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WO2025184828A1 - Procédé et dispositif de communication - Google Patents

Procédé et dispositif de communication

Info

Publication number
WO2025184828A1
WO2025184828A1 PCT/CN2024/080304 CN2024080304W WO2025184828A1 WO 2025184828 A1 WO2025184828 A1 WO 2025184828A1 CN 2024080304 W CN2024080304 W CN 2024080304W WO 2025184828 A1 WO2025184828 A1 WO 2025184828A1
Authority
WO
WIPO (PCT)
Prior art keywords
prediction
measurement
communication device
event
frequency band
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/CN2024/080304
Other languages
English (en)
Chinese (zh)
Other versions
WO2025184828A8 (fr
Inventor
杜忠达
伍浩
尤心
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Guangdong Oppo Mobile Telecommunications Corp Ltd
Original Assignee
Guangdong Oppo Mobile Telecommunications Corp Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Guangdong Oppo Mobile Telecommunications Corp Ltd filed Critical Guangdong Oppo Mobile Telecommunications Corp Ltd
Priority to PCT/CN2024/080304 priority Critical patent/WO2025184828A1/fr
Publication of WO2025184828A1 publication Critical patent/WO2025184828A1/fr
Publication of WO2025184828A8 publication Critical patent/WO2025184828A8/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W8/00—Network data management
    • H04W8/22—Processing or transfer of terminal data, e.g. status or physical capabilities
    • H04W8/24—Transfer of terminal data

Definitions

  • the present application relates to the field of communications, and more specifically, to a communication method and device.
  • the network can obtain the UE capabilities by directly obtaining the UE capabilities through the wireless interface or by downloading the stored UE capabilities through the core network.
  • An embodiment of the present application provides a communication method, including:
  • the first communication device sends first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.
  • An embodiment of the present application provides a communication method, including:
  • the second communication device receives and sends first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.
  • An embodiment of the present application provides a first communication device, including:
  • the sending unit is configured to send first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.
  • An embodiment of the present application provides a second communication device, including:
  • the receiving unit is configured to receive and send first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.
  • An embodiment of the present application provides a communication device, comprising: a transceiver, a processor, and a memory.
  • the memory is used to store a computer program
  • the transceiver is used to communicate with other devices
  • the processor is used to call and execute the computer program stored in the memory so that the communication device performs the above-mentioned communication method.
  • An embodiment of the present application provides a chip for implementing the above-mentioned communication method.
  • the chip includes: a processor, which is used to call and run a computer program from a memory, so that a device equipped with the chip executes the above-mentioned communication method.
  • An embodiment of the present application provides a computer-readable storage medium for storing a computer program, which, when executed by a device, enables the device to execute the above-mentioned communication method.
  • An embodiment of the present application provides a computer program product, including computer program instructions, which enable a computer to execute the above-mentioned communication method.
  • An embodiment of the present application provides a computer program, which, when executed on a computer, enables the computer to execute the above-mentioned communication method.
  • the mobility management-related algorithms on the communication device side can be reasonably operated.
  • FIG1 is a schematic diagram of an application scenario according to an embodiment of the present application.
  • Figure 2 is a schematic diagram of the measurement model.
  • FIG3 is a schematic flowchart of a communication method according to an embodiment of the present application.
  • FIG4 is a schematic flowchart of a communication method according to another embodiment of the present application.
  • FIG5 is a schematic flowchart of a communication method according to another embodiment of the present application.
  • FIG6 is a schematic flowchart of a communication method according to an embodiment of the present application.
  • FIG7 is a schematic flowchart of a communication method according to another embodiment of the present application.
  • FIG8 is a schematic flowchart of a communication method according to another embodiment of the present application.
  • FIG9 is a schematic block diagram of a first communication device according to an embodiment of the present application.
  • FIG10 is a schematic block diagram of a second communication device according to an embodiment of the present application.
  • FIG11 is a schematic block diagram of a communication device according to an embodiment of the present application.
  • FIG12 is a schematic block diagram of a chip according to an embodiment of the present application.
  • FIG13 is a schematic block diagram of a communication system according to an embodiment of the present application.
  • LTE Long Term Evolution
  • LTE-A Advanced Long Term Evolution
  • NR New Radio
  • NR system evolution system LTE on unlicensed spectrum
  • LTE-U LTE on unlicensed spectrum
  • NR-U Non-Terrestrial Networks
  • NTN Universal Mobile Telecommunication System
  • UMTS Universal Mobile Telecommunication System
  • WLAN Wireless Local Area Networks
  • WiFi Wireless Fidelity
  • 5G 5th-Generation
  • D2D device-to-device
  • M2M machine-to-machine
  • MTC machine-type communication
  • V2V vehicle-to-vehicle
  • V2X vehicle-to-everything
  • the communication system in the embodiment of the present application can be applied to a carrier aggregation (CA) scenario, a dual connectivity (DC) scenario, and a standalone (SA) networking scenario.
  • CA carrier aggregation
  • DC dual connectivity
  • SA standalone
  • the communication system in the embodiment of the present application can be applied to an unlicensed spectrum, wherein the unlicensed spectrum can also be considered as a shared spectrum; or, the communication system in the embodiment of the present application can also be applied to an authorized spectrum, wherein the authorized spectrum can also be considered as an unshared spectrum.
  • the terminal device may also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication equipment, user agent or user device, etc.
  • UE user equipment
  • the terminal device can be a station (STAION, ST) in a WLAN, a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device with wireless communication capabilities, a computing device or other processing device connected to a wireless modem, an in-vehicle device, a wearable device, a terminal device in a next-generation communication system such as a NR network, or a terminal device in a future evolved Public Land Mobile Network (PLMN) network, etc.
  • STAION, ST in a WLAN
  • a cellular phone a cordless phone
  • Session Initiation Protocol (SIP) phone Session Initiation Protocol
  • WLL Wireless Local Loop
  • PDA Personal Digital Assistant
  • PDA Personal Digital Assistant
  • the terminal device can be deployed on land, including indoors or outdoors, handheld, wearable or vehicle-mounted; it can also be deployed on the water surface (such as ships, etc.); it can also be deployed in the air (such as airplanes, balloons and satellites, etc.).
