprises an index value indicating adjustment of a current TA value.

In some implementations, the processor is configured to apply the predicted TA value by: determining, based on the index value, calculated time that is used by the UE to transmit uplink transmission in advance; and applying the calculated time to transmit the uplink transmission in advance.

In some implementations, the processor is configured to apply the predicted TA value as a current TA value. In such implementations, the processor is further configured to: receive, via the transceiver from the network entity, a first index value indicating adjustment of the current TA value; determine a first new TA value based on the current TA value and the first index value; and apply the first new TA value.

In some implementations, the predicted TA value comprises a second index value indicating adjustment of the first new TA value. In such implementations, the processor is further configured to: determine a second new TA value based on the first new TA value and the second index value; and apply the second new TA value.

In some implementations, the predicted TA value comprises a second index value indicating adjustment of the first new TA value. In such implementations, the processor is further configured to: receive, via the transceiver from the network entity, a third index value indicating adjustment of the first new TA value; determine a third new TA value based on the first new TA value and the third index value; and apply the third new TA value.

In some implementations, the processor is configured to apply the predicted TA value as a current TA value. In such implementations, the processor is further configured to: receive, via the transceiver from the network entity, a first index value indicating adjustment of the current TA value; determine a fourth new TA value based on the current TA value and a predicated index value indicating adjustment of the current TA value; and apply the fourth new TA value.

In some implementations, the processor is further configured to: receive, via the transceiver from the network entity, at least one condition for applying the predicted TA information.

In some implementations, the processor is further configured to: transmit the predicted TA information via the transceiver to the network entity.

In some implementations, the processor is further configured to: receive a first indication via the transceiver from the network entity, wherein the first indication indicates whether the UE should apply the predicted TA information. In such implementations, the processor is configured to apply the predicted TA information based on determining that the first indication indicates that the UE should apply the predicted TA information.

In some implementations, the processor is further configured to: receive a second indication via the transceiver from the network entity, wherein the second indication indicates the UE to start to apply the predicted TA information. In such implementations, the processor is configured to apply the predicted TA information based on the second indication.

In some implementations, the processor is further configured to: receive a third indication via the transceiver from the network entity, wherein the third indication indicates the UE to stop applying the predicted TA information; and stop applying the predicted TA information based on the third indication.

In some implementations, the third configuration for TA prediction is used for TA prediction for a neighbour cell.

In some implementations, the third configuration for TA prediction comprises at least one of the following: an identity of the neighbour cell, or location information about at least one serving transmission reception point (TRP) or a further network entity providing the neighbour cell.

In some implementations, the predicted TA information is for a neighbour cell. In such implementations, the processor is further configured to receive a fourth indication via the transceiver from the network entity, the fourth indication indicates one of the following: the predicted TA information is applied in an initial access procedure to the neighbour cell, or the predicted TA information is applied in both the initial access procedure and subsequent uplink transmission in the neighbour cell. In such implementations, the processor is configured to apply the predicted TA information for the neighbour cell based on the fourth indication.

In some implementations, the processor is configured to apply the predicted TA information for the neighbour cell based on the fourth indication by: performing the initial access procedure without initiating a random access procedure.

In some implementations, the processor is configured to apply the predicted TA information for the neighbour cell based on the fourth indication by: applying the predicted TA information for the neighbour cell at the timing of initializing an uplink initial access in the neighbour cell; applying the predicted TA information for the neighbour cell when receiving a handover command; or applying the predicted TA information for the neighbour cell upon conditional handover (CHO) execution initialization.

In some implementations, the processor is further configured to: receive, via the transceiver from the network entity, first historical TA information for training an AI or ML model; log second historical TA information for training the AI or ML model; receive, via the transceiver from the network entity, a receiving time difference between a serving cell and a candidate cell and a TA value for the serving cell; and perform the training of the AI or ML model based on the first historical TA information, the second historical TA information, the receiving time difference and the TA value for the serving cell.

Some implementations of a network entity described herein may include a processor and a transceiver coupled to the processor, wherein the processor is configured to:transmit a third configuration for TA prediction via the transceiver to a UE; and receive uplink transmission based on predicted TA information.

In some implementations, the processor is further configured to: receive capability information via the transceiver from the UE, wherein the capability information indicates that the UE supports AI or ML functionality of the TA prediction or indicates that the UE supports AI/ML enabled TA prediction.

In some implementations, the processor is further configured to: receive, via the transceiver from the UE, information about at least one AI or ML model supported by the UE.

In some implementations, the processor is further configured to: transmit a fourth configuration for applicability determination via the transceiver to the UE.

In some implementations, the processor is further configured to: receive a fourth indication via the transceiver from the UE, wherein the fourth indication indicates the TA prediction is applicable.

In some implementations, the processor is further configured to: transmit a fifth indication via the transceiver to the UE, wherein the fifth indication indicates the UE to perform the TA prediction.

In some implementations, the processor is further configured to: transmit, via the transceiver to the UE, at least one condition for applying the predicted TA information.

In some implementations, the processor is further configured to: receive the predicted TA information via the transceiver from the UE.

In some implementations, the third configuration for TA prediction comprises at least one of the following: an identity of the neighbour cell, or location information about at least one serving TRP or a further network entity providing the neighbour cell.

In some implementations, the predicted TA information is for a neighbour cell. In such implementations, the processor is further configured to transmit a fourth indication via the transceiver to the UE, the fourth indication indicates one of the following: the predicted TA information is applied in an initial access procedure to the neighbour cell, or the predicted TA information is applied in both the initial access procedure and subsequent uplink transmission in the neighbour cell.

In some implementations, the processor is further configured to: transmit, via the transceiver to the UE, first historical TA information for training an AI or ML model.

In some implementations, the network entity comprises a source network entity.

In some implementations, the processor is further configured to: receive a fourth configuration for applicability determination for a neighbour cell via the transceiver from a target network entity providing the neighbour cell; and transmit the fourth configuration via the transceiver to the UE.

In some implementations, the processor is further configured to: receive the predicted TA information for a neighbour cell via the transceiver from the UE; and transmit the predicted TA information for the neighbour cell via the transceiver to a target network entity providing the neighbour cell.

In some implementations, the processor is configured to transmit the predicted TA information by: transmitting the predicted TA information for the neighbour cell in a handover request message.

In some implementations, the processor is further configured to: receive a fourth indication via the transceiver from a target network entity providing a neighbour cell; and transmit the fourth indication via the transceiver to the UE. The fourth indication indicates one of the following: the predicted TA information is applied in an initial access procedure to the neighbour cell, or the predicted TA information is applied in both the initial access procedure and subsequent uplink transmission in the neighbour cell.

In some implementations, the processor is further configured to: receive a fifth indication via the transceiver from a target network entity, wherein the fifth indication indicates the UE to perform the TA prediction; and transmit the fifth indication via the transceiver to the UE.

Some implementations of a method described herein may include: obtaining historical TA information; performing TA prediction to generate predicted TA information for a UE based at least on the historical TA information; and transmitting the predicted TA information to the UE.

Some implementations of a method described herein may include: transmitting historical TA information to a network entity; and receiving predicted TA information from the network entity.

Some implementations of a method described herein may include: receiving a third configuration for TA prediction from a network entity; performing the TA prediction to generate predicted TA information based at least on the third configuration; and applying the predicted TA information.

Some implementations of a method described herein may include: transmitting a third configuration for TA prediction to a UE; and receiving uplink transmission based on predicted TA information.

Some implementations of a processor described herein may include at least one memory and a controller coupled with the at least one memory and configured to cause the controller to: transmit historical TA information via the transceiver to a network entity; and receive predicted TA information via the transceiver from the network entity.

Some implementations of a processor described herein may include at least one memory and a controller coupled with the at least one memory and configured to cause the controller to: receive a third configuration for TA prediction via the transceiver from a network entity; perform the TA prediction to generate predicted TA information based at least on the third configuration; and apply the predicted TA information.

It is to be understood that the summary section is not intended to identify key or essential features of embodiments of the present disclosure, nor is it intended to be used to limit the scope of the present disclosure. Other features of the present disclosure will become easily comprehensible through the following description.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 illustrates an example of a wireless communications system that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure;

Fig. 2 illustrates a signaling diagram illustrating an example process that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure;

Fig. 3 illustrates an example of the network entity in accordance with aspects of the present disclosure;

Figs. 4 to 7 illustrates a signaling diagram illustrating an example process that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure, respectively;

Fig. 8 illustrates an example of a device that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure;

Fig. 9 illustrates an example of a processor that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure; and

Figs. 10 to 13 illustrate a flowchart of a method that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure.

DETAILED DESCRIPTION

Principles of the present disclosure will now be described with reference to some embodiments. It is to be understood that these embodiments are described only for the purpose of illustration and help those skilled in the art to understand and implement the present disclosure, without suggesting any limitation as to the scope of the disclosure. The disclosure described herein may be implemented in various manners other than the ones described below.

In the following description and claims, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skills in the art to which this disclosure belongs.

References in the present disclosure to “one embodiment, ” “an example embodiment, ” “an embodiment, ” “some embodiments, ” and the like indicate that the embodiment (s) described may include a particular feature, structure, or characteristic, but it is not necessary that every embodiment includes the particular feature, structure, or characteristic. Moreover, such phrases do not necessarily refer to the same embodiment (s) . Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.

It shall be understood that although the terms “first” and “second” or the like may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first element could also be termed as a second element, and similarly, a second element could also be termed as a first element, without departing from the scope of embodiments. As used herein, the term “and/or” includes any and all combinations of one or more of the listed terms.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a” , “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” , “comprising” , “has” , “having” , “includes” and/or “including” , when used herein, specify the presence of stated features, elements, and/or components etc., but do not preclude the presence or addition of one or more other features, elements, components and/or combinations thereof.

As described above, TA will vary frequently, which will cause overhead of signalling to update TA by sending TAC MAC CE. In addition, the initial TA value relies on a random access procedure which makes the random access procedure is mandatorily performed in most of handover cases, which will cause handover delay.

In view of the above, the present disclosure provides a solution that supports AI/ML enabled TA prediction. In this solution, a network entity obtains historical TA information. In turn, the network entity performs TA prediction to generate predicted TA information for UE based at least on the historical TA information. Then, the network entity transmits the predicted TA information to the UE. With this solution, overhead caused by sending frequent TA command may be saved.

Aspects of the present disclosure are described in the context of a wireless communications system.

Fig. 1 illustrates an example of a wireless communications system 100 that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure. The wireless communications system 100 may include one at least one of network entities 102 (also referred to as network equipment (NE) ) , one or more terminal devices or UEs 104, a core network 106, and a packet data network 108. The wireless communications system 100 may support various radio access technologies. In some implementations, the wires communications system 100 may be a 6G network. In some implementations, the wireless communications system 100 may be a 4G network, such as an LTE network or an LTE-advanced (LTE-A) network. In some other implementations, the wireless communications system 100 may be a 5G network, such as an NR network. In other implementations, the wireless communications system 100 may be a combination of a 4G network and a 5G network, or other suitable radio access technology including institute of electrical and electronics engineers (IEEE) 802.11 (Wi-Fi) , IEEE 802.16 (WiMAX) , IEEE 802.20. The wireless communications system 100 may support radio access technologies beyond 5G. Additionally, the wireless communications system 100 may support technologies, such as time division multiple access (TDMA) , frequency division multiple access (FDMA) , or code division multiple access (CDMA) , etc.

