WO2023165447A1 - 小区切换方法、装置及用户设备 - Google Patents

小区切换方法、装置及用户设备 Download PDF

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Publication number
WO2023165447A1
WO2023165447A1 PCT/CN2023/078462 CN2023078462W WO2023165447A1 WO 2023165447 A1 WO2023165447 A1 WO 2023165447A1 CN 2023078462 W CN2023078462 W CN 2023078462W WO 2023165447 A1 WO2023165447 A1 WO 2023165447A1
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WIPO (PCT)
Prior art keywords
cell
handover
signal quality
model
side device
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PCT/CN2023/078462
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English (en)
French (fr)
Inventor
宋二浩
潘翔
周通
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维沃移动通信有限公司
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Publication of WO2023165447A1 publication Critical patent/WO2023165447A1/zh

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H04W36/0055—Transmission or use of information for re-establishing the radio link
    • H04W36/0058—Transmission of hand-off measurement information, e.g. measurement reports
    • 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
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H04W36/0011—Control or signalling for completing the hand-off for data sessions of end-to-end connection
    • H04W36/0016—Hand-off preparation specially adapted for end-to-end data sessions

Definitions

  • the present application belongs to the technical field of communications, and in particular relates to a message processing method, device and electronic equipment.
  • the user equipment needs to go through the processes of measurement report trigger, measurement result report, handover preparation, handover command issuance, handover execution and other processes during the cell handover process.
  • a long cell handover delay may lead to poor signal quality of the UE in the serving cell during the cell handover process, resulting in radio link failure (Radio Link Failure, RLF) or failure to receive the handover command.
  • RLF Radio Link Failure
  • the user equipment may have the problem of long handover delay or cell handover failure.
  • Embodiments of the present application provide a cell handover method, device, and user equipment, which can shorten the handover delay for the user equipment to perform cell handover and improve the success rate of cell handover.
  • a cell handover method which is applied to user equipment UE.
  • the method includes: the UE receives the measurement report configuration sent by the network side device, and the measurement report configuration includes at least one of the following: artificial intelligence AI model related information, AI Model input information, AI model output information, AI model reasoning trigger conditions, cell handover event-related configuration, expected report content of network-side equipment, total duration of AI model prediction output, number or interval of AI model prediction output time points, and One indication information, the first indication information is used to indicate whether the UE triggers the measurement report based on the result of the AI model prediction; the UE performs AI model reasoning on at least one handover candidate cell according to the measurement report configuration, obtains the reasoning result, and performs cell based on the reasoning result switch.
  • a cell switching device in a second aspect, includes: a receiving module, an executing module and a triggering module.
  • the receiving module is configured to receive the measurement report configuration sent by the network side device, the measurement report configuration includes at least one of the following: artificial intelligence AI model related information, AI model input information, AI model output information, AI model reasoning trigger conditions, cell handover events Relevant configuration, expected report content of network side equipment, total duration of AI model prediction output, number or interval of time points or intervals of AI model prediction output, first indication information, the first indication information is used to indicate whether UE is based on AI model prediction
  • the results trigger measurement reporting.
  • the executing module is configured to execute AI model reasoning on at least one handover candidate cell according to the measurement report configuration received by the receiving module, and obtain a reasoning result.
  • the trigger module is used to perform cell handover based on the reasoning result obtained by the execution module.
  • a user equipment in a third aspect, includes a processor and a memory, the memory stores programs or instructions that can run on the processor, and the programs or instructions are implemented when executed by the processor The steps of the method as described in the first aspect.
  • a user equipment including a processor and a communication interface, wherein the processor uses To receive the measurement report configuration sent by the network side device, the measurement report configuration includes at least one of the following: artificial intelligence AI model related information, AI model input information, AI model output information, AI model reasoning trigger conditions, cell handover event related configuration, The report content expected by the network side device, the total duration of the AI model prediction output, the number or interval of the AI model prediction output time points, and the first indication information, the first indication information is used to indicate whether the UE is triggered based on the result of the AI model prediction Measurement reporting.
  • AI model inference is performed on at least one handover candidate cell to obtain an inference result. And perform cell handover based on the reasoning result.
  • a readable storage medium is provided, and a program or an instruction is stored on the readable storage medium, and when the program or instruction is executed by a processor, the steps of the method according to the first aspect are implemented.
  • a sixth aspect provides a chip, the chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the method as described in the first aspect .
  • a computer program/program product is provided, the computer program/program product is stored in a storage medium, and the computer program/program product is executed by at least one processor to implement the method described in the first aspect The steps of the cell handover method.
  • the UE receives the measurement report configuration sent by the network side device, and the measurement report configuration includes at least one of the following: artificial intelligence AI model related information, AI model input information, AI model output information, AI model reasoning trigger conditions, Configuration related to cell handover events, expected report content of network side equipment, total duration of AI model prediction output, number or interval of time points or intervals of AI model prediction output, first indication information, the first indication information is used to indicate whether UE is based on AI
  • the result of the model prediction triggers the measurement report; the UE performs AI model reasoning on at least one handover candidate cell according to the measurement report configuration, obtains the reasoning result, and performs cell handover based on the reasoning result.
  • the UE can receive the measurement reporting configuration sent by the network-side device, and perform AI model reasoning on at least one neighboring cell according to the AI model input and output information in the network-side device and the AI model reasoning trigger conditions, and judge whether to trigger the measurement based on the reasoning result Report, and report the measurement report when the predicted signal or real signal meets certain conditions, so that the UE can report the measurement report at an appropriate time. In this way, the handover delay of the UE during cell handover is shortened, and the The success rate of cell handover.
  • FIG. 1 is a schematic structural diagram of a communication system provided by an embodiment of the present application.
  • FIG. 2 is a schematic diagram of a cell handover method provided by an embodiment of the present application.
  • FIG. 3 is a schematic diagram of a cell handover method provided by an embodiment of the present application.
  • FIG. 4 is a schematic diagram of a cell handover method provided by an embodiment of the present application.
  • FIG. 5 is a schematic diagram of a cell handover device provided in an embodiment of the present application.
  • FIG. 6 is a schematic diagram of a hardware structure of a communication device provided by an embodiment of the present application.
  • FIG. 7 is a schematic diagram of a hardware structure of a UE provided by an embodiment of the present application.
  • first, second and the like in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific sequence or sequence. It is to be understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments of the application can be practiced in sequences other than those illustrated or described herein,
  • the objects distinguished by “first” and “second” are generally of one type, and the number of objects is not limited. For example, there may be one or more first objects.
  • “and/or” in the specification and claims indicates at least one of the connected objects, and the character “/" generally indicates that the related objects are an "or” relationship.
  • LTE Long Term Evolution
  • LTE-Advanced LTE-Advanced
  • LTE-A Long Term Evolution-Advanced
  • CDMA Code Division Multiple Access
  • TDMA Time Division Multiple Access
  • FDMA Frequency Division Multiple Access
  • OFDMA Orthogonal Frequency Division Multiple Access
  • SC-FDMA Single-carrier Frequency Division Multiple Access
  • system and “network” in the embodiments of the present application are often used interchangeably, and the described technology can be used for the above-mentioned system and radio technology, and can also be used for other systems and radio technologies.
  • NR New Radio
  • the following description describes the New Radio (NR) system for illustrative purposes, and uses NR terminology in most of the following descriptions, but these techniques can also be applied to applications other than NR system applications, such as the 6th generation (6 th Generation, 6G) communication system.
  • 6G 6th Generation
  • Fig. 1 shows a block diagram of a wireless communication system to which the embodiment of the present application is applicable.
  • the wireless communication system includes a terminal 11 and a network side device 12 .
  • the terminal 11 can be a mobile phone, a tablet computer (Tablet Personal Computer), a laptop computer (Laptop Computer) or a notebook computer, a personal digital assistant (Personal Digital Assistant, PDA), a palmtop computer, a netbook, a super mobile personal computer (ultra-mobile personal computer, UMPC), mobile Internet device (Mobile Internet Device, MID), augmented reality (augmented reality, AR) / virtual reality (virtual reality, VR) equipment, robot, wearable device (Wearable Device) , vehicle equipment (VUE), pedestrian terminal (PUE), smart home (home equipment with wireless communication functions, such as refrigerators, TVs, washing machines or furniture, etc.), game consoles, personal computers (personal computers, PCs), teller machines or self-service Wearable devices include: smart watches, smart bracelets, smart headphones, smart glasses, smart jewelry (
  • the network side device 12 may include an access network device or a core network device, where the access network device 12 may also be called a radio access network device, a radio access network (Radio Access Network, RAN), a radio access network function, or Wireless access network unit.
  • RAN Radio Access Network
  • RAN Radio Access Network
  • Wireless access network unit Wireless access network unit
  • the access network device 12 may include a base station, a WLAN access point, or a WiFi node, etc., and the base station may be called a Node B, an evolved Node B (eNB), an access point, a Base Transceiver Station (Base Transceiver Station, BTS), a radio Base station, radio transceiver, Basic Service Set (BSS), Extended Service Set (ESS), Home Node B, Home Evolved Node B, Transmitting Receiving Point (TRP) or all As long as the same technical effect is achieved, the base station is not limited to a specific technical vocabulary. It should be noted that in this embodiment of the application, only the base station in the NR system is used as an example for introduction, and The specific type of the base station is not limited.
  • the cell handover method provided by the embodiment of the present application will be described in detail below through some embodiments and application scenarios with reference to the accompanying drawings.
  • the UE needs to perform cell handover, it needs to go through the process of measurement report trigger, measurement result report, handover preparation, handover command issuance, and handover execution. Therefore, the UE performs cell handover with a long delay. A longer value may lead to poor signal quality of the UE in the serving cell during cell handover, resulting in As a result, RLF occurs or the handover command cannot be received, so that the UE cell handover fails.
  • the main steps of the existing cell handover include:
  • the source base station sends the measurement configuration to the UE.
  • the UE performs measurement according to the measurement configuration sent by the source base station, and reports a measurement report when conditions are met.
  • the source base station interacts with the target base station and prepares for handover.
  • the UE receives the handover command issued by the source base station, immediately disconnects from the source cell, and accesses the target cell.
  • the UE can determine whether to trigger measurement reporting based on the configured events.
  • events are mainly divided into the following nine types:
  • the commonly used events for Intra-RAT switching are A3 or A5 events.
  • A3 event the meanings of the parameters of the entry condition and exit condition are as follows:
  • Ocn Neighboring cell-level specific offset.
  • Mp the measurement result of the primary serving cell (SpCell), regardless of any offset.
  • SpCell measure object specific offset.
  • Ocp SpCell cell-level specific offset.
  • Hys The hysteresis parameter of the event.
  • the base station configures a trigger time (timeToTrigger) parameter for each event in the measurement report configuration.
  • the UE When the L3 filtered signal quality of one or more cells within the timeToTrigger time meets the entry condition of the event, the UE includes the corresponding cell into the cell trigger list (cellsTriggeredList) and triggers a report.
  • cellsTriggeredList the cell trigger list
  • FIG. 2 shows a flow chart of the cell switching method provided in the embodiment of the present application.
  • the cell handover method provided in the embodiment of the present application may include the following steps 201 and 202 .
  • Step 201 the user equipment UE receives the measurement report configuration sent by the network side equipment.
  • the above measurement report configuration includes at least one of the following: artificial intelligence AI model related information, AI model input information, AI model output information, AI model reasoning trigger conditions, cell handover event related configuration, network side equipment expected
  • the report content the total duration of the AI model prediction output, the number or interval of the AI model prediction output time points, and the first indication information, the first indication information is used to indicate whether the UE triggers measurement reporting based on the AI model prediction result;
  • the foregoing measurement reporting configuration may be configured, pre-configured, predefined, agreed by a protocol, etc. on the network side device.
  • the UE when the UE needs to perform cell handover, it can receive the measurement report configuration sent by the network side device, trigger the measurement report according to the information in the policy report configuration, and report the measurement result, so that the network side device can Prepare for handover, and send a handover command to the UE, so that the UE can receive the handover command sent from the network side device and execute the handover.
