Information transceiving method and apparatus, and communication system

Abstract

Provided in embodiments of the present application are an information transceiving method and apparatus, and a communication system. The method comprises: a terminal device receives prediction configuration information sent by a network device, wherein the prediction configuration information comprises configuration information used for instructing the terminal device to perform AI prediction, and / or report configuration information used for indicating AI prediction-related information; the terminal device performs AI prediction on the basis of the prediction configuration information, and determines prediction value information and / or prediction information; and / or the terminal device sends report information to the network device on the basis of the prediction configuration information, wherein the report information comprises prediction value information of a cell and / or a beam, and / or prediction information related to target cell handover.

Description

Information transceiving method, apparatus, and communication system TECHNICAL FIELD

[0001] Embodiments of the present application relate to the field of communication technology. BACKGROUND

[0002] Multiple scenarios or sub-scenarios are defined in 3GPP artificial intelligence / machine learning (AI / ML) study, such as normal handover, conditional handover, L1 / L2 triggered mobility (LTM) or other scenarios. Different scenarios or sub-scenarios can correspond to one or more features / feature groups. Applying AI / ML to the above feature / feature group is called AI / ML-based / enabled feature / feature group. One AI / ML-based / enabled feature / feature group can correspond to one or more AI functionalities and / or one or more AI models. One AI functionality can correspond to one or more AI models. The function refers to the AI / ML-based / enabled feature / feature group that is configured to be enabled. The possible logic is shown in FIG. 1.

[0003] The AI model can be deployed on the terminal device. For example, the one-sided model deployed on the terminal device can be called the UE-side model. One side sub-model of the two-sided model or the multi-sided model can be deployed on the terminal device, which can be called the UE-part of two-sided models.

[0004] The AI model can be deployed on the network device. For example, the one-sided model deployed on the network device can be called the NW-side model. One side sub-model of the two-sided model or the multi-sided model can be deployed on the network device, which can be called the NW-part of two-sided models.

[0005] When the model is deployed or the model corresponding to the function is deployed, the configuration between the model and the terminal device needs to be considered. Taking the model deployed on the terminal device as an example, the terminal device uses the AI model to perform the inference function related to mobility, and sends the related inference result to the network device for assisting the network device in mobility management. Therefore, the present application mainly considers the mechanism that the terminal device sends the prediction information obtained based on the AI model inference to the network device, so that the network device can perform corresponding mobility management.

[0006] It should be noted that the above introduction to the technical background is only for the convenience of clearly and completely describing the technical scheme of the present application and for the convenience of understanding by those skilled in the art. The above technical scheme cannot be considered as known to those skilled in the art just because it is described in the background section of the present application.

[0007] SUMMARY

[0008] In order to reduce the measurement overhead of the terminal device or improve the robustness of the mobility management, the 3GPP discusses the prediction of the measurement result based on the AI model, and the above AI model can be deployed on the terminal device side, but there is no discussion on the configuration management of the AI model on the terminal device side and / or the reporting scheme of the inference result (also referred to as prediction information) based on the AI model.

[0009] In view of at least one of the above problems or other similar problems, the embodiments of the present application provide an information receiving and transmitting method and device, and a communication system.

[0010] According to an aspect of the embodiments of the present application, an information receiving and transmitting device is provided, which is applied to a terminal device and includes:

[0011] a receiver configured to receive prediction configuration information sent by a network device, the prediction configuration information including configuration information for instructing the terminal device to perform AI prediction and / or reporting configuration information for instructing AI prediction related information;

[0012] a processor configured to perform AI prediction according to the prediction configuration information, determine prediction value information, and / or prediction information; and / or a transmitter configured to send reporting information to the network device according to the prediction configuration information, the reporting information including prediction value information of a cell and / or a beam, and / or prediction information related to a handover target cell.

[0013] According to another aspect of the embodiments of the present application, an information receiving and transmitting device is provided, which is applied to a network device and includes:

[0014] a transmitter configured to send prediction configuration information to the network device, the prediction configuration information including configuration information for instructing the terminal device to perform AI prediction and / or reporting configuration information for instructing AI prediction related information.

[0015] a receiver configured to receive the reporting information sent by the terminal device according to the prediction configuration information, the reporting information comprising the predicted value information of the cell and / or the beam, and / or the prediction information related to the handover target cell.

[0016] According to another aspect of the embodiments of the present application, a communication system is provided, comprising the information transceiving device of the previous aspect and / or the information transceiving device of the another aspect.

[0017] One of the beneficial effects of the embodiments of the present application is that according to the embodiments of the present application, the AI model on the terminal device side can make predictions based on the prediction configuration information of the network device, and report the prediction results to the network device to provide corresponding inference output information for the network device; so that the network device optimizes mobility management based on the prediction results, and improves the mobility robustness of the terminal device.

[0018] Specific embodiments of the application are disclosed in the following description and in the accompanying drawings, indicating the ways in which the principles of the application can be employed. It is understood that the embodiments of the application are not limited in scope to the specific embodiments described herein. Embodiments of the application include many changes, modifications, and equivalents within the spirit and scope of the appended claims as will become apparent to those skilled in the art. It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not intended to be restrictive of the application, as claimed.

[0019] Features described and / or illustrated with respect to one implementation can be used in one or more other implementations in the same or similar manner, in combination with or in place of the features in the other implementations.

[0020] It should be emphasized that the term "comprises / comprising" when used in this text is taken to mean that the features, integers, steps or components referred to are present, but not excluding the presence or addition of one or more other features, integers, steps, components or groups thereof. " / " means "or". BRIEF DESCRIPTION OF DRAWINGS

[0021] Elements and features described with respect to one drawing or implementation of the application can be combined with elements and features illustrated in one or more other drawings or implementations of the application. Also, in the drawings, like reference numerals designate corresponding parts throughout the several views, and can be used to designate like components in more than one implementation.

[0022] FIG. 1 is a logical schematic diagram of AI functions and their corresponding AI models;

[0023] FIG. 2 is a schematic diagram of an information transceiving method according to an embodiment of the present application;

[0024] FIG. 3 is a schematic diagram of an information transceiving method according to an embodiment of the present application;

[0025] FIG. 4 is a schematic diagram of a cell handover process based on AI model prediction according to an embodiment of the present application;

[0026] FIG. 5 is a schematic diagram of an information transceiving apparatus according to an embodiment of the present application;

[0027] FIG. 6 is a schematic diagram of an information transceiving apparatus according to an embodiment of the present application;

[0028] FIG. 7 is a schematic diagram of a communication system according to an embodiment of the present application;

[0029] FIG. 8 is a schematic diagram of a network device according to an embodiment of the present application;

[0030] FIG. 9 is a schematic diagram of a terminal device according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] The foregoing and other features of the present application will become apparent to those skilled in the art upon consideration of the following description of specific embodiments of the present application, which are not intended to limit the scope of the application. In describing specific embodiments of the application, specific terminology is used for the sake of clarity. However, the use of such terminology is not intended to limit the scope of the application, since alternative embodiments of the application can employ techniques that are similar to those described in connection with the embodiments described herein.

