WO2025241592A1

WO2025241592A1 - Cause detection of a problem related to mobility

Info

Publication number: WO2025241592A1
Application number: PCT/CN2025/074899
Authority: WO
Inventors: Mingzeng Dai; Lianhai WU; Le Yan; Congchi ZHANG
Original assignee: Lenovo Beijing Ltd
Current assignee: Lenovo Beijing Ltd
Priority date: 2025-01-24
Filing date: 2025-01-24
Publication date: 2025-11-27
Anticipated expiration: 2027-07-24

Abstract

Various aspects of the present disclosure relate to cause detection of a problem related to mobility. In one aspect, a UE transmits, to a first base station, first information related to mobility prediction based on AI or ML. Then, the UE determines occurrence of a problem related to mobility of the UE. In turn, the UE transmits a report related to the occurrence of the problem related to mobility of the UE to the first base station or a second base station. The report comprises second information related to a problem of the mobility prediction.

Description

CAUSE DETECTION OF A PROBLEM RELATED TO MOBILITY

TECHNICAL FIELD

The present disclosure relates to wireless communications, and more specifically to user equipment (UE) , base stations and methods for cause detection of a problem related to mobility.

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 the third generation partnership project (3GPP) , there is a study on artificial intelligence (AI) /machine learning (ML) for mobility. For example, mobility prediction based on AI/ML may comprise at least one of the following: measurement result prediction with UE sided model or network sided model, handover failure (HOF) or radio link failure (RLF) prediction with UE sided model, or measurement event prediction with UE sided model.

The goals of AI/ML for mobility are to reduce measurement efforts in temporal, spatial or frequency domain by using predicted measurements and to improve the handover performance (e.g., Ping-pong handover, HOF/RLF, short time of stay, handover interruption) .

In some cases, a base station may use the predicted mobility information (including at least one of predicted measurement results, predicted measurement event, or predicted RLF/HOF information) for making a decision on mobility of a UE.

During a mobility procedure, a problem related to mobility may occur. For example, the UE may subject to HOF or RLF or sub-optimal successful handover.

Traditionally, the base station may determine a cause of the problem to be one of the following: too early handover, too late handover and handover to wrong cell, sub-optimal successful handover. Then, the base station may adjust corresponding mobility parameters. However, for AI/ML based mobility, inaccuracy of predicted measurement results could be the primary cause of the problem related to mobility. Thus, how to distinguish the problem caused by inaccuracy of prediction from that caused by the traditional failures needs to be solved.

SUMMARY

The present disclosure relates to UE, base stations and methods that support cause detection of a problem related to mobility. With the UE, base stations, and methods, when a problem related to mobility of the UE occurs, the base station can determine the cause of the problem related to mobility so as to improve performance of mobility.

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, via the transceiver to a first base station, first information related to mobility prediction based on AI or ML; determine occurrence of a problem related to mobility of the UE; and transmit a report related to the occurrence of the problem related to mobility of the UE via the transceiver to the first base station or a second base station, wherein the report comprises second information related to a problem of the mobility prediction.

In some implementations, the first information related to mobility prediction comprises predicted measurement results for a first time instance. In such implementations, the second information related to the problem of the mobility prediction comprises at least one of the following: a first indication indicating whether the UE has actual measurements results for the first time instance for a last serving cell or a neighbour cell when the problem related to mobility occurs, a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station or when the problem related to mobility occurs, a third indication indicating whether the UE has performed actual measurements at the first time instance to obtain the actual measurements results, the predicted measurement results for the first time instance, or an identity of the mobility prediction.

In some implementations, the processor is further configured to: determine that the UE has the actual measurements results for the first time instance; determine a difference between the actual measurement results for the first time instance and the predicted measurement results for the first time instance; and/or determine whether the predicted measurement results are inaccurate based on the difference and a first threshold.

In some implementations, the second information related to the problem of the mobility prediction further comprises at least one of the following: the actual measurements results for the first time instance, the difference between the actual measurement results for the first time instance and the predicted measurement results for the first time instance, or a fourth indication indicating the predicted measurement results are inaccurate.

In some implementations, the first time instance is before the second time instance when the UE receives the command for the mobility from the first base station or when the problem related to mobility occurs. In such implementations, the second information related to the problem of the mobility prediction further comprises at least one of the following: the actual measurements results for the first time instance, last measurements results for a third time instance before the second time instance, a fifth indication indicating whether the last measurements results were obtained before or after the first time instance, or the third time instance.

In some implementations, the first information related to mobility prediction comprises a predicted measurement event for a first time instance. In such implementations, the second information related to the problem of the mobility prediction comprises at least one of the following: a sixth indication indicating whether the UE is able to perform actual measurement at the first time instance, a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station or when the problem related to mobility occurs, a third indication indicating whether the UE has performed actual measurements at the first time instance to obtain the actual measurements results, or the predicted measurement event for the first time instance.

In some implementations, the processor is further configured to: based on determining that the UE is able to perform the actual measurement at the first time instance, include an actual status of a measurement event in the second information related to the problem of the mobility prediction.

In some implementations, the actual status of the measurement event indicates at least one of the following: whether the actual measurement event is fulfilled at the first time instance, whether an entering condition of the actual measurement event is fulfilled at the first time instance, or whether the actual measurement event is triggered at the first time instance.

In some implementations, the actual status of the measurement event indicates that the actual measurement event is not fulfilled at the first time instance. In such implementations, the second information related to the problem of the mobility prediction further comprises a fourth indication indicating the predicted measurement results are inaccurate.

In some implementations, the problem related to mobility of the UE comprises one of the following: HOF, RLF, or sub-optimal successful handover.

In some implementations, the problem related to mobility of the UE comprises RLF. In such implementations, the first information related to mobility prediction comprises a predicted probability of the occurrence of the RLF at a first time instance or within a time window. The second information related to the problem of the mobility prediction comprises at least one of the following: a seventh indication indicating whether the UE is able to evaluate actual radio link condition at the first time instance or within the time window, an eighth indication indicating whether the UE tends to suffer or actually suffers the RLF at the first time instance or within the time window, a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station, or a fourth indication indicating the predicted measurement results are inaccurate, or the actual radio link condition at the first time instance or within the time window.

In some implementations, the processor is configured to transmit the report related to the occurrence of the problem related to mobility of the UE by: transmitting, via the transceiver to the second base station, the report together with an identity of a last serving cell of the UE.

Some implementations of a first base station described herein may include a processor and a transceiver coupled to the processor, wherein the processor is configured to: receive, via the transceiver from a UE, first information related to mobility prediction based on AI or ML; and transmit, based on the first information, a command for mobility of the UE via the transceiver to the UE.

In some implementations, the processor is further configured to: receive, via the transceiver from the UE or a second base station, a report related to occurrence of a problem related to mobility of the UE, wherein the report comprises second information related to a problem of the mobility prediction; and determine, based on the second information, whether the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction.