The network entities 102 may be dispersed throughout a geographic region to form the wireless communications system 100. One or more of the network entities 102 described herein may be or include or may be referred to as a network node, a base station (BS) , a network element, a radio access network (RAN) node, a base transceiver station, an access point, a NodeB, an eNodeB (eNB) , a next-generation NodeB (gNB) , a base station that will be used in 6G, or other suitable terminology. A network entity 102 and a UE 104 may communicate via a communication link 110, which may be a wireless or wired connection. For example, a network entity 102 and a UE 104 may perform wireless communication (e.g., receive signaling, transmit signaling) over a Uu interface. The network entities 102 may be collectively referred to as network entities 102 or individually referred to as a network entity 102.

A network entity 102 may provide a geographic coverage area 112 for which the network entity 102 may support services (e.g., voice, video, packet data, messaging, broadcast, etc. ) for one or more UEs 104 within the geographic coverage area 112. For example, a network entity 102 and a UE 104 may support wireless communication of signals related to services (e.g., voice, video, packet data, messaging, broadcast, etc. ) according to one or multiple radio access technologies. In some implementations, a network entity 102 may be moveable, for example, a satellite associated with a non-terrestrial network. In some implementations, different geographic coverage areas 112 associated with the same or different radio access technologies may overlap, but the different geographic coverage areas 112 may be associated with different network entities 102. Information and signals described herein may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

The one or more UEs 104 may be dispersed throughout a geographic region of the wireless communications system 100. A UE 104 may include or may be referred to as a mobile device, a wireless device, a remote device, a remote unit, a handheld device, or a subscriber device, or some other suitable terminology. In some implementations, the UE 104 may be referred to as a unit, a station, a terminal, or a client, among other examples. Additionally, or alternatively, the UE 104 may be referred to as an internet-of-things (IoT) device, an internet-of-everything (IoE) device, or machine-type communication (MTC) device, among other examples. In some implementations, a UE 104 may be stationary in the wireless communications system 100. In some other implementations, a UE 104 may be mobile in the wireless communications system 100.

The one or more UEs 104 may be devices in different forms or having different capabilities. Some examples of UEs 104 are illustrated in Fig. 1. A UE 104 may be capable of communicating with various types of devices, such as the network entities 102, other UEs 104, or network equipment (e.g., the core network 106, the packet data network 108, a relay device, an integrated access and backhaul (IAB) node, or another network equipment) , as shown in Fig. 1. Additionally, or alternatively, a UE 104 may support communication with other network entities 102 or UEs 104, which may act as relays in the wireless communications system 100.

A UE 104 may also be able to support wireless communication directly with other UEs 104 over a communication link 114. For example, a UE 104 may support wireless communication directly with another UE 104 over a device-to-device (D2D) communication link. In some implementations, such as vehicle-to-vehicle (V2V) deployments, vehicle-to-everything (V2X) deployments, or cellular-V2X deployments, the communication link 114 may be referred to as a sidelink. For example, a UE 104 may support wireless communication directly with another UE 104 over a PC5 interface.

A network entity 102 may support communications with the core network 106, or with another network entity 102, or both. For example, a network entity 102 may interface with the core network 106 through one or more backhaul links 116 (e.g., via an S1, N2, N2, or another network interface) . The network entities 102 may communicate with each other over the backhaul links 116 (e.g., via an X2, Xn, or another network interface) . In some implementations, the network entities 102 may communicate with each other directly (e.g., between the network entities 102) . In some other implementations, the network entities 102 may communicate with each other or indirectly (e.g., via the core network 106) . In some implementations, one or more network entities 102 may include subcomponents, such as an access network entity, which may be an example of an access node controller (ANC) . An ANC may communicate with the one or more UEs 104 through one or more other access network transmission entities, which may be referred to as a radio heads, smart radio heads, or transmission-reception points (TRPs) .

In some implementations, a network entity 102 may be configured in a disaggregated architecture, which may be configured to utilize a protocol stack physically or logically distributed among two or more network entities 102, such as an integrated access backhaul (IAB) network, an open radio access network (O-RAN) (e.g., a network configuration sponsored by the O-RAN Alliance) , or a virtualized RAN (vRAN) (e.g., a cloud RAN (C-RAN) ) . For example, a network entity 102 may include one or more of a central unit (CU) , a distributed unit (DU) , a radio unit (RU) , a RAN intelligent controller (RIC) (e.g., a near-real time RIC (Near-RT RIC) , a non-real time RIC (Non-RT RIC) ) , a service management and orchestration (SMO) system, or any combination thereof.

An RU may also be referred to as a radio head, a smart radio head, a remote radio head (RRH) , a remote radio unit (RRU) , or a transmission reception point (TRP) . One or more components of the network entities 102 in a disaggregated RAN architecture may be co-located, or one or more components of the network entities 102 may be located in distributed locations (e.g., separate physical locations) . In some implementations, one or more network entities 102 of a disaggregated RAN architecture may be implemented as virtual units (e.g., a virtual CU (VCU) , a virtual DU (VDU) , a virtual RU (VRU) ) .

Split of functionality between a CU, a DU, and an RU may be flexible and may support different functionalities depending upon which functions (e.g., network layer functions, protocol layer functions, baseband functions, radio frequency functions, and any combinations thereof) are performed at a CU, a DU, or an RU. For example, a functional split of a protocol stack may be employed between a CU and a DU such that the CU may support one or more layers of the protocol stack and the DU may support one or more different layers of the protocol stack. In some implementations, the CU may host upper protocol layer (e.g., a layer 3 (L3) , a layer 2 (L2) ) functionality and signaling (e.g., radio resource control (RRC) , service data adaption protocol (SDAP) , packet data convergence protocol (PDCP) ) . The CU may be connected to one or more DUs or RUs, and the one or more DUs or RUs may host lower protocol layers, such as a layer 1 (L1) (e.g., physical (PHY) layer) or an L2 (e.g., radio link control (RLC) layer, medium access control (MAC) layer) functionality and signaling, and may each be at least partially controlled by the CU.

Additionally, or alternatively, a functional split of the protocol stack may be employed between a DU and an RU such that the DU may support one or more layers of the protocol stack and the RU may support one or more different layers of the protocol stack. The DU may support one or multiple different cells (e.g., via one or more RUs) . In some implementations, a functional split between a CU and a DU, or between a DU and an RU may be within a protocol layer (e.g., some functions for a protocol layer may be performed by one of a CU, a DU, or an RU, while other functions of the protocol layer are performed by a different one of the CU, the DU, or the RU) .

A CU may be functionally split further into CU control plane (CU-CP) and CU user plane (CU-UP) functions. A CU may be connected to one or more DUs via a midhaul communication link (e.g., F1, F1-c, F1-u) , and a DU may be connected to one or more RUs via a fronthaul communication link (e.g., open fronthaul (FH) interface) . In some implementations, a midhaul communication link or a fronthaul communication link may be implemented in accordance with an interface (e.g., a channel) between layers of a protocol stack supported by respective network entities 102 that are in communication via such communication links.

The core network 106 may support user authentication, access authorization, tracking, connectivity, and other access, routing, or mobility functions. The core network 106 may be an evolved packet core (EPC) , or a 5G core (5GC) , which may include a control plane entity that manages access and mobility (e.g., a mobility management entity (MME) , an access and mobility management functions (AMF) ) and a user plane entity that routes packets or interconnects to external networks (e.g., a serving gateway (S-GW) , a packet data network (PDN) gateway (P-GW) , or a user plane function (UPF) ) . In some implementations, the control plane entity may manage non-access stratum (NAS) functions, such as mobility, authentication, and bearer management (e.g., data bearers, signal bearers, etc. ) for the one or more UEs 104 served by the one or more network entities 102 associated with the core network 106.

The core network 106 may communicate with the packet data network 108 over one or more backhaul links 116 (e.g., via an S1, N2, N2, or another network interface) . The packet data network 108 may include an application server 118. In some implementations, one or more UEs 104 may communicate with the application server 118. A UE 104 may establish a session (e.g., a protocol data unit (PDU) session, or the like) with the core network 106 via a network entity 102. The core network 106 may route traffic (e.g., control information, data, and the like) between the UE 104 and the application server 118 using the established session (e.g., the established PDU session) . The PDU session may be an example of a logical connection between the UE 104 and the core network 106 (e.g., one or more network functions of the core network 106) .

In the wireless communications system 100, the network entities 102 and the UEs 104 may use resources of the wireless communications system 100 (e.g., time resources (e.g., symbols, slots, subframes, frames, or the like) or frequency resources (e.g., subcarriers, carriers) ) to perform various operations (e.g., wireless communications) . In some implementations, the network entities 102 and the UEs 104 may support different resource structures. For example, the network entities 102 and the UEs 104 may support different frame structures. In some implementations, such as in 4G, the network entities 102 and the UEs 104 may support a single frame structure. In some other implementations, such as in 5G and among other suitable radio access technologies, the network entities 102 and the UEs 104 may support various frame structures (i.e., multiple frame structures) . The network entities 102 and the UEs 104 may support various frame structures based on one or more numerologies.

One or more numerologies may be supported in the wireless communications system 100, and a numerology may include a subcarrier spacing and a cyclic prefix. A first numerology (e.g., μ=0) may be associated with a first subcarrier spacing (e.g., 15 kHz) and a normal cyclic prefix. In some implementations, the first numerology (e.g., μ=0) associated with the first subcarrier spacing (e.g., 15 kHz) may utilize one slot per subframe. A second numerology (e.g., μ=1) may be associated with a second subcarrier spacing (e.g., 30 kHz) and a normal cyclic prefix. A third numerology (e.g., μ=2) may be associated with a third subcarrier spacing (e.g., 60 kHz) and a normal cyclic prefix or an extended cyclic prefix. A fourth numerology (e.g., μ=3) may be associated with a fourth subcarrier spacing (e.g., 120 kHz) and a normal cyclic prefix. A fifth numerology (e.g., μ=4) may be associated with a fifth subcarrier spacing (e.g., 240 kHz) and a normal cyclic prefix.

A time interval of a resource (e.g., a communication resource) may be organized according to frames (also referred to as radio frames) . Each frame may have a duration, for example, a 10 millisecond (ms) duration. In some implementations, each frame may include multiple subframes. For example, each frame may include 10 subframes, and each subframe may have a duration, for example, a 1 ms duration. In some implementations, each frame may have the same duration. In some implementations, each subframe of a frame may have the same duration.

Additionally or alternatively, a time interval of a resource (e.g., a communication resource) may be organized according to slots. For example, a subframe may include a number (e.g., quantity) of slots. The number of slots in each subframe may also depend on the one or more numerologies supported in the wireless communications system 100. For instance, the first, second, third, fourth, and fifth numerologies (i.e., μ=0, μ=1, μ=2, μ=3, μ=4) associated with respective subcarrier spacings of 15 kHz, 30 kHz, 60 kHz, 120 kHz, and 240 kHz may utilize a single slot per subframe, two slots per subframe, four slots per subframe, eight slots per subframe, and 16 slots per subframe, respectively. Each slot may include a number (e.g., quantity) of symbols (e.g., OFDM symbols) . In some implementations, the number (e.g., quantity) of slots for a subframe may depend on a numerology. For a normal cyclic prefix, a slot may include 14 symbols. For an extended cyclic prefix (e.g., applicable for 60 kHz subcarrier spacing) , a slot may include 12 symbols. The relationship between the number of symbols per slot, the number of slots per subframe, and the number of slots per frame for a normal cyclic prefix and an extended cyclic prefix may depend on a numerology. It should be understood that reference to a first numerology (e.g., μ=0) associated with a first subcarrier spacing (e.g., 15 kHz) may be used interchangeably between subframes and slots.