[0032] In the embodiments of the present application, the terms "first", "second", and the like are used to distinguish different elements from each other, but do not indicate spatial arrangement or time sequence of the elements, and the elements should not be limited by these terms. The term "and / or" includes any one and all combinations of the associated listed terms. The terms "comprise", "include", "have", and the like mean the presence of the stated feature, element, component, or assembly, but do not exclude the presence or addition of one or more other features, elements, components, or assemblies.

[0033] In the embodiments of the present application, the singular forms "a", "an", and "the" include the plural forms, should be broadly understood as "one" or "one type", rather than limited to the meaning of "one"; in addition, the term "said" should be understood to include both singular and plural forms, unless the context clearly indicates otherwise. In addition, the term "according to" should be understood as "at least partially according to", and the term "based on" should be understood as "at least partially based on", unless the context clearly indicates otherwise.

[0034] In the embodiments of the present application, the scenario of including a network device and / or a terminal device is taken as an example.

[0035] In the above scenario, network devices may include at least one of core network devices, third-party application devices, operation administration and maintenance (OAM) devices, and access network devices.

[0036] Core network equipment refers to equipment in the core network (CN) that provides service support to terminal equipment. As examples, core network equipment can be at least one of the following: Mobility and Management Entity (MME), Access and Mobility Management Function (AMF) entity, Session Management Function (SMF) entity, User Plane Function (UPF) entity, Location Management Function (LMF) entity, etc., and not all will be listed here. The AMF entity is responsible for terminal access management and mobility management; the SMF entity is responsible for session management, such as user session establishment; the UPF entity can be a user plane function entity, mainly responsible for connecting to external networks; and the LMF entity manages the overall coordination and scheduling of resources required for the location of terminal equipment registered with or accessing the core network equipment. It should be noted that in the embodiments of this application, an entity can also be called a network element or functional entity; for example, an AMF entity can also be called an AMF network element or an AMF functional entity, etc.

[0037] Third-party application devices can be OTT services (over the top server) or other third-party devices.

[0038] OAM (Operation, Administration, Maintenance) is a network device that performs network management tasks such as operation, administration, and maintenance according to the actual needs of the operator's network operation.

[0039] The access network device is an access device through which a terminal device accesses a communication system in a wireless manner. The access network device can be a base station (BS), an evolved NodeB (eNodeB), a transmission reception point (TRP), a base station (gNB) in a 5th generation (5G) mobile communication system, a base station in a 6th generation (6G) mobile communication system, a base station in a future mobile communication system, or an access node in a WiFi system, etc. The access network device can also be a module or unit that completes part of the functions of a base station, for example, at least one of the following modules or units: a central unit (CU), a distributed unit (DU), a CU control plane (CU-CP), a CU user plane (CU-UP), an integrated access backhaul (IAB), or other modules or units. The embodiments of the present application do not limit the specific technology and / or specific device form adopted by the access network device. The access network device can be deployed on land, including indoors / outdoors, can be handheld or vehicle-mounted; it can also be deployed on water, on an airplane, on a balloon or on a satellite; the access network device can be deployed at a fixed location or on a mobile carrier, and the embodiments of the present application do not limit this.

[0040] In the above scenarios, the terminal device can be a device with wireless transceiver function, which can send signals to the access network device and / or receive signals from the access network device. The terminal device can also be referred to as a terminal, a mobile station, a mobile terminal, etc. The terminal device can be a mobile phone, a tablet, or other devices with wireless intelligent transceiver function. The terminal device can be widely used in various scenarios, such as device-to-device (D2D), vehicle-to-everything (V2X) communication, machine-type communication (MTC), Internet of things (IoT), virtual reality, augmented reality, industrial control, autonomous driving, remote medical treatment, or various smart scenarios.

[0041] In the above scenarios, the access network device and the terminal device, the terminal device and the terminal device can communicate through the licensed spectrum, or through the unlicensed spectrum, or through the licensed spectrum and the unlicensed spectrum at the same time. The embodiments of the present application do not limit the spectrum resources used for wireless communication.

[0042] In the following description of the present application, artificial intelligence (AI) can also be referred to as artificial intelligence / machine learning (AI / ML) or machine learning (ML), which can be interchangeable, for example, "AI-based feature or feature group" and "AI or ML-based feature or feature group" have the same meaning, and their corresponding English can be AI / ML-based feature / FG. "Prediction" and "inference" can be interchangeable.

[0043] The embodiments of the present application will be described below in conjunction with the accompanying drawings and specific embodiments. For ease of description, the following describes a base station as an example of an access network device. In the following description, "if", "in the case of" and "when" can be used interchangeably without causing confusion.

[0044] The following describes the embodiments in conjunction with the embodiments.

[0045] Embodiments of the first aspect

[0046] The embodiments of the present application provide an information transceiving method, which is described from the side of the terminal device. In the embodiments of the present application, the AI model is deployed on the terminal device side, and the terminal device performs AI prediction on the measurement result.

[0047] FIG. 2 is a schematic diagram of an information transceiving method according to an embodiment of the present application. As shown in FIG. 2, the method comprises:

[0048] 201, the terminal device receives the prediction configuration information sent by the network device, the prediction configuration information comprising configuration information for instructing the terminal device to perform AI prediction, and / or reporting configuration information for instructing AI prediction related information;

[0049] 202, the terminal device performs AI prediction according to the prediction configuration information, determines the prediction value information, and / or the prediction information; and / or,

[0050] 203, the terminal device sends the reporting information to the network device according to the prediction configuration information, the reporting information comprising the prediction value information of the cell and / or beam, and / or the prediction information related to the target cell of the handover.

[0051] It is worth noting that the above FIG. 2 only schematically illustrates the embodiments of the present application, but the present application is not limited thereto. For example, some other operations can be added or some operations therein can be reduced. Those skilled in the art can make appropriate modifications according to the above description, and the modifications are not limited to the description of the above FIG. 2.

[0052] According to the embodiments of the present application, the AI model on the terminal device side can make a prediction based on the prediction configuration information of the network device, and report the prediction result to the network device to provide corresponding inference output information for the network device; so that the network device optimizes mobility management based on the prediction result, and improves the mobility robustness of the terminal device.