  • the terminal device may be a mobile phone, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, or a wireless terminal device in a smart home, etc.
  • VR virtual reality
  • AR augmented reality
  • the terminal device may also be a wearable device.
  • Wearable devices may also be called wearable smart devices, which are a general term for wearable devices that are intelligently designed and developed using wearable technology for daily wear, such as glasses, gloves, watches, clothing, and shoes.
  • a wearable device is a portable device that is worn directly on the body or integrated into the user's clothes or accessories. Wearable devices are not only hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction.
  • wearable smart devices include those that are fully functional, large in size, and can achieve complete or partial functions without relying on smartphones, such as smart watches or smart glasses, as well as those that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.
  • the network device may be a device for communicating with a mobile device, and the network device may be an access point (AP) in a WLAN, an evolved base station (eNB or eNodeB) in an LTE, or a relay station or access point, or an in-vehicle device, a wearable device, a network device (gNB) in an NR network, or a network device in a future evolved PLMN network or a network device in an NTN network, etc.
  • AP access point
  • eNB or eNodeB evolved base station
  • LTE long-term evolution
  • gNB network device
  • gNB network device
  • future evolved PLMN network or a network device in an NTN network
  • the network device may have a mobile feature, for example, the network device may be a mobile device.
  • the network device may be a satellite or a balloon station.
  • the satellite may be a low earth orbit (LEO) satellite, a medium earth orbit (MEO) satellite, a geostationary earth orbit (GEO) satellite, a high elliptical orbit (HEO) satellite, etc.
  • the network device may also be a base station set up in a location such as land or water.
  • a network device can provide services for a cell, and a terminal device communicates with the network device through the transmission resources used by the cell (for example, frequency domain resources, or spectrum resources).
  • the cell can be a cell corresponding to a network device (for example, a base station).
  • the cell can belong to a macro base station or a base station corresponding to a small cell.
  • the small cells here may include: metro cells, micro cells, pico cells, femto cells, etc. These small cells have the characteristics of small coverage and low transmission power, and are suitable for providing high-speed data transmission services.
  • FIG1 exemplarily illustrates a communication system 100.
  • the communication system includes a network device 110 and two terminal devices 120.
  • the communication system 100 may include multiple network devices 110, and each network device 110 may include a different number of terminal devices 120 within its coverage area, which is not limited in this embodiment of the present application.
  • the communication system 100 may also include other network entities such as a Mobility Management Entity (MME) and an Access and Mobility Management Function (AMF), but this embodiment of the present application does not limit this.
  • MME Mobility Management Entity
  • AMF Access and Mobility Management Function
  • network equipment can include access network equipment and core network equipment. That is, the wireless communication system also includes multiple core networks for communicating with the access network equipment.
  • the access network equipment can be an evolved base station (eNB or e-NodeB) in a long-term evolution (LTE) system, a next-generation (mobile communication system) (next radio, NR) system, or an authorized auxiliary access long-term evolution (LAA-LTE) system, such as a macro base station, a micro base station (also known as a "small base station"), a pico base station, an access point (AP), a transmission point (TP), or a new generation Node B (gNodeB).
  • eNB evolved base station
  • e-NodeB evolved base station
  • LTE long-term evolution
  • NR next-generation
  • LAA-LTE authorized auxiliary access long-term evolution
  • macro base station such as a macro base station, a micro base station (also known as a "small base station"), a pico base station, an access
  • a device having a communication function in a network/system may be referred to as a communication device.
  • the communication device may include a network device and a terminal device having a communication function.
  • the network device and the terminal device may be specific devices in the embodiments of the present application and will not be described in detail here.
  • the communication device may also include other devices in the communication system, such as a network controller, a mobility management entity, and other network entities, which are not limited in the embodiments of the present application.
  • indication can be a direct indication, an indirect indication, or an indication of an association.
  • “A indicates B” can mean that A directly indicates B, for example, B can be obtained through A; it can also mean that A indirectly indicates B, for example, A indicates C, and B can be obtained through C; it can also mean that there is an association between A and B.
  • corresponding may indicate a direct or indirect correspondence between the two, or an association relationship between the two, or a relationship between indication and being indicated, configuration and being configured, etc.
  • the network can request the UE to report the technical features it supports through Radio Resource Control (RRC) signaling.
  • RRC Radio Resource Control
  • the network can obtain the UE's capabilities in the following ways:
  • Method 1 Directly obtain via wireless interface
  • the base station to which the UE is connected establishes a connection with the core network, if the core network finds that the UE capabilities of the UE are not stored, it will request the base station to obtain the UE capabilities of the UE through the NG interface.
  • the base station then sends a Capability Enquiry message to the UE on the Uu interface.
  • This message primarily requests the UE to send UE capability signaling.
  • the message may contain auxiliary information elements, such as filters used to reduce the uplink signaling load (the UE filters out content based on the filter and then reports the remaining content).
  • the UE After receiving the request message, the UE reports its wireless capabilities.
  • the reported technical features differ significantly in their granularity and in the differences between frequency division duplex (FDD) and/or time division duplex (TDD) communication modes.
  • the granularity of technical features is mainly described from the perspective of frequency domain.
  • each UE per UE
  • each bandwidth per band
  • each bandwidth combination (per band combination) (set according to the bandwidth combination granularity supported by the UE, there will be one or more bandwidths in a bandwidth combination for configuring dual link or carrier aggregation)
  • each feature set (per feature set) (set according to the granularity of different bandwidths in the bandwidth combination)
  • each feature set per carrier aggregation (per feature set per CC) (set according to the granularity of carrier aggregation (Component Carrier, CC) under the premise of supporting carrier aggregation according to different bandwidths in the bandwidth combination).
  • the base station will record the received UE capabilities (included in the UE Capability Information message) locally for use in this communication process. In addition, the base station will send the UE capabilities to the next generation interface (NG) interface.
  • NG next generation interface
  • the core network stores these UE capabilities.
  • Method 2 Downloading stored UE capabilities through the core network.