In the wireless communications system 100, an electromagnetic (EM) spectrum may be split, based on frequency or wavelength, into various classes, frequency bands, frequency channels, etc. By way of example, the wireless communications system 100 may support one or multiple operating frequency bands, such as frequency range designations FR1 (410 MHz –7.125 GHz) , FR2 (24.25 GHz –52.6 GHz) , FR3 (7.125 GHz –24.25 GHz) , FR4 (52.6 GHz –114.25 GHz) , FR4a or FR4-1 (52.6 GHz –71 GHz) , and FR5 (114.25 GHz –300 GHz) . In some implementations, the network entities 102 and the UEs 104 may perform wireless communications over one or more of the operating frequency bands. In some implementations, FR1 may be used by the network entities 102 and the UEs 104, among other equipment or devices for cellular communications traffic (e.g., control information, data) . In some implementations, FR2 may be used by the network entities 102 and the UEs 104, among other equipment or devices for short-range, high data rate capabilities.

FR1 may be associated with one or multiple numerologies (e.g., at least three numerologies) . For example, FR1 may be associated with a first numerology (e.g., μ=0) , which includes 15 kHz subcarrier spacing; a second numerology (e.g., μ=1) , which includes 30 kHz subcarrier spacing; and a third numerology (e.g., μ=2) , which includes 60 kHz subcarrier spacing. FR2 may be associated with one or multiple numerologies (e.g., at least 2 numerologies) . For example, FR2 may be associated with a third numerology (e.g., μ=2) , which includes 60 kHz subcarrier spacing; and a fourth numerology (e.g., μ=3) , which includes 120 kHz subcarrier spacing.

Fig. 2 illustrates a signaling diagram illustrating an example process 200 that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure. The process 200 may involve the UE 104 and the network entity 102 in Fig. 1. For the purpose of discussion, the process 200 will be described with reference to Fig. 1.

Generally, in the process 200, the network entity 102 is capable of supporting AL/ML functionalities. The network entity 102 can predict TA information to be used in the future time and transmit it to the UE 104 for using the predicted TA information. Thus, overhead caused by sending frequent TA command may be saved.

As shown in Fig. 2, the network entity 102 obtains 210 historical TA information.

In turn, the network entity 102 performs 220 TA prediction to generate predicted TA information for the UE 104 based at least on the historical TA information. For example, the network entity 102 performs inference for TA prediction to generate predicted TA information for the UE 104.

In some implementations, the network entity 102 may determine a predicted UE trajectory and a historical UE trajectory by itself. In turn, the network entity 102 may generate the predicted TA information for the UE 104 based on the historical TA information, the predicted UE trajectory and the historical UE trajectory.

Then, the network entity 102 transmits 230 the predicted TA information to the UE 104.

The UE 104 applies 240 the predicted TA information.

In some implementations, the UE 104 may apply the predicted TA information for UL transmission.

In some implementations, the network entity 102 may perform data collection for TA prediction to obtain the historical TA information from the UE 104. In such implementations, the network entity 102 may transmit, to the UE 104, a first configuration for logging the historical TA information.

In some implementations, the first configuration may indicate at least one of the following: the historical TA information to be logged, a type of logging the historical TA information, at least one condition for reporting the logged historical TA information, or an identity of data collection for the TA prediction.

In some implementations, the historical TA information to be logged may comprise at least one of the following: a historical TA value (e.g., N_TA ) that is applied for uplink transmission, a time duration during which the UE 104 applies the historical TA value, a remaining value of a time alignment timer, a location (e.g., longitude and latitude) of the UE 104 at the time of logging the historical TA value, measurements information (e.g., L1 reference signal receiving power (RSRP) or L3 RSRP or reference signal receiving quality (RSRQ) ) at the time of logging the historical TA value, an identity of a serving cell of the UE 104 at the time of logging the historical TA value, or an identity of a beam that is applied by the UE 104 at the time of logging the historical TA value.

In some implementations, the type of logging the historical TA information may comprise periodical logging of the historical TA information, or logging the historical TA information based on at least one event.

In some implementations, the first configuration may indicate the periodical logging of the historical TA information by indicating at least one of the following: time when the historical TA information starts to be logged, a cycle of logging the historical TA information, or an interval between two historical TA information logging. For example, a start offset is defined as subframes and/or slots where the historical TA information logging starts. The first configuration may indicate the start offset.

In some implementations, the at least one event may comprise at least one of the following: the first configuration being received, the TA value that the UE 104 is using being adjusted or changed, adjustment or change of the TA value that the UE 104 is using being above a threshold, or a location of the UE 104 where the TA value needs to be logged.

In some implementations, the at least one condition for reporting the logged historical TA information may comprise at least one of the following: a first number of the logged historical TA information, a time duration associated with the logged historical TA information, or a request for the logged historical TA information from the network entity 102.

In some implementations, the network entity 102 may transmit the first configuration for logging the historical TA information to multiple UEs comprising the UE 104.

Upon receiving the first configuration, the UE 104 may log the historical TA information based on the first configuration.

In some implementations, if the first configuration indicates periodical logging of the historical TA information, the UE 104 may start to log the historical TA information at the indicated time and on each interval or in each cycle.

In some implementations, if the first configuration indicates logging the historical TA information based on at least one event, the UE 104 may log the historical TA information on each event. For example, when the first configuration is received, the UE 104 may log a TA value that the UE 104 is using. For another example, when the TA value that the UE 104 is using is adjusted or changed, the UE 104 may log the latest using TA value. For another example, when adjustment or change of the TA value that the UE 104 is using is above a threshold, the UE 104 may log the latest using TA value. For a further example, when the UE 104 moves to the location where the TA value needs to be logged, the UE 104 may log the latest using TA value.

Based on the first configuration, the UE 104 may log at least one of the following: a historical TA value (e.g., N_TA ) that is applied for uplink transmission, a time duration during which the UE 104 applies the historical TA value, a remaining value of a time alignment timer, a location (e.g., longitude and latitude) of the UE 104 at the time of logging the historical TA value, measurements information (e.g., L1 reference signal receiving power (RSRP) or L3 RSRP) at the time of logging the historical TA value, an identity of a serving cell of the UE 104 at the time of logging the historical TA value, or an identity of a beam that is applied by the UE 104 at the time of logging the historical TA value.

In turn, the UE 104 may stores each entry of the logged historical TA information.

Then, the UE 104 may report the logged historical TA information to the network entity 102.

In some implementations, the UE 104 may report the logged historical TA information based on the at least one condition for reporting the logged historical TA information or upon receiving a request from the network entity 102. In such implementations, when one of the at least one condition is fulfilled or a request is received from the network entity 102, the UE 104 may trigger reporting of the logged historical TA information.

For example, when the UE 104 has logged the first number of the logged historical TA information, the UE 104 may trigger reporting of the logged historical TA information.

For another example, when a time duration associated with the logged historical TA information has been elapsed since the first configuration was received, the UE 104 may trigger reporting of the logged historical TA information.

In some implementations, the UE 104 may report the logged historical TA information by an RRC message or by a MAC CE.

Alternatively, in some implementations, the network entity 102 may comprise a CU and a DU, and the CU may obtain at least part of the historical TA information from the DU. In such implementations, the CU may transmit, to the DU, a first configuration for logging the historical TA information.

Fig. 3 illustrates an example of the network entity 102 in accordance with aspects of the present disclosure. As shown in Fig. 3, the network entity 102 comprises a CU 310 and a DU 320. The CU 310 may obtain at least part of the historical TA information from the DU 320. The CU 310 may transmit, to the DU 320, a first configuration for logging the historical TA information. The DU 320 may log at least part of the historical TA information based on the first configuration. In turn, the DU 320 may report the logged historical TA information to the CU 310.

In some implementations, the first configuration may indicate at least one of the following: the historical TA information to be logged, a type of logging the historical TA information, at least one condition for reporting the logged historical TA information, an identity of data collection for the TA prediction, or identities of UEs, historical TA information of which is to be logged.

In some implementations, the historical TA information to be logged may comprise at least one of the following: a historical TA value (e.g., N_TA ) that is applied for uplink transmission, a time duration during which the UE 104 applies the historical TA value, a remaining value of a time alignment timer, a location (e.g., longitude and latitude) of the UE 104 at the time of logging the historical TA value, measurements information (e.g., L1 reference signal receiving power (RSRP) or L3 RSRP) at the time of logging the historical TA value, an identity of a serving cell of the UE 104 at the time of logging the historical TA value, an identity of a beam that is applied by the UE 104 at the time of logging the historical TA value, or time when the historical TA value is logged.

In some implementations, the type of logging the historical TA information may comprise one of the following: periodical logging of the historical TA information, or logging the historical TA information based on at least one event.

In some implementations, the first configuration may indicate the periodical logging of the historical TA information by indicating at least one of the following: time when the historical TA information starts to be logged, or a cycle of logging the historical TA information.

In some implementations, the at least one condition for reporting the logged historical TA information may comprise at least one of the following: a first number of the logged historical TA information, a time duration associated with the logged historical TA information, or a request for the logged historical TA information from the CU 310.

Upon receiving the first configuration, the DU 320 may log the historical TA information based on the first configuration.

In some implementations, if the first configuration indicates periodical logging of the historical TA information, the DU 320 may start to log the historical TA information at the indicated time and on each interval or in each cycle.

In some implementations, if the first configuration indicates logging the historical TA information based on at least one event, the DU 320 may log the historical TA information on each event. For example, when the first configuration is received, the DU 320 may log a TA value that the UE 104 is using. For another example, when the TA value that the UE 104 is using is adjusted or changed, the DU 320 may log the latest using TA value. For another example, when adjustment or change of the TA value that the UE 104 is using is above a threshold, the DU 320 may log the latest using TA value. For a further example, when the UE 104 moves to the location where the TA value needs to be logged, the DU 320 may log the latest using TA value.

Based on the first configuration, the DU 320 may log at least one of the following: a historical TA value (e.g., N_TA ) that is applied for uplink transmission, a time duration during which the UE 104 applies the historical TA value, a remaining value of a time alignment timer, a location (e.g., longitude and latitude) of the UE 104 at the time of logging the historical TA value, measurements information (e.g., L1 reference signal receiving power (RSRP) or L3 RSRP) at the time of logging the historical TA value, an identity of a serving cell of the UE 104 at the time of logging the historical TA value, or an identity of a beam that is applied by the UE 104 at the time of logging the historical TA value.

In turn, the DU 320 may stores each entry of the logged historical TA information.

Then, the DU 320 may report the logged historical TA information to the CU 310.

In some implementations, the DU 320 may report the logged historical TA information based on the at least one condition for reporting the logged historical TA information or upon receiving a request from the CU 310. In such implementations, when one of the at least one condition is fulfilled or a request is received from the network entity 102, the DU 320 may trigger reporting of the logged historical TA information.