[0053] In some embodiments, the network device can send prediction configuration information to the terminal device, so that the terminal device performs measurement, determines a prediction result (including prediction value information and / or prediction information) based on the measurement result by performing AI prediction. Further, the terminal device can also perform reporting of the prediction result and the like. The prediction configuration information includes configuration information for instructing the terminal device to perform AI prediction, and / or reporting configuration information for instructing AI prediction related information. The prediction configuration information can include at least one of measurement configuration information, mode configuration information, reporting configuration information and measurement identification information. The measurement configuration information is used to instruct the measurement information of the terminal device; the mode configuration information is used to instruct the mode information of the terminal device performing AI prediction; the reporting configuration information is used to instruct the information to be reported by the terminal device; and the measurement identification information is used to associate at least one measurement configuration information, at least one mode configuration information and / or at least one reporting configuration information. The following are described respectively.

[0054] It can be understood that the above-mentioned configuration information for instructing the terminal device to perform AI prediction and the above-mentioned reporting configuration information for instructing AI prediction related information can be carried in the same signaling or in different signaling. If the above-mentioned information is carried in different signaling, the step 201 can be divided into different steps.

[0055] In some embodiments, the measurement configuration information includes at least one of the following information: measurement object information, first indication information, reference signal configuration information of the measurement object or other measurement configuration information. The measurement object information can include frequency point information. Optionally, the measurement object information can also include cell information and / or beam information. The first indication information is used to instruct whether the terminal device needs to perform AI prediction on the measurement object. Correspondingly, the first indication information can be in frequency point granularity, cell granularity or beam granularity. It can be understood that if the prediction configuration information includes measurement identification information, the first indication information can also be in measurement identification granularity.

[0056] In some embodiments, for the above-mentioned reference signal (measurement resource) configuration information, the reference signal can be a CSI-RS and / or an SSB, and the like. The reference signal configuration information is used to indicate at least one resource set information (reference signal set information). Further, the above-mentioned resource set information can be used to indicate one or more measurement resources (reference signals). As an example, the reference signal configuration information can include at least one reference signal set identifier (measurement resource set identifier) information and the identifier information of one or more measurement resources (reference signals) constituting the reference signal set (measurement resource set). For example, taking the reference signal as a CSI-RS as an example, the reference signal configuration information can include a CSI-ResourceConfigId and at least one CSI-RS-ResourceSetId, wherein the CSI-RS-ResourceSetId can include at least one of the following information: at least one NZP-CSI-RS-ResourceSetId, at least one CSI-SSB-ResourceSetId, at least one CSI-IM-ResourceSetId, and further can include at least one NZP-CSI-RS-ResourceId, at least one CSI-SSB-ResourceId, at least one CSI-IM-ResourceId. However, this is only an example for illustration, and the embodiments of the present application are not limited thereto.

[0057] In the above embodiments, the measurement result (predicted value) based on AI prediction and the measurement result (measured value) obtained by performing actual measurement can be at least one corresponding measurement result of a channel state information reference signal (CSI-RS) or a synchronization signaling block (SSB) or other reference information. The possible measurement result information (predicted value information and measured value information) includes quality information, and the quality information (predicted value and measured value) includes at least one of the following information: reference signal receiving power (RSRP), reference signal receiving quality (RSRQ), reference signal strength indicator (RSSI), signal to interference plus noise ratio (SINR), or other signal quality information. The measurement result can be a layer 1 (L1) measurement result and / or a layer 3 (L3) measurement result.

[0058] In some embodiments, the mode configuration information includes at least one of the following information: time information of performing AI prediction, time configuration information / number configuration information of performing AI prediction and measurement, trigger configuration information of falling back to measurement when performing AI prediction, correlation information of performing AI prediction, or other mode configuration information. The above correlation information is used to indicate the correlation between at least one measurement object (first measurement object) that needs to perform measurement and at least one measurement object (second measurement object) that performs AI prediction based on the at least one measurement object that needs to perform measurement.

[0059] For example, the time information of performing AI prediction includes absolute time information, or absolute start time information and relative time information of relative start time information. The embodiments of the present application are not limited thereto.

[0060] For example, the time configuration information / number configuration information of performing AI prediction and measurement can include cycle information of AI prediction and prediction time information / number information within the cycle, and / or cycle information of measurement and measurement time information / number information within the cycle. The above time information can include absolute time information, or absolute start time information and relative time information of relative start time information. The embodiments of the present application are not limited thereto.

[0061] For example, the trigger configuration information for falling back to measurement when performing AI prediction can be first accuracy threshold information of the predicted value. When the terminal device determines that the accuracy of the predicted value does not meet the first accuracy threshold, the terminal device falls back to actual measurement and obtains the measurement value. Optionally, the first accuracy threshold information can be an absolute threshold or a relative threshold, and the embodiments of the present application are not limited thereto.

[0062] For example, the correlation information can be {frequency point 1, frequency point 2}, which is used to instruct the terminal device to measure the cell on the frequency point 1, and based on the measurement value, the measurement result (predicted value) of the cell on the frequency point 2 can be predicted. For another example, the correlation information can be {(frequency point 1, cell 1, cell 2), (frequency point 2, cell 3)}, which is used to instruct the terminal device to measure cell 1 and cell 2 on the frequency point 1 and obtain the corresponding measurement value, and based on the corresponding measurement value, the measurement result of cell 3 on the frequency point 2 can be predicted.

[0063] It should be noted that the AI prediction in the embodiments of the present application includes at least one of time domain prediction, frequency domain prediction, or space domain prediction. For example, the terminal device can predict the predicted value of a measurement object at at least one second time in the future based on the measurement value of the measurement object at at least one first time in the past; for example, the terminal device can predict the predicted value of a cell on a second frequency point (an example of a second measurement object) based on the measurement value of a cell on a first frequency point (an example of a first measurement object); for example, the terminal device can predict the predicted value of other beams (second measurement object) of a cell based on the measurement result of at least one beam (first measurement object) of the measured cell. The mechanism corresponding to the AI prediction in the embodiments of the present application is not limited. It can be understood that in the frequency domain prediction and the space domain prediction, the mode configuration information can further include the correlation information for performing AI prediction, so as to determine the first measurement object and the second measurement object. The description of the correlation information is referred to the above, and will not be repeated here.

[0064] In some embodiments, the reporting configuration information can indicate the information required to be reported by the terminal device, or indicate the information required to be reported by the terminal device and the timing (time) information of the reporting. The reporting configuration information includes at least one of the following information: first configuration information, second indication information, handover type information, trigger condition configuration, third indication information, or other reporting configuration information. Among them, the first configuration information is used to indicate the predicted value information required to be reported; the second indication information is used to indicate whether the predicted information needs to be reported; the handover type information is used to indicate the handover type related to the predicted information; the trigger condition configuration is used to indicate the configuration for triggering the terminal device to report the predicted value and / or the measurement value; and the third indication information is used to indicate the time range information of the predicted value information and / or the predicted information required to be reported by the terminal device.