In some implementations, the second information related to the problem of the mobility prediction further comprises at least one of the following: the actual measurements results for the first time instance, a difference between the actual measurement results for the first time instance and the predicted measurement results for the first time instance, or a fourth indication indicating the predicted measurement results are inaccurate.

In some implementations, the first time instance is before the second time instance when the UE receives the command for the mobility from the first base station. In such implementations, the second information related to the problem of the mobility prediction further comprises at least one of the following: the actual measurements results for the first time instance, last measurements results for a third time instance before the second time instance, a fifth indication indicating whether the last measurements results were obtained before or after the first time instance, or the third time instance.

In some implementations, the processor is configured to determine whether the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction by: determining the predicted measurement results are inaccurate based on comparison of the predicted measurement results with the actual measurements results; and determining the problem related to mobility of the UE is caused by inaccuracy of the predicted measurement results.

In some implementations, the first information related to mobility prediction comprises a predicted measurement event for a first time instance. In such implementations, the second information related to the problem of the mobility prediction comprises at least one of the following: a sixth indication indicating whether the UE is able to perform actual measurement at the first time instance, a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station, a third indication indicating whether the UE has performed actual measurements at the first time instance to obtain the actual measurements results, or the predicted measurement event for the first time instance.

In some implementations, the second information related to the problem of the mobility prediction further comprises an actual status of a measurement event.

In some implementations, the processor is configured to determine whether the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction by: determining the predicted measurement event is inaccurate based on comparison of the predicted measurement event with the actual status of the measurement event; and determining the problem related to mobility of the UE is caused by inaccuracy of the predicted measurement event.

In some implementations, the problem related to mobility of the UE comprises RLF. In such implementations, the first information related to mobility prediction comprises a predicted probability of the occurrence of the RLF at a first time instance or within a time window. The second information related to the problem of the mobility prediction comprises at least one of the following: a seventh indication indicating whether the UE is able to evaluate actual radio link condition at the first time instance or within the time window, an eighth indication indicating whether the UE tends to suffer or actually suffers the RLF at the first time instance or within the time window, a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station, a fourth indication indicating the predicted measurement results are inaccurate, or the actual radio link condition at the first time instance or within the time window.

In some implementations, the processor is configured to determine whether the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction by: determining the predicted probability of the occurrence of the RLF is inaccurate based on the actual radio link condition at the first time instance or within the time window and the predicted probability of the occurrence of the RLF; and determining the problem related to mobility of the UE is caused by inaccuracy of the predicted probability.

In some implementations, the processor is configured to receive the report related to occurrence of the problem related to mobility of the UE from the second base station. In such implementations, the processor is further configured to: based on determining that the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction, transmit a ninth indication via the transceiver to the second base station. The ninth indication indicates a problem of the mobility prediction.

In some implementations, the ninth indication indicates the problem of the mobility prediction by indicating the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction.

In some implementations, the ninth indication further indicates at least one of the following: predicted measurement results before the occurrence of the problem related to mobility of the UE are inaccurate, a predicted measurement event before the occurrence of the problem related to mobility of the UE is inaccurate, or a predicted probability of occurrence of the RLF before the occurrence of the RLF is inaccurate.

Some implementations of a second base station described herein may include a processor and a transceiver coupled to the processor, wherein the processor is configured to: receive, via the transceiver from a UE, a report related to occurrence of a problem related to mobility of the UE, wherein the report comprises second information related to a problem of mobility prediction based on AI or ML; and perform one of the following: transmitting, via the transceiver to a first base station, the report related to the occurrence of the problem related to mobility of the UE; or determining, based on the second information, whether the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction.

In some implementations, the processor is configured to receive a ninth indication via the transceiver from the first base station. The ninth indication indicates a problem of the mobility prediction.

In some implementations, the processor is further configured to: deactivate, stop or release a procedure for the mobility prediction for the UE based on the ninth indication.

In some implementations, the second information related to the problem of the mobility prediction comprises at least one of the following: a first indication indicating whether the UE has actual measurements results for the first time instance for a last serving cell or a neighbour cell when the problem related to mobility occurs, a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station or when the problem related to mobility occurs, a third indication indicating whether the UE has performed actual measurements at the first time instance to obtain the actual measurements results, the predicted measurement results for the first time instance, or an identity of the mobility prediction.

In some implementations, the second information related to the problem of the mobility prediction comprises at least one of the following: a sixth indication indicating whether the UE is able to perform actual measurement at the first time instance, a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station, a third indication indicating whether the UE has performed actual measurements at the first time instance to obtain the actual measurements results, or the predicted measurement event for the first time instance.

In some implementations, the problem related to mobility of the UE comprises RLF. In such implementations, the second information related to the problem of the mobility prediction comprises at least one of the following: a seventh indication indicating whether the UE is able to evaluate actual radio link condition at the first time instance or within the time window, an eighth indication indicating whether the UE tends to suffer or actually suffers the RLF at the first time instance or within the time window, a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station, a fourth indication indicating the predicted measurement results are inaccurate, or the actual radio link condition at the first time instance or within the time window.

Some implementations of a method described herein may include: transmitting, to a first base station, first information related to mobility prediction based on AI or ML; determining occurrence of a problem related to mobility of the UE; and transmitting a report related to the occurrence of the problem related to mobility of the UE to the first base station or a second base station, wherein the report comprises second information related to a problem of the mobility prediction.

Some implementations of a method described herein may include: receiving, from a UE, first information related to mobility prediction based on AI or ML; and transmitting, based on the first information, a command for mobility of the UE to the UE.

Some implementations of a method described herein may include: receiving, from a UE, a report related to occurrence of a problem related to mobility of the UE, wherein the report comprises second information related to a problem of mobility prediction based on AI or ML; and performing one of the following: transmitting, to a first base station, the report related to the occurrence of the problem related to mobility of the UE; or determining, based on the second information, whether the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction.

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, to a first base station, first information related to mobility prediction based on AI or ML; determine occurrence of a problem related to mobility of the UE; and transmit a report related to the occurrence of the problem related to mobility of the UE to the first base station or a second base station, wherein the report comprises second information related to a problem of the mobility prediction.

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 cause detection of a problem related to mobility in accordance with aspects of the present disclosure;

Fig. 2 illustrates another example of a wireless communications system that supports cause detection of a problem related to mobility in accordance with aspects of the present disclosure;

Fig. 3 illustrates a signaling diagram illustrating an example process that supports cause detection of a problem related to mobility in accordance with aspects of the present disclosure;

Figs. 4A, 4B and 4C illustrate an example of timing of the process in Fig. 3 in accordance with aspects of the present disclosure, respectively;

Fig. 5 illustrates a signaling diagram illustrating an example process that supports cause detection of a problem related to mobility in accordance with aspects of the present disclosure;

Fig. 6 illustrates an example of a device that supports cause detection of a problem related to mobility in accordance with some aspects of the present disclosure;

Fig. 7 illustrates an example of a processor that supports cause detection of a problem related to mobility in accordance with aspects of the present disclosure; and

Figs. 8 to 10 illustrate a flowchart of a method that supports cause detection of a problem related to mobility in accordance with aspects of the present disclosure, respectively.