For example, when the DU 320 has logged the first number of the logged historical TA information, the DU 320 may trigger reporting of the logged historical TA information.

For another example, when a time duration associated with the logged historical TA information has been elapsed since the first configuration was received, the DU 320 may trigger reporting of the logged historical TA information.

In some implementations, the DU 320 may also report logged historical TA information per UE to the CU 310 and the DU 320 may also report identities of UEs, the historical TA information of which is logged.

In some implementations, the UE trajectory information or location information is managed by the CU 310 while the historical TA value is maintained in the DU 320. In such implementations, the historical TA information to be logged may comprise at least one of the following: a historical TA value that is applied for uplink transmission, or time when the historical TA value is logged.

Upon receiving the logged historical TA information, the CU 310 may combine the logged historical TA information and historical location information to generate historical TA information. For example, the CU 310 correlates or associates the historical TA value and the location (e.g., longitude and latitude) of the UE 104 when the UE 104 applied the historical TA value based on the time when the historical TA value is logged. Then, the CU 310 generates the historical TA information.

Alternatively, upon receiving the logged historical TA information, the CU 310 may combine the logged historical TA information and historical location information to generate historical TA information. For example, the CU 310 correlates or associates the historical TA value and the measurement information (e.g., RSRP or RSRQ) when the UE 104 applied the historical TA value based on the time when the historical TA value is logged. Then, the CU 310 generates the historical TA information.

In some implementations, if the TA prediction functionality is performed at the CU 310, the CU 310 may perform TA prediction to generate the predicted TA information for the UE 104 based at least on the historical TA information.

In some implementations, if the TA prediction functionality is performed at the DU 320, the CU 310 needs to provide assistance information to the DU 320. For example, the assistance information may comprise the historical TA information. For another example, the assistance information may further comprise one of the following: the historical or predicted trajectory of the UE 104. The DU 320 may perform TA prediction to generate the predicted TA information for the UE 104 based at least on the historical TA information.

In some implementations, the network entity 102 may comprise a target network entity in handover and the target network entity may obtain the historical TA information from a source network entity in handover. In such implementations, the target network entity may perform the TA prediction to generate a TA value to be used in the target network entity. The source network entity may provide inputs to the target network entity for TA prediction in the target network entity.

In some implementations, the inputs of the TA prediction may comprise at least one of predicted UE trajectory, historical UE trajectory and historical TA information.

In some implementations, the source network entity may determine the predicted UE trajectory and the historical UE trajectory, and the source network entity may obtain the historical TA information from the UE 104.

Based on the inputs of TA prediction, the target network entity may perform the TA prediction to generate a TA value to be used in the target network entity. The target network entity provides the predicted TA information to the UE 104.

The UE 104 applies the predicted TA information for UL initial access and subsequent UL transmission in a target cell. The UE 104 may apply the predicted TA information for UL initial access in the target cell.

Upon receiving a handover command with a first indication indicating the UE 104 should apply the predicted TA information, the UE104 applies the predicted TA information for UL initial access and/or subsequent UL transmission in the target cell. Hereinafter, the first indication is also referred to as a predicted TA usage indication.

In some implementations, the first indication indicates the UE 104 applies the predicted TA information for UL initial access in the target cell. Alternatively, in some implementations, the first indication indicates the UE 104 applies the predicted TA information for both UL initial access and subsequent UL transmission in the target cell.

The UE 104 may apply the predicted TA information based on the predicted TA usage indication of the neighbour cell.

In some implementations, the UE 104 may perform the initial access procedure without initiating a random access (RACH) procedure.

In some implementations, the UE 104 may apply the predict TA value of the target cell at the time of initializing the UL initial access in the target cell.

Alternatively, the UE 104 may apply the predict TA value of the target cell when receiving the handover command.

Alternatively, the UE 104 may apply the predict TA value of the target cell upon conditional handover (CHO) execution initialization.

In some implementations, the predicted TA value for initial access may be an initial index value, e.g., 12bits with range from 0-3846, that is the predicted T_A in the following formula.
N_TA = T_A·16·64/2^u

Alternatively, in some implementations, the predicted TA value for initial access may be an initial absolute timing advance value, that is a predicted N_TA in the above formula.

In some implementations, the inputs of TA prediction may be provided to the target network entity over Xn-AP signalling e.g., a handover request message.

In some implementations, the predicted TA information may be provided by the target network entity in a handover command message.

Alternatively, in some implementations, the network entity 102 may comprise a source network entity in handover and the source network entity may obtain the historical TA information from a target network entity in handover. In such implementations, before handover, the target network entity may provide inputs to the source network entity for TA prediction in the target network entity.

In such implementations, the inputs of TA prediction may comprise historical TA information for at least one UE, and the at least one UE may or may not comprise the UE 104. The inputs of TA prediction may further comprise location information about the network entity or TRP serving the at least one UE.

Based on the inputs, the source network entity performs the TA prediction for the target cell. The source network entity may transmit the predicted TA information to the target network entity and then the target network entity forwards it to the UE 104 in a handover command. Alternatively, the source network entity may transmit the predicted TA information to the UE 104 directly. Upon receiving the handover command with a first indication indicating the UE 104 should apply the predicted TA information, UE 104 applies the predicted TA information for UL initial access and/or subsequent UL transmission in the target cell.

In some implementations, the predicted TA information may comprise a list of a predicted TA value and information about time when the predicted TA value is to be applied.

In some implementations, the information about time when the predicted TA value is to be applied may be absolute time. For example, the information about time may be “time 12: 00: 00” , and the predicted TA value that is predicted to be applied at time 12: 00: 00 is 20us.

Alternatively, the information about time when the predicted TA value is to be applied may be relative time representing by System Frame Number (SFN) and slot number. For example, the information about time may be “SFN#3 and slot#5” , and the predicted TA value that is predicted to be applied in slot#5 of SFN#3 is 15us.

Alternatively or additionally, in some implementations, the predicted TA information may comprise a list of the predicted TA value and information about a location where the predicted TA value is to be applied. The information about the location may be longitude and latitude. When the UE 104 moves the location (as indicated in the longitude and latitude) , the UE 104 shall apply the corresponding predicted TA value.

Alternatively or additionally, in some implementations, the predicted TA information may comprise a predicted time alignment timer. The UE 104 may start the predicted time alignment timer when starting to apply the predicted TA value. The predicted time alignment timer controls how long the UE 104 considers the serving cells to be uplink time aligned.

Alternatively or additionally, in some implementations, the predicted TA information may comprise a prediction that a current TA will expire or the current TA will be invalid at first time before the predicted time alignment timer expires.

In some implementations, the predicted TA value may comprise calculated time that is used by the UE 104 to transmit uplink transmission in advance. The calculated time is represented by N_TA and N_TA is calculated as:
N_TA = T_A·16·64/2^u

where T_A represents an index value indicating adjustment of a current TA value, and u is the sub-carrier spacing (SCS) configuration for PDSCH reception. T_A is about 12 bits and its value can range from 0-3846.

Alternatively or additionally, in some implementations, the predicted TA value may comprise an index value indicating adjustment of a current TA value. The index value is represented by T_A. Based on a current TA value and the index value T_A, the UE 104 can calculate a new TA value as below:
N_{TA_New} = T_{A_ild}+ (T_A-31) ·16·64/2^u

where N_{TA_New} represents the new TA value, T_{A_ild} represents the current TA value, T_A is about 6 bits and its value can range from 0-63.

In some implementations, the network entity 102 may transmit the predicted TA information via a MAC CE or an RRC message.

In some implementations, the network entity 102 may transmit the first indication (i.e., predicted TA usage indication) to the UE 104. The first indication may indicate whether the UE 104 should apply the predicted TA information. The UE 104 may apply the predicted TA information based on the predicted TA usage indication.

For example, the network entity 102 provides one bit indication in Timing Advance Command MAC CE to indicate whether the UE 104 should apply the predicted TA information. If the bit is set to ‘1’ or ‘true’ , the UE 104 shall apply the predicted TA information. Else if the bit is set to ‘0’ or ‘false’ , the UE 104 shall not apply the predicted TA information. In other words, the UE 104 shall apply the legacy TA maintenance procedure. Instead of the MAC CE, the network entity 102 may also provide the one bit indication in an RRC message.

In some implementations, the network entity 102 may transmit a second indication to the UE 104. The second indication may indicate the UE 104 to start to apply the predicted TA information. The UE 104 may start to apply the predicted TA information based on the second indication. The second indication may be provided by MAC CE or RRC message.

In some implementations, the network entity 102 may transmit a third indication to the UE 104. The third indication may indicate the UE 104 to stop applying the predicted TA information. The UE 104 may stop applying the predicted TA information based on the third indication. The third indication may be provided by MAC CE or RRC message.

In some implementations, if the predicted TA value is the calculated time that is used by the UE 104 to transmit uplink transmission in advance (i.e., predicted N_TA ) , the UE 104 may apply it directly. For example, at the corresponding timing point or location, the UE 104 takes effect and applies the predicted TA value.

In some implementations, if the predicted TA value is the index value T_A, the UE 104 shall calculate the time that is used by the UE 104 to transmit uplink transmission in advance using the predicted T_A as follows:
N_{TA_New} = T_{A_old}+ (T_A-31) ·16·64/2^u

where the T_A is the predicted TA value in the time point or location.

In some implementations, once the UE 104 applies the predicted TA value, the UE 104 may start or restart a time alignment timer configured by the network entity 102 or the predicted time alignment timer.

In some implementations, the network entity 102 may transmit, to the UE 104, at least one condition for applying the predicted TA value.

In some implementations, the at least one condition for applying the predicted TA value may comprise a percentage of running time of a time alignment timer being greater than or equal to a first threshold (e.g., 90%) . If the percentage of running time of the time alignment timer is greater than or equal to the first threshold, the UE 104 may apply the predicted TA value.

Alternatively, the at least one condition for applying the predicted TA value may comprise a percentage of remaining running time of the time alignment timer being less than or equal to a third threshold (e.g., 10%) . If the percentage of remaining running time of the time alignment timer is less than or equal to the third threshold, the UE 104 may apply the predicted TA value.

Alternatively, in some implementations, the at least one condition for applying the predicted TA value may comprise the running time of the time alignment timer being greater than or equal to a second threshold. If the running time of the time alignment timer is greater than or equal to the second threshold, the UE 104 may apply the predicted TA value.

Fig. 4 illustrates a signaling diagram illustrating an example process 400 that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure. The process 400 may involve the UE 104 and the network entity 102 in Fig. 1. For the purpose of discussion, the process 400 will be described with reference to Fig. 1.

Generally, in the process 400, the UE may be capable of supporting AL/ML functionalities. If the UE 104 can predict a TA value to be used in the future time and use the predicted TA, it can save the overhead caused by sending frequent TA command and it does not need to perform a random access procedure which can reduce the interruption time sufficiently.

As shown in Fig. 4, the network entity 102 transmits 410 a third configuration for TA prediction to the UE 104.

In some implementations, the third configuration for TA prediction may comprise historical TA information.