[0065] The prediction value information can include at least one of predicted cell information, predicted measurement result information of the cell, predicted beam information under the cell, and predicted measurement result information of the beam. The cell information includes at least one of cell global identifier (CGI), physical cell identifier (PCI) and frequency point information, cell identifier (cell ID), non-public network identifier (NPN ID), non-terrestrial network identifier (NTN ID), or other cell identifiers. The CGI can include a public land mobile network (PLMN ID) and a cell ID. Optionally, the cell information can further include tracking area code (TAC) and / or identifier information of a network device to which the cell belongs, such as a global network device identifier. The beam information can be beam identifier information, beam index information, or other information that can identify a beam. The measurement result information is described above and will not be repeated here.

[0066] The prediction information can include at least one of predicted and / or recommended handover target cell information, predicted and / or recommended handover target cell handover configuration information, predicted and / or recommended handover target cell prediction value and time correspondence, predicted and / or recommended handover target cell handover time information, predicted and / or recommended handover target cell residence information, or other prediction information. The predicted handover target cell can be at least one potential handover target predicted by the terminal, and the recommended handover target cell can be a handover target cell for which the terminal device predicts to perform handover. As an example, the recommended handover target cell can be at least one predicted handover target cell. For example, the predicted handover target cell is cell 1, cell2 and cell3, and the recommended handover target cell of the terminal device is cell1.

[0067] The handover type can include at least one of: normal handover, conditional handover (CHO), dual active protocol stack handover (DAPS), layer 1 / 2 triggered mobility (LTM), or other handover types.

[0068] In some embodiments, according to the first configuration information, the terminal device can determine the predicted value information that needs to be reported; and according to the second indication information, the terminal device can determine the prediction information in the reported information. It can be understood that, according to the first configuration information and / or the second indication information, the terminal device can also determine whether the predicted value information and / or the prediction information needs to be reported.

[0069] In some embodiments, the first configuration information includes at least one of the following information:

[0070] The number information (e.g., the maximum number information) of the predicted cells that needs to be reported;

[0071] The fourth indication information is used to indicate whether to report the predicted beam information under the cell. For example, the fourth indication information can be 1-bit indication information, when the bit value is 1 (or the bit value exists), it indicates that the predicted beam information under the cell needs to be reported; when the bit value is 0 (or the bit value does not exist), it indicates that the predicted beam information under the cell does not need to be reported, and vice versa, which is not limited by the embodiments of the present application;

[0072] The number information (e.g., the maximum number information) of the predicted beams that can be reported;

[0073] The quality threshold information of the predicted beams that can be reported.

[0074] The terminal device can determine whether (how) to report the predicted value information according to the first configuration information.

[0075] In some embodiments, the second indication information can be replaced by at least one of the following indication information: indication information of whether to report predicted handover target cell information, indication information of whether to report handover configuration information of the predicted handover target cell, indication information of whether to report suggested handover target cell information, indication information of whether to report handover configuration information of the suggested handover target cell, indication information of whether to report residence information of the predicted handover target cell, indication information of whether to report residence information of the suggested handover target cell, indication information of whether to report handover time information of the predicted handover target cell, indication information of whether to report handover time information of the suggested handover target cell, indication information of whether to report the correspondence between the predicted value and time of the predicted handover target cell, and indication information of whether to report the correspondence between the predicted value and time of the suggested handover target cell. The possible handover configuration information can include random access type, beam information of random access, time domain and / or frequency domain resource information of random access, time advance information of random access, or other handover configuration information.

[0076] It can be understood that, as an implementation manner a, the at least one indication information can be an independent information element respectively; as another possible implementation manner b, the at least one indication information can be an information element (bitmap). In implementation manner b-1, the information element can include one bit. At this time, the implementation manner b-1 can refer to the implementation manner a. If the information element includes at least two bits, different bits in the bitmap can respectively implement the function of one indication information. In implementation manner b-2, different values of the bitmap can implement the combined function of different at least one indication information. It can be understood that, the implementation manner b can also be considered as an implementation manner of the second indication information.

[0077] As an example of the above-mentioned implementation manner a, the above-mentioned one kind of indication information can be used to indicate whether one kind of prediction information needs to be reported. At least one kind of indication information can be sent to respectively indicate whether different prediction information needs to be reported. If each kind of indication information is 1-bit indication information, when the bit value is 1 (or the bit value exists), it indicates that the corresponding prediction information needs to be reported; when the bit value is 0 (or the bit value does not exist), it indicates that the corresponding prediction information does not need to be reported, and vice versa, which is not limited by the embodiments of the present application. For example, the reporting configuration information can include three above-mentioned indication information, which can be indication information indicating that the predicted handover target cell information needs to be reported, indication information indicating that the predicted handover configuration information of the handover target cell needs to be reported, and indication information indicating that the recommended handover target cell information needs to be reported. The terminal device determines that the predicted handover target cell information, the predicted handover configuration information of the handover target cell and the recommended handover target cell information need to be reported according to the above-mentioned three indication information, and other prediction information does not need to be reported.

[0078] As another example of the above-mentioned implementation manner b, in the bit map of the implementation manner b-1, when the bit value of the corresponding bit is 1, it indicates that the corresponding prediction information needs to be reported; when the bit value of the corresponding bit is 0, it indicates that the corresponding prediction information does not need to be reported, and vice versa. For example, the reporting configuration information includes second indication information, and the second indication information is a 5-bit bit map. Each bit of the bit map from left to right respectively indicates that the predicted handover target cell information needs to be reported, the predicted handover configuration information of the handover target cell needs to be reported, the corresponding relationship between the predicted value and the time of the predicted handover target cell does not need to be reported, the handover time information of the predicted handover target cell does not need to be reported, and the camping information of the predicted handover target cell does not need to be reported. For example, the value of the bit map is 11000. The terminal device determines that the predicted handover target cell information and the predicted handover configuration information of the handover target cell need to be reported according to the second indication information, and the corresponding relationship between the predicted value and the time of the predicted handover target cell, the handover time information of the predicted handover target cell and the camping information of the predicted handover target cell do not need to be reported. Alternatively, in the implementation manner b-2, different values of the bit map can indicate whether different combinations of prediction information need to be reported. For example, the value 00000 indicates that the terminal device does not need to report the above-mentioned information; the value 00001 indicates that the terminal device needs to report the predicted handover target cell information; the value 00010 indicates that the terminal device needs to report the predicted handover target cell information and the predicted handover configuration information of the handover target cell; the value 00011 indicates that the terminal device needs to report the predicted handover target cell information, the predicted handover configuration information of the handover target cell and the corresponding relationship between the predicted value and the time of the predicted handover target cell; and so on, which is not described here.

[0079] In some embodiments, the triggering condition is configured for the terminal device to determine a timing of reporting the predicted value information and / or the measurement value information and / or the prediction information.