  • the above AI model input information includes at least one of the following: network side equipment The signal quality of the serving cell and/or the neighboring cell of the UE at the target time; the mobile parameters of the UE at the target time; the antenna panel parameters of the UE at the target time, and the antenna panel parameters include at least one of the following: antenna panel orientation, antenna panel rotation Direction, antenna panel rotation speed; UE position information at the target moment; target position information, target position information is used to indicate the network side device and/or the position of the network side device corresponding to the UE's neighboring cell, target direction information, target direction information It is used to indicate the orientation of the antenna panel of the network side equipment; the current frequency point information of the UE and/or other frequency point information/radio access technology RAT information; the beam angle and beam quality of the UE at the target time and/or historical time; among them , the target moment is the moment or historical moment that triggers the execution of AI model reasoning.
  • the above-mentioned AI model output information includes at least one of the following: at least one predicted signal quality; the lowest signal quality in at least one predicted signal quality; the difference between every two signal qualities in at least one predicted signal quality The minimum difference in values; the handover success rate of at least one handover candidate cell; the handover delay of at least one handover candidate cell; the probability of an unexpected event occurring in at least one handover candidate cell; at least one beam quality;
  • the quality is the signal quality of the serving cell of the network side device and/or the neighboring cell of the UE at at least one first moment, and the at least one first moment is a moment within the total duration of the AI model prediction output, at least one signal quality and at least one second One-to-one correspondence at a time.
  • the above-mentioned undesired events include at least one of the following: a too late handover event; an early handover event; and handover to a wrong cell.
  • the above-mentioned too late handover event refers to: the UE stays on the source cell for too long to cause RLF, and tries to reestablish Radio Resource Control (RRC) in other cells.
  • RRC Radio Resource Control
  • the above-mentioned premature handover event refers to: the UE occurs RLF within a short period of time after successfully handing over to the target cell, or during the process of handing over to the target cell, and attempts RRC reestablishment on the source cell.
  • Handover to the wrong cell refers to: within a short period of time after the UE successfully switches to the target cell, or during the process of switching to the target cell, RLF occurs, RRC reestablishment is attempted on a non-target cell).
  • the AI model reasoning trigger conditions include at least one of the following: periodic trigger conditions, event trigger conditions, and measurement report trigger conditions.
  • the above-mentioned event triggering conditions include at least one of the following: the signal quality of the serving cell of the network side device is less than or equal to the first preset threshold; the signal quality of the UE's neighbor cell is greater than or equal to The second preset threshold value; the signal quality difference between the serving cell of the network side device and the neighboring cell of the UE is less than or equal to the third preset threshold value.
  • the above cycle trigger condition is: the network side device needs to configure a model reasoning cycle.
  • the above measurement reporting trigger condition is: when the UE triggers the measurement report according to the information in the measurement reporting configuration, it triggers the execution of AI model reasoning and reports the reasoning result.
  • the above-mentioned signal quality includes at least one of the following: Reference Signal Received Power (Reference Signal Receiving Power, RSRP), Reference Signal Received Quality (Reference Signal Receiving Quality, RSRQ), signal to interference and noise ratio (Signal to Interference and Noise Ratio, SINR).
  • RSRP Reference Signal Received Power
  • RSRQ Reference Signal Received Quality
  • SINR Signal to Interference and Noise Ratio
  • the above-mentioned report content includes at least one of the following: the signal quality of the serving cell of the network side device and/or the neighboring cell of the UE at the second moment, and the second moment is the moment when the measurement report is triggered;
  • the signal quality is the signal quality of the serving cell of the network side device and/or the adjacent cell of the UE; or, the signal quality is to The signal quality of one less beam;
  • the handover time point is the optimal handover time point among the time points predicted and output by the AI model, and the target signal quality prediction result is the signal quality prediction result of the serving cell of the network side device and/or the neighboring cell of the UE at at least one handover time point;
  • the reported content is determined based on a reasoning result.
  • Step 202 the UE performs AI model reasoning on at least one handover candidate cell according to the measurement report configuration, obtains a reasoning result, and performs cell handover based on the reasoning result.
  • the above reasoning result is used to trigger the UE to perform cell handover.
  • the above reasoning results include at least one of the following: the predicted signal quality of at least one handover candidate cell within the total duration of AI model prediction output, and the real signal quality of at least one handover candidate cell.
  • the above-mentioned predicted signal quality includes at least one of the following: RSRP, RSRQ, and SINR.
  • the process of performing cell handover based on the inference result includes: the UE triggers measurement reporting based on the inference result.
  • the "triggering measurement reporting based on the inference result" in the above step 202 may specifically be implemented through at least one of the following three steps: step 202a, step 202b, and step 202c.
  • Step 202a when the predicted signal quality of the target handover candidate cell always meets the preset handover event entry condition within the total duration of the AI model prediction output, the UE triggers to report the first measurement report.
  • the above-mentioned first measurement report is used to indicate that the predicted signal quality of the target handover candidate cell satisfies a preset handover event entry condition.
  • Step 202b when the predicted signal quality of the target handover candidate cell always meets the preset handover event leaving condition within the total duration of the AI model prediction output, the UE triggers to report the second measurement report.
  • the above-mentioned second measurement report is used to indicate that the predicted signal quality of the target handover candidate cell satisfies the preset handover event leaving condition.
  • Step 202c when the real signal quality of the target handover candidate cell meets the preset handover event entry condition within the measurement reporting trigger time configured by the network side device, the UE triggers reporting of a third measurement report.
  • An embodiment of the present application provides a cell handover method.
  • the UE receives the measurement report configuration sent by the network side device, and the measurement report configuration includes at least one of the following: artificial intelligence AI model related information, AI model input information, AI model output information, AI model reasoning trigger conditions, cell handover event related configuration, expected report content of network side equipment, total duration of AI model prediction output, time point number or interval of AI model prediction output, first instruction information,
  • the first indication information is used to indicate whether the UE triggers measurement reporting based on the result of the AI model prediction; the UE performs AI model reasoning on at least one handover candidate cell according to the measurement reporting configuration, obtains a reasoning result, and performs cell handover based on the reasoning result.
  • the above target cell may be selected by the UE based on the reasoning result, or may be configured for the UE by the network side device based on the received reasoning result.
  • the embodiment of the present application provides a cell handover method, which corresponds to step 202a in the first embodiment above. Exemplarily, as shown in FIG. The following steps 21 to 26 will be described.
  • the content of the report is: the number of time points or intervals of the AI model prediction output within the total duration of the AI model prediction output, and the measurement results of the predicted signal quality of the serving cell and neighboring cells of the network side device .
  • the above time t 0 is the time when the UE triggers the execution of AI model reasoning.
  • step 23 the UE obtains the predicted signal quality values of the serving cell and the neighboring cell A of the network side device at each ⁇ t time during t 0 -t 0 +T by reasoning.
  • the above-mentioned T is the total duration of the AI model prediction output, and ⁇ t is the number or interval of time points of the AI model prediction output.
  • Step 24 When the signal quality prediction values of the serving cell and the neighboring cell A of the network side device always meet the entry condition of the handover event within the time T, the UE reports the first measurement report to the network side device.
  • the above-mentioned first measurement report includes the signal quality of the serving cell and the neighboring cell A of the network side device every ⁇ t time within the time T.
  • Step 25 the UE receives the handover command sent by the network side device within time t1 .
  • the above handover command is used to instruct the UE to handover to the neighboring cell A.
  • the above time t1 is the time when the UE receives the handover command sent by the network side device.
  • step 26 the UE initiates a random access request to the neighboring cell A according to the handover command, and completes the handover at time t2 .
  • the foregoing random access request is used to request the neighboring cell A.
  • the above time t2 is the time when UE handover is completed.
  • the embodiment of the present application provides a cell handover method, because the UE can receive the measurement reporting configuration sent by the network side device, and perform AI on at least one neighboring cell according to the AI model input and output information in the network side device and the AI model inference trigger condition Model reasoning, and judge whether to trigger the measurement report based on the reasoning results, and report the measurement report when the predicted signal or the real signal meets certain conditions, so that the UE can report the measurement report at an appropriate time.
  • the handover delay during cell handover improves the success rate of cell handover.
  • the embodiment of the present application provides a cell switching method, corresponding to step 202b in the first embodiment above, and the cell switching method provided in the embodiment of the present application is described through the following step 31.
  • Step 31 the UE receives the measurement report configuration sent by the network side device.
  • the configuration includes timeToTrigger configuration and indication information of the event.
  • the above indication information is used to indicate whether the UE triggers measurement reporting based on the prediction result output by the AI model.
  • step 31 includes two ways, namely, way one and way two.
  • the predicted signal quality of the target candidate cells in the cell trigger list within timeToTrigger all meet the departure conditions of the configured handover event, remove the corresponding target candidate cells from the cell trigger list, and trigger reporting.
  • the above indication information may be for each UE/each measurement ID (measurement ID)/each event (reportConfig).
  • the embodiment of the present application provides a cell handover method, because the UE can receive the measurement reporting configuration sent by the network side device, and perform AI on at least one neighboring cell according to the AI model input and output information in the network side device and the AI model inference trigger condition Model reasoning, and judge whether to trigger the measurement report based on the reasoning results, and report the measurement report when the predicted signal or the real signal meets certain conditions, so that the UE can report the measurement report at an appropriate time.
  • the handover delay during cell handover improves the success rate of cell handover.
  • the embodiment of the present application provides a cell handover method, which corresponds to step 202c in the first embodiment above.
  • a cell handover method which corresponds to step 202c in the first embodiment above.
  • FIG. C Exemplarily, as shown in FIG. C) as an example, the following steps 41 to 46 are used for illustration.
  • Step 41 the UE receives the measurement report configuration sent by the network side device.
  • some configurations in the above-mentioned measurement reporting configuration include: cell handover event-related configuration, total duration of AI model prediction output, time point number or interval of AI model prediction output, AI model reasoning trigger Conditions, trigger measurement reporting conditions, and reporting content.
  • the AI model reasoning trigger reasoning condition is as follows: when the real signal quality of the target handover candidate cell meets the preset handover event entry condition within the measurement reporting trigger time configured by the network side device, The UE reports the third measurement report to the network side device.
  • the foregoing real signal is an L3 filtered signal.
  • the third measurement report is used to indicate that the real signal quality of the target handover candidate cell satisfies a preset handover event entry condition.
  • the above-mentioned triggering measurement reporting condition is: a measurement reporting triggering condition.
  • the triggering condition for the above measurement report is: when the UE triggers the measurement report according to the information in the measurement report configuration, it triggers the execution of the AI model reasoning and reports the reasoning result.
  • the content of the report is: the number of time points or intervals of the AI model prediction output within the total duration of the AI model prediction output, and the measurement results of the predicted signal quality of the serving cell and neighboring cells of the network side device .
  • Step 42 at time t3 , the UE meets the entry condition of the configuration related to the cell handover event for the first time.
  • Step 43 at time t4 , when the measurement reporting trigger timeout expires and neighboring cell B and neighboring cell C meet the trigger reporting conditions at the same time, the UE performs AI model reasoning on neighboring cell B and neighboring cell C according to the measurement reporting configuration.
  • time t4 is a time when the UE performs AI model inference on neighboring cell B and neighboring cell C.
  • the third measurement report is used to indicate that the real signal quality of neighboring cell B and neighboring cell C satisfies the preset handover event entry condition, and the above third measurement report includes The signal quality of the serving cell, neighboring cell B, and neighboring cell C of the network-side device.
  • Step 45 the UE receives the handover command sent by the network side device within time t5 .
  • the above handover command is used to instruct the UE to handover to the neighboring cell C.
  • the above time t5 is the time when the UE receives the handover command sent by the network side device.
  • Step 46 the UE initiates a random access request to the neighboring cell C according to the handover command, and completes the handover at time t6 .