  • the core network finds that the UE capabilities of the UE have been stored, the core network directly sends these UE capabilities related to radio access to the base station through the NG interface for use in this communication process.
  • UE capabilities include measurement and/or mobility-related UE capabilities. These UE capabilities are per-UE capabilities. Table 1 shows examples of UE capabilities related to mobility. "M" indicates whether the technical feature is mandatory. If mandatory, the signaling bit of the UE capability is used to indicate whether the technical feature has been tested jointly between the network and the terminal.
  • LCM life cycle management
  • the UE In the 3GPP cellular communication system, the UE needs to measure the strength or quality of the wireless signals of the current serving cell and the surrounding neighboring cells, and then report this information to the network in the form of an RRC message called a measurement report. Generally, the network can make relevant switching decisions based on this information.
  • Model Figure 2 which includes how the UE performs intra-frequency or inter-frequency measurements, how it performs beam-based measurement sampling at Layer 1 (L1), and how it determines measurement events based on network-configured parameters.
  • the UE performs physical layer measurement sampling at the granularity of beams (e.g. gNB beam1, gNB beam1...gNB beamK).
  • beams e.g. gNB beam1, gNB beam1...gNB beamK.
  • A1 The UE performs Layer 1 filtering on the beam measurement results.
  • the protocol specifies the length of the measurement period under specific RRC configurations. This measurement period dictates that the UE must perform at least one sampling operation, and that the beam measurement results after L1 filtering must meet the performance requirements specified in the 3GPP specification.
  • the UE performs a specific number of sampling operations within a measurement period. In test cases, an oversampling of 4 to 5 is typically used.
  • A1 performs a consolidation operation on the beam measurement results obtained in a certain cell to synthesize the L1 cell-level measurement results.
  • L1 cell-level measurement results of a certain cell are filtered through Layer 3 (Layer 3, L3) (Layer 3 Beam filtering) to obtain the L3 cell-level measurement results.
  • Layer 3 Layer 3, L3 (Layer 3 Beam filtering)
  • Measurement results from the serving cell and/or neighboring cells are used to determine whether a specific measurement event has occurred, based on certain criteria (configured by the network). For example, whether the neighboring cell's measurement result is higher than the primary cell (PCell)'s measurement result by an offset value (A3 event) is used.
  • certain criteria configured by the network. For example, whether the neighboring cell's measurement result is higher than the primary cell (PCell)'s measurement result by an offset value (A3 event) is used.
  • a specific measurement task may include:
  • the measurement object including the measured frequency and reference signal description. If the measured frequency is the same as the center frequency of the current serving cell and the subcarrier spacing is the same, it is an intra-frequency measurement; otherwise, it is an inter-frequency measurement.
  • Measurement configuration including the type of measurement reporting (including event triggering, periodic reporting, and periodic reporting after event triggering, etc.), as well as various configuration parameters corresponding to each reporting type.
  • the measurement tasks configured for the UE in the dual connectivity architecture can be configured with their own measurement tasks for each cell group.
  • the same measurement objects can even be configured in each measurement task.
  • the measurement tasks are configured by the MCG.
  • 3GPP has studied what factors affect mobility performance when deploying multi-layer networks (hetnet). Research. In these studies, some key indicators are defined. These include:
  • Handover failure When the network sends a handover command message to the UE, if the timer T310 used to determine radio link failure is running or has timed out, this situation is judged as a handover failure. The judgment of radio link failure is made according to the LTE protocol. After receiving N310 consecutive indications of link deterioration (Qout), the UE will start the T310 timer. If the T310 timer times out, the UE will assume that a radio link failure has occurred. When T310 is running, if N311 indications of link improvement (Qin) are received, the timer T310 will be stopped. The length of the T310 timer and the counters N310 and N311 are all configured by the network.
  • Ping-pong handover When a UE switches from cell A to cell B and then switches back to cell A within a specified time threshold (e.g., 1 second), such a handover is considered a ping-pong handover.
  • a specified time threshold e.g. 1 second
  • Too short handover When a UE switches from cell A to cell B and then switches back to cell C within a specified time threshold (e.g., 1 second), and cell C is not cell A, such handover is considered too short.
  • a specified time threshold e.g. 1 second
  • FIG3 is a schematic flow chart of a communication method 300 according to an embodiment of the present application.
  • the method can optionally be applied to the system shown in FIG1 , but is not limited thereto.
  • the method includes at least part of the following contents.
  • a first communication device sends first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.
  • a first communication device may report to a second communication device prediction capabilities related to mobility management supported by the first communication device, such as reporting one or more prediction capabilities supported by an AI/ML model that supports mobility management. Prediction capabilities may also be referred to as prediction functions.
  • the mobility management-related algorithms on the communication device side can be reasonably operated.
  • the mobility management-related prediction capability includes at least one of the following: measurement result prediction; measurement event prediction; and abnormal event prediction.
  • the measurement result may include one or more of Reference Signal Receiving Power (RSRP), Reference Signal Receiving Quality (RSRQ), Signal to Interference plus Noise Ratio (SINR), etc.
  • the measurement result prediction may include obtaining a predicted measurement result based on historical measurement results.
  • the historical measurement result may be an actual measurement result or a historically predicted result.
  • the predicted measurement result may include at least one of the following: a measurement result for a period of time in the future, a measurement result at a future time point, and a measurement result at a time point in the past when no measurement was performed.
  • the measurement event may include one or more of an A1 event (a serving cell exceeds a threshold value), an A2 event (a serving cell falls below a threshold value), an A3 event (a neighboring cell exceeds a primary serving cell by an offset value), and the like.
  • the measurement event prediction may include a measurement event predicted based on historical measurement results or predicted measurement results. For example, if within a time period, the predicted value of the measurement result of the neighboring cell is higher than the predicted value of the measurement result of the primary cell (PCell) of the current cell by an offset value, it can be predicted that an A3 event will occur within the time period.
  • the abnormal event may include one or more of handover failure, radio link failure, too short a handover time, ping-pong handover, etc. Whether an abnormal event occurs can be predicted based on the measurement results and/or measurement events.