Alternatively, in some implementations, the UE 104 may obtain the historical TA information for the TA prediction by logging the historical TA information. In such implementations, the UE 104 may receive the first configuration for logging the historical TA information from the network entity 102. In turn, the UE 104 may log the historical TA information based on the first configuration. Some implementations of the first configuration have been described with reference to Fig. 2. Details of such implementations are omitted for brevity.

In some implementations, the historical TA information may comprise at least one of the following: a historical TA value (e.g., N_TA) that is applied for uplink transmission, a time duration during which the UE 104 applies the historical TA value, a location (e.g., longitude and latitude) where the UE 104 applies the historical TA value, measurements information (e.g., RSRP or RSRQ) when the UE 104 applies the historical TA value, or an identity of a serving cell of the UE 104 when the UE 104 applies the historical TA value.

Alternatively or additionally, in some implementations, the historical TA information may comprise location information about at least one serving transmission reception point (TRP) or a network entity providing the serving cell. The network entity providing the serving cell may be the same as or different from the network entity 102. The location information about at least one serving TRP or the network entity may comprise a logical identity indicating a location of the at least one serving TRP or the network entity to avoid exposing network configurations. For example, the logical identity may be an association identity.

Alternatively or additionally, in some implementations, the third configuration for TA prediction may comprise at least one model that is used for the TA prediction in the UE 104. The third configuration for TA prediction may indicate an identity of the at least one model to indicate which model the UE 104 shall use for TA prediction.

Alternatively or additionally, in some implementations, the third configuration for TA prediction may comprise at least one condition for starting or stopping the TA prediction in the UE 104.

In some implementations, the at least one condition for starting or stopping the TA prediction in the UE 104 may comprise a threshold for change of a path loss between the UE 104 and the network entity 102. If the change of the path loss within a period is lower than or equal to the threshold, the UE 104 may start the TA prediction. Otherwise, if the change of the path loss within a period is higher than the threshold, the UE 104 may stop the TA prediction.

Alternatively, the at least one condition for starting or stopping the TA prediction in the UE 104 may comprise a threshold for change of a measured RSRP/RSRQ. If the change of the measured RSRP/RSRQ within a period is lower than or equal to the threshold, the UE 104 may start the TA prediction. Otherwise, if the change of the measured RSRP/RSRQ within a period is higher than the threshold, the UE 104 may stop the TA prediction.

Alternatively or additionally, in some implementations, the third configuration for TA prediction may comprise accuracy of the TA prediction, which means TA prediction should satisfy the accuracy requirement.

Alternatively or additionally, in some implementations, the third configuration for TA prediction may comprise a time duration during with a predicted TA value is to be applied. The network entity 102 may indicate the time duration to indicate the UE 104 to predict the TA value that will be used in the time duration. The time duration can be absolute time or can be relative time representing by SFN and slot number.

The UE 104 performs 420 the TA prediction to generate predicted TA information based at least on the third configuration. For example, the UE 104 performs inference for TA prediction to generate predicted TA information for the UE 104.

Alternatively or additionally, in some implementations, the predicted TA value may comprise an index value indicating adjustment of a current TA value. The index value is represented by T_A. Based on a current TA value and the index value T_A, the UE 104 can calculate a new TA value as below:
N_{TA_New} = T_{A_old}+ (T_A-31) ·16·64/2^u

where N_{TA_New} represents the new TA value, T_{A_old} represents the current TA value, T_A is about 6 bits and its value can range from 0-63.

In turn, the UE 104 applies 430 the predicted TA information.

In some implementations, the network entity 102 may transmit the first indication (i.e., the predicted TA usage indication) to the UE 104. The first indication may indicate whether the UE 104 should apply the predicted TA information. The UE 104 may apply the predicted TA information based on the predicted TA usage indication.

In some implementations, if the predicted TA value comprises the calculated time (e.g. predicated N_TA) that is used by the UE 104 to transmit uplink transmission in advance, the UE 104 may apply the calculated time to transmit the uplink transmission in advance. For example, at the corresponding timing point or location, the UE 104 takes effect and applies the predicted TA value.

Alternatively, in some implementations, if the predicted TA value comprises an index value (T_A) indicating adjustment of a current TA value, the UE 104 may determine, based on the index value, calculated time that is used by the UE 104 to transmit uplink transmission in advance. For example, the UE 104 may determine the calculated time based on the index value as follows:
N_{TA_New} = T_{A_old}+ (T_A-31) ·16·64/2^u

wherein the T_A is the predicted TA value in the time point or location, N_{TA_New} represents the new TA value, T_{A_old} represents the current TA value, T_A is about 6 bits and its value can range from 0-63.

In turn, the UE 104 may apply the calculated time to transmit the uplink transmission in advance.

Fig. 5 illustrates a signaling diagram illustrating an example process 500 that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure. The process 500 may be considered as an example implementation of the process 400. The process 500 may involve the UE 104 and the network entity 102 in Fig. 1. For the purpose of discussion, the process 500 will be described with reference to Fig. 1.

As shown in Fig. 5, the UE 104 may transmit 510 capability information to the network entity 102. The capability information may indicate that the UE 104 supports AI or ML functionality of the TA prediction or may indicate that the UE 104 supports AI/ML enabled TA prediction.

In some implementations, the capability information may be transmitted as a part of UE AS capability in RRC related message (i.e., UE CapabilityInformation) .

In some implementations, the UE 104 may further transmit, to the network entity 102, information about at least one AI or ML model supported by the UE 104. The information about at least one AI or ML model may comprise an identity of the at least one AI or ML model.

The network entity 102 may transmit 520, to the UE 104, a fourth configuration for applicability determination.

In some implementations, the fourth configuration may comprise at least one of the following: a location of a serving TRP or the network entity 102, a logical identity indicating the location of the TRP or the network entity 102, or network conditions. For example, the location of the serving TRP or the network entity 102 may be indicated by antenna height of the serving TRP or the network entity 102. For example, the network conditions may comprise deployment scenarios (e.g., Inter-Site Distance (ISD) , Urban Micro (Umi) /Urban Macro (Uma) ) .

The UE 104 may determine 530 whether the TA prediction is applicable for based on the fourth configuration.

For example, the UE 104 may determine whether the training model is ready for TA prediction under the network conditions, whether the collected data is sufficient for the TA prediction under the network conditions, whether the UE 104 has sufficient computing resource for TA prediction under the network conditions.

In some implementations, the fourth configuration may be implicitly indicated by a logical identity, e.g., an association identity.

The network entity 102 transmits 540 the third configuration for TA prediction to the UE 104. The action 540 is the similar to the action 410 in Fig. 4. Details of this action is omitted for brevity.

In some implementations, the network entity 102 may transmit the third configuration for TA prediction together with the fourth configuration for applicability determination.

In some implementations, if the UE 104 determines the TA prediction is applicable, the UE 104 may transmit 550 a fourth indication to the network entity 102. The fourth indication may indicate the TA prediction is applicable or available in the UE 104. Hereinafter, the fourth indication is also referred to as a TA prediction applicable indication.

For example, if the training model is ready for TA prediction, the collected data is sufficient for TA prediction, and the UE 104 has sufficient computing resource for TA prediction, the UE 104 may determine the TA prediction is applicable.

In some implementations, the TA prediction applicable indication may be transmitted by UE Assistance Information message to the network entity 102.

It shall be noted that although the action 550 is shown after the action 540, the action 550 may be performed in parallel to or prior to the action 540. The scope of the present disclosure is not limited in this regard.

The network entity 102 may transmit 560 a fifth indication to the UE 104. The fifth indication may indicate the UE 104 to perform the TA prediction. Hereinafter, the fifth indication is also referred to as a TA prediction execution indication.

In some implementations, upon receiving the TA prediction applicable indication, the network entity 102 may decide to execute the TA prediction. And then the network entity 102 transmits the TA prediction execution indication to indicate the UE 104 to perform TA prediction according to the third configuration in the action 540.

In some implementations, the TA prediction execution indication may also comprise the logical identity, e.g., the association identity in the action 520 to associate the fourth configuration for applicability determination.

The UE 104 performs 570 the TA prediction to generate predicted TA information based at least on the third configuration. For example, the UE 104 performs inference for TA prediction to generate predicted TA information for the UE 104. The action 570 is the similar to the action 420 in Fig. 4. Details of this action is omitted for brevity.

Optionally, in some implementations, the UE 104 may transmit 580 the predicted TA information to the network entity 102.

In some implementations, the UE 104 may transmit the predicted TA information upon receiving a configuration or request for the predicted TA information from the network entity 102.

In some implementations, the network entity 102 can use the predicted TA information to perform AL/ML performance measurement to judge the accuracy of the predicted TA information compared with the ground truth (i.e., the actually required TA as the timing or location) .

One of reasons for the UE 104 reporting the predicted TA information is for performance monitoring in the network entity 102 to monitor the predicted TA information.

Another reason for the UE 104 reporting the predicted TA information is for switching to legacy TA. When switching to legacy TA, the network entity 102 needs to transmit Timing Advance Command to adjust the TA value in the UE 104 so that the network entity 102 needs to the absolute TA value used in the UE 104. The network entity 102 can know the absolute TA value used in the UE 104 by the predicted TA information reported by the UE 104.

In some implementations, the UE 104 may transmit the predicted TA information via a MAC CE or an RRC message. For example, the UE 104 may transmit the predicted TA information via a Predicated TA Information MAC CE. A new logical channel identity (LCID) or extended logical channel identity (eLCID) can be allocated for the Predicated TA Information MAC CE for identifying the MAC CE.

The UE 104 applies 590 the predicted TA information. The action 590 is the similar to the action 430 in Fig. 4. Details of this action is omitted for brevity.

In some implementations, the network entity 102 may not transmit the first indication, the second indication and the third indication, as described with reference to Fig. 4. In such implementations, the UE 104 may apply the predicted TA information directly after generating the predicted TA information. In order to avoid the ambiguity on when to apply the predicted TA information or legacy TA information between the network entity 102 and the UE 104, the following options can be used.

In one option, when receiving the fifth indication (i.e., the TA prediction execution indication) in the action 560, the UE 104 shall complete the TA predication within a specified time. The network entity 102 assumes that the UE 104 starts to apply the predicted TA information before the specified time elapses since the TA prediction execution indication was transmitted.

In another option, the network entity 102 can configure a timer. When receiving the fifth indication (i.e., the TA prediction execution indication) in the action 560, the UE 104 starts the timer. When the timer expires, the UE 104 starts to apply the predicted TA information. Before the timer expires, the UE 104 applies the legacy TA information.

In some implementations, there may be coexistence between legacy Timing Advance Command MAC CE and the predicted TA value.

In a first case, when the UE 104 is using a predicted TA value, the UE 104 receives a legacy Timing Advance Command MAC CE. In this case, the T_{A_old} is a using TA value (i.e., a TA value the UE 104 is currently using) that is based on the predicted TA value, and the T_A is the TA value received in the Timing Advance Command MAC CE. In this case, the UE 104 may apply one of the following three options.

In a first option, the UE 104 shall apply the TA indicated in the Timing Advance Command MAC CE, after that the UE 104 continues to use the predicted TA value. In the first option, when the UE 104 is applying the predicted TA value as a current TA value, the UE 104 receives, from the network entity 102, a first index value indicating adjustment of the current TA value. In turn, the UE 104 determines a first new TA value based on the current TA value and the first index value and applies the first new TA value. For example, the UE 104 may determine the first new TA value based on the following:
N_{TA_New1} = T_{A_old1}+ (T_A-legacy-31) ·16·64/2^u

where T_{A_old1} represents the current TA value which is calculated by predicted TA value, T_A-legacy represents the first index value indicating adjustment of the current TA value received via a Timing Advance Command MAC CE, and N_{TA_Nww1} represents the first new TA value.