  • the foregoing random access request is used to request the neighboring cell C.
  • the above time t6 is the time when UE handover is completed.
  • the embodiment of the present application provides a cell handover method, because the UE can receive the measurement reporting configuration sent by the network side device, and perform AI on at least one neighboring cell according to the AI model input and output information in the network side device and the AI model inference trigger condition Model reasoning, and judge whether to trigger the measurement report based on the reasoning results, and report the measurement report when the predicted signal or the real signal meets certain conditions, so that the UE can report the measurement report at an appropriate time.
  • the handover delay during cell handover improves the success rate of cell handover.
  • the cell switching method provided in the embodiment of the present application may be executed by a cell switching device.
  • the cell switching method performed by the cell switching device is taken as an example to describe the cell switching device provided in the embodiment of the present application.
  • FIG. 5 shows a possible structural diagram of a cell handover apparatus involved in the embodiment of the present application.
  • the cell switching device 60 may include: a receiving module 61 , an executing module 62 and a triggering module 63 .
  • the receiving module 61 is configured to receive the measurement report configuration sent by the network side device, the measurement report configuration includes at least one of the following: artificial intelligence AI model related information, AI model input information, AI model output information, AI model reasoning trigger conditions, Configuration related to cell handover events, expected report content of network side equipment, total duration of AI model prediction output, number or interval of time points or intervals of AI model prediction output, first indication information, the first indication information is used to indicate whether UE is based on AI
  • the results of model predictions trigger measurement reporting.
  • the executing module 62 is configured to execute AI model reasoning on at least one handover candidate cell according to the measurement reporting configuration received by the receiving module 61 to obtain a reasoning result.
  • a triggering module 63 configured to perform cell handover based on the reasoning result obtained by the executing module 62.
  • the embodiment of the present application provides a cell handover device, because the UE can receive the measurement report configuration sent by the network side equipment, and perform AI on at least one neighboring cell according to the AI model input and output information in the network side equipment and the AI model inference trigger condition Model reasoning, and judge whether to trigger the measurement report based on the reasoning results, and report the measurement report when the predicted signal or the real signal meets certain conditions, so that the UE can report the measurement report at an appropriate time.
  • the handover delay during cell handover improves the success rate of cell handover.
  • the input information of the AI model includes at least one of the following: the signal quality of the serving cell of the network side device and/or the neighboring cell of the UE at the target time; the mobility parameters of the UE at the target time;
  • the antenna panel parameters at any time, the antenna panel parameters include at least one of the following: antenna panel orientation, antenna panel rotation direction, antenna panel rotation speed; UE position information at the target time; target position information, the target position information is used to indicate the network side equipment and/or the position of the network-side device corresponding to the UE’s adjacent cell, the target direction information, and the target direction information is used to indicate the orientation of the antenna panel of the network-side device; the frequency point information where the UE is currently located and/or other frequency point information/wireless access information Enter the technology RAT information; the beam angle and beam quality of the UE at the target time and/or historical time; wherein, the target time is the time when the AI model reasoning is triggered or the historical time is triggered.
  • the AI model output information includes at least one of the following: at least one predicted signal quality; the lowest signal quality in at least one predicted signal quality; the difference between every two signal qualities in at least one predicted signal quality The minimum difference; the handover success rate of at least one handover candidate cell; at least one handover candidate The handover delay of the selected cell; the probability of an unexpected event occurring in at least one handover candidate cell; at least one beam quality; wherein, at least one signal quality is the serving cell of the network side device and/or the neighboring cell of the UE at least one first moment The signal quality of the at least one first moment is a moment within the total duration of the AI model prediction output, and the at least one signal quality corresponds to the at least one first moment.
  • the unexpected event includes at least one of the following: a too late handover event; an early handover event; and handover to a wrong cell.
  • the AI model reasoning trigger condition includes at least one of the following: a periodic trigger condition, an event trigger condition, and a measurement report trigger condition.
  • the event trigger condition includes at least one of the following: the signal quality of the serving cell of the network side device is less than or equal to a first preset threshold; the signal quality of a neighboring cell of the UE is greater than or equal to a second threshold. A preset threshold value; the signal quality difference between the serving cell of the network side device and the neighboring cell of the UE is less than or equal to a third preset threshold value.
  • the report content includes at least one of the following: the signal quality of the serving cell of the network side device and/or the neighboring cell of the UE at the second moment, and the second moment is the moment when the measurement report is triggered; the signal quality It is the signal quality of the serving cell of the network-side device and/or the adjacent cell of the UE, or the signal quality is the signal quality of at least one beam;
  • the reported content is determined based on a reasoning result.
  • the inference result includes at least one of the following: the predicted signal quality of at least one handover candidate cell within the total duration of AI model prediction output, and the real signal quality of at least one handover candidate cell.
  • the process of performing cell handover based on the inference result includes: the UE triggers measurement reporting based on the inference result.
  • the trigger module 63 is specifically configured to trigger the UE to report the first handover event when the predicted signal quality of the target handover candidate cell always meets the preset handover event entry condition within the total duration of the AI model prediction output.
  • a measurement report when the predicted signal quality of the target handover candidate cell always meets the preset handover event departure condition within the total duration of the AI model prediction output, the UE triggers reporting of the second measurement report; in the real case of the target handover candidate cell
  • the UE triggers reporting of the third measurement report; wherein, the target handover candidate cell is one or more of at least one handover candidate cell districts.
  • the total duration of the AI model prediction output and the trigger duration of measurement report are the duration configured separately by the network side device; Measure the duration configured in the reporting configuration.
  • the cell handover apparatus further includes: an initiating module.
  • the receiving module 61 is further configured to receive a handover command sent by the network side device after the triggering module 63 triggers the measurement report based on the inference result, the handover command is used to instruct the UE to handover to a target cell selected based on the inference result among at least one handover candidate cell.
  • the initiating module is configured to initiate a random access request to the target cell according to the handover command received by the receiving module 61, and the random access request is used to request access to the target cell.
  • the cell handover apparatus in this embodiment of the present application may be an electronic device, such as an electronic device with an operating system, or a component of the electronic device, such as an integrated circuit or a chip.
  • the electronic device may be a UE, or other devices other than the UE.
  • the UE may include, but is not limited to, the types of terminals 11 listed above, and other devices may be servers, Network Attached Storage (Network Attached Storage, NAS), etc., which are not specifically limited in this embodiment of the present application.
  • Network Attached Storage Network Attached Storage
  • the cell handover device provided in the embodiment of the present application can realize various processes realized by the method embodiments in FIG. 1 to FIG. 4 , and achieve the same technical effect. To avoid repetition, details are not repeated here.
  • the embodiment of the present application also provides a communication device 700, including a processor 701 and a memory 702, and the memory 702 stores programs or instructions that can run on the processor 701, such as
  • the communication device 700 is a UE
  • the program or instruction is executed by the processor 701
  • each step of the above cell handover method embodiment can be implemented, and the same technical effect can be achieved.
  • the communication device 700 is a network-side device
  • the program or instruction is executed by the processor 701
  • the steps of the above-mentioned cell handover method embodiment can be achieved, and the same technical effect can be achieved. To avoid repetition, details are not repeated here.
  • the embodiment of the present application also provides a UE, including a processor and a communication interface, the processor is used to receive the measurement report configuration sent by the network side device, the measurement report configuration includes at least one of the following: artificial intelligence AI model related information, AI model input Information, AI model output information, AI model reasoning trigger conditions, cell handover event related configuration, expected report content of network side equipment, total duration of AI model prediction output, time point number or interval of AI model prediction output, first indication information, where the first indication information is used to indicate whether the UE triggers measurement reporting based on the AI model prediction result.
  • AI model inference is performed on at least one handover candidate cell to obtain an inference result. And perform cell handover based on the reasoning result.
  • FIG. 7 is a schematic diagram of a hardware structure of a UE implementing an embodiment of the present application.
  • the UE100 includes but is not limited to: at least one of a radio frequency unit 101, a network module 102, an audio output unit 103, an input unit 104, a sensor 105, a display unit 106, a user input unit 107, an interface unit 108, a memory 109, and a processor 110. part parts.
  • the UE 100 may also include a power supply (such as a battery) for supplying power to various components, and the power supply may be logically connected to the processor 110 through the power management system, so as to manage charging, discharging, and power consumption through the power management system. and other functions.
  • a power supply such as a battery
  • the UE structure shown in FIG. 7 does not limit the UE, and the UE may include more or fewer components than shown in the figure, or combine certain components, or arrange different components, which will not be repeated here.
  • the input unit 104 may include a graphics processing unit (Graphics Processing Unit, GPU) 1041 and a microphone 1042, and the graphics processor 1041 is used in the video capture mode or image capture mode by the image capture device (such as the image data of the static picture or video obtained by the camera) for processing reason.
  • the display unit 106 may include a display panel 1061, and the display panel 1061 may be configured in the form of a liquid crystal display, an organic light emitting diode, or the like.
  • the user input unit 107 includes at least one of a touch panel 1071 and other input devices 1072 .
  • the touch panel 1071 is also called a touch screen.
  • the touch panel 1071 may include two parts, a touch detection device and a touch controller.
  • Other input devices 1072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, switch buttons, etc.), trackballs, mice, and joysticks, which will not be repeated here.
  • the radio frequency unit 101 after the radio frequency unit 101 receives the downlink data from the network side device, it can transmit it to the processor 110 for processing; in addition, the radio frequency unit 101 can send the uplink data to the network side device.
  • the radio frequency unit 101 includes, but is not limited to, an antenna, an amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like.
  • the memory 109 can be used to store software programs or instructions as well as various data.
  • the memory 109 can mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area can store an operating system, an application program or instructions required by at least one function (such as a sound playing function, image playback function, etc.), etc.
  • memory 109 may include volatile memory or nonvolatile memory, or, memory 109 may include both volatile and nonvolatile memory.
  • the non-volatile memory can be read-only memory (Read-Only Memory, ROM), programmable read-only memory (Programmable ROM, PROM), erasable programmable read-only memory (Erasable PROM, EPROM), electronically programmable Erase Programmable Read-Only Memory (Electrically EPROM, EEPROM) or Flash.
  • ROM Read-Only Memory
  • PROM programmable read-only memory
  • Erasable PROM Erasable PROM
  • EPROM erasable programmable read-only memory
  • Electrical EPROM Electrical EPROM
  • EEPROM electronically programmable Erase Programmable Read-Only Memory
  • Volatile memory can be random access memory (Random Access Memory, RAM), static random access memory (Static RAM, SRAM), dynamic random access memory (Dynamic RAM, DRAM), synchronous dynamic random access memory (Synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (Double Data Rate SDRAM, DDRSDRAM), enhanced synchronous dynamic random access memory (Enhanced SDRAM, ESDRAM), synchronous connection dynamic random access memory (Synch link DRAM , SLDRAM) and Direct Memory Bus Random Access Memory (Direct Rambus RAM, DRRAM).
  • RAM Random Access Memory
  • SRAM static random access memory
  • DRAM dynamic random access memory
  • DRAM synchronous dynamic random access memory
  • SDRAM double data rate synchronous dynamic random access memory
  • Double Data Rate SDRAM Double Data Rate SDRAM
  • DDRSDRAM double data rate synchronous dynamic random access memory
  • Enhanced SDRAM, ESDRAM enhanced synchronous dynamic random access memory
  • Synch link DRAM , SLDRAM
  • Direct Memory Bus Random Access Memory Direct Rambus
  • the processor 110 may include one or more processing units; optionally, the processor 110 integrates an application processor and a modem processor, wherein the application processor mainly processes operations related to the operating system, user interface, and application programs, etc., Modem processors mainly process wireless communication signals, such as baseband processors. It can be understood that the foregoing modem processor may not be integrated into the processor 110 .