  • the measurement result prediction includes at least one of the following:
  • L1 beam measurement result prediction may include predicting an L1 beam measurement result based on historical L1 beam measurement results of a cell.
  • the predicted L1 beam measurement result after merging and L3 filtering, is called a predicted L3 cell measurement result.
  • the predicted L1 beam measurement result may be a time domain prediction result, a frequency domain prediction result, or a spatial domain prediction result.
  • the time domain prediction result may include measurement results for a future period predicted using actual measurement results from a past period, or measurement results for unmeasured time points in a past period predicted using actual measurement results from a past period.
  • the frequency domain prediction result may include unmeasured frequency band measurement results predicted based on actually measured frequency bands.
  • the spatial domain prediction result may include unmeasured beam/cell measurement results predicted based on actually measured beam/cell measurement results.
  • the L3 cell measurement result prediction includes: predicting subsequent L3 cell measurement results based on historical L1 beam measurement results, and/or predicting subsequent L3 cell measurement results based on historical L3 cell measurement results.
  • the L3 cell measurement result prediction capability may include L3 cell measurement result prediction capability 1 and L3 cell measurement result prediction capability 2.
  • the L3 cell measurement result prediction capability 1 may include directly predicting the L3 cell measurement result of a cell based on the L1 beam measurement results of the cell in history.
  • L3 cell measurement result prediction capability 2 may include predicting the L3 cell measurement result of a cell based on historical L3 cell measurement results of the cell.
  • the measurement event prediction includes: predicting the measurement event based on historical L1 beam measurement results, and/or predicting the measurement event based on historical L3 cell measurement results.
  • the measurement event prediction function may include measurement event prediction capability 1 and measurement event prediction capability 2.
  • Measurement event prediction capability 1 includes predicting a measurement event for a cell based on historical L1 beam measurement results of the cell.
  • Measurement event prediction capability 2 includes predicting a measurement event for the cell based on historical L3 cell measurement results of the cell.
  • the abnormal event prediction includes at least one of the following:
  • radio link failure prediction includes: predicting whether the radio link of the serving cell has failed based on the L1 beam measurement results.
  • handover failure prediction includes combining the measurement event and the prediction results of the radio link failure, as well as some internal auxiliary information such as the UE's location or moving speed, to predict whether a handover failure will occur. For another example, it is predicted whether the UE will switch to cell C quickly after switching from cell A to cell B, and whether the time spent in cell B is less than a threshold, thereby predicting whether the UE will experience a too-short handover event. For another example, it is predicted whether the UE will switch back to cell A quickly after switching from cell A to cell B, and whether the time spent in cell B is less than a threshold, thereby predicting whether the UE will experience a ping-pong handover event.
  • FIG4 is a schematic flow chart of a communication method 400 according to another embodiment of the present application.
  • the method may include one or more features of the above method 300.
  • the method further includes:
  • the first communication device receives second information, which is used to request the first communication device to report prediction capabilities related to mobility management. For example, this step may be before S310. After receiving the second information from the second communication device, the first communication device sends the first information to the second communication device.
  • An AI/ML model in the first communication device can support one or more prediction capabilities related to mobility management, and a prediction capability can be called a technical feature. There may be more than one model supporting the same or similar technical features inside the first communication device.
  • the AI/ML models can be numbered for accurate identification in signaling. For example, model 1 supports technical feature 1 and technical feature 2, and model 2 supports technical feature 2 and technical feature 3. Among them, technical feature 1 represents L1 beam measurement result prediction capability, technical feature 2 represents L3 cell measurement result prediction capability 1, and technical feature 3 represents measurement event prediction capability 2.
  • the filtering condition includes at least one of the following:
  • the one technical feature corresponds to a prediction capability related to mobility management, and a model supports the one or more technical features.
  • the first communication device may also describe the switching scenarios to which these models are applicable.
  • the switching scenarios to which these models are applicable include at least one of the following: switching between macro cells, between micro cells, between multi-layer cells, switching of low-speed UEs, switching of medium- and high-speed UEs, etc.
  • the filtering condition includes requiring the first communication device to report models that support technical feature 1, then the first communication device may report the number of model 1 and the switching scenario of model 1.
  • the filtering condition includes requiring the first communication device to report models that support technical feature 2
  • the first communication device may report the numbers of model 1 and model 2, as well as the switching scenarios of model 1 and model 2.
  • the first communication device may also describe the technical features supported by each model. For example, if the filtering condition includes requiring the first communication device to report a model that supports switching scenario S1. If switching scenario S1 includes ping-pong switching, the number of the model that supports ping-pong switching event prediction may be reported, and all technical features supported by the model, such as technical features 1, 2, and 3, may also be reported. If switching scenario S1 includes too short a time switching, the number of the model that supports too short a time switching event prediction may be reported, and all technical features supported by the model, such as technical features 2, 3, and 4, may also be reported.
  • the filtering condition includes requiring the first communication device to report supported specific technical features
  • the model may not be described.
  • the filtering condition includes requiring the first communication device to report supported technical feature 1
  • the first communication device may report technical feature 1.
  • the reporting granularity of the mobility management-related prediction capability includes terminal, frequency band, or frequency band combination.
  • the reporting granularity is the model and corresponding to all frequency bands and frequency band combinations supported by a terminal. and/or technical characteristics; or
  • the reporting granularity is frequency band, indicating reporting of the model and/or technical features corresponding to a frequency band; or
  • the reporting granularity is a frequency band combination, which means reporting a model and/or technical features corresponding to a frequency band combination.
  • the frequency bands supported by UE1 include bandA, bandB, and bandC, where bandA corresponds to technical feature A1 and technical feature A2, bandB corresponds to technical feature B1 and technical feature B2, and bandC corresponds to technical feature C1 and technical feature C2.
  • bandA corresponds to technical feature A1 and technical feature A2
  • bandB corresponds to technical feature B1 and technical feature B2
  • bandC corresponds to technical feature C1 and technical feature C2.
  • the technical features of the two frequency bands can be matched one-to-one according to the serial numbers, and these one-to-one corresponding technical feature combinations ⁇ A1, B1 ⁇ , ⁇ A2, B2 ⁇ become the technical feature combinations in the frequency band combination. These technical feature combinations can be reported subsequently.