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, a base station may use the predicted mobility information for making a decision on mobility of a UE. Traditionally, when a problem related to mobility occurs, the base station may determine a cause of the problem be one of the following: too early handover, too late handover and handover to wrong cell, sub-optimal successful handover. However, for AI/ML based mobility, inaccuracy of predicted measurement results could be the primary cause of the problem related to mobility. Thus, how to distinguish the problem caused by inaccuracy of prediction from that caused by the traditional failures needs to be solved.

In view of the above, the present disclosure provides a solution that supports cause detection of a problem related to mobility. In this solution, a UE transmits, to a first base station, first information related to mobility prediction based on AI or ML. Then, the UE determines occurrence of a problem related to mobility of the UE. In turn, the UE transmits a report related to the occurrence of the problem related to mobility of the UE to the first base station or a second base station. The report comprises second information related to a problem of the mobility prediction. With this solution, when a problem related to mobility of the UE occurs, the first base station or the second base station can determine the cause of the problem related to mobility so as to improve performance of mobility.

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 cause detection of a problem related to mobility 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 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) , 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. Hereinafter, some implementations of the present disclosure will be described by taking base stations as an example of the network entities 102. Thus, the network entity 102 may be used interchangeably with base stations 102. For example, the base stations 102 may comprise a first base station 102-1 and a second base station 102-2.

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., an L3, an 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 an 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 another example of a wireless communications system 200 that supports cause detection of a problem related to mobility in accordance with aspects of the present disclosure. As shown in Fig. 2, the wireless communications system 200 may comprise the first base station 102-1, the second base station 102-2 and the UE 104. The second base station 102-2 is different from the first base station 102-1.

In some implementations, initially, the UE 104 may access to a first cell of the first base station 102-1. Then, the UE 104 may perform a mobility procedure to a second cell of the second base station 102-2.

In some implementations, the UE 104 may perform the mobility procedure by performing handover. In such implementations, the first base station 102-1 and the first cell may be referred to as a source base station 102-1 and a source cell, respectively. The second base station 102-2 and the second cell may be referred to as a target base station 102-2 and a target cell, respectively.

Alternatively, in some implementations, the UE 104 may perform the mobility procedure by detecting radio link failure (RLF) or handover failure (HOF) or by performing an RRC state transition. In such implementations, the first base station 102-1 and the first cell may be referred to as a last serving base station 102-1 and a last serving cell, respectively. The second base station 102-2 may be referred to as an establishment base station 102-2 or reestablishment base station 102-2. The second cell may be referred to as an establishment cell or reestablishment cell.

In some implementations, initially, the UE 104 may access to the first cell of the first base station 102-1. Then, the UE 104 may perform a mobility procedure to a second cell of the second base station 102-2. After a problem related to the mobility occurs, the UE 104 may reconnect to a third cell of the first base station 102-1 or the second base station 102-2. The third cell to which the UE 104 reconnects may be the same as or different from the first cell (i.e., the source cell) of the first base station 102-1.

Fig. 3 illustrates a signaling diagram illustrating an example process 300 that supports cause detection of a problem related to mobility in accordance with aspects of the present disclosure. The process 300 may involve the first base station 102-1 and the UE 104 in Fig. 1 or 2.

Generally, in the process 300, initially, the UE 104 accesses to the first cell (i.e., a source cell) of the first base station 102-1. Then, the UE 104 may perform a mobility procedure to a second cell. After a problem related to the mobility occurs, the UE 104 may reconnect to a third cell of the first base station 102-1. The third cell to which the UE 104 reconnects may be the same as or different from the first cell (i.e., the source cell) of the first base station 102-1.

As shown in Fig. 3, the UE 104 transmits 310, to the first base station 102-1, first information related to mobility prediction based on AI or ML.

In some implementations, the first base station 102-1 may transmit, to the UE 104, a configuration for reporting the first information related to mobility prediction. The UE 104 may transmits the first information related to mobility prediction to the first base station 102-1 based on the configuration.

In some implementations, the first information related to mobility prediction may comprise at least one of the following: predicted measurement results, a predicted measurement event or a predicted probability of occurrence of RLF.

In some implementations, the predicted measurement results may comprise at least one of the following: predicted L3 cell or beam level measurements results (e.g L3 reference signal received power (RSRP) ) , or predicted L1 beam level measurement results (e.g. L1 RSRP) based on one or more actual L3 cell-level measurement results and/or one or more actual L1 cell-level measurement results. The predicted measurement results may be for serving cells or for one or more neighbour cells. The predicted measurement results are also referred to as predicted radio resource management (RRM) measurement results。

In some implementations, a measurement event may comprise one of the following:
◆ Event A1: Serving cell becomes better than absolute threshold;
◆ Event A2: Serving cell becomes worse than absolute threshold;
◆ Event A3: Neighbour becomes amount of offset better than primary cell
(PCell) /primary secondary cell (PSCell) ;
◆ Event A4: Neighbour becomes better than absolute threshold; or
◆ Event A5: PCell/PSCell becomes worse than absolute threshold1 AND
Neighbour/SCell becomes better than another absolute threshold2.

In some implementations, the predicted measurement event may comprise one of the predicted measurement events A1, A2, A3, A4 and A5.

In some implementations, RLF can be predicted directly based on one or more actual measurement results, e.g. signal to interference plus noise ratio (SINR) of a PCell. In indirect RLF prediction, based on one or more actual measurement results, one or more PCell measurement results are predicted at first, based on which RLF is derived. The RLF prediction yields a predicted probability that RLF occurs within a time window or at time instance at least for direct RLF prediction.

Fig. 4A illustrates an example of timing of the process 300 in accordance with aspects of the present disclosure. In the example of Fig. 4A, T0 is a time instance when the UE 104 transmits the first information related to mobility prediction to the first base station 102-1. The first information related to mobility prediction may be generated before or at the time instance T0.

In some implementations, the first information related to mobility prediction may comprise at least one of the following: predicted measurement results for a first time instance (represented by T1) , a predicted measurement event for the first time instance T1, or a predicted probability of occurrence of RLF for the first time instance T1 as shown in Fig. 4A or within a time window from a time instance T4 to a time instance T5 as shown in Fig. 4B.

For example, the predicted measurement results for the first time instance T1 may comprise cell or beam level L3-RSRP or beam level L1-RSRP of the serving cell or one or more neighbour cells for the first time instance T1.

For example, the predicted measurement event for the first time instance T1 may comprise a predicted measurement event A3 for the first time instance T1.

Fig. 4B illustrates another example of timing of the process 300 in accordance with aspects of the present disclosure. The example of Fig. 4B is different from the example of Fig. 4A in that the first information related to mobility prediction may comprise a predicted probability of occurrence of RLF within a time window from a time instance T4 to a time instance T5.

Return to Fig. 3, the first base station 102-1 may make 320 a decision on mobility of the UE 104 based on the first information related to mobility prediction.