  • the radio frequency unit 101 is configured to receive the measurement report configuration sent by the network side device, the measurement report configuration includes at least one of the following: artificial intelligence AI model related information, AI model input information, AI model output information, AI model reasoning trigger conditions, Configuration related to cell handover events, expected report content of network side equipment, total duration of AI model prediction output, number or interval of time points or intervals of AI model prediction output, first indication information, the first indication information is used to indicate whether UE is based on AI The results of model predictions trigger measurement reporting.
  • the processor 110 is configured to perform AI model inference on at least one handover candidate cell according to the measurement report configuration, obtain an inference result, and perform cell handover based on the inference result.
  • the embodiment of the present application provides a UE, because the UE can receive the measurement reporting configuration sent by the network side device, and perform AI model reasoning on at least one neighboring cell according to the AI model input and output information in the network side device and the AI model reasoning trigger condition , and judge whether to trigger the measurement report based on the reasoning result, and report the measurement report when the predicted signal or the real signal meets certain conditions, so that the UE can report the measurement report at an appropriate time
  • the handover delay of the UE during cell handover is shortened, and the success rate of cell handover is improved.
  • the processor 110 is specifically configured to trigger the UE to report when the predicted signal quality of the target handover candidate cell always meets the preset handover event entry condition within the total duration of the AI model prediction output Reporting of the first measurement report; when the predicted signal quality of the target handover candidate cell always meets the preset handover event departure condition within the total duration of the AI model prediction output, the UE triggers reporting of the second measurement report; in the target handover candidate cell In the case that the real signal quality of the real signal quality meets the preset handover event entry condition within the measurement report trigger time configured by the network side device, the UE triggers the reporting of the third measurement report; wherein, the target handover candidate cell is one of at least one handover candidate cell or multiple districts.
  • the radio frequency unit 101 is further configured to receive a handover command sent by the network side device after the measurement report is triggered based on the reasoning result, and the handover command is used to instruct the UE to handover to at least one handover candidate cell based on The target cell selected by the inference result.
  • the processor 110 is further configured to initiate a random access request to the target cell according to the handover command, where the random access request is used to request access to the target cell
  • the embodiment of the present application also provides a readable storage medium, the readable storage medium stores a program or an instruction, and when the program or instruction is executed by a processor, each process of the above-mentioned cell handover method embodiment is realized, and the same To avoid repetition, the technical effects will not be repeated here.
  • the processor is the processor in the UE described in the foregoing embodiments.
  • the readable storage medium includes a computer-readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk, and the like.
  • the embodiment of the present application further provides a chip, the chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the above cell handover method embodiment
  • the chip includes a processor and a communication interface
  • the communication interface is coupled to the processor
  • the processor is used to run programs or instructions to implement the above cell handover method embodiment
  • the chip mentioned in the embodiment of the present application may also be called a system-on-chip, a system-on-chip, a system-on-a-chip, or a system-on-a-chip.
  • the embodiment of the present application further provides a computer program/program product, the computer program/program product is stored in a storage medium, and the computer program/program product is executed by at least one processor to implement the above cell handover method embodiment
  • the computer program/program product is stored in a storage medium, and the computer program/program product is executed by at least one processor to implement the above cell handover method embodiment
  • the term “comprising”, “comprising” or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article or apparatus comprising a set of elements includes not only those elements, It also includes other elements not expressly listed, or elements inherent in the process, method, article, or device. Without further limitations, an element defined by the phrase “comprising a " does not preclude the presence of additional identical elements in the process, method, article, or apparatus comprising that element.
  • the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved. Functions are performed, for example, the described methods may be performed in an order different from that described, and various steps may also be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

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Abstract

本申请公开了一种小区切换方法、装置及用户设备，属于通信领域，本申请实施例的小区切换方法包括：用户设备UE接收网络侧设备发送的测量上报配置，测量上报配置包括以下至少一项：人工智能AI模型相关信息、AI模型输入信息、AI模型输出信息、AI模型推理触发条件、小区切换事件相关配置、网络侧设备期望的上报内容、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、第一指示信息，第一指示信息用于指示UE是否基于AI模型预测的结果触发测量上报；UE根据测量上报配置，对至少一个切换候选小区执行AI模型推理，得到推理结果，并基于推理结果进行小区切换。

Description