[0080] As an implementation, the triggering condition comprises reporting period information, and the terminal device can periodically report the information according to the reporting period information. The reporting period information can comprise at least one of the following period information: predicted value information reporting period information, prediction information reporting period information, and measurement value information reporting period information. The periods can be the same or different. If the same, the reporting period information can only contain the same reporting period information, so as to reduce unnecessary signaling overhead. For example, if the predicted value information reporting period and the prediction information reporting period are the same, the reporting period information can only include one reporting period information, and the terminal device determines that the reporting period information can be applied to the predicted value information reporting and the prediction information reporting. The embodiments of the present application are not limited in this regard.

[0081] As another implementation, the triggering condition comprises second accuracy threshold information of event-triggered reporting. The second accuracy threshold information can be an absolute threshold or a relative threshold. The terminal device can determine whether to report the predicted value information or the predicted value information and the measurement value information according to the accuracy threshold information. For example, when the terminal device determines that the accuracy of the predicted value does not meet the second accuracy threshold information, the terminal device also needs to report the measurement value information corresponding to the predicted value information. For example, the terminal device predicts the predicted value at T1 time at T0 time, and reports the predicted value information at T1 time to the network device; when the terminal device obtains the measurement value at T1 time, it is determined that the accuracy of the predicted value is less than or equal to the second accuracy threshold information according to the measurement value and the predicted value, and the terminal device also reports the measurement value information at T1 time to the network device.

[0082] As still another implementation, the triggering condition comprises quality threshold information of event-triggered reporting. The quality threshold information is used to indicate that the terminal device reports the predicted value that meets the quality threshold information; for example, when the terminal device determines that the predicted value output by the AI model meets the quality threshold information, the predicted value is reported. Only as an example, the event can comprise any one of triggering events A1 to A6, or comprise other triggering events, and the embodiments of the present application are not limited in this regard.

[0083] The above triggering condition is only an example, and the embodiments of the present application are not limited in this regard.

[0084] In some embodiments, the reporting configuration information can also indicate the maximum number of predicted handover target cells that can be reported, and / or the maximum number of recommended handover target cells that can be reported.

[0085] In some embodiments, the reporting configuration information further includes third indication information. Correspondingly, the third indication information indicates a time range for reporting the predicted value information and / or the prediction information. After performing AI prediction, the terminal device reports the predicted value information and / or the prediction information in the above time range.

[0086] The above describes the prediction configuration information in the embodiments of the present application. The following describes how to perform measurement, prediction and reporting according to the prediction configuration information.

[0087] In some embodiments, in 202, the terminal device performs measurement according to the measurement configuration information and the mode configuration information in the prediction configuration information, and performs AI prediction (using the measurement result as the input of the AI model) using the measurement result (measurement value information) and the AI model to obtain the predicted value information and / or the prediction information. According to the configuration of the network device, the AI prediction performed by the terminal device can be in the granularity of frequency point, cell or measurement identifier. The predicted value information and / or the measurement value information can be cell and / or beam. How to perform measurement and prediction according to the prediction configuration information to obtain the predicted value information and / or the prediction information is described above, and will not be described here.

[0088] In some embodiments, optionally, when the terminal device performs AI prediction on the measurement object, the terminal device can ignore the reference signal configuration information corresponding to the measurement object.

[0089] In some embodiments, in 203, the terminal device can send the reporting information to the network device according to the reporting configuration information in the prediction configuration information, the reporting information including the predicted value information of the cell and / or the beam, and / or the prediction information related to the target cell of handover. Optionally, the reporting information can also include the measurement value information of the cell and / or the beam. In addition, as mentioned above, optionally, if the reporting configuration information includes the third indication information, the terminal device can only report the predicted value information and / or the prediction information within the time range indicated by the third indication information. In addition, as mentioned above, optionally, if the reporting configuration information indicates that the terminal device needs to report the suggested target cell information of handover, the reporting information can also include the indication information indicating the suggested target cell information of handover, or can include the suggested target cell information of handover and the handover configuration information of the target cell. As an example, the reporting information includes the predicted target cell information and the indication information indicating the suggested target cell information of handover, i.e. indicator_S; for example, the reporting information includes {[predicted cell1 information], [predicated cell 2 information, indicator_S]}, in which cell1 and cell2 are both the predicted target cell information of handover, and cell2 is the suggested target cell of handover. As another example, the reporting information also includes an independent information element for indicating the suggested target cell information of handover; for example, the reporting information includes suggested target cell information.

[0090] In some embodiments, the method can further include (not shown):

[0091] The terminal device receives the mobility configuration information sent by the network device, the mobility configuration information being used to indicate the terminal device to perform the handover to the target cell of handover; and the terminal device performs the handover to the target cell of handover according to the mobility configuration information.

[0092] In some embodiments, the mobility configuration information includes the target cell information of handover and the handover configuration information corresponding to the target cell. The description of the handover configuration information is as above, which will not be repeated here.

[0093] In some embodiments, the target cell for switching is a cell determined based on the reported predicted value information of the cell, and / or a cell determined based on the prediction information. For example, the network device selects a cell with the highest cell quality, or a cell with the most good beams, or a cell with the longest residence time, as the target cell for switching according to the prediction information and / or the predicted value information (e.g., predicted measurement result information of the cell, predicted residence information of the target cell for switching, predicted beam information under the cell, predicted measurement result information of the beam, etc.), and sends mobility configuration information including the target cell for switching and corresponding switching configuration information to the terminal device, and the terminal device performs a switching process with the cell according to the corresponding mobility configuration information.

[0094] In some embodiments, optionally, the method can further include that the terminal device can also receive AI function activation indication information from the network device, for indicating the AI function or AI model that needs to be activated by the terminal device. The AI function activation indication information can be identification information of the AI function or AI model. The AI function activation indication information and the prediction configuration information can be sent in the same message or in different messages respectively, and the embodiments of the present application are not limited in this regard.

[0095] In some embodiments, for the above switching process, reference can be made to the related art, and the embodiments of the present application are not limited in this regard. The above prediction configuration information and / or reporting information and / or mobility configuration information and / or AI function activation indication information can be carried by RRC signaling and / or MAC CE and / or physical layer signaling, and each of the above configuration information can be carried by the same or different signaling, and the embodiments of the present application are not limited in this regard.

[0096] The above embodiments only exemplarily illustrate the method of the embodiments of the present application, but the present application is not limited thereto, and appropriate modifications can be made on the basis of the above embodiments. For example, each of the above embodiments can be used alone, or one or more of the above embodiments can be combined.

[0097] According to the embodiments of the present application, the AI model on the terminal device side can make predictions based on the prediction configuration information of the network device, and report the prediction results to the network device to provide corresponding inference output information for the network device; so that the network device optimizes mobility management based on the prediction results, and improves the mobility robustness of the terminal device.