Based on the first information related to mobility prediction, the first base station 102-1 transmits 330, to the UE 104, a command for mobility of the UE 104. For example, as shown in Figs. 4A and 4B, the first base station 102-1 may transmit the command for mobility to the UE 104 at a second time instance (represented by T2) . Accordingly, the UE 104 may receive the command for mobility at the second time instance T2.

Upon receiving the command for mobility, the UE 104 may perform a mobility procedure based on the command for mobility.

In turn, the UE 104 determines 340 occurrence of a problem related to mobility of the UE 104.

In some implementations, the problem related to mobility of the UE 104 may comprise one of the following: HOF, RLF, or sub-optimal successful handover.

In some implementations, one of the functions of Mobility Robustness Optimization is to detect a sub-optimal successful handover event. The aim is to identify underlying conditions during successful ordinary handovers. The sub-optimal successful handover is also called as “near failure” . Even the handover is successful, but it is almost failures or near failure.

Consider an example. In this example, the first base station 102-1 may make a decision on handover based on the first information related to mobility prediction for the first time instance T1. Then, the first base station 102-1 may transmit a handover command to the UE 104 at the second time instance T2. Accordingly, the UE 104 may receive the handover command at the second time instance T2. For example, the handover command may comprise an RRC Reconfiguration message with synchronization. When receiving the handover command, the UE 104 may start a timer T304. When T304 expires, if the UE 104 has not successfully accessed to a target cell of the second base station 102-2 (for example, the UE 104 has not performed contention resolution successfully in a random access procedure) , the UE 104 determines or declares HOF.

It shall be noted that although the above example has been described by taking HOF as example, the solution of the present disclosure may be applied to RLF.

With continued reference to Fig. 3, upon determining occurrence of the problem related to mobility of the UE 104, the UE 104 may initiate an RRC connection re-establishment procedure.

For example, upon determining the HOF or RLF occurs in the source cell of the first base station 102-1, the UE 104 may initiate an RRC connection re-establishment procedure.

In some implementations, the UE 104 may reconnect to a third cell of the first base station 102-1 during the RRC connection re-establishment procedure. The third cell to which the UE 104 reconnects may be the same as or different from the first cell (i.e., the source cell) of the first base station 102-1.

In some implementations, after the UE 104 reconnects to the first base station 102-1, the UE 104 may transmit 350 a report related to the occurrence of the problem related to mobility to the first base station 102-1.

In some implementations, the report may indicate occurrence of the problem related to mobility. Alternatively, the report may comprise an indication of occurrence of the problem related to mobility.

In some implementations, if the UE 104 determines HOF occurs, the UE 104 may transmit a HOF report to the first base station 102-1. The HOF report may indicate occurrence of HOF. Alternatively, the HOF report may comprise an indication of occurrence of HOF.

Alternatively, in some implementations, if the UE 104 determines RLF occurs, the UE 104 may transmit an RLF report to the first base station 102-1. The RLF report may indicate occurrence of RLF. Alternatively, the RLF report may comprise an indication of occurrence of RLF.

Alternatively, in some implementations, if the UE 104 determines RLF occurs, the UE 104 may transmit a successful handover report (SHR) to the first base station 102-1. The SHR may indicate occurrence of sub-optimal successful handover. Alternatively, the SHR may comprise an indication of occurrence of sub-optimal successful handover. In some implementations, the UE 104 may collect the SHR based on a configuration from the first base station 102-1.

In some implementations, the UE 104 may transmit the report related to the occurrence of the problem related to mobility to the first base station 102-1 upon receiving a request from the first base station 102-1.

The report related to the occurrence of the problem related to mobility comprises second information related to a problem of the mobility prediction.

Upon receiving the report comprising the second information, the first base station 102-1 determines 360, based on the second information, whether the problem related to mobility of the UE 104 is caused by inaccuracy of the mobility prediction. Some implementations of the action 360 will be described later.

In some implementations, the first information related to mobility prediction may comprise predicted measurement results for the first time instance T1. In such implementations, the second information related to the problem of the mobility prediction may comprise at least one of the following:
· a first indication indicating whether the UE 104 has actual measurements
results for the first time instance T1 for a last serving cell or a neighbour cell when the problem related to mobility occurs,
· a second indication indicating whether the first time instance T1 is before
or after a second time instance T2 when the UE 104 receives a command for the mobility from the first base station 102-1 or when the problem related to mobility occurs,
· a third indication indicating whether the UE 104 has performed actual
measurements at the first time instance T1 to obtain the actual measurements results,
● the predicted measurement results for the first time instance T1 (for
example, if the UE 104 stored) , or
● an identity (ID) of the mobility prediction (for example, an association ID
or measurement ID of the measurement prediction) .

In some implementations, if the UE 104 has the actual measurements results for the first time instance T1, the second information related to the problem of the mobility prediction may comprise the actual measurements results for the first time instance T1.

Alternatively or additionally, in some implementations, if the UE 104 has the actual measurements results for the first time instance T1, the UE 104 may determine a difference between the actual measurement results for the first time instance T1 and the predicted measurement results for the first time instance T1. The second information related to the problem of the mobility prediction may comprise the difference between the actual measurement results for the first time instance T1 and the predicted measurement results for the first time instance T1.

Alternatively or additionally, in some implementations, if the UE 104 has the actual measurements results for the first time instance T1, the UE 104 may determine a difference between the actual measurement results for the first time instance T1 and the predicted measurement results for the first time instance T1. The UE 104 may further determine whether the predicted measurement results are inaccurate based on the difference and a first threshold. If the difference is above the first threshold, the UE 104 may determine the predicted measurement results are inaccurate. In turn, the UE 104 may include a fourth indication in the second information related to the problem of the mobility prediction. The fourth indication indicates the predicted measurement results are inaccurate. Alternatively, if the difference is above the first threshold, the UE 104 may include, in the second information related to the problem of the mobility prediction, the difference between the actual measurement results and the predicted measurement results.

In some implementations, the first information related to mobility prediction may comprise a predicted measurement event for the first time instance T1. In such implementations, the second information related to the problem of the mobility prediction may comprise at least one of the following:
· a sixth indication indicating whether the UE 104 is able to perform actual
measurement at the first time instance T1,
· the second indication indicating whether the first time instance T1 is
before or after a second time instance T2 when the UE 104 receives a command for the mobility from the first base station 102-1 or when the problem related to mobility occurs,
· the third indication indicating whether the UE 104 has performed actual
measurements at the first time instance T1 to obtain the actual measurements results, or
● the predicted measurement event for the first time instance T1 (for
example, if the UE 104 stored) .

In some implementations, if the UE 104 is able to perform the actual measurement at the first time instance T1, the UE 104 may include an actual status of a measurement event in the second information related to the problem of the mobility prediction.

In some implementations, the actual status of the measurement event indicates at least one of the following: whether the actual measurement event is fulfilled at the first time instance T1, whether an entering condition of the actual measurement event is fulfilled at the first time instance T1, or whether the actual measurement event is triggered at the first time instance T1.