  • the relationship between the predictive capabilities includes at least one of the following:
  • the above-mentioned various prediction capabilities may be differentiated by level. For example, the prediction of a too short or ping-pong handover event is higher than the prediction of a measurement event, the prediction of a measurement event is higher than the prediction of a measurement result, the prediction of a handover failure event is higher than the prediction of a measurement event, and the prediction of a radio link failure is higher than the prediction of a measurement result.
  • the entire UE also supports prediction capabilities lower than measurement event prediction, such as measurement result prediction.
  • the network may interpret it as the UE also supports measurement result prediction on the frequency band bandA.
  • the network may interpret it as the UE also supporting measurement event prediction and radio link failure prediction on the frequency bands bandA and bandB.
  • FIG5 is a schematic flow chart of a communication method 500 according to another embodiment of the present application.
  • the method may include one or more features of the above methods 300 and 400.
  • the method further includes:
  • the first communication device receives third information, where the third information is used to configure the mobility management-related prediction capability reported by the first communication device. For example, this step may occur after S310.
  • the second communication device may send corresponding configuration information to the first communication device based on the mobility management-related prediction capability supported by the first communication device in the first information, such as one or more of the measurement amount, measurement period, number of sampling times, measurement reporting type, measurement object, and measurement task.
  • the first communication device may be a terminal
  • the second communication device may be a network device.
  • the interaction between the network device and the terminal may be understood as a two-way selection process, so that the technical features executed by the terminal are technical features supported by both parties.
  • the configuration granularity of the mobility management-related prediction capability includes a terminal, a measurement object, or a measurement task.
  • the configuration granularity is that the terminal represents configuring all measurement tasks of a terminal.
  • the configuration granularity is that the measurement object represents configuration of measurement tasks corresponding to all measurement task identifiers associated with one measurement object;
  • the configuration granularity is that the measurement task represents the configuration of a measurement object associated with a measurement task identifier.
  • the configuration information may be used for all measurement tasks of the UE.
  • the configuration information can be used for measurement tasks corresponding to all measurement task identifiers T1, T2, and T3 associated with the measurement object O1.
  • the configuration information can be used for measurement objects O1 and O2 associated with T1.
  • the configuration granularity of the measurement result prediction, the measurement event prediction, the too-short-time handover event prediction, or the ping-pong handover event prediction is a terminal, a measurement object, or a measurement task.
  • the measurement result prediction on all measurement tasks in the UE can use the configuration information of the measurement result prediction.
  • the configuration granularity of the measurement event prediction is measurement object
  • the measurement event prediction on all measurement tasks associated with the measurement object in the UE can use the configuration information of the measurement event prediction.
  • the measurement object associated with the measurement task can use the configuration information of the too short time switching event prediction or the ping-pong switching event prediction.
  • the configuration granularity of the radio link failure prediction is the measurement of the frequency point where the primary cell or the primary and secondary cells are located. Quantity tasks.
  • the configuration granularity of handover failure prediction includes a combination of radio link failure configuration granularity and measurement event granularity.
  • the radio link failure configuration granularity is UE and the measurement event granularity is frequency band
  • the configuration granularity of handover failure prediction can be UE and frequency band.
  • the UE in the embodiments of the present application can also be replaced by a mobile device.
  • the third information is used to configure one or more measurement event predictions, too-short-time handover event predictions, ping-pong handover event predictions, radio link failure predictions, or handover failure predictions on a measurement task.
  • FIG6 is a schematic flow chart of a communication method 600 according to an embodiment of the present application.
  • the method can optionally be applied to the system shown in FIG1 , but is not limited thereto.
  • the method includes at least part of the following contents.
  • the second communication device receives and sends first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.
  • the mobility management-related prediction capability includes at least one of the following: measurement result prediction; measurement event prediction; and abnormal event prediction.
  • the measurement result prediction includes at least one of the following:
  • the L3 cell measurement result prediction includes: predicting subsequent L3 cell measurement results based on historical L1 beam measurement results, and/or predicting subsequent L3 cell measurement results based on historical L3 cell measurement results.
  • the measurement event prediction includes: predicting the measurement event based on historical L1 beam measurement results, and/or predicting the measurement event based on historical L3 cell measurement results.
  • FIG7 is a schematic flow chart of a communication method 700 according to another embodiment of the present application.
  • the method may include one or more features of the above method 600.
  • the method further includes:
  • the second communication device sends second information, where the second information is used to request the first communication device to report prediction capabilities related to mobility management.
  • the second information includes a filtering condition requiring the first communication device to report a mobility management-related prediction capability.
  • the filtering condition includes at least one of the following:
  • the one technical feature corresponds to a prediction capability related to mobility management, and a model supports the one or more technical features.
  • the reporting granularity of the mobility management-related prediction capability includes terminal, frequency band, or frequency band combination.
  • the reporting granularity is that the terminal indicates reporting the models and/or technical features corresponding to all frequency bands and frequency band combinations supported by the terminal; or
  • the reporting granularity is frequency band, indicating reporting of the model and/or technical features corresponding to a frequency band; or
  • the reporting granularity is a frequency band combination, which means reporting a model and/or technical features corresponding to a frequency band combination.
  • the relationship between the predictive capabilities includes at least one of the following:
  • FIG8 is a schematic flow chart of a communication method 800 according to another embodiment of the present application.
  • the method may include one or more features of the above methods 600 and 700.
  • the method further includes:
  • the second communication device sends third information, where the third information is used to configure a prediction capability related to mobility management reported by the first communication device.
  • the configuration granularity of the mobility management-related prediction capability includes a terminal, a measurement object, or a measurement task.
  • the configuration granularity is that the terminal represents configuring all measurement tasks of a terminal.
  • the configuration granularity is that the measurement object represents configuration of measurement tasks corresponding to all measurement task identifiers associated with one measurement object;
  • the configuration granularity is that the measurement task represents the configuration of a measurement object associated with a measurement task identifier.