[0098] In addition, the predicted value information is the inference output information of the AI model on the terminal device side, the terminal device can interact with the network device for the inference output information, and the network device can select a suitable target cell based on the prediction information or the predicted value information reported by the terminal device to instruct the terminal device to switch.

[0099] Embodiments of the second aspect

[0100] Embodiments of the present application provide an information transmission method, which is described from the side of a network device. In the embodiments of the present application, an AI model is deployed on a terminal device side, and the terminal device performs AI prediction on measurement results.

[0101] The network device can be a base station, a CU or a DU, or a core network device (such as an LMF), and the embodiments of the present application are not limited in this regard.

[0102] FIG. 3 is a schematic diagram of a measurement reporting method according to an embodiment of the present application. As shown in FIG. 3, the method comprises the following steps:

[0103] 301. The network device sends prediction configuration information to the terminal device, the prediction configuration information comprising configuration information for instructing the terminal device to perform AI prediction, and / or reporting configuration information for instructing AI prediction related information.

[0104] 302. The network device receives reporting information sent by the terminal device according to the prediction configuration information, the reporting information comprising predicted value information of a cell and / or a beam, and / or predicted information related to a handover target cell.

[0105] For 301 and 302, and the implementation of the configuration information and the reporting information, refer to the embodiments of the first aspect, and the repeated parts will not be described herein.

[0106] In some embodiments, the method can further comprise (not shown in the figure):

[0107] The network device completes a handover preparation procedure with a target network device to which the target cell belongs.

[0108] In some embodiments, the method can further comprise (not shown in the figure):

[0109] The network device sends mobility configuration information to the terminal device, the mobility configuration information being used to instruct the terminal device to perform handover to a handover target cell. The mobility configuration information can refer to the embodiments of the first aspect, and will not be described herein.

[0110] In some embodiments, the method can further comprise (not shown in the figure):

[0111] The network device receives connection time information sent by the target cell, the connection time information being time information of the terminal device in a connected state in the target cell after handover, the time information being used to indicate the length of time between the time when the terminal device successfully accesses the target cell and the time when the terminal device enters an unconnected state in the target cell or is handed over to another cell.

[0112] FIG. 4 is a schematic diagram of a cell handover process based on AI model prediction according to an embodiment of the present application. As shown in FIG. 4, the method comprises the following steps.

[0113] 401. The network device sends prediction configuration information to the terminal device.

[0114] 402. The terminal device performs measurement and prediction according to the prediction configuration information to obtain measurement value information and / or prediction value information and / or prediction information.

[0115] 403. The terminal device sends reporting information to the network device according to the prediction configuration information, wherein the reporting information comprises prediction value information and / or prediction information, and optionally, can further comprise measurement value information.

[0116] 404. The network device determines a target cell according to the reporting information, and completes a handover preparation process between the target network device to which the target cell belongs and the network device.

[0117] 405. The network device sends mobility configuration information to the terminal device.

[0118] 406. The terminal device performs handover to the target cell according to the mobility configuration information.

[0119] 407. The network device receives connection time information sent by the target cell.

[0120] The implementation of 401-407 can refer to the foregoing embodiments, and the repeated parts will not be described again.

[0121] The above embodiments only exemplarily illustrate the method of the embodiments of the present application, but the present application is not limited thereto, and appropriate modifications can be made on the basis of the above embodiments. For example, the above embodiments can be used alone, or one or more of the above embodiments can be combined.

[0122] According to the embodiments of the present application, the AI model on the terminal device side can make prediction based on the prediction configuration information of the network device, and report the prediction result to the network device to provide corresponding inference output information for the network device; and the network device optimizes mobility management based on the prediction result to improve the mobility robustness of the terminal device.

[0123] Embodiments of the third aspect

[0124] The embodiments of the present application provide an information transceiving device.

[0125] FIG. 5 is a schematic diagram of an information transceiving device for information transceiving according to an embodiment of the present application. The device can be a terminal device, or a component or assembly of the terminal device. The device has the same problem-solving principle as the method of the first aspect, and its specific implementation can refer to the implementation of the method of the first aspect. The same content will not be repeated. As shown in FIG. 5, the device 500 includes a receiver 501 and a transmitter 502.

[0126] In some embodiments, the receiver 501 receives prediction configuration information sent by the network device; the prediction configuration information includes configuration information for instructing the terminal device to perform AI prediction, and / or reporting configuration information for indicating AI prediction related information; the processor 503 performs AI prediction according to the prediction configuration information, determines prediction value information, and / or prediction information; and / or the transmitter 502 sends reporting information to the network device according to the prediction configuration information, the reporting information including prediction value information of the cell and / or beam, and / or prediction information related to the handover target cell.

[0127] In some embodiments, the receiver 501 can also receive mobility configuration information sent by the network device, and the processor 503 can also perform handover with the handover target cell according to the mobility configuration information.

[0128] The above transmitter, receiver and processor can refer to the embodiments of the first aspect, which will not be repeated here.

[0129] The above embodiments of the present application are exemplary, but the present application is not limited thereto, and can be appropriately modified based on the above various embodiments. For example, the above various embodiments can be used alone, or one or more of the above various embodiments can be combined.

[0130] It is worth noting that the above only describes the components or modules related to the present application, but the present application is not limited thereto. The above device can also include other components or modules, and the specific content of these components or modules can refer to related technologies. In addition, the above various components or modules can be implemented by hardware facilities such as processors, memories, transmitters, receivers, etc.; the present application is not limited thereto.

[0131] According to the embodiments of the present application, the AI model on the terminal device side can perform prediction based on the prediction configuration information of the network device, and report the prediction result to the network device to provide corresponding inference output information for the network device; so that the network device optimizes mobility management based on the prediction result, and improves the mobility robustness of the terminal device.

[0132] Embodiments of the fourth aspect

[0133] The embodiment of the present application provides an information transceiving device.

[0134] FIG. 6 is a schematic diagram of an information transceiving device according to the embodiment of the present application, which can be a network device, or some component or assembly configured in the network device. Since the principle of solving the problem of the device is the same as that of the method of the embodiment of the second aspect, the specific implementation can refer to the implementation of the method of the embodiment of the second aspect, and the same content is not described repeatedly. As shown in FIG. 6, the device 600 includes a transmitter 601 and a receiver 602.

[0135] In some embodiments, the transmitter 601 sends prediction configuration information to the terminal device, the prediction configuration information including configuration information for instructing the terminal device to perform AI prediction, and / or reporting configuration information for instructing AI prediction related information; and the receiver 602 receives reporting information sent by the terminal device according to the prediction configuration information, the reporting information including predicted value information of a cell and / or a beam, and / or prediction information related to a handover target cell.