小区切换方法、装置及用户设备
相关申请的交叉引用
本申请主张在2022年3月1日在中国提交的中国专利申请号202210195875.6的优先权，其全部内容通过引用包含于此。
技术领域
本申请属于通信技术领域，具体涉及一种消息处理方法、装置和电子设备。
背景技术
目前，在无线通信***中，当用户设备UE从一个小区进入至另一个小区时，为了保证电子设备在移动期间业务的连续性，电子设备需要进行小区切换。
然而，在现有的小区切换流程中，用户设备在小区切换过程中需要经过测量上报触发，测量结果上报，切换准备，切换命令下发，切换执行等过程，因此UE进行小区切换的时延较长；并且，小区切换时延较长可能导致小区切换过程中，UE在服务小区的信号质量较差，从而导致发生无线链路失败(Radio Link Failure，RLF)或接收不到切换命令，如此现有技术中用户设备在小区切换过程中，会存在切换时延较长或切换小区失败的问题。
发明内容
本申请实施例提供一种小区切换方法、装置及用户设备，能够缩短用户设备进行小区切换的切换时延以及提升切换小区成功率。
第一方面，提供了一种小区切换方法，应用于用户设备UE，该方法包括：UE接收网络侧设备发送的测量上报配置，测量上报配置包括以下至少一项：人工智能AI模型相关信息、AI模型输入信息、AI模型输出信息、AI模型推理触发条件、小区切换事件相关配置、网络侧设备期望的上报内容、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、第一指示信息，第一指示信息用于指示UE是否基于AI模型预测的结果触发测量上报；UE根据测量上报配置，对至少一个切换候选小区执行AI模型推理，得到推理结果，并基于推理结果进行小区切换。
第二方面，提供了一种小区切换装置，小区切换装置包括：接收模块、执行模块和触发模块。接收模块，用于接收网络侧设备发送的测量上报配置，测量上报配置包括以下至少一项：人工智能AI模型相关信息、AI模型输入信息、AI模型输出信息、AI模型推理触发条件、小区切换事件相关配置、网络侧设备期望的上报内容、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、第一指示信息，第一指示信息用于指示UE是否基于AI模型预测的结果触发测量上报。执行模块用于根据接收模块接收的测量上报配置，对至少一个切换候选小区执行AI模型推理，得到推理结果。触发模块，用于基于执行模块得到的推理结果进行小区切换。
第三方面，提供了一种用户设备，该用户设备包括处理器和存储器，所述存储器存储可在所述处理器上运行的程序或指令，所述程序或指令被所述处理器执行时实现如第一方面所述的方法的步骤。
第四方面，提供了一种用户设备，包括处理器及通信接口，其中，所述处理器用 于接收网络侧设备发送的测量上报配置，该测量上报配置包括以下至少一项：人工智能AI模型相关信息、AI模型输入信息、AI模型输出信息、AI模型推理触发条件、小区切换事件相关配置、网络侧设备期望的上报内容、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、第一指示信息，该第一指示信息用于指示UE是否基于AI模型预测的结果触发测量上报。根据测量上报配置，对至少一个切换候选小区执行AI模型推理，得到推理结果。并基于推理结果进行小区切换。
第五方面，提供了一种可读存储介质，所述可读存储介质上存储程序或指令，所述程序或指令被处理器执行时实现如第一方面所述的方法的步骤。
第六方面，提供了一种芯片，所述芯片包括处理器和通信接口，所述通信接口和所述处理器耦合，所述处理器用于运行程序或指令，实现如第一方面所述的方法。
第七方面，提供了一种计算机程序/程序产品，所述计算机程序/程序产品被存储在存储介质中，所述计算机程序/程序产品被至少一个处理器执行以实现如第一方面所述的小区切换方法的步骤。
在本申请实施例中，UE接收网络侧设备发送的测量上报配置，测量上报配置包括以下至少一项：人工智能AI模型相关信息、AI模型输入信息、AI模型输出信息、AI模型推理触发条件、小区切换事件相关配置、网络侧设备期望的上报内容、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、第一指示信息，第一指示信息用于指示UE是否基于AI模型预测的结果触发测量上报；UE根据测量上报配置，对至少一个切换候选小区执行AI模型推理，得到推理结果，并基于推理结果进行小区切换。由于UE可以接收到网络侧设备发送的测量上报配置，并根据网络侧设备中的AI模型输入输出信息以及AI模型推理触发条件对至少一个邻小区执行AI模型推理，并通过推理结果判断是否触发测量上报，并在预测信号或真实信号满足一定条件时，再将测量报告进行上报，以使得UE可以在合适的时间上报测量报告，如此，缩短了UE在小区切换时的切换时延，并提升了小区切换的成功率。
附图说明
图1是本申请实施例提供的一种通信***的架构示意图；
图2是本申请实施例提供的一种小区切换方法的示意图；
图3是本申请实施例提供的一种小区切换方法的示意图；
图4是本申请实施例提供的一种小区切换方法的示意图；
图5是本申请实施例提供的一种小区切换装置的示意图；
图6是本申请实施例提供的一种通信设备的硬件结构示意图；
图7是本申请实施例提供的一种UE的硬件结构示意图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员所获得的所有其他实施例，都属于本申请保护的范围。
本申请的说明书和权利要求书中的术语“第一”、“第二”等是用于区别类似的对象，而不用于描述特定的顺序或先后次序。应该理解这样使用的术语在适当情况下可以互换，以便本申请的实施例能够以除了在这里图示或描述的那些以外的顺序实施， 且“第一”、“第二”所区别的对象通常为一类，并不限定对象的个数，例如第一对象可以是一个，也可以是多个。此外，说明书以及权利要求中“和/或”表示所连接对象的至少其中之一，字符“/”一般表示前后关联对象是一种“或”的关系。
值得指出的是，本申请实施例所描述的技术不限于长期演进型(Long Term Evolution，LTE)/LTE的演进(LTE-Advanced，LTE-A)***，还可用于其他无线通信***，诸如码分多址(Code Division Multiple Access，CDMA)、时分多址(Time Division Multiple Access，TDMA)、频分多址(Frequency Division Multiple Access，FDMA)、正交频分多址(Orthogonal Frequency Division Multiple Access，OFDMA)、单载波频分多址(Single-carrier Frequency Division Multiple Access，SC-FDMA)和其他***。本申请实施例中的术语“***”和“网络”常被可互换地使用，所描述的技术既可用于以上提及的***和无线电技术，也可用于其他***和无线电技术。以下描述出于示例目的描述了新空口(New Radio，NR)***，并且在以下大部分描述中使用NR术语，但是这些技术也可应用于NR***应用以外的应用，如第6代(6th Generation，6G)通信***。
图1示出本申请实施例可应用的一种无线通信***的框图。无线通信***包括终端11和网络侧设备12。其中，终端11可以是手机、平板电脑(Tablet Personal Computer)、膝上型电脑(Laptop Computer)或称为笔记本电脑、个人数字助理(Personal Digital Assistant，PDA)、掌上电脑、上网本、超级移动个人计算机(ultra-mobile personal computer，UMPC)、移动上网装置(Mobile Internet Device，MID)、增强现实(augmented reality，AR)/虚拟现实(virtual reality，VR)设备、机器人、可穿戴式设备(Wearable Device)、车载设备(VUE)、行人终端(PUE)、智能家居(具有无线通信功能的家居设备，如冰箱、电视、洗衣机或者家具等)、游戏机、个人计算机(personal computer，PC)、柜员机或者自助机等终端侧设备，可穿戴式设备包括：智能手表、智能手环、智能耳机、智能眼镜、智能首饰(智能手镯、智能手链、智能戒指、智能项链、智能脚镯、智能脚链等)、智能腕带、智能服装等。需要说明的是，在本申请实施例并不限定终端11的具体类型。网络侧设备12可以包括接入网设备或核心网设备，其中，接入网设备12也可以称为无线接入网设备、无线接入网(Radio Access Network,RAN)、无线接入网功能或无线接入网单元。接入网设备12可以包括基站、WLAN接入点或WiFi节点等，基站可被称为节点B、演进节点B(eNB)、接入点、基收发机站(Base Transceiver Station，BTS)、无线电基站、无线电收发机、基本服务集(Basic Service Set，BSS)、扩展服务集(Extended Service Set，ESS)、家用B节点、家用演进型B节点、发送接收点(Transmitting Receiving Point，TRP)或所述领域中其他某个合适的术语，只要达到相同的技术效果，所述基站不限于特定技术词汇，需要说明的是，在本申请实施例中仅以NR***中的基站为例进行介绍，并不限定基站的具体类型。下面结合附图，通过一些实施例及其应用场景对本申请实施例提供的小区切换方法进行详细地说明。
目前，若UE需求进行小区切换时，需要经过测量上报触发，测量结果上报，切换准备，切换命令下发，切换执行等过程，因此，UE进行小区切换时延较长，并且，小区切换时延较长可能导致小区切换过程中，UE在服务小区的信号质量较差，从而导 致发生RLF或接收不到切换命令，使得UE小区切换失败。
现有的小区切换的主要步骤包括：
(1)源基站向UE发送测量配置。
(2)UE根据源基站发送的测量配置进行测量，并在满足条件时上报测量报告。
(3)源基站与目标基站交互，并进行切换准备。
(4)UE接收源基站下发的切换命令，立即与源小区断开连接，并接入到目标小区。
下面对本申请实施例提供的小区切换方法、装置、用户设备及存储介质中涉及的一些概念和/或术语做一下解释说明。
1、事件触发的测量上报
通常，在测量配置中的reportType字段设置为eventTriggered时，UE可以基于配置的事件判决是否触发测量上报，如表1所示，事件主要分为以下9种：

表1
其中，Intra-RAT切换常用的事件为A3或A5事件，以A3事件为例，进入条件和离开条件的各参数含义如下：
Mn：邻小区测量结果，不考虑任何偏移。
Ofn：邻小区测量对象特定偏移量。
Ocn：邻小区小区级特定偏移量。
Mp：主服务小区(SpCell)测量结果，不考虑任何偏移。
Ofp：SpCell测量对象特定偏移量。
Ocp：SpCell小区级特定偏移量。
Hys：事件的滞后参数。
Off：事件的偏移参数。
为了避免乒乓切换，基站在测量上报配置中针对每一事件配置触发时间(timeToTrigger)参数。
(1)当一个或多个小区在timeToTrigger时间内的L3滤波信号质量都满足事件的进入条件时，UE将对应小区包含进小区触发列表(cellsTriggeredList)，并触发上报。
(2)若上报配置中使能ReportOnLeave，则当cellsTriggeredList中的一个或多个小区在timeToTrigger时间内的L3滤波信号质量都满足事件的离开条件时，UE将对应小区从cellsTriggeredList中移除，并触发上报。
本申请实施例提供一种基于AI的小区切换方法，应用AI预测网络侧设备的服务小区和/或UE的邻小区在未来一个或多个时刻的信号质量，从而可以根据预测结果判断是否触发测量上报，并上报相关预测结果。
本申请实施例提供一种小区切换方法，图2示出了本申请实施例提供的一种小区切换方法的流程图。如图2所示，本申请实施例提供的小区切换方法可以包括下述的步骤201和步骤202。
步骤201、用户设备UE接收网络侧设备发送的测量上报配置。
本申请实施例中，上述测量上报配置包括以下至少一项：人工智能AI模型相关信息、AI模型输入信息、AI模型输出信息、AI模型推理触发条件、小区切换事件相关配置、网络侧设备期望的上报内容、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、第一指示信息，第一指示信息用于指示UE是否基于AI模型预测的结果触发测量上报；
可选地，本申请实施例中，上述测量上报配置可以为网络侧设备配置的、预配置的、预定义的、协议约定的等。
本申请实施例中，UE在需求进行小区切换时，可以接收网络侧设备发送的测量上报配置，并根据策略上报配置中的信息进行测量上报触发，并将测量结果进行上报，从而网络侧设备可以进行切换准备，并向UE发送切换命令，以使得UE可以接收来自网络侧设备发送的切换命令并执行切换。
可选地，本申请实施例中，上述AI模型输入信息包括以下至少一项：网络侧设备 的服务小区和/或UE的邻小区在目标时刻的信号质量；UE在目标时刻的移动参数；UE在目标时刻的天线面板参数，天线面板参数包括以下至少一项：天线面板朝向、天线面板旋转方向、天线面板旋转速度；UE在目标时刻的位置信息；目标位置信息，目标位置信息用于指示网络侧设备和/或UE的邻小区对应的网络侧设备的位置，目标方向信息，目标方向信息用于指示网络侧设备的天线面板朝向；UE当前所在的频点信息和/或其他频点信息/无线接入技术RAT信息；UE在目标时刻和/或历史时刻的波束角度及波束质量；其中，目标时刻为触发执行AI模型推理的时刻或历史时刻。
可选地，本申请实施例中，上述AI模型输出信息包括以下至少一项：至少一个预测信号质量；至少一个预测信号质量中的最低信号质量；至少一个预测信号质量中每两个信号质量差值中的最小差值；至少一个切换候选小区的切换成功率；至少一个切换候选小区的切换时延；至少一个切换候选小区发生非期望事件的概率；至少一个波束质量；其中，至少一个预测信号质量为网络侧设备的服务小区和/或UE的邻小区在至少一个第一时刻的信号质量，至少一个第一时刻为AI模型预测输出的总时长内的时刻，至少一个信号质量与至少一个第一时刻一一对应。