In some implementations, if the UE 104 has the actual measurements results for the first time instance T1 and the actual status of the measurement event indicates that the actual measurement event is not fulfilled at the first time instance T1, the UE 104 may include a fourth indication in the second information related to the problem of the mobility prediction. The fourth indication indicates the predicted measurement results are inaccurate.

In some implementations, the problem related to mobility of the UE 104 may comprise RLF. In such implementations, the first information related to mobility prediction may comprise a predicted probability of the occurrence of the RLF at the first time instance T1 or within a time window from T4 to T5. The second information related to the problem of the mobility prediction may comprise at least one of the following:
● a seventh indication indicating whether the UE 104 is able to evaluate
actual radio link condition at the first time instance T1 or within the time window from T4 to T5, or
· an eighth indication indicating whether the UE 104 tends to suffer or
actually suffers the RLF at the first time instance T1 or within the time window from T4 to T5.

For example, the seventh indication may indicate whether the UE 104 is able to evaluate actual radio link condition at the first time instance T1 or within the time window from T4 to T5 by indicating whether the UE 104 starts timers T310 and/or T312 (or whether timers T310 and/or T312 are running) at the time instance of T2 or within the time window from T4 to T5.

For example, the UE 104 may start the timer T310 upon detecting physical layer problems for a Special Cell (SpCell) , i.e. upon receiving N310 consecutive out-of-sync indications from lower layers. The UE 104 may stop the timer T310 upon receiving N311 consecutive in-sync indications from lower layers for the SpCell. If the timer T310 expires, the UE 104 may initiate the connection re-establishment procedure.

For example, the UE 104 may start the timer T312 upon triggering a measurement report for a measurement identity for which the timer T312 has been configured. The UE 104 may stop the timer T312 upon receiving N311 consecutive in-sync indications from lower layers for the SpCell. If the timer T312 expires, the UE 104 may initiate the connection re-establishment procedure.

In some implementations, the problem related to mobility of the UE 104 may comprise RLF. In such implementations, the first information related to mobility prediction may comprise a predicted probability of the occurrence of the RLF at the first time instance T1 or within a time window from T4 to T5. The second information related to the problem of the mobility prediction may comprise at least one of the following:
● the second indication indicating whether the first time instance T1 is
before or after a second time instance T2 when the UE 104 receives a command for the mobility from the first base station 102-1, or
· the fourth indication indicating the predicted measurement results are
inaccurate, or
● the actual radio link condition at the first time instance T1 or within the
time window from T4 to T5.

Fig. 4C illustrates a further example of timing of the process 300 in accordance with aspects of the present disclosure. The example of Fig. 4C is different from the examples of Figs. 4A and 4B in that the first time instance T1 is before the second time instance T2 when the UE 104 receives the command for the mobility from the first base station 102-1 or when the problem related to mobility occurs. The last measurement results of the serving cell or neighbour cells is obtained by the UE 104 at a third time instance T3. The time instance T3 is between the first time instance T1 and the second time instance T2.

In example of Fig. 4C, the second information related to the problem of the mobility prediction may further comprise at least one of the following:
· the actual measurements results for the first time instance T1,
· last measurements results for the third time instance T3 before the second
time instance T2,
· a fifth indication indicating whether the last measurements results were
obtained before or after the first time instance T1, or
· the third time instance T3.

For example, the second information related to the problem of the mobility prediction may comprise the actual measurements results for the first time instance T1 and the last measurements results for the third time instance T3.

For another example, the second information related to the problem of the mobility prediction may comprise the last measurements results for the third time instance T3 and the fifth indication indicating whether the last measurements results were obtained before or after the first time instance T1.

For a further example, the second information related to the problem of the mobility prediction may comprise the last measurements results for the third time instance T3 and the third time instance T3.

As described above, upon receiving the report, the first base station 102-1 determines, based on the second information related to the problem of the mobility prediction, whether the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction.

In some implementations, if the first information related to mobility prediction comprises the predicted measurement results for the first time instance T1 and the second information related to the problem of the mobility prediction comprises the actual measurements results for the first time instance T1, the first base station 102-1 may compare the predicted measurement results with the actual measurements results. Then, the first base station 102-1 may determine whether the predicted measurement results are inaccurate based on the comparison. For example, if the predicted measurement results are different from the actual measurements results, the first base station 102-1 may determine that the predicted measurement results are inaccurate. In turn, the first base station 102-1 may determine the problem related to mobility of the UE 104 is caused by inaccuracy of the predicted measurement results.

In some implementations, the predicted measurement results may be stored at the first base station 102-1 as a part of UE context or reported by the UE 104 together with the actual measurement results.

In some implementations, if the first information related to mobility prediction comprises the predicated measurement event at the first time instance T1 and the second information related to the problem of the mobility prediction comprises the actual status of the measurement event at the first time instance T1, the first base station 102-1 may compare the actual status of the measurement event with the predicted measurement event. For example, if the actual status of the measurement event is different from a status of the predicted measurement event, the first base station 102-1 may determine that the predicted measurement event is inaccurate. In turn, the first base station 102-1 may determine the problem related to mobility of the UE 104 is caused by inaccuracy of the predicted measurement event

In some implementations, the predicted measurement event may be stored at the first base station 102-1 as a part of UE context or reported by the UE 104 together with the actual status of the measurement event.

In some implementations, if the first information related to mobility prediction comprises the predicted probability of the occurrence of the RLF at the first time instance T1 or within the time window from T4 to T5 and the second information related to the problem of the mobility prediction comprises the actual radio link condition at the first time instance T1 or within the time window from T4 to T5, the first base station 102-1 may determine whether the predicted probability is inaccurate based on the actual radio link condition. If the predicted probability is inaccurate, the first base station 102-1 may determine the problem related to mobility of the UE 104 is caused by inaccuracy of the predicted probability.

Fig. 5 illustrates a signaling diagram illustrating an example process 500 that supports cause detection of a problem related to mobility in accordance with aspects of the present disclosure. The process 500 may involve the first base station 102-1, the second base station 102-2 and the UE 104 in Fig. 1 or 2.

Generally, in the process 500, initially, the UE 104 accesses to the first cell (i.e., a source cell) of the first base station 102-1. Then, the UE 104 may perform a mobility procedure to a second cell of a target base station. After a problem related to the mobility occurs, the UE 104 may reconnect to a third cell of the second base station 102-2. The second base station 102-2 may be the same as or different from the target base station providing the second cell.

Actions 310, 320, 330 and 340 in the process 500 are similar to those in the process 300. Details of these actions are omitted for brevity.

The process 500 is different from the process 300 in actions 510, 520, 530 and 540.

Specifically, after the UE 104 reconnects to the second base station 102-2, the UE 104 may transmit 510 a report related to the occurrence of the problem related to mobility to the second base station 102-2.

In some implementations, if the UE 104 determines HOF occurs, the UE 104 may transmit a HOF report to the second base station 102-2. The HOF report may indicate occurrence of HOF. Alternatively, the HOF report may comprise an indication of occurrence of HOF.