[0136] In some embodiments, the device 600 further includes a processor (not shown in the figure), which is further used to complete a handover preparation process between the device and a target network device to which the predicted target cell belongs. The transmitter 601 is further used to send mobility configuration information to the terminal device, the mobility configuration information being used to instruct the terminal device to perform handover to the handover target cell.

[0137] The implementation of the transmitter, the receiver and the processor can refer to the embodiment of the second aspect, which is not described repeatedly here.

[0138] The above embodiment of the present application is exemplarily described, but the present application is not limited thereto, and can be appropriately modified on the basis of the above various embodiments. For example, the above various embodiments can be used individually, or one or more of the above various embodiments can be combined.

[0139] It is worth noting that the above only describes the components or modules related to the present application, but the present application is not limited thereto. The above device can further include other components or modules, and the specific content of these components or modules can refer to related technologies. In addition, the above various components or modules can be realized by hardware facilities such as processors, memories, transmitters, receivers, etc., and the present application is not limited thereto.

[0140] According to the embodiment of the present application, the AI model on the terminal device side can perform prediction based on the prediction configuration information of the network device, and report the prediction result to the network device to provide corresponding inference output information for the network device; so that the network device optimizes mobility management based on the prediction result, and improves the mobility robustness of the terminal device.

[0141] Embodiments of the fifth aspect

[0142] Embodiments of the present application also provide a communication system, including a network device and / or a terminal device.

[0143] FIG. 7 is a schematic diagram of a communication system according to an embodiment of the present application. As shown in FIG. 7, the communication system 700 can include a network device 701 and a terminal device 702. FIG. 7 only takes one terminal device and one network device as an example for illustration, but the embodiments of the present application are not limited thereto.

[0144] In some embodiments, the terminal device 702 is configured to perform the method according to the embodiments of the first aspect. Since the method has been described in detail in the embodiments of the first aspect, the content is incorporated herein and will not be repeated.

[0145] In some embodiments, the network device 701 is configured to perform the method according to the embodiments of the second aspect. Since the method has been described in detail in the embodiments of the second aspect, the content is incorporated herein and will not be repeated.

[0146] Embodiments of the present application also provide a network device, which can be a base station or a CU or a DU or a LMF device, but the present application is not limited thereto, and can also be other network devices.

[0147] FIG. 8 is a schematic diagram of a network device according to an embodiment of the present application. As shown in FIG. 8, the network device 800 can include a processor 801 and a memory 802, and the memory 802 is coupled to the processor 801. The memory 802 can store various data, and further store a program 803 for information processing and execute the program under the control of the processor 801.

[0148] In some embodiments, the functions of the apparatus 600 according to the embodiments of the fourth aspect can be integrated into the processor 801, wherein the processor 801 can be configured to execute the program to realize the method according to the embodiments of the second aspect, and the content is incorporated herein and will not be repeated here.

[0149] In other embodiments, the apparatus 600 according to the embodiments of the fourth aspect can be configured separately from the processor 801, for example, the apparatus 600 according to the embodiments of the fourth aspect can be configured as a chip connected to the processor 801, and the functions of the apparatus 600 according to the embodiments of the fourth aspect are realized through the control of the processor 801.

[0150] In addition, as shown in FIG. 8, the network device 800 can further include a transceiver 804 and an antenna 805. The functions of these components are similar to those in the prior art, and thus will not be described here. It should be noted that the network device 800 does not necessarily include all the components shown in FIG. 8; in addition, the network device 800 can include components that are not shown in FIG. 8, which can be referred to the prior art.

[0151] Embodiments of the present application further provide a terminal device.

[0152] FIG. 9 is a schematic diagram of a terminal device according to an embodiment. As shown in FIG. 9, the terminal device 900 can include a processor 910 and a memory 920. The memory 920 stores data and programs and is coupled to the processor 910. It should be noted that this diagram is exemplary; other types of structures can also be used to supplement or replace this structure to implement telecommunications functions or other functions.

[0153] In some embodiments, the functions of the apparatus 500 of the embodiments of the third aspect can be integrated into the processor 910, where, for example, the processor 910 can be configured to execute programs to implement the method as in the embodiments of the first aspect.

[0154] As shown in FIG. 9, the terminal device 900 can further include a communication module 930, an input unit 940, a display 950, and a power supply 960. The functions of these components are similar to those in the prior art, and thus will not be described here. It should be noted that the terminal device 900 does not necessarily include all the components shown in FIG. 9; in addition, the terminal device 900 can include components that are not shown in FIG. 9, which can be referred to the prior art.

[0155] In other embodiments, the apparatus 500 of the embodiments of the third aspect can be configured separately from the processor 910, for example, the apparatus 500 of the embodiments of the third aspect can be configured as a chip connected to the processor 910, and the functions of the apparatus 500 of the embodiments of the third aspect are implemented through the control of the processor 910.

[0156] Embodiments of the present application further provide a computer program, which, when executed in a terminal device, causes the terminal device to perform the method according to the embodiments of the first aspect.

[0157] Embodiments of the present application further provide a storage medium storing a computer program, which causes a terminal device to perform the method according to the embodiments of the first aspect.

[0158] Embodiments of the present application further provide a computer program, which, when executed in a network device, causes the network device to perform the method according to the embodiments of the second aspect.

[0159] The embodiments of the present application further provide a storage medium storing a computer program, wherein the computer program causes the network device to perform the method described in the embodiments of the second aspect.

[0160] The apparatus and method described above can be implemented by hardware, or by hardware in combination with software. The present application relates to a computer readable program, which, when executed by a logic component, causes the logic component to implement the apparatus or constituent components described above, or causes the logic component to implement the various methods or steps described above. The present application also relates to a storage medium for storing the above program, such as a hard disk, a magnetic disk, an optical disk, a DVD, a flash memory, and the like.

[0161] The method / apparatus described in combination with the embodiments of the present application can be directly embodied as hardware, a software module executed by a processor, or a combination of the two. For example, one or more of the functional block diagrams shown in the figures and / or a combination of one or more of the functional block diagrams can correspond to each software module of the computer program flow, or to each hardware module. The software modules can correspond to each step shown in the figures, respectively. These hardware modules can be implemented by, for example, fixing the software modules with a field programmable gate array (FPGA).

[0162] The software modules can be located in a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a mobile disk, a CD-ROM, or any other form of storage medium known in the art. A storage medium can be coupled to the processor, so that the processor can read information from the storage medium, and write information to the storage medium; or the storage medium can be an integral part of the processor. The processor and the storage medium can be located in an ASIC. The software modules can be stored in the memory of the mobile terminal, or in a memory card that can be inserted into the mobile terminal. For example, if the device (such as a mobile terminal) uses a MEGA-SIM card or a large-capacity flash memory device, the software modules can be stored in the MEGA-SIM card or the large-capacity flash memory device.

