Wireless communication method and related apparatus

Abstract

Embodiments of the present application provide a wireless communication method and related apparatus, the wireless communication method comprising: receiving a first message, the first message being used to indicate a monitoring report configuration; and sending a monitoring report, the monitoring report being used to indicate a number of monitoring reference signal occasions that satisfy a first condition within a monitoring window; the first condition comprising: an optimal beam in a monitoring set indicated by a monitoring result being included in K optimal beams indicated by channel prediction results, the monitoring set comprising the K optimal beams indicated by the channel prediction results and N first beams, the first beams having continuity with a spatial distribution of any one of the K optimal beams indicated by the channel prediction results. Since the monitoring set comprises the K optimal beams indicated by the channel prediction results and the N first beams, the number of beams in the monitoring set is expanded, the spatial dimension of monitoring is increased, effective monitoring of the AI model is achieved, and the accuracy of AI model prediction is enhanced by monitoring whether the performance of the AI model decreases.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless communication, and particularly relates to a wireless communication method and related apparatus. BACKGROUND

[0002] With the development of artificial intelligence technology, in some application scenarios, the function of a terminal can be realized by an artificial intelligence (AI) model. For example, the terminal performs channel prediction by using an AI model. Specifically, the terminal can perform channel measurement based on a first reference signal set to obtain a measurement result, and the measurement result can be used as input of the AI model. The AI model obtains a channel prediction result of a second reference signal set based on the input information.

[0003] The terminal can also perform channel measurement based on a monitoring set to obtain a measurement result, and then compare the measurement result with the channel prediction result of the second reference signal set to monitor the accuracy of the channel prediction result of the second reference signal set.

[0004] The monitoring set is a subset of the second reference signal set. In some cases, the optimal beam (i.e., Top 1 beam) selected by the terminal according to the channel prediction result of the second reference signal set can be different from the optimal beam selected by the terminal based on the measurement result of the monitoring set. This indicates that the optimal beam predicted by the AI model is not the actual optimal beam, and the accuracy of the AI model prediction is not high. SUMMARY

[0005] The present application provides a wireless communication method and related apparatus, aiming to enhance the accuracy of AI model prediction.

[0006] To achieve the above object, the present application provides the following technical solutions:

[0007] In a first aspect, the present application provides a wireless communication method, which can be executed by a terminal, or can be executed by a component (such as a circuit, a chip or a chip system, etc.) configured in the terminal, and can also be realized by a logic module or software which can realize all or part of the terminal function. The present application does not make any limitation in this regard. Hereinafter, the terminal is taken as an example for description.

[0008] The wireless communication method comprises: receiving a first message, the first message being used for indicating a monitoring report configuration, the monitoring report configuration being used for indicating performance monitoring on a channel prediction result; and sending a monitoring report, the monitoring report being used for indicating a number of monitoring reference signal occasions satisfying a first condition within a monitoring window; wherein: the first condition comprises that an optimal beam in a monitoring set indicated by a monitoring result comprises K optimal beams indicated by the channel prediction result, the monitoring result being based on a channel measurement result obtained by the monitoring set at the monitoring reference signal occasion, the monitoring set comprising the K optimal beams indicated by the channel prediction result and N first beams, the first beam having continuity with a spatial distribution of any one of the K optimal beams indicated by the channel prediction result, K and N being positive integers.

[0009] In the above technical solution, the monitoring set comprises the K optimal beams indicated by the channel prediction result and the N first beams, the number of beams in the monitoring set is expanded, the spatial dimension of monitoring is increased, more accurate monitoring of the channel prediction result is achieved, effective monitoring of the AI model is achieved, whether the performance of the AI model decreases or not can be quickly and sensitively monitored, measures can be taken in time, the robustness of the AI model is improved, and the accuracy of prediction of the AI model is enhanced.

[0010] Further, since the first beam has continuity with the spatial distribution of any one of the K optimal beams indicated by the channel prediction result, it is also ensured that the beams expanded to the monitoring set also belong to beams with better channel quality, and the efficiency of monitoring the channel prediction result by the monitoring set is improved.

[0011] In one possible implementation manner, the first beam has continuity with the spatial distribution of any one of the K optimal beams indicated by the channel prediction result comprises that a reference signal transmitted by the first beam has a quasi-co-location (QCL) relationship with a reference signal transmitted by any one of the K optimal beams indicated by the channel prediction result.

[0012] In one possible implementation manner, the determination of N comprises: screening the number of first beams corresponding to the confidence information in a mapping relationship, the mapping relationship comprising a plurality of confidence information and the number of first beams corresponding to each confidence information; and the confidence information being used for indicating a confidence degree of the channel prediction result.

[0013] In one possible implementation manner, the confidence information comprises a difference between a probability that the Kth optimal beam indicated by the channel prediction result is the optimal beam and a probability that the K+1th beam indicated by the channel prediction result is the optimal beam.

[0014] In a possible implementation, the confidence information comprises: a difference between a probability that a first optimal beam indicated by the channel prediction result is the optimal beam and a first probability sum, the first probability sum being a sum of probabilities that a second optimal beam indicated by the channel prediction result is the optimal beam to a probability that a Kth optimal beam indicated by the channel prediction result is the optimal beam.