  • the configuration granularity of the measurement result prediction, the measurement event prediction, the too-short-time handover event prediction, or the ping-pong handover event prediction is a terminal, a measurement object, or a measurement task.
  • the configuration granularity of the radio link failure prediction is a measurement task in which the frequency point where the primary cell or the primary and secondary cells are located is the measurement object.
  • the configuration granularity of handover failure prediction includes a combination of radio link failure configuration granularity and measurement event granularity.
  • the third information is used to configure one or more measurement event predictions, too-short-time handover event predictions, ping-pong handover event predictions, radio link failure predictions, or handover failure predictions on a measurement task.
  • the UE may report the AI/ML model capabilities for improving the mobility management (handover) function and/or performance of the cellular communication system through UE capability signaling, and the network may configure how the UE runs the AI/ML model based on the capabilities reported by the UE.
  • the AI/ML model supporting mobility management can support multiple functions (capabilities), including but not limited to at least one of the following technical features:
  • L1 (physical layer) beam measurement result prediction function The L1 beam measurement result is predicted based on the historical L1 beam measurement results of the cell.
  • the predicted L1 beam measurement result is called the predicted L3 cell measurement result after merging and L3 filtering.
  • the historical measurement result can be an actual measurement result or a historical predicted result. This applies to all relevant function descriptions below.
  • the predicted L1 beam measurement result can be a time domain prediction result (for example, the actual measurement result of the past period of time is used to predict the measurement result of the future period of time, or the actual measurement result of the past period of time is used to predict the measurement result of an unmeasured time point in the past period of time), a frequency domain prediction result (for example, the unmeasured frequency band measurement result is predicted based on the actually measured frequency band), or a spatial domain prediction result (for example, the unmeasured beam/cell measurement result is predicted based on the actually measured beam/cell measurement result); the L3 cell measurement result prediction functions 1 and 2 can also make the above distinction, which will not be repeated below.
  • a time domain prediction result for example, the actual measurement result of the past period of time is used to predict the measurement result of the future period of time, or the actual measurement result of the past period of time is used to predict the measurement result of an unmeasured time point in the past period of time
  • a frequency domain prediction result for example, the unmeasured frequency band measurement result is predicted based on the
  • L3 cell measurement result prediction function 1 directly predict the L3 cell measurement result of the cell based on the historical L1 beam measurement results of the cell.
  • L3 cell measurement result prediction function 2 predict the L3 cell measurement result of the cell based on the historical L3 cell measurement results of the cell.
  • Measurement event prediction function 1 predict the measurement event of the cell based on the historical L1 beam measurement results of the cell.
  • Measurement event prediction function 2 predicts the measurement event of the cell based on the historical L3 cell measurement results of the cell.
  • the L1 beam quality measurement results predict the failure of the serving cell radio link.
  • Handover failure prediction Combines measurement events and predictions of radio link failures, as well as possible other internal auxiliary information (such as UE location or movement speed) to predict whether a handover failure will occur.
  • Ping-pong handover event prediction predicts that after switching from source cell (A) to cell B, the time spent in cell B is less than a pre-defined threshold, and then the event of switching to cell A is quickly predicted.
  • An AI/ML model can support one or more of the above functions.
  • AI/ML models For example, due to hardware (computing power) or software factors (such as format, etc.), when such AI/ML models are first applied, there may be more than one model supporting the same or similar functions within the UE, which can be called AI/ML models of the same family. In order to properly manage these AI/ML models of the same family, these models can be numbered for accurate identification in signaling.
  • the UE When the UE reports UE capabilities in response to a request from the network, the UE may report the capabilities it supports according to the dimensions of the model or the dimensions of the technical features.
  • the network can set filter conditions in the filter of the UE Capability Enquiry message.
  • the network can require the UE to report models that support certain technical features.
  • the UE reports the filtered models, it can also provide a brief additional description of these models, such as the handover scenarios in which these models are applicable (such as handover between macro cells, micro cells, or multi-layer cells; handover between low-speed UEs and medium-speed UEs, etc.).
  • the network may require the UE to report models that meet certain handover scenarios.
  • the UE may describe each model, such as which specific technical features it supports among the above technical features.
  • the network simply requires the UE to report support for certain technical features, but does not provide a specific description of the model itself.
  • the granularity of these UE capabilities reported by the UE can be per UE, per band, or per band combination.
  • the network After the network obtains the aforementioned information related to the mobility AI/ML capabilities from the UE's capabilities after the initial access process, it configures how the UE uses the mobility AI/ML model based on the current network and the actual situation of the UE.
  • An example is shown below:
  • the granularity is per UE (e.g., all measurement objects associated with all measIDs of a UE), per MO (e.g., a measurement object (MO) and all measurement tasks associated with that MO), or per measurement task (i.e., measurement objects associated with a measID). These three granularities are arranged from coarse to fine.
  • the granularity range can be the same as the granularity of the RRM measurement prediction capability configuration. Since RRM measurement prediction is the basis of measurement events, or conversely, measurement event prediction is often the purpose of RRM measurement prediction, when the measurement event prediction capability is configured according to a certain granularity, the requirement for RRM measurement prediction can be implicit, so there is no need to repeatedly configure the RRM measurement prediction capability at this granularity. However, the RRM measurement prediction capability can be configured separately on the MO and/or measurement task that is not configured with the measurement event prediction capability, for different purposes such as saving UE energy consumption (replacing part of the original measurement samples or measurement results with predicted measurement results).
  • the prediction of Radio Link Failure (RLF) or handover failure can be configured on at least one intra-frequency measurement task or measurement object in the frequency point where the primary secondary cell (PSCell) is located.
  • the PSCell is the primary cell in a cell cluster. This is because there are two criteria for determining RLF or handover failure: one is whether a radio link failure has occurred in the PSCell, and the other is whether the network requires a handover command to be sent when the RLF has occurred (or the corresponding timer T310 is running).
  • the current RLM measurement is for the PSCell.
  • subsequent RLF or handover failure predictions can also be for the Scell or non-serving cell.