In the first option, after determining the first new TA value, the UE 104 may determine a second new TA value based on the first new TA value and a second index value indicating adjustment of the first new TA value. Then, the UE 104 may apply the second new TA value. For example, the UE 104 may determine the second new TA value based on the following:
N_{TA_New2} = N_{TA_New1}+ (T_A-predicted-31) ·16·64/2^u

where N_{TA_New1} represents the first new TA value, T_A-predicted represents the second new TA value which is a predicted TA value, and N_{TA_New2} represents the second new TA value.

In a second option, the UE 104 shall apply the TA value indicated in the Timing Advance Command MAC CE, and the UE 104 stops applying the predicted TA value when receiving the Timing Advance Command MAC CE. The UE 104 shall not apply the predicted TA value T_A to further determine N_{TA_New} . In the second option, after determining the first new TA value, the UE 104 may receive, from the network entity 102, a third index value indicating adjustment of the first new TA value via the Timing Advance Command MAC CE. The UE 104 may determine a third new TA value based on the first new TA value and the third index value. Then, the UE 104 may apply the third new TA value. For example, the UE 104 may determine the third new TA value based on the following:
N_{TA_New3} = N_{TA_New1}+ (T_A-lgeacy2-31) ·16·64/2^u

whereN_{TA_New1} represents the first new TA value, T_A-lgeacy2 represents the third new TA value received via the Timing Advance Command MAC CE, and N_{TA_New3} represents the third new TA value.

In the first option and the second option, it is assumed that the network entity 102 knows the absolute TA value the UE 104 is using. The UE 104 may report predicted TA information comprising the absolute TA value to the network entity 102 as in the action 580.

In a third option, the UE 104 ignores the received Timing Advance Command MAC CE and continues to apply the predicted TA information. In the third option, the UE 104 may receive, from the network entity 102, a first index value indicating adjustment of the current TA value via the Timing Advance Command MAC CE. The UE 104 may determine a fourth new TA value based on the current TA value and a predicated index value indicating adjustment of the current TA value. That is, the UE 104 ignores the first index value received via the Timing Advance Command MAC CE. Then, the UE 104 may apply the fourth new TA value. For example, the UE 104 may determine the fourth new TA value based on the following:
N_{TA_New4}= T_{A_old1}+ (T_A-predicted-31) ·16·64/2^u

where T_{A_old1} represents the current TA value which is calculated by predicted TA value, T_A-predicted represents the predicated index value indicating adjustment of the current TA value, and N_{TA_New4} represents the fourth new TA value.

In a second case, the UE 104 is using a legacy TA value and starts to apply the predicted TA information. In the second case, the T_{A_old} is the currently using TA value that is based on the legacy TA value, and the T_A is the predicted TA value.

In the second case, the UE 104 shall apply the predicted TA value. When the predicted TA value is not available, the UE 104 may transmit an indication that indicates the predicated TA value is not available or is about to be unavailable to the network entity 102. In this way, the network entity 102 can apply a legacy Timing Advance Command MAC CE to adjust the currently using TA value.

In some examples, when the predicted TA value is not available (for example, the time alignment timer for the predicted TA value is expired) , the UE 104 may initialize a random access procedure for UL synchronization propose.

In some implementations, the UE 104 may perform the TA prediction for handover to generate predicted TA information for a neighbour cell. This will be described with reference to Fig. 6.

Fig. 6 illustrates a signaling diagram illustrating an example process 600 that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure. The process 600 may be considered as another example implementation of the process 400. The process 600 may involve the UE 104 and the network entity 102 in Fig. 1. For the purpose of discussion, the process 600 will be described with reference to Fig. 1.

As shown in Fig. 6, a source network entity 102-1 transmits 610 the third configuration for TA prediction for a neighbour cell to the UE 104. The action 610 is the similar to the action 410 in Fig. 4. Details of this action is omitted for brevity.

In some implementations, an identity of the neighbour cell should be provided in the third configuration for TA prediction for the neighbour cell.

In some implementations, similar to the action 510 in Fig. 5, the UE 104 may transmit capability information to the source network entity 102-1. The capability information may indicate that the UE 104 supports AI or ML functionality of the TA prediction or may indicate that the UE 104 supports AI/ML enabled TA prediction.

If the UE 104 supports AI/ML enabled TA prediction as indicated in the capability information, the source network entity 102-1 may decide to configure the UE 104 to perform AI/ML enabled TA prediction for a neighbour cell for purpose of handover.

In some implementations, similar to the action 520 in Fig. 5, the source network entity 102-1 may transmit, to the UE 104, the fourth configuration for applicability determination.

In some implementations, the identity of the neighbour cell should be provided in the fourth configuration for applicability determination.

In some implementations, the source network entity 102-1 may also provide the location information of a TRP or the target network entity 102-2 of the neighbour cell to the UE 104.

Alternatively, in some implementations, the target network entity 102-2 may transmit the fourth configuration for applicability determination to the source network entity 102-1. The source network entity 102-1 may forward the fourth configuration for applicability determination to the UE 104.

In such implementations, the source network entity 102-1 may request the target network entity 102-2 to provide the fourth configuration for applicability determination for the UE 104. When the source network entity 102-1 tends to handover the UE 104 to the neighbour cell, the source network entity 102-1 can request the target network entity 102-2 to provide the fourth configuration for applicability determination for the UE 104. In response to the request, the target network entity 102-2 provides the fourth configuration for applicability determination to the source network entity 102-1 so that the source network entity 102-1 can provide it to the UE 104.

The UE 104 performs 615 the TA prediction to generate predicted TA information for the neighbour cell based on the third configuration for TA prediction for the neighbour cell. The action 615 is the similar to the action 420 in Fig. 4. Details of this action is omitted for brevity.

In turn, the UE 104 transmits 620 the predicted TA information for the neighbour cell to the source network entity 102-1

The source network entity 102-1 transmits 625 the predicted TA information for the neighbour cell to the target network entity 102-2

In some implementations, if the predicted TA information for the neighbour cell is available in source network entity 102-1, the source network entity 102-1 transmits the predicted TA information for the neighbour cell to the target network entity 102-2 which is serving the neighbour cell. The predicted TA information for the neighbour cell can be included in a Handover Request message.

In some implementations, the predicted TA information may only indicate a predicted TA value available in the UE 104.

The target network entity 102-2 transmits 630 a fourth indication in a handover command message to the source network entity 102-1. Hereinafter, the fourth indication is also referred to as a predicted TA usage indication of the neighbour cell.

The source network entity 102-1 may transmit 635, to the UE 104, the handover command message comprising the predicted TA usage indication of the neighbour cell.

In some implementations, the target network entity 102-2 may decide to use the predicted TA for the handover to the neighbour cell and/or subsequent UL transmission following handover procedure. The target network entity 102-2 provides the predicted TA usage indication of the neighbour cell to the UE 104.

For example, the target network entity 102-2 includes the predicted TA usage indication of the neighbour cell in an inter-node RRC message and transmits it to the source network entity 102-1, and the source network entity 102-1 forwards it to the UE 104.

In some implementations, the predicted TA usage indication of the neighbour cell may indicate that the predicted TA information is applied in an initial access procedure to the neighbour cell (i.e., a target cell) .

Alternatively, in some implementations, the predicted TA usage indication of the neighbour cell may indicate that the predicted TA information is applied in both the initial access procedure and subsequent uplink transmission in the neighbour cell. In such implementations, the target network entity 102-2 may receive the uplink transmission based on the predicted TA information.

The UE 104 applies 640 the predicted TA information based on the predicted TA usage indication of the neighbour cell.

In some implementations, the UE 104 may perform 645 the initial access procedure without initiating a random access (RACH) procedure.

Fig. 7 illustrates a signaling diagram illustrating an example process 700 that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure. The process 700 may be considered as another example implementation of the process 400. The process 700 may involve the UE 104 and the network entity 102 in Fig. 1. For the purpose of discussion, the process 700 will be described with reference to Fig. 1.

As shown in Fig. 7, a source network entity 102-1 transmits 710 the third configuration for TA prediction for a neighbour cell to the UE 104. The action 710 is the similar to the action 410 in Fig. 4. Details of this action is omitted for brevity.

Similar to the action 530 in Fig. 5, the UE 104 may determine whether the TA prediction is applicable for based on the fourth configuration.

In some implementations, if the UE 104 determines the TA prediction is applicable, the UE 104 may transmit 715 the fourth indication (i.e., the TA prediction applicable indication) to the source network entity 102-1. The fourth indication may indicate the TA prediction is applicable or available in the UE 104.

The source network entity 102-1 transmits 720 the TA prediction applicable indication to the target network entity 102-2. For example, the source network entity 102-1 may transmit the TA prediction applicable indication to the target network entity 102-2 in a Handover Request message.

The target network entity 102-2 may decide to execute the TA prediction. And then the target network entity 102-2 transmits 725, to the source network entity 102-1, the TA prediction execution indication to indicate UE 104 to perform TA prediction according to the third configuration in the action 710. For example, the target network entity 102-2 may transmit, to the source network entity 102-1, the TA prediction execution indication in a handover command message.

The source network entity 102-1 may transmit 730, to the UE 104, the TA prediction execution indication in a handover command message.

Upon receiving the handover command with the TA prediction execution indication, the UE 104 performs 735 the TA prediction to generate predicted TA information based at least on the third configuration. For example, the UE 104 performs inference for TA prediction to generate predicted TA information for the UE 104. The action 735 is the similar to the action 420 in Fig. 4. Details of this action is omitted for brevity.

The UE 104 applies 740 the predicted TA information based on the predicted TA usage indication of the neighbour cell. The action 740 is the similar to the action 640 in Fig. 6. Details of this action is omitted for brevity.

The UE 104 may perform 745 the initial access procedure without initiating a random access (RACH) procedure. The action 745 is the similar to the action 645 in Fig. 6. Details of this action is omitted for brevity.

In some implementations, the UE 104 may perform data collection for training an AI or ML model. In such implementations, the UE 104 may receive, from the network entity 102, first historical TA information for training the AI or ML model. The UE 104 may log second historical TA information for training the AI or ML model. In addition, the UE 104 may receive, from the network entity 102, a receiving time difference between a serving cell and a candidate cell and a TA value for the serving cell. In turn, the UE 104 may perform the training of the AI or ML model based on the first historical TA information, the second historical TA information, the receiving time difference and the TA value for the serving cell.

In some implementations, the first historical TA information for training the AI or ML model may comprise at least one of the following: at least one historical TA value that is applied for uplink transmission, at least one time duration during which at least one UE applies the at least one historical TA value, at least one location (e.g., longitude and latitude) where the at least one UE applies the at least one historical TA value, or measurements information (e.g., RSRP or RSRQ) when the at least one UE applies the at least one historical TA value.

In some implementations, the at least one historical TA value may be used by at least one UE which may or may not comprise the UE 104.

In some implementations, the at least one historical TA value and the at least one location may be per cell, e.g., may be for serving cell or for a neighbour cell.