可选地，本申请实施例中，上述非期望事件包括以下至少一项：过晚切换事件；过早切换事件；切换到错误的小区。
可选地，本申请实施例中，上述过晚切换事件是指：UE在源小区上时间太长导致出现RLF，并在其他小区尝试无线资源控制(Radio Resource Control，RRC)重建。上述过早切换事件是指：UE在成功切换到目标小区后较短的时间内，或在切换到目标小区的过程中，出现RLF，并在源小区上尝试RRC重建。切换到错误的小区是指：UE在成功切换到目标小区后很短的时间内，或在切换到目标小区的过程中，出现了RLF，并在其他小区(非上次切换的源小区，也非目标小区)上尝试RRC重建。
可选地，本申请实施例中，上述AI模型推理触发条件包括以下至少一项：周期触发条件、事件触发条件、测量上报触发条件。
可选地，本申请实施例中，上述事件触发条件包括以下至少一项：网络侧设备的服务小区的信号质量小于或等于第一预设门限值；UE的邻小区的信号质量大于或等于第二预设门限值；网络侧设备的服务小区与UE的邻小区的信号质量的差值小于或等于第三预设门限值。
可选地，本申请实施例中，上述周期触发条件为：网络侧设备需要配置模型推理周期。
可选地，本申请实施例中，上述测量上报触发条件为：在UE根据测量上报配置中的信息进行测量上报触发的同时触发执行AI模型推理，并将推理结果上报。
可选地，本申请实施例中，上述信号质量包含以下至少之一：参考信号接收功率(Reference Signal Receiving Power，RSRP)，参考信号接收质量(Reference Signal Receiving Quality，RSRQ)、信号与干扰噪声比(Signal to Interference and Noise Ratio，SINR)。
可选地，本申请实施例中，上述上报内容包括以下至少一项：网络侧设备的服务小区和/或UE的邻小区在第二时刻的信号质量，第二时刻为触发测量上报的时刻；信号质量为网络侧设备的服务小区和/或UE的邻小区的信号质量；或者，信号质量为至 少一个波束信号质量；网络侧设备的服务小区和/或UE的邻小区在UE在AI模型预测输出的各个时间点的信号质量预测结果；至少一个切换时间点和目标信号质量预测结果，至少一个切换时间点为AI模型预测输出的时间点中的最优切换时间点，目标信号质量预测结果为网络侧设备的服务小区和/或UE的邻小区在至少一个切换时间点的信号质量预测结果；UE在AI模型预测输出的各个时间点上切换到各个切换候选小区的切换成功率；UE在AI模型预测输出的各个时间点上切换到各个切换候选小区的切换时延；UE在AI模型预测输出的各个时间点上切换到各个切换候选小区发生非期望事件的概率。
可选地，本申请实施例中，上报内容是基于推理结果确定的。
步骤202、UE根据测量上报配置，对至少一个切换候选小区执行AI模型推理，得到推理结果，并基于推理结果进行小区切换。
本申请实施例中，上述推理结果用于触发UE进行小区切换。
可选地，本申请实施例中，上述推理结果包括以下至少一项：至少一个切换候选小区在AI模型预测输出的总时长内的预测信号质量、至少一个切换候选小区的真实信号质量。
可选地，本申请实施例中，上述预测信号质量包含以下至少之一：RSRP，RSRQ、SINR。
可选地，本申请实施例中，基于推理结果进行小区切换的过程包括：UE基于推理结果触发测量上报。
可选地，本申请实施例中，上述步骤202中的“基于推理结果触发测量上报”具体可以通过下述的三个步骤中的至少一个实现：步骤202a、步骤202b以及步骤202c。
步骤202a、在目标切换候选小区的预测信号质量在AI模型预测输出的总时长内始终满足预设切换事件进入条件的情况下，UE触发上报第一测量报告。
本申请实施例中，上述第一测量报告用于指示目标切换候选小区的预测信号质量满足预设切换事件进入条件。
步骤202b、在目标切换候选小区的预测信号质量在AI模型预测输出的总时长内始终满足预设切换事件离开条件的情况下，UE触发上报第二测量报告。
本申请实施例中，上述第二测量报告用于指示目标切换候选小区的预测信号质量满足预设切换事件离开条件。
步骤202c、在目标切换候选小区的真实信号质量在网络侧设备配置的测量上报触发时长内满足预设切换事件进入条件的情况下，UE触发上报第三测量报告。
本申请实施例中，第三测量报告用于指示目标切换候选小区的真实信号质量满足预设切换事件进入条件；
其中，目标切换候选小区为至少一个切换候选小区中的一个或多个小区。
可选地，本申请实施例中，上述第一测量报告包括的内容可以包括上述上报内容中的至少一项；上述第二测量报告包括的内容可以包括上述上报内容中的至少一项；上述第三测量报告包括的内容可以包括上述上报内容中的至少一项。
需要说明的是，第一测量报告包括的内容、第二测量报告包括的内容以及第三测量报告包括的内容相同或不同(例如：完全不同或部分不同)。
可选地，本申请实施例中，AI模型预测输出的总时长和测量上报触发时长为网络侧设备单独配置的时长；或者，AI模型预测输出的总时长和测量上报触发时长均为网络侧设备通过测量上报配置所配置的时长。
本申请实施例提供一种小区切换方法，在本申请实施例中，UE接收网络侧设备发送的测量上报配置，测量上报配置包括以下至少一项：人工智能AI模型相关信息、AI模型输入信息、AI模型输出信息、AI模型推理触发条件、小区切换事件相关配置、网络侧设备期望的上报内容、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、第一指示信息，第一指示信息用于指示UE是否基于AI模型预测的结果触发测量上报；UE根据测量上报配置，对至少一个切换候选小区执行AI模型推理，得到推理结果，并基于推理结果进行小区切换。由于UE可以接收到网络侧设备发送的测量上报配置，并根据网络侧设备中的AI模型输入输出信息以及AI模型推理触发条件对至少一个邻小区执行AI模型推理，并通过推理结果判断是否触发测量上报，并在预测信号或真实信号满足一定条件时，再将测量报告进行上报，以使得UE可以在合适的时间上报测量报告，如此，缩短了UE在小区切换时的切换时延，并提升了小区切换的成功率。
可选地，本申请实施例中，在上述步骤202之后，本申请实施例提供的的小区切换方法还包括下述的步骤301和步骤302。
步骤301、UE接收网络侧设备发送的切换命令，切换命令用于指示UE切换至至少一个切换候选小区中基于所述推理结果选择的目标小区。
可选地，本申请实施例中，上述目标小区可以是UE基于推理结果选择的，也可以是网络侧设备基于接收到的推理结果为UE配置的。
步骤302、UE根据切换命令，对目标小区发起随机接入请求，随机接入请求用于请求接入目标小区。
本申请实施例提供一种小区切换方法，对应上述实施例一中的步骤202a，示例性地，如图3所示，以目标切换候选小区中包括一个候选小区(例如邻区A)为例，通过下述的步骤21至步骤26进行说明。
步骤21、UE接收网络侧设备发送的测量上报配置。
可选地，本申请实施例中，上述测量上报配置中的部分配置包括：小区切换事件相关配置、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、AI模型推理触发条件、触发测量上报条件以及上报内容。
可选地，本申请实施例中，上述AI模型推理触发推理条件为：网络侧设备的服务小区与UE的邻小区的信号质量的差值小于或等于第三预设门限值。
可选地，本申请实施例中，上述触发测量上报条件为：在目标切换候选小区的预测信号质量在AI模型预测输出的总时长内始终满足预设切换事件进入条件的情况下，UE将目标切换候选小区包含进小区触发列表，并UE将第一测量报告上报至网络侧设备。
可选地，本申请实施例中，上报内容为：AI模型预测输出的总时长内AI模型预测输出的时间点个数或间隔的网络侧设备的服务小区和邻小区的预测信号质量的测量结果。
步骤22、t0时刻，在网络侧设备的服务小区信号质量与邻区A的信号质量的差值小于或等于第三预设门限值的情况下，UE根据测量上报配置，对邻区A执行AI模型推理。
可选地，本申请实施例中，上述t0时刻为UE触发执行AI模型推理的时刻。
步骤23、UE通过推理得到t0～t0+T时间内每Δt时间的网络侧设备的服务小区和邻区A的信号质量预测值。
可选地，本申请实施例中，上述T为AI模型预测输出的总时长，Δt为AI模型预测输出的时间点个数或间隔。
步骤24、在网络侧设备的服务小区和邻区A的信号质量预测值在时间T内始终满足切换事件的进入条件的情况下，UE将第一测量报告上报至网络侧设备。
可选地，本申请实施例中，上述第一测量报告中包括时间T内每Δt时间的网络侧设备的服务小区和邻区A的信号质量。
步骤25、UE在t1时刻内接收网络侧设备发送的切换命令。
可选地，本申请实施例中，上述切换命令用于指示UE切换至邻区A。
可选地，本申请实施例中，上述t1时刻为UE接收到网络侧设备发送的切换命令的时刻。
步骤26、UE根据切换命令，对邻区A发起随机接入请求，并于t2时刻完成切换。
可选地，本申请实施例中，上述随机接入请求用于请求接邻区A。
可选地，本申请实施例中，上述t2时刻为UE切换完成的时刻。
本申请实施例提供一种小区切换方法，由于UE可以接收到网络侧设备发送的测量上报配置，并根据网络侧设备中的AI模型输入输出信息以及AI模型推理触发条件对至少一个邻小区执行AI模型推理，并通过推理结果判断是否触发测量上报，并在预测信号或真实信号满足一定条件时，再将测量报告进行上报，以使得UE可以在合适的时间上报测量报告，如此，缩短了UE在小区切换时的切换时延，并提升了小区切换的成功率。本申请实施例提供一种小区切换方法，对应上述实施例一中的步骤202b，并通过下述的步骤31对本申请实施例提供的小区切换方法进行说明。
步骤31、UE接收网络侧设备发送的测量上报配置。
可选地，本申请实施例中，配置中包含事件的timeToTrigger配置及指示信息。
可选地，本申请实施例中，上述指示信息用于指示UE是否基于AI模型输出的预测结果触发测量上报。
其中，步骤31包括两种方式，即方式一和方式二。
方式一
在至少一个目标候选小区在timeToTrigger内的预测信号质量都满足事件的进入条件的情况下，将对应的目标候选小区包含进小区触发列表，并触发上报。
方式二
在小区触发列表中的目标候选小区在timeToTrigger内的预测信号质量都满足所配切换事件的离开条件，将对应的目标候选小区从小区触发列表中移除，并触发上报。
需要说明的是，上述指示信息可以针对每个UE/每个测量标识(measurement ID)/每个事件(reportConfig)。
本申请实施例提供一种小区切换方法，由于UE可以接收到网络侧设备发送的测量上报配置，并根据网络侧设备中的AI模型输入输出信息以及AI模型推理触发条件对至少一个邻小区执行AI模型推理，并通过推理结果判断是否触发测量上报，并在预测信号或真实信号满足一定条件时，再将测量报告进行上报，以使得UE可以在合适的时间上报测量报告，如此，缩短了UE在小区切换时的切换时延，并提升了小区切换的成功率。
本申请实施例提供一种小区切换方法，对应上述实施例一中的步骤202c，示例性地，如图4所示，以目标切换候选小区中包括两个候选小区(例如邻区B和邻区C)为例，通过下述的步骤41至步骤46进行说明。
步骤41、UE接收网络侧设备发送的测量上报配置。
可选地，本申请实施例中，上述测量上报配置中的部分配置包括：小区切换事件相关配置、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、AI模型推理触发条件、触发测量上报条件以及上报内容。
可选地，本申请实施例中，上述AI模型推理触发推理条件为：在目标切换候选小区的真实信号质量在网络侧设备配置的测量上报触发时长内满足预设切换事件进入条件的情况下，UE将第三测量报告上报至网络侧设备。
可选地，本申请实施例中，上述真实信号为L3滤波信号。
可选地，本申请实施例中，第三测量报告用于指示目标切换候选小区的真实信号质量满足预设切换事件进入条件。
可选地，本申请实施例中，上述触发测量上报条件为：测量上报触发条件。
需要说明的是，上述测量上报触发条件为：在UE根据测量上报配置中的信息进行测量上报触发的同时触发执行AI模型推理，并将推理结果上报。
可选地，本申请实施例中，上报内容为：AI模型预测输出的总时长内AI模型预测输出的时间点个数或间隔的网络侧设备的服务小区和邻小区的预测信号质量的测量结果。
步骤42、t3时刻，UE首次满足小区切换事件相关配置的进入条件。
可选地，本申请实施例中，t3时刻为UE首次满足小区切换事件相关配置的进入条件的时刻。
步骤43、t4时刻，在测量上报触发时长超时，邻区B和邻区C同时满足触发上报条件的情况下，UE根据测量上报配置，对邻区B和邻区C执行AI模型推理。
可选地，本申请实施例中，t4时刻为UE对邻区B和邻区C执行AI模型推理的时刻。步骤44、UE通过推理得到t3～t3+T时间内每Δt时间的网络侧设备的服务小区、邻区B和邻区C的信号质量预测值，并将第三测量报告上报至网络侧设备。
可选地，本申请实施例中，第三测量报告用于指示邻区B和邻区C的真实信号质量满足预设切换事件进入条件，上述第三测量报告中包括时间T内每Δt时间的网络侧设备的服务小区、邻区B和邻区C的信号质量。
步骤45、UE在t5时刻内接收网络侧设备发送的切换命令。
可选地，本申请实施例中，上述切换命令用于指示UE切换至邻区C。
可选地，本申请实施例中，上述t5时刻为UE接收到网络侧设备发送的切换命令的时刻。
步骤46、UE根据切换命令，对邻区C发起随机接入请求，并于t6时刻完成切换。
可选地，本申请实施例中，上述随机接入请求用于请求接邻区C。
可选地，本申请实施例中，上述t6时刻为UE切换完成的时刻。
本申请实施例提供一种小区切换方法，由于UE可以接收到网络侧设备发送的测量上报配置，并根据网络侧设备中的AI模型输入输出信息以及AI模型推理触发条件对至少一个邻小区执行AI模型推理，并通过推理结果判断是否触发测量上报，并在预测信号或真实信号满足一定条件时，再将测量报告进行上报，以使得UE可以在合适的时间上报测量报告，如此，缩短了UE在小区切换时的切换时延，并提升了小区切换的成功率。