  • the configuration granularity for short-duration handover event prediction or ping-pong handover event prediction can be the same as that for measurement event prediction. Given that these two prediction capabilities are based on measurement task prediction, their configuration granularity can be the same as or even finer. For example, if measurement events are configured at the MO granularity, these two events can be configured based on the measurement tasks associated with that MO.
  • the switching in the embodiment of the present application can also be replaced by SCG change, that is, adding or replacing the SCG without changing the MCG.
  • SCG change can also occur at the same time as the MCG change.
  • the UE of the embodiment of the present application can support reporting of AI/ML-related capabilities related to mobility, and the network can perform relevant configurations based on the received capabilities so that the AI/ML algorithm supporting mobility on the UE side can operate reasonably.
  • FIG9 is a schematic block diagram of a first communication device 900 according to an embodiment of the present application.
  • the first communication device 900 may include:
  • the sending unit 901 is configured to send first information, where the first information is used to indicate a mobility management-related prediction capability supported by the first communication device.
  • the mobility management-related prediction capability includes at least one of the following: measurement result prediction; measurement event prediction; and abnormal event prediction.
  • the measurement result prediction includes at least one of the following:
  • the L3 cell measurement result prediction includes: predicting subsequent L3 cell measurement results based on historical L1 beam measurement results, and/or predicting subsequent L3 cell measurement results based on historical L3 cell measurement results.
  • the measurement event prediction includes: predicting the measurement event based on historical L1 beam measurement results, and/or predicting the measurement event based on historical L3 cell measurement results.
  • the abnormal event prediction includes at least one of the following:
  • the first communication device further includes: a receiving unit 902 .
  • the receiving unit 902 is configured to receive second information, where the second information is used to request the first communication device to report the mobility management-related prediction capability.
  • the second information includes a filtering condition requiring the first communication device to report a mobility management-related prediction capability.
  • the filtering condition includes at least one of the following:
  • the one technical feature corresponds to a prediction capability related to mobility management, and a model supports the one or more technical features.
  • the reporting granularity of the mobility management-related prediction capability includes terminal, frequency band, or frequency band combination.
  • the reporting granularity is that the terminal indicates reporting the models and/or technical features corresponding to all frequency bands and frequency band combinations supported by the terminal; or
  • the reporting granularity is frequency band, indicating reporting of the model and/or technical features corresponding to a frequency band; or
  • the reporting granularity is a frequency band combination, which means reporting a model and/or technical features corresponding to a frequency band combination.
  • the relationship between the predictive capabilities includes at least one of the following:
  • the receiving unit 902 is configured to receive third information, where the third information is used to configure the mobility management-related prediction capability reported by the first communication device.
  • the configuration granularity of the mobility management-related prediction capability includes a terminal, a measurement object, or a measurement task.
  • the configuration granularity is that the terminal represents configuring all measurement tasks of a terminal.
  • the configuration granularity is that the measurement object represents configuration of measurement tasks corresponding to all measurement task identifiers associated with one measurement object;
  • the configuration granularity is that the measurement task represents the configuration of a measurement object associated with a measurement task identifier.
  • the configuration granularity of the measurement result prediction, the measurement event prediction, the too-short-time handover event prediction, or the ping-pong handover event prediction is a terminal, a measurement object, or a measurement task.
  • the configuration granularity of the radio link failure prediction is a measurement task in which the frequency point where the primary cell or the primary and secondary cells are located is the measurement object.
  • the configuration granularity of handover failure prediction includes a combination of radio link failure configuration granularity and measurement event granularity.
  • the third information is used to configure one or more measurement event predictions, too-short-time handover event predictions, ping-pong handover event predictions, radio link failure predictions, or handover failure predictions on a measurement task.
  • the first communication device 900 of the embodiment of the present application can implement the corresponding functions of the first communication device in the aforementioned method embodiment.
  • the processes, functions, implementation methods and beneficial effects corresponding to the various modules (sub-modules, units or components, etc.) in the first communication device 900 can be found in the corresponding descriptions in the above-mentioned method embodiments, and will not be repeated here.
  • the functions described in the various modules (sub-modules, units or components, etc.) in the first communication device 900 of the embodiment of the application can be implemented by different modules (sub-modules, units or components, etc.) or by the same module (sub-module, unit or component, etc.).
  • FIG10 is a schematic block diagram of a second communication device 1000 according to an embodiment of the present application.
  • the second communication device 1000 may include:
  • the receiving unit 1001 is configured to receive and send first information, where the first information is used to indicate a mobility management-related prediction capability supported by a first communication device.
  • the mobility management-related prediction capability includes at least one of the following: measurement result prediction; measurement event prediction; and abnormal event prediction.
  • the measurement result prediction includes at least one of the following:
  • the L3 cell measurement result prediction includes: predicting subsequent L3 cell measurement results based on historical L1 beam measurement results, and/or predicting subsequent L3 cell measurement results based on historical L3 cell measurement results.
  • the measurement event prediction includes: predicting the measurement event based on historical L1 beam measurement results, and/or Predict measurement events based on historical L3 cell measurement results.
  • the abnormal event prediction includes at least one of the following:
  • the second communication device further includes: a sending unit 1002 .
  • the sending unit 1002 is configured to send second information, where the second information is used to request the first communication device to report the mobility management-related prediction capability.
  • the second information includes a filtering condition requiring the first communication device to report a mobility management-related prediction capability.
  • the filtering condition includes at least one of the following:
  • the one technical feature corresponds to a prediction capability related to mobility management, and a model supports the one or more technical features.
  • the reporting granularity of the mobility management-related prediction capability includes terminal, frequency band, or frequency band combination.
  • the reporting granularity is that the terminal indicates reporting the models and/or technical features corresponding to all frequency bands and frequency band combinations supported by the terminal; or
  • the reporting granularity is frequency band, indicating reporting of the model and/or technical features corresponding to a frequency band; or
  • the reporting granularity is a frequency band combination, which means reporting a model and/or technical features corresponding to a frequency band combination.
  • the relationship between the predictive capabilities includes at least one of the following:
  • the sending unit 1002 is configured to send third information, where the third information is used to configure a mobility management-related prediction capability reported by the first communication device.
  • the configuration granularity of the mobility management-related prediction capability includes a terminal, a measurement object, or a measurement task.