In some implementations, the second historical TA information for training the AI or ML model may comprise at least one of the following: a historical TA value that is applied for uplink transmission, a time duration during which the UE 104 applies the historical TA value, a remaining value of a time alignment timer, a location of the UE 104 at the time of logging the historical TA value, measurements information at the time of logging the historical TA value, an identity of a serving cell of the UE 104 at the time of logging the historical TA value, an identity of a beam that is applied by the UE 104 at the time of logging the historical TA value, or time when the historical TA value is logged.

In some implementations, the UE 104 may log second historical TA information for training the AI or ML model based on a configuration for logging the second historical TA information. The configuration for logging the second historical TA information is similar to the first configuration for logging the historical TA information as described with reference to Fig. 2.

In some implementations, for handover case, the UE 104 may receive, from the network entity 102, the receiving time difference between the serving cell and the candidate cell and the TA value for the serving cell.

Fig. 8 illustrates an example of a device 800 that supports AI/ML enabled TA prediction in accordance with some aspects of the present disclosure. The device 800 may be an example of a first apparatus, a second apparatus or the UE 104 as described herein. The device 800 may support wireless communication with one or more network entities 102, UEs 104, or any combination thereof. The device 800 may include components for bi-directional communications including components for transmitting and receiving communications, such as a processor 802, a memory 804, a transceiver 806, and, optionally, an I/O controller 808. These components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces (e.g., buses) .

The processor 802, the memory 804, the transceiver 806, or various combinations thereof or various components thereof may be examples of means for performing various aspects of the present disclosure as described herein. For example, the processor 802, the memory 804, the transceiver 806, or various combinations or components thereof may support a method for performing one or more of the operations described herein.

In some implementations, the processor 802, the memory 804, the transceiver 806, or various combinations or components thereof may be implemented in hardware (e.g., in communications management circuitry) . The hardware may include a processor, a digital signal processor (DSP) , an application-specific integrated circuit (ASIC) , a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic, discrete hardware components, or any combination thereof configured as or otherwise supporting a means for performing the functions described in the present disclosure. In some implementations, the processor 802 and the memory 804 coupled with the processor 802 may be configured to perform one or more of the functions described herein (e.g., executing, by the processor 802, instructions stored in the memory 804) .

For example, the processor 802 may support wireless communication at the device 800 in accordance with examples as disclosed herein. The processor 802 may be configured to operable to support a means for performing the following: obtaining historical TA information; performing TA prediction to generate predicted TA information for a UE based at least on the historical TA information; and transmitting the predicted TA information to the UE.

Alternatively, in some implementations, the processor 802 may be configured to operable to support a means for performing the following: transmitting historical TA information to a network entity; and receiving predicted TA information from the network entity.

Alternatively, in some implementations, the processor 802 may be configured to operable to support a means for performing the following: receiving a third configuration for TA prediction from a network entity; performing the TA prediction to generate predicted TA information based at least on the third configuration; and applying the predicted TA information.

Alternatively, in some implementations, the processor 802 may be configured to operable to support a means for performing the following: transmitting a third configuration for TA prediction to a UE; and receiving uplink transmission based on predicted TA information.

The processor 802 may include an intelligent hardware device (e.g., a general-purpose processor, a DSP, a CPU, a microcontroller, an ASIC, an FPGA, a programmable logic device, a discrete gate or transistor logic component, a discrete hardware component, or any combination thereof) . In some implementations, the processor 802 may be configured to operate a memory array using a memory controller. In some other implementations, a memory controller may be integrated into the processor 802. The processor 802 may be configured to execute computer-readable instructions stored in a memory (e.g., the memory 804) to cause the device 800 to perform various functions of the present disclosure.

The memory 804 may include random access memory (RAM) and read-only memory (ROM) . The memory 804 may store computer-readable, computer-executable code including instructions that, when executed by the processor 802 cause the device 800 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such as system memory or another type of memory. In some implementations, the code may not be directly executable by the processor 802 but may cause a computer (e.g., when compiled and executed) to perform functions described herein. In some implementations, the memory 804 may include, among other things, a basic I/O system (BIOS) which may control basic hardware or software operation such as the interaction with peripheral components or devices.

The I/O controller 808 may manage input and output signals for the device 800. The I/O controller 808 may also manage peripherals not integrated into the device M02. In some implementations, the I/O controller 808 may represent a physical connection or port to an external peripheral. In some implementations, the I/O controller 808 may utilize an operating system such as or another known operating system. In some implementations, the I/O controller 808 may be implemented as part of a processor, such as the processor 806. In some implementations, a user may interact with the device 800 via the I/O controller 808 or via hardware components controlled by the I/O controller 808.

In some implementations, the device 800 may include a single antenna 810. However, in some other implementations, the device 800 may have more than one antenna 810 (i.e., multiple antennas) , including multiple antenna panels or antenna arrays, which may be capable of concurrently transmitting or receiving multiple wireless transmissions. The transceiver 806 may communicate bi-directionally, via the one or more antennas 810, wired, or wireless links as described herein. For example, the transceiver 806 may represent a wireless transceiver and may communicate bi-directionally with another wireless transceiver. The transceiver 806 may also include a modem to modulate the packets, to provide the modulated packets to one or more antennas 810 for transmission, and to demodulate packets received from the one or more antennas 810. The transceiver 806 may include one or more transmit chains, one or more receive chains, or a combination thereof.

A transmit chain may be configured to generate and transmit signals (e.g., control information, data, packets) . The transmit chain may include at least one modulator for modulating data onto a carrier signal, preparing the signal for transmission over a wireless medium. The at least one modulator may be configured to support one or more techniques such as amplitude modulation (AM) , frequency modulation (FM) , or digital modulation schemes like phase-shift keying (PSK) or quadrature amplitude modulation (QAM) . The transmit chain may also include at least one power amplifier configured to amplify the modulated signal to an appropriate power level suitable for transmission over the wireless medium. The transmit chain may also include one or more antennas 810 for transmitting the amplified signal into the air or wireless medium.

A receive chain may be configured to receive signals (e.g., control information, data, packets) over a wireless medium. For example, the receive chain may include one or more antennas 810 for receive the signal over the air or wireless medium. The receive chain may include at least one amplifier (e.g., a low-noise amplifier (LNA) ) configured to amplify the received signal. The receive chain may include at least one demodulator configured to demodulate the receive signal and obtain the transmitted data by reversing the modulation technique applied during transmission of the signal. The receive chain may include at least one decoder for decoding the processing the demodulated signal to receive the transmitted data.

Fig. 9 illustrates an example of a processer 900 that supports AI/ML enabled TA prediction in accordance with other aspects of the present disclosure. The processor 900 may be an example of a processor configured to perform various operations in accordance with examples as described herein. The processor 900 may include a controller 902 configured to perform various operations in accordance with examples as described herein. The processor 900 may optionally include at least one memory 904. Additionally, or alternatively, the processor 900 may optionally include one or more arithmetic-logic units (ALUs) 906. One or more of these components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces (e.g., buses) .

The processor 900 may be a processor chipset and include a protocol stack (e.g., a software stack) executed by the processor chipset to perform various operations (e.g., receiving, obtaining, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, reading) in accordance with examples as described herein. The processor chipset may include one or more cores, one or more caches (e.g., memory local to or included in the processor chipset (e.g., the processor 900) or other memory (e.g., random access memory (RAM) , read-only memory (ROM) , dynamic RAM (DRAM) , synchronous dynamic RAM (SDRAM) , static RAM (SRAM) , ferroelectric RAM (FeRAM) , magnetic RAM (MRAM) , resistive RAM (RRAM) , flash memory, phase change memory (PCM) , and others) .

The controller 902 may be configured to manage and coordinate various operations (e.g., signaling, receiving, obtaining, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, reading) of the processor 900 to cause the processor 900 to support various operations in accordance with examples as described herein. For example, the controller 902 may operate as a control unit of the processor 900, generating control signals that manage the operation of various components of the processor 900. These control signals include enabling or disabling functional units, selecting data paths, initiating memory access, and coordinating timing of operations.

The controller 902 may be configured to fetch (e.g., obtain, retrieve, receive) instructions from the memory 904 and determine subsequent instruction (s) to be executed to cause the processor 900 to support various operations in accordance with examples as described herein. The controller 902 may be configured to track memory address of instructions associated with the memory 904. The controller 902 may be configured to decode instructions to determine the operation to be performed and the operands involved. For example, the controller 902 may be configured to interpret the instruction and determine control signals to be output to other components of the processor 900 to cause the processor 900 to support various operations in accordance with examples as described herein. Additionally, or alternatively, the controller 902 may be configured to manage flow of data within the processor 900. The controller 902 may be configured to control transfer of data between registers, arithmetic logic units (ALUs) , and other functional units of the processor 900.

The memory 904 may include one or more caches (e.g., memory local to or included in the processor 900 or other memory, such RAM, ROM, DRAM, SDRAM, SRAM, MRAM, flash memory, etc. In some implementation, the memory 904 may reside within or on a processor chipset (e.g., local to the processor 900) . In some other implementations, the memory 904 may reside external to the processor chipset (e.g., remote to the processor 900) .

The memory 904 may store computer-readable, computer-executable code including instructions that, when executed by the processor 900, cause the processor 900 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such as system memory or another type of memory. The controller 902 and/or the processor 900 may be configured to execute computer-readable instructions stored in the memory 904 to cause the processor 900 to perform various functions (e.g., functions or tasks supporting transmit power prioritization) . For example, the processor 900 and/or the controller 902 may be coupled with or to the memory 904, the processor 900, the controller 902, and the memory 904 may be configured to perform various functions described herein. In some examples, the processor 900 may include multiple processors and the memory 904 may include multiple memories. One or more of the multiple processors may be coupled with one or more of the multiple memories, which may, individually or collectively, be configured to perform various functions herein.

The one or more ALUs 906 may be configured to support various operations in accordance with examples as described herein. In some implementation, the one or more ALUs 906 may reside within or on a processor chipset (e.g., the processor 900) . In some other implementations, the one or more ALUs 906 may reside external to the processor chipset (e.g., the processor 900) . One or more ALUs 906 may perform one or more computations such as addition, subtraction, multiplication, and division on data. For example, one or more ALUs 906 may receive input operands and an operation code, which determines an operation to be executed. One or more ALUs 906 be configured with a variety of logical and arithmetic circuits, including adders, subtractors, shifters, and logic gates, to process and manipulate the data according to the operation. Additionally, or alternatively, the one or more ALUs 906 may support logical operations such as AND, OR, exclusive-OR (XOR) , not-OR (NOR) , and not-AND (NAND) , enabling the one or more ALUs 906 to handle conditional operations, comparisons, and bitwise operations.

The processor 900 may support wireless communication in accordance with examples as disclosed herein. The processor 900 may be configured to operable to support a means for performing the following: obtaining historical TA information; performing TA prediction to generate predicted TA information for a UE based at least on the historical TA information; and transmitting the predicted TA information to the UE.

Alternatively, in some implementations, the processor 900 may be configured to operable to support a means for performing the following: transmitting historical TA information to a network entity; and receiving predicted TA information from the network entity.

Alternatively, in some implementations, the processor 900 may be configured to operable to support a means for performing the following: receiving a third configuration for TA prediction from a network entity; performing the TA prediction to generate predicted TA information based at least on the third configuration; and applying the predicted TA information.