本申请实施例提供的小区切换方法，执行主体可以为小区切换装置。本申请实施例中以小区切换装置执行小区切换方法为例，说明本申请实施例提供的小区切换装置。
图5示出了本申请实施例中涉及的小区切换装置的一种可能的结构示意图。如图5所示，该小区切换装置60可以包括：接收模块61、执行模块62和触发模块63。
其中，接收模块61，用于接收网络侧设备发送的测量上报配置，测量上报配置包括以下至少一项：人工智能AI模型相关信息、AI模型输入信息、AI模型输出信息、AI模型推理触发条件、小区切换事件相关配置、网络侧设备期望的上报内容、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、第一指示信息，第一指示信息用于指示UE是否基于AI模型预测的结果触发测量上报。执行模块62用于根据接收模块61接收的测量上报配置，对至少一个切换候选小区执行AI模型推理，得到推理结果。触发模块63，用于基于执行模块62得到的推理结果进行小区切换。
本申请实施例提供一种小区切换装置，由于UE可以接收到网络侧设备发送的测量上报配置，并根据网络侧设备中的AI模型输入输出信息以及AI模型推理触发条件对至少一个邻小区执行AI模型推理，并通过推理结果判断是否触发测量上报，并在预测信号或真实信号满足一定条件时，再将测量报告进行上报，以使得UE可以在合适的时间上报测量报告，如此，缩短了UE在小区切换时的切换时延，并提升了小区切换的成功率。
在一种可能实现的方式中，AI模型输入信息包括以下至少一项：网络侧设备的服务小区和/或UE的邻小区在目标时刻的信号质量；UE在目标时刻的移动参数；UE在目标时刻的天线面板参数，天线面板参数包括以下至少一项：天线面板朝向、天线面板旋转方向、天线面板旋转速度；UE在目标时刻的位置信息；目标位置信息，目标位置信息用于指示网络侧设备和/或UE的邻小区对应的网络侧设备的位置，目标方向信息，目标方向信息用于指示网络侧设备的天线面板朝向；UE当前所在的频点信息和/或其他频点信息/无线接入技术RAT信息；UE在目标时刻和/或历史时刻的波束角度及波束质量；其中，目标时刻为触发执行AI模型推理的时刻或历史时刻。
在一种可能实现的方式中，AI模型输出信息包括以下至少一项：至少一个预测信号质量；至少一个预测信号质量中的最低信号质量；至少一个预测信号质量中每两个信号质量差值中的最小差值；至少一个切换候选小区的切换成功率；至少一个切换候 选小区的切换时延；至少一个切换候选小区发生非期望事件的概率；至少一个波束质量；其中，至少一个信号质量为网络侧设备的服务小区和/或UE的邻小区在至少一个第一时刻的信号质量，至少一个第一时刻为AI模型预测输出的总时长内的时刻，至少一个信号质量与至少一个第一时刻一一对应。
在一种可能实现的方式中，非期望事件包括以下至少一项：过晚切换事件；过早切换事件；切换到错误的小区。
在一种可能实现的方式中，AI模型推理触发条件包括以下至少一项：周期触发条件、事件触发条件、测量上报触发条件。
在一种可能实现的方式中，事件触发条件包括以下至少一项：网络侧设备的服务小区的信号质量小于或等于第一预设门限值；UE的邻小区的信号质量大于或等于第二预设门限值；网络侧设备的服务小区与UE的邻小区的信号质量的差值小于或等于第三预设门限值。
在一种可能实现的方式中，上报内容包括以下至少一项：网络侧设备的服务小区和/或UE的邻小区在第二时刻的信号质量，第二时刻为触发测量上报的时刻；信号质量为网络侧设备的服务小区和/或UE的邻小区的信号质量，或者，信号质量为至少一个波束信号质量；网络侧设备的服务小区和/或UE的邻小区在UE在AI模型预测输出的各个时间点的信号质量预测结果；至少一个切换时间点和目标信号质量预测结果，至少一个切换时间点为AI模型预测输出的时间点中的最优切换时间点，目标信号质量预测结果为网络侧设备的服务小区和/或UE的邻小区在至少一个切换时间点的信号质量预测结果；UE在AI模型预测输出的各个时间点上切换到各个切换候选小区的切换成功率；UE在AI模型预测输出的各个时间点上切换到各个切换候选小区的切换时延；UE在AI模型预测输出的各个时间点上切换到各个切换候选小区发生非期望事件的概率。
在一种可能实现的方式中，上报内容是基于推理结果确定的。
在一种可能实现的方式中，推理结果包括以下至少一项：至少一个切换候选小区在AI模型预测输出的总时长内的预测信号质量、至少一个切换候选小区的真实信号质量。
在一种可能实现的方式中，基于推理结果进行小区切换的过程包括：UE基于推理结果触发测量上报。
在一种可能实现的方式中，触发模块63，具体用于在目标切换候选小区的预测信号质量在AI模型预测输出的总时长内始终满足预设切换事件进入条件的情况下，UE触发上报第一测量报告；在目标切换候选小区的预测信号质量在AI模型预测输出的总时长内始终满足预设切换事件离开条件的情况下，UE触发上报第二测量报告上报；在目标切换候选小区的真实信号质量在网络侧设备配置的测量上报触发时长内满足预设切换事件进入条件的情况下，UE触发上报第三测量报告上报；其中，目标切换候选小区为至少一个切换候选小区中的一个或多个小区。
在一种可能实现的方式中，AI模型预测输出的总时长和测量上报触发时长为网络侧设备单独配置的时长；或者，AI模型预测输出的总时长和测量上报触发时长均为网络侧设备通过测量上报配置所配置的时长。
在一种可能实现的方式中，小区切换装置还包括：发起模块。接收模块61，还用于在触发模块63基于推理结果触发测量上报之后，接收网络侧设备发送的切换命令，切换命令用于指示UE切换至至少一个切换候选小区中基于推理结果选择的目标小区。发起模块，用于根据接收模块61接收的切换命令，对目标小区发起随机接入请求，随机接入请求用于请求接入目标小区。
本申请实施例中的小区切换装置可以是电子设备，例如具有操作***的电子设备，也可以是电子设备中的部件，例如集成电路或芯片。该电子设备可以是UE，也可以为除UE之外的其他设备。示例性的，UE可以包括但不限于上述所列举的终端11的类型，其他设备可以为服务器、网络附属存储器(Network Attached Storage，NAS)等，本申请实施例不作具体限定。
本申请实施例提供的小区切换装置能够实现图1至图4的方法实施例实现的各个过程，并达到相同的技术效果，为避免重复，这里不再赘述。
可选的，如图6所示，本申请实施例还提供一种通信设备700，包括处理器701和存储器702，存储器702上存储有可在所述处理器701上运行的程序或指令，例如，该通信设备700为UE时，该程序或指令被处理器701执行时实现上述小区切换方法实施例的各个步骤，且能达到相同的技术效果。该通信设备700为网络侧设备时，该程序或指令被处理器701执行时实现上述小区切换方法实施例的各个步骤，且能达到相同的技术效果，为避免重复，这里不再赘述。
本申请实施例还提供一种UE，包括处理器和通信接口，处理器用于接收网络侧设备发送的测量上报配置，该测量上报配置包括以下至少一项：人工智能AI模型相关信息、AI模型输入信息、AI模型输出信息、AI模型推理触发条件、小区切换事件相关配置、网络侧设备期望的上报内容、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、第一指示信息，该第一指示信息用于指示UE是否基于AI模型预测的结果触发测量上报。根据测量上报配置，对至少一个切换候选小区执行AI模型推理，得到推理结果。并基于推理结果进行小区切换。该UE实施例与上述UE侧方法实施例对应，上述方法实施例的各个实施过程和实现方式均可适用于该UE实施例中，且能达到相同的技术效果。具体地，图7为实现本申请实施例的一种UE的硬件结构示意图。
该UE100包括但不限于：射频单元101、网络模块102、音频输出单元103、输入单元104、传感器105、显示单元106、用户输入单元107、接口单元108、存储器109以及处理器110等中的至少部分部件。
本领域技术人员可以理解，UE100还可以包括给各个部件供电的电源(比如电池)，电源可以通过电源管理***与处理器110逻辑相连，从而通过电源管理***实现管理充电、放电、以及功耗管理等功能。图7中示出的UE结构并不构成对UE的限定，UE可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置，在此不再赘述。
应理解的是，本申请实施例中，输入单元104可以包括图形处理单元(Graphics Processing Unit，GPU)1041和麦克风1042，图形处理器1041对在视频捕获模式或图像捕获模式中由图像捕获装置(如摄像头)获得的静态图片或视频的图像数据进行处 理。显示单元106可包括显示面板1061，可以采用液晶显示器、有机发光二极管等形式来配置显示面板1061。用户输入单元107包括触控面板1071以及其他输入设备1072中的至少一种。触控面板1071，也称为触摸屏。触控面板1071可包括触摸检测装置和触摸控制器两个部分。其他输入设备1072可以包括但不限于物理键盘、功能键(比如音量控制按键、开关按键等)、轨迹球、鼠标、操作杆，在此不再赘述。
本申请实施例中，射频单元101接收来自网络侧设备的下行数据后，可以传输给处理器110进行处理；另外，射频单元101可以向网络侧设备发送上行数据。通常，射频单元101包括但不限于天线、放大器、收发信机、耦合器、低噪声放大器、双工器等。
存储器109可用于存储软件程序或指令以及各种数据。存储器109可主要包括存储程序或指令的第一存储区和存储数据的第二存储区，其中，第一存储区可存储操作***、至少一个功能所需的应用程序或指令(比如声音播放功能、图像播放功能等)等。此外，存储器109可以包括易失性存储器或非易失性存储器，或者，存储器109可以包括易失性和非易失性存储器两者。其中，非易失性存储器可以是只读存储器(Read-Only Memory，ROM)、可编程只读存储器(Programmable ROM，PROM)、可擦除可编程只读存储器(Erasable PROM，EPROM)、电可擦除可编程只读存储器(Electrically EPROM，EEPROM)或闪存。易失性存储器可以是随机存取存储器(Random Access Memory，RAM)，静态随机存取存储器(Static RAM，SRAM)、动态随机存取存储器(Dynamic RAM，DRAM)、同步动态随机存取存储器(Synchronous DRAM，SDRAM)、双倍数据速率同步动态随机存取存储器(Double Data Rate SDRAM，DDRSDRAM)、增强型同步动态随机存取存储器(Enhanced SDRAM，ESDRAM)、同步连接动态随机存取存储器(Synch link DRAM，SLDRAM)和直接内存总线随机存取存储器(Direct Rambus RAM，DRRAM)。本申请实施例中的存储器109包括但不限于这些和任意其它适合类型的存储器。
处理器110可包括一个或多个处理单元；可选的，处理器110集成应用处理器和调制解调处理器，其中，应用处理器主要处理涉及操作***、用户界面和应用程序等的操作，调制解调处理器主要处理无线通信信号，如基带处理器。可以理解的是，上述调制解调处理器也可以不集成到处理器110中。
其中，射频单元101，用于接收网络侧设备发送的测量上报配置，测量上报配置包括以下至少一项：人工智能AI模型相关信息、AI模型输入信息、AI模型输出信息、AI模型推理触发条件、小区切换事件相关配置、网络侧设备期望的上报内容、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、第一指示信息，第一指示信息用于指示UE是否基于AI模型预测的结果触发测量上报。处理器110用于根据测量上报配置，对至少一个切换候选小区执行AI模型推理，得到推理结果，并基于推理结果进行小区切换。
本申请实施例提供一种UE，由于UE可以接收到网络侧设备发送的测量上报配置，并根据网络侧设备中的AI模型输入输出信息以及AI模型推理触发条件对至少一个邻小区执行AI模型推理，并通过推理结果判断是否触发测量上报，并在预测信号或真实信号满足一定条件时，再将测量报告进行上报，以使得UE可以在合适的时间上报测 量报告，如此，缩短了UE在小区切换时的切换时延，并提升了小区切换的成功率。
可选地，本申请实施例中，处理器110，具体用于在目标切换候选小区的预测信号质量在AI模型预测输出的总时长内始终满足预设切换事件进入条件的情况下，UE触发上报第一测量报告上报；在目标切换候选小区的预测信号质量在AI模型预测输出的总时长内始终满足预设切换事件离开条件的情况下，UE触发上报第二测量报告上报；在目标切换候选小区的真实信号质量在网络侧设备配置的测量上报触发时长内满足预设切换事件进入条件的情况下，UE触发上报第三测量报告上报；其中，目标切换候选小区为至少一个切换候选小区中的一个或多个小区。
可选地，本申请实施例中，射频单元101，还用于在基于推理结果触发测量上报之后，接收网络侧设备发送的切换命令，切换命令用于指示UE切换至至少一个切换候选小区中基于推理结果选择的目标小区。处理器110，还用于根据切换命令，对目标小区发起随机接入请求，随机接入请求用于请求接入目标小区
本申请实施例还提供一种可读存储介质，所述可读存储介质上存储有程序或指令，该程序或指令被处理器执行时实现上述小区切换方法实施例的各个过程，且能达到相同的技术效果，为避免重复，这里不再赘述。
其中，所述处理器为上述实施例中所述的UE中的处理器。所述可读存储介质，包括计算机可读存储介质，如计算机只读存储器ROM、随机存取存储器RAM、磁碟或者光盘等。
本申请实施例另提供了一种芯片，所述芯片包括处理器和通信接口，所述通信接口和所述处理器耦合，所述处理器用于运行程序或指令，实现上述小区切换方法实施例的各个过程，且能达到相同的技术效果，为避免重复，这里不再赘述。
应理解，本申请实施例提到的芯片还可以称为***级芯片，***芯片，芯片***或片上***芯片等。
本申请实施例另提供了一种计算机程序/程序产品，所述计算机程序/程序产品被存储在存储介质中，所述计算机程序/程序产品被至少一个处理器执行以实现上述小区切换方法实施例的各个过程，且能达到相同的技术效果，为避免重复，这里不再赘述。