Alternatively, in some implementations, if the UE 104 determines RLF occurs, the UE 104 may transmit an RLF report to the second base station 102-2. The RLF report may indicate occurrence of RLF. Alternatively, the RLF report may comprise an indication of occurrence of RLF.

Alternatively, in some implementations, if the UE 104 determines RLF occurs, the UE 104 may transmit an SHR to the second base station 102-2. The SHR may indicate occurrence of sub-optimal successful handover. Alternatively, the SHR may comprise an indication of occurrence of sub-optimal successful handover.

In some implementations, the UE 104 may transmit the report related to the occurrence of the problem related to mobility to the second base station 102-2 upon receiving a request from the second base station 102-2.

The report related to the occurrence of the problem related to mobility comprises the second information related to the problem of the mobility prediction. Some implementations of the second information have been described above with reference to Figs. 3, 4A, 4B and 4C. Details of such implementations are omitted for brevity.

In some implementations, in addition to the second information, the report related to the occurrence of the problem related to mobility may further comprise an ID of the last serving cell.

In some implementations, the last serving cell may be the source cell or a cell in which the problem related to mobility occurs. For example, the last serving cell may be the source cell or a cell in which the UE 104 suffers to HOF, RLF or sub-optimal successful handover.

In some implementations, when receiving the report related to the occurrence of the problem related to mobility from the UE 104, the second base station 102-2 may transmit 520 the second information related to the problem of the mobility prediction to the first base station 102-1.

In some implementations, the second base station 102-2 may use the ID of the last serving cell to identify the first base station 102-1. In some implementations, the second base station 102-2 may also transmit the ID of the last serving cell to the first base station 102-1.

In some implementations, if the UE 104 determines RLF occurs and trigger of an SHR is the timer T310 or T312, the second base station 102-2 may transmit the second information related to the problem of the mobility prediction to the first base station 102-1. For example, the second base station 102-2 may transmit, to the first base station 102-1, an ACCESS AND MOBILITY INDICATION message over Xn interface. The ACCESS AND MOBILITY INDICATION message may comprise the second information.

Alternatively, in some implementations, if the UE 104 determines RLF occurs and trigger of the SHR is a timer T04, the second base station 102-2 may not transmit the second information related to the problem of the mobility prediction to the first base station 102-1. In such implementations, the second base station 102-2 may determine, based on the second information, whether the problem related to mobility is caused by inaccuracy of the mobility prediction. The second base station 102-2 may determine whether the problem related to mobility is caused by inaccuracy of the mobility prediction by performing an action similar to the action 360 in the process 300. Some implementations of the action 360 have been described above. Details of those implementations are omitted for brevity.

In some implementations, upon receiving the second information related to the problem of the mobility prediction, the first base station 102-1 may determine 530, based on the second information, whether the problem related to mobility is caused by inaccuracy of the mobility prediction. The action 530 is similar to the action 360 in the process 300. Some implementations of the action 360 have been described above. Details of those implementations are omitted for brevity.

In some implementations, if the first base station 102-1 determines the problem related to mobility of the UE 104 is caused by inaccuracy of the mobility prediction, the first base station 102-1 may transmit 540 a ninth indication to the second base station 102-2. The ninth indication indicates a problem of the mobility prediction. Hereinafter, the ninth indication is also referred to as a prediction problem indication.

In some implementations, the prediction problem indication indicates the problem of the mobility prediction by indicating the problem related to mobility of the UE 104 is caused by inaccuracy of the mobility prediction.

In some implementations, the prediction problem indication may further indicate at least one of the following: predicted measurement results before the occurrence of the problem related to mobility of the UE 104 are inaccurate, a predicted measurement event before the occurrence of the problem related to mobility of the UE 104 is inaccurate, or a predicted probability of occurrence of the RLF before the occurrence of the RLF is inaccurate.

In some implementations, upon receiving the prediction problem indication, the second base station 102-2 may deactivate 550, stop or release a procedure for the mobility prediction for the UE 104 based on the prediction problem indication.

Fig. 6 illustrates an example of a device 600 that supports cause detection of a problem related to mobility in accordance with aspects of the present disclosure. The device 600 may be an example of a network entity 102 or a UE 104 as described herein. The device 600 may support wireless communication with one or more network entities 102, UEs 104, or any combination thereof. The device 600 may include components for bi-directional communications including components for transmitting and receiving communications, such as a processor 602, a memory 604, a transceiver 606, and, optionally, an I/O controller 608. 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 602, the memory 604, the transceiver 606, 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 602, the memory 604, the transceiver 606, 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 602, the memory 604, the transceiver 606, 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 602 and the memory 604 coupled with the processor 602 may be configured to perform one or more of the functions described herein (e.g., executing, by the processor 602, instructions stored in the memory 604) .

For example, the processor 602 may support wireless communication at the device 600 in accordance with examples as disclosed herein. The processor 602 may be configured to operable to support a means for performing the following: transmitting, to a first base station, first information related to mobility prediction based on AI or ML; determining occurrence of a problem related to mobility of the UE; and transmitting a report related to the occurrence of the problem related to mobility of the UE to the first base station or a second base station, wherein the report comprises second information related to a problem of the mobility prediction.

Alternatively, the processor 602 may be configured to operable to support a means for performing the following: receiving, from a UE, first information related to mobility prediction based on AI or ML; and transmitting, based on the first information, a command for mobility of the UE to the UE.

Alternatively, the processor 602 may be configured to operable to support a means for performing the following: receiving, from a UE, a report related to occurrence of a problem related to mobility of the UE, wherein the report comprises second information related to a problem of mobility prediction based on AI or ML; and performing one of the following: transmitting, to a first base station, the report related to the occurrence of the problem related to mobility of the UE; or determining, based on the second information, whether the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction.

The processor 602 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 602 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 602. The processor 602 may be configured to execute computer-readable instructions stored in a memory (e.g., the memory 604) to cause the device 600 to perform various functions of the present disclosure.

The memory 604 may include random access memory (RAM) and read-only memory (ROM) . The memory 604 may store computer-readable, computer-executable code including instructions that, when executed by the processor 602 cause the device 600 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 602 but may cause a computer (e.g., when compiled and executed) to perform functions described herein. In some implementations, the memory 604 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 608 may manage input and output signals for the device 600. The I/O controller 608 may also manage peripherals not integrated into the device M02. In some implementations, the I/O controller 608 may represent a physical connection or port to an external peripheral. In some implementations, the I/O controller 608 may utilize an operating system such as or another known operating system. In some implementations, the I/O controller 608 may be implemented as part of a processor, such as the processor 606. In some implementations, a user may interact with the device 600 via the I/O controller 608 or via hardware components controlled by the I/O controller 608.