Alternatively, in some implementations, the processor 900 may be configured to operable to support a means for performing the following: transmitting a third configuration for TA prediction to a UE; and receiving uplink transmission based on predicted TA information.

Fig. 10 illustrates a flowchart of a method 1000 that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure. The operations of the method 1000 may be implemented by a device or its components as described herein. For example, the operations of the method 1000 may be performed by the network entity 102 as described herein. In some implementations, the device may execute a set of instructions to control the function elements of the device to perform the described functions. Additionally, or alternatively, the device may perform aspects of the described functions using special-purpose hardware.

At 1010, the method may include obtaining historical TA information. The operations of 1010 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1010 may be performed by a device as described with reference to Fig. 1.

At 1020, the method may include performing TA prediction to generate predicted TA information for a UE based at least on the historical TA information. The operations of 1020 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1020 may be performed by a device as described with reference to Fig. 1.

At 1030, the method may include transmitting the predicted TA information to the UE. The operations of 1030 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1030 may be performed by a device as described with reference to Fig. 1.

Fig. 11 illustrates a flowchart of a method 1100 that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure. The operations of the method 1100 may be implemented by a device or its components as described herein. For example, the operations of the method 1100 may be performed by the UE 104 as described herein. In some implementations, the device may execute a set of instructions to control the function elements of the device to perform the described functions. Additionally, or alternatively, the device may perform aspects of the described functions using special-purpose hardware.

At 1110, the method may include transmitting historical TA information to a network entity. The operations of 1110 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1110 may be performed by a device as described with reference to Fig. 1.

At 1120, the method may include receiving predicted TA information from the network entity. The operations of 1120 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1120 may be performed by a device as described with reference to Fig. 1.

Fig. 12 illustrates a flowchart of a method 1200 that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure. The operations of the method 1200 may be implemented by a device or its components as described herein. For example, the operations of the method 1200 may be performed by the UE 104 as described herein. In some implementations, the device may execute a set of instructions to control the function elements of the device to perform the described functions. Additionally, or alternatively, the device may perform aspects of the described functions using special-purpose hardware.

At 1210, the method may include receiving a third configuration for TA prediction from a network entity. The operations of 1210 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1210 may be performed by a device as described with reference to Fig. 1.

At 1220, the method may include performing the TA prediction to generate predicted TA information based at least on the third configuration. The operations of 1220 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1220 may be performed by a device as described with reference to Fig. 1.

At 1230, the method may include applying the predicted TA information. The operations of 1230 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1230 may be performed by a device as described with reference to Fig. 1.

Fig. 13 illustrates a flowchart of a method 1300 that supports AI/ML enabled TA prediction in accordance with aspects of the present disclosure. The operations of the method 1300 may be implemented by a device or its components as described herein. For example, the operations of the method 1300 may be performed by the network entity 102 as described herein. In some implementations, the device may execute a set of instructions to control the function elements of the device to perform the described functions. Additionally, or alternatively, the device may perform aspects of the described functions using special-purpose hardware.

At 1310, the method may include transmitting a third configuration for TA prediction to a UE. The operations of 1310 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1310 may be performed by a device as described with reference to Fig. 1.

At 1320, the method may include receiving uplink transmission based on predicted TA information. The operations of 1320 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1320 may be performed by a device as described with reference to Fig. 1.

It shall be understood that the implementations described with reference to Figs. 2 to 7 are also applicable to the device 800, the processor 900 as well as the methods 1000, 1100, 1200 and 1300. Details of these implementations are omitted for brevity.

It should be noted that the methods described herein describes possible implementations, and that the operations and the steps may be rearranged or otherwise modified and that other implementations are possible. Further, aspects from two or more of the methods may be combined.

The various illustrative blocks and components described in connection with the disclosure herein may be implemented or performed with a general-purpose processor, a DSP, an ASIC, a CPU, an FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices (e.g., a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Other examples and implementations are within the scope of the disclosure and appended claims. For example, due to the nature of software, functions described herein may be implemented using software executed by a processor, hardware, firmware, hardwiring, or combinations of any of these. Features implementing functions may also be physically located at various positions, including being distributed such that portions of functions are implemented at different physical locations.

Computer-readable media includes both non-transitory computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A non-transitory storage medium may be any available medium that may be accessed by a general-purpose or special-purpose computer. By way of example, non-transitory computer-readable media may include RAM, ROM, electrically erasable programmable ROM (EEPROM) , flash memory, compact disk (CD) ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that may be used to carry or store desired program code means in the form of instructions or data structures and that may be accessed by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor.

As used herein, including in the claims, an article “a” before an element is unrestricted and understood to refer to “at least one” of those elements or “one or more” of those elements. The terms “a, ” “at least one, ” “one or more, ” and “at least one of one or more” may be interchangeable. As used herein, including in the claims, “or” as used in a list of items (e.g., a list of items prefaced by a phrase such as “at least one of” or “one or more of” or “one or both of” ) indicates an inclusive list such that, for example, a list of at least one of A, B, or C means A or B or C or AB or AC or BC or ABC (i.e., A and B and C) . Also, as used herein, the phrase “based on” shall not be construed as a reference to a closed set of conditions. For example, an example step that is described as “based on condition A” may be based on both a condition A and a condition B without departing from the scope of the present disclosure. In other words, as used herein, the phrase “based on” shall be construed in the same manner as the phrase “based at least in part on. Further, as used herein, including in the claims, a “set” may include one or more elements.

The description herein is provided to enable a person having ordinary skill in the art to make or use the disclosure. Various modifications to the disclosure will be apparent to a person having ordinary skill in the art, and the generic principles defined herein may be applied to other variations without departing from the scope of the disclosure. Thus, the disclosure is not limited to the examples and designs described herein but is to be accorded the broadest scope consistent with the principles and novel features disclosed herein.

Claims

A network entity, comprising:

a processor; and

a transceiver coupled to the processor,

wherein the processor is configured to:

obtain historical timing advance (TA) information;

perform TA prediction to generate predicted TA information for a user equipment (UE) based at least on the historical TA information; and

transmit the predicted TA information via the transceiver to the UE.
The network entity of claim 1, wherein the processor is configured to obtain the historical TA information from the UE; and

wherein the processor is further configured to transmit, via the transceiver to the UE, a first configuration for logging the historical TA information.
The network entity of claim 1, wherein the network entity comprises a central unit (CU) and a distributed unit (DU) , and the CU obtains at least part of the historical TA information from the DU; and

wherein the processor is further configured to transmit, via the transceiver from the CU to the DU, a first configuration for logging the historical TA information.
The network entity of claim 2 or 3, wherein the first configuration indicates at least one of the following:

the historical TA information to be logged,

a type of logging the historical TA information,

at least one condition for reporting the logged historical TA information,

an identity of data collection for the TA prediction, or

identities of UEs, historical TA information of which is to be logged.
The network entity of claim 4, wherein the historical TA information to be logged comprises at least one of the following:

a historical TA value that is applied for uplink transmission,

a time duration during which the UE applies the historical TA value,

a remaining value of a time alignment timer,

a location of the UE at the time of logging the historical TA value,

measurements information at the time of logging the historical TA value,

an identity of a serving cell of the UE at the time of logging the historical TA value,

an identity of a beam that is applied by the UE at the time of logging the historical TA value, or

time when the historical TA value is logged.
The network entity of claim 4, wherein the type of logging the historical TA information comprises one of the following:

periodical logging of the historical TA information, or

logging the historical TA information based on at least one event.
The network entity of claim 1, wherein the predicted TA information comprises at least one of the following:

a list of a predicted TA value and information about time when the predicted TA value is to be applied,

a list of the predicted TA value and information about a location where the predicted TA value is to be applied,

a predicted time alignment timer, or

a prediction that a current TA will expire or the current TA will be invalid at first time.
The network entity of claim 1, wherein the processor is further configured to:

transmit a first indication via the transceiver to the UE, wherein the first indication indicates whether the UE should apply the predicted TA information.
A user equipment (UE) , comprising:

a processor; and

a transceiver coupled to the processor,

wherein the processor is configured to:

transmit historical timing advance (TA) information via the transceiver to a network entity; and

receive predicted TA information via the transceiver from the network entity.
The UE of claim 9, wherein the predicted TA information comprises at least one of the following:

a list of a predicted TA value and information about time when the predicted TA value is to be applied,

a list of the predicted TA value and information about a location where the predicted TA value is to be applied,

a predicted time alignment timer, or

a prediction that a current TA will expire or the current TA will be invalid at first time.
The UE of claim 9, wherein the processor is further configured to:

receive a first indication via the transceiver from the network entity, wherein the first indication indicates whether the UE should apply the predicted TA information.
A user equipment (UE) , comprising:

a processor; and

a transceiver coupled to the processor,

wherein the processor is configured to:

receive a third configuration for timing advance (TA) prediction via the transceiver from a network entity;

perform the TA prediction to generate predicted TA information based at least on the third configuration; and

apply the predicted TA information.
The UE of claim 12, wherein the third configuration for TA prediction comprises at least one of the following:

historical TA information,

at least one model that is used for the TA prediction in the UE,

at least one condition for starting or stopping the TA prediction in the UE,

accuracy of the TA prediction, or

a time duration during with a predicted TA value is to be applied.
The UE of claim 12, wherein the processor is further configured to:

transmit capability information via the transceiver to the network entity, wherein the capability information indicates that the UE supports artificial intelligence (AI) or machine learning (ML) functionality of the TA prediction or indicates that the UE supports AI/ML enabled TA prediction.
The UE of claim 12, wherein the processor is further configured to:

receive a fourth configuration for applicability determination via the transceiver from the network entity; and

determine whether the TA prediction is applicable for based on the fourth configuration.
The UE of claim 15, wherein the processor is further configured to:

based on determining that the TA prediction is applicable, transmit a fourth indication via the transceiver to the network entity, wherein the fourth indication indicates the TA prediction is applicable.
The UE of claim 12, wherein the predicted TA information comprises at least one of the following:

a list of a predicted TA value and information about time when the predicted TA value is to be applied,

a list of the predicted TA value and information about a location where the predicted TA value is to be applied,

a predicted time alignment timer, or

a prediction that a current TA will expire or the current TA will be invalid at first time.
The UE of claim 12, wherein the processor is further configured to:

receive a first indication via the transceiver from the network entity, wherein the first indication indicates whether the UE should apply the predicted TA information; and

wherein the processor is configured to apply the predicted TA information based on determining that the first indication indicates that the UE should apply the predicted TA information.
The UE of claim 12, wherein the predicted TA information is for a neighbour cell; and

wherein the processor is further configured to receive a fourth indication via the transceiver from the network entity, the fourth indication indicates one of the following:

the predicted TA information is applied in an initial access procedure to the neighbour cell, or

the predicted TA information is applied in both the initial access procedure and subsequent uplink transmission in the neighbour cell; and

wherein the processor is configured to apply the predicted TA information for the neighbour cell based on the fourth indication.
A network entity, comprising:

a processor; and

a transceiver coupled to the processor,

wherein the processor is configured to:

transmit a third configuration for timing advance (TA) prediction via the transceiver to a user equipment (UE) ; and

receive uplink transmission based on predicted TA information.