需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者装置不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者装置所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者装置中还存在另外的相同要素。此外，需要指出的是，本申请实施方式中的方法和装置的范围不限按示出或讨论的顺序来执行功能，还可包括根据所涉及的功能按基本同时的方式或按相反的顺序来执行功能，例如，可以按不同于所描述的次序来执行所描述的方法，并且还可以添加、省去、或组合各种步骤。另外，参照某些示例所描述的特征可在其他示例中被组合。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本申请的技术方案本质上或者说对现 有技术做出贡献的部分可以以计算机软件产品的形式体现出来，该计算机软件产品存储在一个存储介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端(可以是手机，计算机，服务器，空调器，或者网络设备等)执行本申请各个实施例所述的方法。
上面结合附图对本申请的实施例进行了描述，但是本申请并不局限于上述的具体实施方式，上述的具体实施方式仅仅是示意性的，而不是限制性的，本领域的普通技术人员在本申请的启示下，在不脱离本申请宗旨和权利要求所保护的范围情况下，还可做出很多形式，均属于本申请的保护之内。

Claims (28)

  1. 一种小区切换方法，包括：
    用户设备UE接收网络侧设备发送的测量上报配置，所述测量上报配置包括以下至少一项：人工智能AI模型相关信息、AI模型输入信息、AI模型输出信息、AI模型推理触发条件、小区切换事件相关配置、所述网络侧设备期望的上报内容、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、第一指示信息，所述第一指示信息用于指示所述UE是否基于AI模型预测的结果触发测量上报；
    所述UE根据所述测量上报配置，对至少一个切换候选小区执行AI模型推理，得到推理结果，并基于所述推理结果进行小区切换。
  2. 根据权利要求1所述的方法，其中，所述AI模型输入信息包括以下至少一项：
    所述网络侧设备的服务小区和/或所述UE的邻小区在目标时刻的信号质量；
    所述UE在目标时刻的移动参数；
    所述UE在目标时刻的天线面板参数，所述天线面板参数包括以下至少一项：天线面板朝向、天线面板旋转方向、天线面板旋转速度；
    所述UE在目标时刻的位置信息；
    目标位置信息，所述目标位置信息用于指示所述网络侧设备和/或所述UE的邻小区对应的网络侧设备的位置；
    目标方向信息，所述目标方向信息用于指示所述网络侧设备的天线面板朝向；
    所述UE当前所在的频点信息和/或其他频点信息/无线接入技术RAT信息；
    所述UE在所述目标时刻和/或历史时刻的波束角度及波束质量；
    其中，所述目标时刻为触发执行AI模型推理的时刻或历史时刻。
  3. 根据权利要求1所述的方法，其中，所述AI模型输出信息包括以下至少一项：
    至少一个预测信号质量；
    至少一个预测信号质量中的最低信号质量；
    至少一个预测信号质量中每两个信号质量差值中的最小差值；
    所述至少一个切换候选小区的切换成功率；
    所述至少一个切换候选小区的切换时延；
    所述至少一个切换候选小区发生非期望事件的概率；
    至少一个波束质量；
    其中，所述至少一预测个信号质量为所述网络侧设备的服务小区和/或所述UE的邻小区在至少一个第一时刻的信号质量，所述至少一个第一时刻为AI模型预测输出的总时长内的时刻，所述至少一个信号质量与所述至少一个第一时刻一一对应。
  4. 根据权利要求3所述的方法，其中，所述非期望事件包括以下至少一项：
    过晚切换事件；
    过早切换事件；
    切换到错误的小区。
  5. 根据权利要求1所述的方法，其中，所述AI模型推理触发条件包括以下至少一项：周期触发条件、事件触发条件、测量上报触发条件。
  6. 根据权利要求5所述的方法，其特征在于，所述事件触发条件包括以下至少一项：
    所述网络侧设备的服务小区的信号质量小于或等于第一预设门限值；
    所述UE的邻小区的信号质量大于或等于第二预设门限值；
    所述网络侧设备的服务小区与所述UE的邻小区的信号质量的差值小于或等于第三预设门限值。
  7. 根据权利要求1所述的方法，其中，所述上报内容包括以下至少一项：
    所述网络侧设备的服务小区和/或所述UE的邻小区在第二时刻的信号质量，所述第二时刻为触发测量上报的时刻；所述信号质量为所述网络侧设备的服务小区和/或所述UE的邻小区的信号质量，或者，所述信号质量为至少一个波束信号质量；
    所述网络侧设备的服务小区和/或所述UE的邻小区在所述UE在AI模型预测输出的各个时间点的信号质量预测结果；
    至少一个切换时间点和目标信号质量预测结果，所述至少一个切换时间点为AI模型预测输出的时间点中的最优切换时间点，所述目标信号质量预测结果为所述网络侧设备的服务小区和/或所述UE的邻小区在所述至少一个切换时间点的信号质量预测结果；
    所述UE在AI模型预测输出的各个时间点上切换到各个切换候选小区的切换成功率；
    所述UE在AI模型预测输出的各个时间点上切换到各个切换候选小区的切换时延；
    所述UE在AI模型预测输出的各个时间点上切换到各个切换候选小区发生非期望事件的概率。
  8. 根据权利要求7所述的方法，其中，所述上报内容是基于所述推理结果确定的。
  9. 根据权利要求1所述的方法，其中，所述推理结果包括以下至少一项：所述至少一个切换候选小区在AI模型预测输出的总时长内的预测信号质量、所述至少一个切换候选小区的真实信号质量。
  10. 根据权利要求1所述的方法，其中，基于所述推理结果进行小区切换的过程包括：所述UE基于所述推理结果触发测量上报。
  11. 根据权利要求10所述的方法，其中，所述基于所述推理结果触发测量上报，包括：
    在目标切换候选小区的预测信号质量在AI模型预测输出的总时长内始终满足预设切换事件进入条件的情况下，所述UE触发上报第一测量报告；
    在目标切换候选小区的预测信号质量在AI模型预测输出的总时长内始终满足预设切换事件离开条件的情况下，所述UE触发上报将第二测量报告；
    在目标切换候选小区的真实信号质量在所述网络侧设备配置的测量上报触发时长内满足预设切换事件进入条件的情况下，所述UE触发上报将第三测量报告；
    其中，所述目标切换候选小区为所述至少一个切换候选小区中的一个或多个小区。
  12. 根据权利要求11所述的方法，其中，
    AI模型预测输出的总时长和所述测量上报触发时长为所述网络侧设备单独配置的时长；或者，AI模型预测输出的总时长和所述测量上报触发时长均为所述网络侧设备通过所述测量上报配置所配置的时长。
  13. 根据权利要求1、10或11所述的方法，其中，所述基于所述推理结果进行小区切换，包括：
    所述UE接收所述网络侧设备发送的切换命令，所述切换命令用于指示所述UE切换至所述至少一个切换候选小区中基于所述推理结果选择的目标小区；
    所述UE根据所述切换命令，对所述目标小区发起随机接入请求，所述随机接入请求用于请求接入所述目标小区。
  14. 一种小区切换装置，所述小区切换装置包括：接收模块、执行模块和触发模块；
    所述接收模块，用于接收网络侧设备发送的测量上报配置，所述测量上报配置包括以下至少一项：人工智能AI模型相关信息、AI模型输入信息、AI模型输出信息、AI模型推理触发条件、小区切换事件相关配置、所述网络侧设备期望的上报内容、AI模型预测输出的总时长、AI模型预测输出的时间点个数或间隔、第一指示信息，所述第一指示信息用于指示所述UE是否基于AI模型预测的结果触发测量上报；
    所述执行模块用于根据所述接收模块接收的所述测量上报配置，对至少一个切换候选小区执行AI模型推理，得到推理结果；
    所述触发模块，用于基于所述执行模块得到的所述推理结果进行小区切换。
  15. 根据权利要求14所述的装置，其中，所述AI模型输入信息包括以下至少一项：
    所述网络侧设备的服务小区和/或所述UE的邻小区在目标时刻的信号质量；
    所述UE在目标时刻的移动参数；
    所述UE在目标时刻的天线面板参数，所述天线面板参数包括以下至少一项：天线面板朝向、天线面板旋转方向、天线面板旋转速度；
    所述UE在目标时刻的位置信息；
    目标位置信息，所述目标位置信息用于指示所述网络侧设备和/或所述UE的邻小区对应的网络侧设备的位置；
    目标方向信息，所述目标方向信息用于指示所述网络侧设备的天线面板朝向；
    所述UE当前所在的频点信息和/或其他频点信息/无线接入技术RAT信息；
    所述UE在所述目标时刻和/或历史时刻的波束角度及波束质量；
    其中，所述目标时刻为触发执行AI模型推理的时刻或历史时刻。
  16. 根据权利要求14所述的装置，其中，所述AI模型输出信息包括以下至少一项：
    至少一个预测信号质量；
    至少一个预测信号质量中的最低信号质量；
    至少一个预测信号质量中每两个信号质量差值中的最小差值；
    所述至少一个切换候选小区的切换成功率；
    所述至少一个切换候选小区的切换时延；
    所述至少一个切换候选小区发生非期望事件的概率；
    至少一个波束质量；
    其中，所述至少一个预测信号质量为所述网络侧设备的服务小区和/或所述UE的邻小区在至少一个第一时刻的信号质量，所述至少一个第一时刻为AI模型预测输出的总时长内的时刻，所述至少一个信号质量与所述至少一个第一时刻一一对应。
  17. 根据权利要求16所述的装置，其中，所述非期望事件包括以下至少一项：
    过晚切换事件；
    过早切换事件；
    切换到错误的小区。
  18. 根据权利要求14所述的装置，其中，所述AI模型推理触发条件包括以下至少一项：周期触发条件、事件触发条件、测量上报触发条件。
  19. 根据权利要求18所述的装置，其中，所述事件触发条件包括以下至少一项：
    所述网络侧设备的服务小区的信号质量小于或等于第一预设门限值；
    所述UE的邻小区的信号质量大于或等于第二预设门限值；
    所述网络侧设备的服务小区与所述UE的邻小区的信号质量的差值小于或等于第三预设门限值。
  20. 根据权利要求14所述的装置，其中，所述上报内容包括以下至少一项：
    所述网络侧设备的服务小区和/或所述UE的邻小区在第二时刻的信号质量，所述第二时刻为触发测量上报的时刻；
    所述信号质量为所述网络侧设备的服务小区和/或所述UE的邻小区的信号质量； 或者，所述信号质量为至少一个波束信号质量；
    所述网络侧设备的服务小区和/或所述UE的邻小区在所述UE在AI模型预测输出的各个时间点的信号质量预测结果；
    至少一个切换时间点和目标信号质量预测结果，所述至少一个切换时间点为AI模型预测输出的时间点中的最优切换时间点，所述目标信号质量预测结果为所述网络侧设备的服务小区和/或所述UE的邻小区在所述至少一个切换时间点的信号质量预测结果；
    所述UE在AI模型预测输出的各个时间点上切换到各个切换候选小区的切换成功率；
    所述UE在AI模型预测输出的各个时间点上切换到各个切换候选小区的切换时延；
    所述UE在AI模型预测输出的各个时间点上切换到各个切换候选小区发生非期望事件的概率。
  21. 根据权利要求20所述的装置，其中，所述上报内容是基于所述推理结果确定的。
  22. 根据权利要求14所述的装置，其中，所述推理结果包括以下至少一项：所述至少一个切换候选小区在AI模型预测输出的总时长内的预测信号质量、所述至少一个切换候选小区的真实信号质量。
  23. 根据权利要求14所述的装置，其中，基于所述推理结果进行小区切换的过程包括：所述UE基于所述推理结果触发测量上报。
  24. 根据权利要求23所述的装置，其中，
    所述触发模块，具体用于在目标切换候选小区的预测信号质量在AI模型预测输出的总时长内始终满足预设切换事件进入条件的情况下，所述UE触发上报第一测量报告；在目标切换候选小区的预测信号质量在AI模型预测输出的总时长内始终满足预设切换事件离开条件的情况下，所述UE触发上报第二测量报告；在目标切换候选小区的真实信号质量在所述网络侧设备配置的测量上报触发时长内满足预设切换事件进入条件的情况下，所述UE触发上报第三测量报告；
    其中，所述目标切换候选小区为所述至少一个切换候选小区中的一个或多个小区。
  25. 根据权利要求24所述的装置，其中，
    AI模型预测输出的总时长和所述测量上报触发时长为所述网络侧设备单独配置的时长；或者，AI模型预测输出的总时长和所述测量上报触发时长均为所述网络侧设备通过所述测量上报配置所配置的时长。
  26. 根据权利要求14、23或24所述的装置，其中，所述小区切换装置还包括：发起模块；
    所述接收模块，还用于在所述触发模块基于所述推理结果触发测量上报之后，接收所述网络侧设备发送的切换命令，所述切换命令用于指示所述UE切换至所述至少一个切换候选小区中的目标小区；
    所述发起模块，用于根据所述接收模块接收的所述切换命令，对所述目标小区发起随机接入请求，所述随机接入请求用于请求接入所述目标小区。
  27. 一种用户设备UE，包括处理器和存储器，所述存储器存储可在所述处理器上运行的程序或指令，所述程序或指令被所述处理器执行时实现如权利要求1至13任一项所述的小区切换方法的步骤。
  28. 一种可读存储介质，所述可读存储介质上存储程序或指令，所述程序或指令被处理器执行时实现如权利要求1至13中任一项所述的小区切换方法。
PCT/CN2023/078462 2022-03-01 2023-02-27 小区切换方法、装置及用户设备 WO2023165447A1 (zh)

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