[0163] One or more of the functional blocks described in the figures can be implemented as a general -purpose processor, a Digital Signal Processor (DSP), an Application-Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any appropriate combination of the foregoing, in which case the functions described with respect to the functional blocks can be implemented with either software or hardware, or a combination of the two. One or more of the functional blocks described in the figures can also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

[0164] The application has been described in relation to particular embodiments, which are intended in all respects to be illustrative rather than restrictive. Those skilled in the art could readily devise variations and modifications of the present application without departing from the scope of the present application. Such variations and modifications are intended to come within the scope of the present application.

Claims

1. An information transceiving apparatus applied to a terminal device, comprising: a receiver configured to receive prediction configuration information transmitted by a network device, the prediction configuration information comprising configuration information for instructing the terminal device to perform AI prediction, and / or reporting configuration information for instructing AI prediction related information; a processor configured to perform AI prediction according to the prediction configuration information, determine prediction value information, and / or prediction information; and / or a transmitter configured to transmit reporting information to the network device according to the prediction configuration information, the reporting information comprising prediction value information of a cell and / or a beam, and / or prediction information related to a handover target cell. The prediction value information comprises at least one of the following information: predicted cell information, predicted measurement result information of a cell, predicted beam information under a cell, and predicted measurement result information of a beam. And / or, the prediction information comprises at least one of the following information: predicted and / or recommended handover target cell information, handover configuration information of a predicted and / or recommended handover target cell, correspondence between prediction value and time of a predicted and / or recommended handover target cell, handover time information of a predicted and / or recommended handover target cell, and camping information of a predicted and / or recommended handover target cell. The prediction configuration information comprises at least one of the following information: measurement configuration information, measurement information for the terminal device; mode configuration information, mode information for instructing the terminal device to perform AI prediction; reporting configuration information, information to be reported by the terminal device; and measurement identification information, the measurement identification information being used to associate at least one measurement configuration information, at least one mode configuration information, and / or at least one reporting configuration information.

2. The apparatus of claim 1, wherein, The measurement configuration information comprises at least one of the following information: measurement object information; first indication information for indicating whether the terminal device needs to perform AI prediction on the measurement object; and reference signal configuration information of the measurement object. The measurement object information comprises at least one of the following information: frequency point information, frequency point information and at least one cell information on the frequency point, and frequency point information and at least one cell information on the frequency point and at least one beam information under the cell. The granularity of the first indication information can be at least one of the following granularities: frequency point granularity, cell granularity, beam granularity, and measurement identification granularity; wherein the measurement identification granularity comprises at least one frequency point information. The mode configuration information comprises at least one of the following information: time information for performing AI prediction; time configuration information / number configuration information for performing AI prediction and measurement; trigger configuration information for falling back to measurement when performing AI prediction; and correlation information for performing AI prediction, the correlation information being used to indicate the correlation between at least one measurement object that needs to perform measurement and at least one measurement object that performs AI prediction based on the at least one measurement object that needs to perform measurement.

3. The apparatus of claim 1, wherein, The reporting configuration information comprises at least one of the following information: first configuration information for indicating prediction value information to be reported; ​ ​ ​ ​ 4. The apparatus of claim 3, wherein, ​ ​ ​ ​ 5. The apparatus of claim 4, wherein, ​ 6. The apparatus of claim 4, wherein, ​ 7. The apparatus of claim 3, wherein, ​ ​ ​ ​ ​ 8. The apparatus of claim 3, wherein, ​ ​ second indication information for indicating whether the prediction information needs to be reported; switch type information related to the prediction information; trigger condition configuration for indicating configuration of triggering the terminal device to report the predicted value and / or the measurement value; third indication information for indicating time range information of the predicted value information and / or the prediction information that needs to be reported; maximum number of reported predicted and / or recommended handover target cells.

9. The apparatus of claim 8, wherein, The first configuration information includes at least one of the following information: number information of the predicted cells that needs to be reported; fourth indication information for indicating whether to report the predicted beam information under the cell; number information of the reported predicted beams; quality threshold information of the reported predicted beams.

10. The apparatus of claim 8, wherein, The second indication information includes at least one independent information element, and each information element is used to indicate whether one or at least two prediction information needs to be reported; or the second indication information includes a bit map, and one bit of the bit map is used to indicate whether one prediction information needs to be reported, or different bit values of the bit map are used to indicate whether a combination of different prediction information needs to be reported.

11. The apparatus of claim 3, wherein, The processor ignores the reference signal configuration information corresponding to the measurement object when performing AI prediction on the measurement object.

12. The apparatus of claim 8, wherein, The reported information includes the predicted value information and / or the prediction information in the time range indicated by the time range information.

13. The apparatus of claim 1, wherein, The receiver is further configured to receive mobility configuration information sent by the network device, the mobility configuration information being used to indicate that the terminal device performs handover to a handover target cell; and the processor performs handover to the handover target cell according to the mobility configuration information.

14. The apparatus of claim 13, wherein, The handover target cell is a cell determined based on the reported predicted value information of the cell, and / or a cell determined based on the prediction information.

15. The apparatus of claim 8, wherein, The reported information further includes measurement value information of the reported cell; and the transmitter determines to send the predicted value information or the predicted value information and the measurement value information according to the trigger condition configuration.

16. An information transceiver apparatus applied to a network device, comprising: a transmitter configured to send prediction configuration information to a terminal device, the prediction configuration information including configuration information for indicating that the terminal device performs AI prediction, and / or reporting configuration information for indicating AI prediction related information; a receiver configured to receive reported information sent by the terminal device according to the prediction configuration information, the reported information including predicted value information of a cell and / or a beam, and / or prediction information related to a handover target cell.

17. The apparatus of claim 16, wherein, The transmitter is further configured to send mobility configuration information to the terminal device, the mobility configuration information being used to indicate that the terminal device performs handover to a handover target cell.

18. The apparatus of claim 16, wherein, The transmitter is further configured to send AI function activation indication information to the terminal device, the AI function activation indication information being used to indicate AI functions or AI models that need to be activated by the terminal device.

19. The apparatus of claim 16, wherein, The predicted value information includes at least one of the following information: predicted cell information, measurement result information of the predicted cell, beam information under the predicted cell, measurement result information of the predicted beam; And / or, the prediction information comprises at least one of the following information: predicted and / or recommended handover target cell information, handover configuration information of the predicted and / or recommended handover target cell, correspondence between predicted values and time of the predicted and / or recommended handover target cell, handover time information of the predicted and / or recommended handover target cell, camping information of the predicted and / or recommended handover target cell.

20. A communication system comprising the information transceiving device of any one of claims 1 to 19.

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