In some implementations, the device 600 may include a single antenna 610. However, in some other implementations, the device 600 may have more than one antenna 610 (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 606 may communicate bi-directionally, via the one or more antennas 610, wired, or wireless links as described herein. For example, the transceiver 606 may represent a wireless transceiver and may communicate bi-directionally with another wireless transceiver. The transceiver 606 may also include a modem to modulate the packets, to provide the modulated packets to one or more antennas 610 for transmission, and to demodulate packets received from the one or more antennas 610. The transceiver 606 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 610 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 610 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. 7 illustrates an example of a processor 700 that supports cause detection of a problem related to mobility in accordance with aspects of the present disclosure. The processor 700 may be an example of a processor configured to perform various operations in accordance with examples as described herein. The processor 700 may include a controller 702 configured to perform various operations in accordance with examples as described herein. The processor 700 may optionally include at least one memory 704, such as L1/L2/L3 cache. Additionally, or alternatively, the processor 700 may optionally include one or more arithmetic-logic units (ALUs) 706. 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 700 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 700) 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 702 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 700 to cause the processor 700 to support various operations in accordance with examples as described herein. For example, the controller 702 may operate as a control unit of the processor 700, generating control signals that manage the operation of various components of the processor 700. These control signals include enabling or disabling functional units, selecting data paths, initiating memory access, and coordinating timing of operations.

The controller 702 may be configured to fetch (e.g., obtain, retrieve, receive) instructions from the memory 704 and determine subsequent instruction (s) to be executed to cause the processor 700 to support various operations in accordance with examples as described herein. The controller 702 may be configured to track memory address of instructions associated with the memory 704. The controller 702 may be configured to decode instructions to determine the operation to be performed and the operands involved. For example, the controller 702 may be configured to interpret the instruction and determine control signals to be output to other components of the processor 700 to cause the processor 700 to support various operations in accordance with examples as described herein. Additionally, or alternatively, the controller 702 may be configured to manage flow of data within the processor 700. The controller 702 may be configured to control transfer of data between registers, arithmetic logic units (ALUs) , and other functional units of the processor 700.

The memory 704 may include one or more caches (e.g., memory local to or included in the processor 700 or other memory, such RAM, ROM, DRAM, SDRAM, SRAM, MRAM, flash memory, etc. In some implementation, the memory 704 may reside within or on a processor chipset (e.g., local to the processor 700) . In some other implementations, the memory 704 may reside external to the processor chipset (e.g., remote to the processor 700) .

The memory 704 may store computer-readable, computer-executable code including instructions that, when executed by the processor 700, cause the processor 700 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 702 and/or the processor 700 may be configured to execute computer-readable instructions stored in the memory 704 to cause the processor 700 to perform various functions. For example, the processor 700 and/or the controller 702 may be coupled with or to the memory 704, the processor 700, the controller 702, and the memory 704 may be configured to perform various functions described herein. In some examples, the processor 700 may include multiple processors and the memory 704 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 706 may be configured to support various operations in accordance with examples as described herein. In some implementation, the one or more ALUs 706 may reside within or on a processor chipset (e.g., the processor 700) . In some other implementations, the one or more ALUs 706 may reside external to the processor chipset (e.g., the processor 700) . One or more ALUs 706 may perform one or more computations such as addition, subtraction, multiplication, and division on data. For example, one or more ALUs 706 may receive input operands and an operation code, which determines an operation to be executed. One or more ALUs 706 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 706 may support logical operations such as AND, OR, exclusive-OR (XOR) , not-OR (NOR) , and not-AND (NAND) , enabling the one or more ALUs 706 to handle conditional operations, comparisons, and bitwise operations.

The processor 700 may support wireless communication at the device 600 in accordance with examples as disclosed herein. The processor 700 may be configured to operable to support a means for performing the following: transmitting, to a first base station, first information related to mobility prediction based on AI or ML; determining occurrence of a problem related to mobility of the UE; and transmitting a report related to the occurrence of the problem related to mobility of the UE to the first base station or a second base station, wherein the report comprises second information related to a problem of the mobility prediction.

Alternatively, the processor 700 may be configured to operable to support a means for performing the following: receiving, from a UE, first information related to mobility prediction based on AI or ML; and transmitting, based on the first information, a command for mobility of the UE to the UE.

Alternatively, the processor 700 may be configured to operable to support a means for performing the following: receiving, from a UE, a report related to occurrence of a problem related to mobility of the UE, wherein the report comprises second information related to a problem of mobility prediction based on AI or ML; and performing one of the following: transmitting, to a first base station, the report related to the occurrence of the problem related to mobility of the UE; or determining, based on the second information, whether the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction.

Fig. 8 illustrates a flowchart of a method 800 supporting cause detection of a problem related to mobility in accordance with aspects of the present disclosure. The operations of the method 800 may be implemented by a device or its components as described herein. For example, the operations of the method 800 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 810, the method may include transmitting, to a first base station, first information related to mobility prediction based on AI or ML. The operations of 810 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 810 may be performed by a device as described with reference to Fig. 1 or 2.

At 820, the method may include determining occurrence of a problem related to mobility of the UE. The operations of 820 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 820 may be performed by a device as described with reference to Fig. 1 or 2.

At 830, the method may include transmitting a report related to the occurrence of the problem related to mobility of the UE to the first base station or a second base station. The report comprises second information related to a problem of the mobility prediction. The operations of 830 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 830 may be performed by a device as described with reference to Fig. 1 or 2.

Fig. 9 illustrates a flowchart of a method 900 supporting cause detection of a problem related to mobility in accordance with aspects of the present disclosure. The operations of the method 900 may be implemented by a device or its components as described herein. For example, the operations of the method 900 may be performed by the first base station 102-1 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 910, the method may include receiving, from a UE, first information related to mobility prediction based on AI or ML. The operations of 910 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 910 may be performed by a device as described with reference to Fig. 1 or 2.

At 920, the method may include transmitting, based on the first information, a command for mobility of the UE to the UE. The operations of 920 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 920 may be performed by a device as described with reference to Fig. 1 or 2.

Fig. 10 illustrates a flowchart of a method 1000 supporting cause detection of a problem related to mobility 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 first base station 102-1 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 receiving, from a UE, a report related to occurrence of a problem related to mobility of the UE. The report comprises second information related to a problem of mobility prediction based on AI or ML. 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 or 2.

At 1020, the method may include performing one of the following: transmitting, to a first base station, the report related to the occurrence of the problem related to mobility of the UE; or determining, based on the second information, whether the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction. 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 or 2.

It shall be noted that implementations of the present disclosure which have been described with reference to Figs. 1 to 5 are also applicable to the device 600, the processor 700 as well as the methods 800, 900 and 1000.