  • the configuration granularity is that the terminal represents configuring all measurement tasks of a terminal.
  • the configuration granularity is that the measurement object represents configuration of measurement tasks corresponding to all measurement task identifiers associated with one measurement object;
  • the configuration granularity is that the measurement task represents the configuration of a measurement object associated with a measurement task identifier.
  • the configuration granularity of the measurement result prediction, the measurement event prediction, the too-short-time handover event prediction, or the ping-pong handover event prediction is a terminal, a measurement object, or a measurement task.
  • the configuration granularity of the radio link failure prediction is a measurement task in which the frequency point where the primary cell or the primary and secondary cells are located is the measurement object.
  • the configuration granularity of handover failure prediction includes a combination of radio link failure configuration granularity and measurement event granularity.
  • the third information is used to configure one or more measurement event predictions, too-short-time handover event predictions, ping-pong handover event predictions, radio link failure predictions, or handover failure predictions on a measurement task.
  • the second communication device 1000 of the embodiment of the present application can implement the corresponding functions of the second communication device in the aforementioned method embodiment.
  • the processes, functions, implementation methods and beneficial effects corresponding to the various modules (sub-modules, units or components, etc.) in the second communication device 1000 can be found in the corresponding descriptions in the above-mentioned method embodiments, and will not be repeated here.
  • the functions described in the various modules (sub-modules, units or components, etc.) in the second communication device 1000 of the embodiment of the application can be implemented by different modules (sub-modules, units or components, etc.) or by the same module (sub-module, unit or component, etc.).
  • FIG 11 is a schematic structural diagram of a communication device 1100 according to an embodiment of the present application.
  • the communication device 1100 includes a processor 1110, which can call and execute a computer program from a memory to enable the communication device 1100 to implement the method in the embodiment of the present application.
  • the communication device 1100 may further include a memory 1120.
  • the processor 1110 may call and execute a computer program from the memory 1120 to enable the communication device 1100 to implement the method in the embodiment of the present application.
  • the memory 1120 may be a separate device independent of the processor 1110 , or may be integrated into the processor 1110 .
  • the communication device 1100 may further include a transceiver 1130 , and the processor 1110 may control the transceiver 1130 to communicate with other devices.
  • the transceiver 1130 may send information or data to other devices, or receive information or data sent by other devices.
  • the transceiver 1130 may include a transmitter and a receiver.
  • the transceiver 1130 may further include an antenna, and the number of antennas may be one or more.
  • the communication device 1100 may be the first communication device of the embodiment of the present application, and the communication device 1100 may implement the corresponding processes implemented by the first communication device in each method of the embodiment of the present application. For the sake of brevity, they will not be repeated here.
  • the communication device 1100 may be the second communication device of the embodiment of the present application, and the communication device 1100 may implement the corresponding processes implemented by the second communication device in each method of the embodiment of the present application. For the sake of brevity, they will not be repeated here.
  • the chip 700 includes a processor 710, which can call and execute a computer program from a memory to implement the method according to the embodiment of the present application.
  • the chip 700 may further include a memory 720.
  • the processor 710 may call and execute a computer program from the memory 720 to implement the method executed by the terminal device or the network device in the embodiment of the present application.
  • the memory 720 may be a separate device independent of the processor 710 , or may be integrated into the processor 710 .
  • the chip 700 may further include an input interface 730.
  • the processor 710 may control the input interface 730 to communicate with other devices or chips, and specifically, may obtain information or data sent by other devices or chips.
  • the chip 700 may further include an output interface 740.
  • the processor 710 may control the output interface 740 to communicate with other devices or chips, and specifically, may output information or data to other devices or chips.
  • the chip can be applied to the first communication device in the embodiment of the present application, and the chip can implement the corresponding processes implemented by the first communication device in each method of the embodiment of the present application. For the sake of brevity, it will not be repeated here.
  • the chip can be applied to the second communication device in the embodiment of the present application, and the chip can implement the corresponding processes implemented by the second communication device in each method of the embodiment of the present application. For the sake of brevity, it will not be repeated here.
  • the chips used in the first communication device and the second communication device may be the same chip or different chips.
  • the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.
  • the memory mentioned above may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.
  • the non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory.
  • the volatile memory may be random access memory (RAM).
  • the memories in the embodiments of the present application may also be static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM RAM (DR RAM), etc.
  • SRAM static random access memory
  • DRAM dynamic random access memory
  • SDRAM synchronous dynamic random access memory
  • DDR SDRAM double data rate synchronous dynamic random access memory
  • ESDRAM enhanced synchronous dynamic random access memory
  • SLDRAM synchronous link dynamic random access memory
  • DR RAM direct RAM
  • FIG13 is a schematic block diagram of a communication system 1300 according to an embodiment of the present application.
  • the communication system 1300 includes a first communication device 1310 and a second communication device 1320 .
  • the first communication device 1310 is configured to send first information, where the first information is used to indicate a prediction capability related to mobility management supported by the first communication device.
  • the second communication device 1320 is configured to receive and send first information.
  • the computer program product includes one or more computer instructions.
  • the computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.
  • the computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium.
  • the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.)
  • the computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that includes one or more available media.
  • the available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, or a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).
  • SSD solid-state drive
  • the size of the serial numbers of the above-mentioned processes does not mean the order of execution.
  • the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
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  • Mobile Radio Communication Systems (AREA)

Abstract

La présente demande se rapporte à un procédé de communication et un dispositif de communication. Le procédé comprend les étapes suivantes : un premier dispositif de communication envoie des premières informations, les premières informations étant utilisées pour indiquer une capacité de prédiction liée à la gestion de mobilité prise en charge par le premier dispositif de communication. Dans des modes de réalisation de la présente demande, en rapportant une capacité de prédiction liée à la gestion de mobilité prise en charge par un dispositif de communication, un algorithme associé à la gestion de mobilité du côté dispositif de communication peut être exploité raisonnablement.
PCT/CN2024/080304 2024-03-06 2024-03-06 Procédé et dispositif de communication Pending WO2025184828A1 (fr)

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