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 user equipment (UE) , comprising:

a processor; and

a transceiver coupled to the processor,

wherein the processor is configured to:

transmit, via the transceiver to a first base station, first information related to mobility prediction based on artificial intelligence (AI) or machine learning (ML) ;

determine occurrence of a problem related to mobility of the UE; and

transmit a report related to the occurrence of the problem related to mobility of the UE via the transceiver to the first base station or a second base station, wherein the report comprises second information related to a problem of the mobility prediction.
The UE of claim 1, wherein the first information related to mobility prediction comprises predicted measurement results for a first time instance; and

wherein the second information related to the problem of the mobility prediction comprises at least one of the following:

a first indication indicating whether the UE has actual measurements results for the first time instance for a last serving cell or a neighbour cell when the problem related to mobility occurs,

a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station or when the problem related to mobility occurs,

a third indication indicating whether the UE has performed actual measurements at the first time instance to obtain the actual measurements results,

the predicted measurement results for the first time instance, or

an identity of the mobility prediction.
The UE of claim 2, wherein the first time instance is before the second time instance when the UE receives the command for the mobility from the first base station or when the problem related to mobility occurs; and

wherein the second information related to the problem of the mobility prediction further comprises at least one of the following:

the actual measurements results for the first time instance,

last measurements results for a third time instance before the second time instance,

a fifth indication indicating whether the last measurements results were obtained before or after the first time instance, or

the third time instance.
The UE of claim 1, wherein the first information related to mobility prediction comprises a predicted measurement event for a first time instance; and

wherein the second information related to the problem of the mobility prediction comprises at least one of the following:

a sixth indication indicating whether the UE is able to perform actual measurement at the first time instance,

a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station or when the problem related to mobility occurs,

a third indication indicating whether the UE has performed actual measurements at the first time instance to obtain the actual measurements results, or

the predicted measurement event for the first time instance.
The UE of claim 1, wherein the problem related to mobility of the UE comprises one of the following:

handover failure (HOF) ,

radio link failure (RLF) , or

sub-optimal successful handover.
The UE of claim 1, wherein the problem related to mobility of the UE comprises radio link failure (RLF) ;

wherein the first information related to mobility prediction comprises a predicted probability of the occurrence of the RLF at a first time instance or within a time window; and

wherein the second information related to the problem of the mobility prediction comprises at least one of the following:

a seventh indication indicating whether the UE is able to evaluate actual radio link condition at the first time instance or within the time window,

an eighth indication indicating whether the UE tends to suffer or actually suffers the RLF at the first time instance or within the time window,

a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station, or

a fourth indication indicating the predicted measurement results are inaccurate, or

the actual radio link condition at the first time instance or within the time window.
The UE of claim 1, wherein the processor is configured to transmit the report related to the occurrence of the problem related to mobility of the UE by:

transmitting, via the transceiver to the second base station, the report together with an identity of a last serving cell of the UE.
A first base station, comprising:

a processor; and

a transceiver coupled to the processor,

wherein the processor is configured to:

receive, via the transceiver from a user equipment (UE) , first information related to mobility prediction based on artificial intelligence (AI) or machine learning (ML) ; and

transmit, based on the first information, a command for mobility of the UE via the transceiver to the UE.
The first base station of claim 8, wherein the processor is further configured to:

receive, via the transceiver from the UE or a second base station, a report related to occurrence of a problem related to mobility of the UE, wherein the report comprises second information related to a problem of the mobility prediction; and

determine, based on the second information, whether the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction.
The first base station of claim 9, wherein the first information related to mobility prediction comprises predicted measurement results for a first time instance; and

wherein the second information related to the problem of the mobility prediction comprises at least one of the following:

a first indication indicating whether the UE has actual measurements results for the first time instance for a last serving cell or a neighbour cell when the problem related to mobility occurs,

a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station or when the problem related to mobility occurs,

a third indication indicating whether the UE has performed actual measurements at the first time instance to obtain the actual measurements results,

the predicted measurement results for the first time instance, or

an identity of the mobility prediction.
The first base station of claim 9, wherein the first information related to mobility prediction comprises a predicted measurement event for a first time instance; and

wherein the second information related to the problem of the mobility prediction comprises at least one of the following:

a sixth indication indicating whether the UE is able to perform actual measurement at the first time instance,

a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station,

a third indication indicating whether the UE has performed actual measurements at the first time instance to obtain the actual measurements results, or

the predicted measurement event for the first time instance.
The first base station of claim 9, wherein the problem related to mobility of the UE comprises one of the following:

handover failure (HOF) ,

radio link failure (RLF) , or

sub-optimal successful handover.
The first base station of claim 9, wherein the problem related to mobility of the UE comprises radio link failure (RLF) ;

wherein the first information related to mobility prediction comprises a predicted probability of the occurrence of the RLF at a first time instance or within a time window; and

wherein the second information related to the problem of the mobility prediction comprises at least one of the following:

a seventh indication indicating whether the UE is able to evaluate actual radio link condition at the first time instance or within the time window,

an eighth indication indicating whether the UE tends to suffer or actually suffers the RLF at the first time instance or within the time window,

a second indication indicating whether the first time instance is before or after a second time instance when the UE receives a command for the mobility from the first base station,

a fourth indication indicating the predicted measurement results are inaccurate, or

the actual radio link condition at the first time instance or within the time window.
The first base station of claim 9, wherein the processor is configured to receive the report related to occurrence of the problem related to mobility of the UE from the second base station; and

wherein the processor is further configured to:

based on determining that the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction, transmit a ninth indication via the transceiver to the second base station, wherein the ninth indication indicates a problem of the mobility prediction.
A second base station, comprising:

a processor; and

a transceiver coupled to the processor,

wherein the processor is configured to:

receive, via the transceiver from a user equipment (UE) , a report related to occurrence of a problem related to mobility of the UE, wherein the report comprises second information related to a problem of mobility prediction based on artificial intelligence (AI) or machine learning (ML) ; and

perform one of the following:

transmitting, via the transceiver to a first base station, the report related to the occurrence of the problem related to mobility of the UE; or

determining, based on the second information, whether the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction.
The second base station of claim 15, wherein the processor is configured to

receive a ninth indication via the transceiver from the first base station, wherein the ninth indication indicates a problem of the mobility prediction.
The second base station of claim 16, wherein the ninth indication indicates the problem of the mobility prediction by indicating the problem related to mobility of the UE is caused by inaccuracy of the mobility prediction.
The second base station of claim 17, wherein the problem related to mobility of the UE comprises one of the following:

handover failure (HOF) ,

radio link failure (RLF) , or

sub-optimal successful handover.
The second base station of claim 18, wherein the ninth indication further indicates at least one of the following:

predicted measurement results before the occurrence of the problem related to mobility of the UE are inaccurate,

a predicted measurement event before the occurrence of the problem related to mobility of the UE is inaccurate, or

a predicted probability of occurrence of the RLF before the occurrence of the RLF is inaccurate.
A processor for wireless communication, comprising:

at least one memory; and

a controller coupled with the at least one memory and configured to cause the controller to:

transmit, via a transceiver to a first base station, first information related to mobility prediction based on artificial intelligence (AI) or machine learning (ML) ;

determine occurrence of a problem related to mobility of the UE; and

transmit a report related to the occurrence of the problem related to mobility of the UE via the transceiver to the first base station or a second base station, wherein the report comprises second information related to a problem of the mobility prediction.