[0015] In a possible implementation, the confidence information comprises: a KL divergence of a distribution P with respect to a distribution Q, the distribution P being a probability distribution of the multiple beams indicated by the channel prediction result being the optimal beam, the distribution Q being an ideal probability distribution of the multiple beams being the optimal beam.

[0016] In a possible implementation, the mapping relationship is comprised in the first message.

[0017] In a second aspect, a wireless communication method is provided. The method can be performed by a network device, or can be performed by a component (such as a circuit, a chip, or a chip system) configured in the network device, or can be implemented by a logic module or software that can implement all or part of the functions of the network device. The present application does not make any limitation in this regard. Hereinafter, the network device is taken as an example for description.

[0018] The wireless communication method comprises: sending a first message, the first message being used to indicate a monitoring report configuration, the monitoring report configuration being used to indicate performance monitoring on a channel prediction result; and receiving a monitoring report, the monitoring report being used to indicate a number of monitoring reference signal occasions that satisfy a first condition within a monitoring window; wherein: the first condition comprises that an optimal beam in a monitoring set indicated by a monitoring result is included in K optimal beams indicated by the channel prediction result, the monitoring result being a channel measurement result obtained by the monitoring set at the monitoring reference signal occasion, the monitoring set comprising the K optimal beams indicated by the channel prediction result and N first beams, the first beam having continuity with a spatial distribution of any one of the K optimal beams indicated by the channel prediction result, K and N being positive integers.

[0019] In a third aspect, a communication apparatus is provided. The communication apparatus comprises a transceiver module, which is configured to receive a first message, the first message being used to indicate a monitoring report configuration, the monitoring report configuration being used to indicate performance monitoring on a channel prediction result; and send a monitoring report, the monitoring report being used to indicate a number of monitoring reference signal occasions that satisfy a first condition within a monitoring window; wherein: the first condition comprises that an optimal beam in a monitoring set indicated by a monitoring result is included in K optimal beams indicated by the channel prediction result, the monitoring result being a channel measurement result obtained by the monitoring set at the monitoring reference signal occasion, the monitoring set comprising the K optimal beams indicated by the channel prediction result and N first beams, the first beam having continuity with a spatial distribution of any one of the K optimal beams indicated by the channel prediction result, K and N being positive integers.

[0020] In a fourth aspect, the present application provides a communication apparatus, comprising a transceiver, configured to send a first message, wherein the first message is used to indicate a monitoring report configuration, and the monitoring report configuration is used to indicate performance monitoring on a channel prediction result; and receive a monitoring report, wherein the monitoring report is used to indicate a number of monitoring reference signal occasions satisfying a first condition within a monitoring window; wherein the first condition comprises that an optimal beam in a monitoring set indicated by a monitoring result comprises in K optimal beams indicated by the channel prediction result, the monitoring result is based on a channel measurement result obtained by the monitoring set at the monitoring reference signal occasion, the monitoring set comprises the K optimal beams indicated by the channel prediction result and N first beams, the first beam has continuity with a spatial distribution of any one of the K optimal beams indicated by the channel prediction result, and K and N are positive integers.

[0021] In a fifth aspect, the present application provides a communication apparatus, comprising a processor coupled to a memory, configured to execute instructions or data in the memory to implement the method in the first aspect.

[0022] In a possible implementation, the communication apparatus further comprises the memory.

[0023] In a possible implementation, the communication apparatus further comprises a communication interface, and the processor is coupled to the communication interface. In an implementation, the communication interface can be a transceiver, or an input / output interface.

[0024] In another implementation, the communication apparatus is a chip configured in a terminal. When the communication apparatus is the chip configured in the terminal, the communication interface can be the input / output interface.

[0025] In a sixth aspect, the present application provides a communication apparatus, comprising a processor coupled to a memory, configured to execute instructions or data in the memory to implement the method in the second aspect.

[0026] In a possible implementation, the communication apparatus further comprises the memory.

[0027] In a possible implementation, the communication apparatus further comprises a communication interface, and the processor is coupled to the communication interface. In an implementation, the communication interface can be a transceiver, or an input / output interface.

[0028] In another implementation, the communication apparatus is a chip configured in a network device. When the communication apparatus is the chip configured in the network device, the communication interface can be the input / output interface.

[0029] In a seventh aspect, the present application provides a processor, comprising: an input circuit, an output circuit, and a processing circuit. The processing circuit is configured to receive a signal through the input circuit and transmit a signal through the output circuit, so that the processor performs the method in any one of the aspects.

[0030] In a specific implementation process, the processor can be one or more chips, the input circuit can be an input pin, the output circuit can be an output pin, and the processing circuit can be a transistor, a gate circuit, a flip-flop, and various logic circuits, etc. The input signal received by the input circuit can be received and input by, for example but not limited to, a receiver, the signal output by the output circuit can be output to and transmitted by, for example but not limited to, a transmitter, and the input circuit and the output circuit can be the same circuit which is used as the input circuit and the output circuit at different times. The embodiments of the present application do not limit the specific implementation mode of the processor and various circuits.

[0031] In an eighth aspect, the present application provides a computer program product, comprising: a computer program (also referred to as code or instructions), which, when executed, causes a computer to perform the method in any one of the aspects.

[0032] In a ninth aspect, a computer readable storage medium is provided, which stores a computer program (also referred to as code or instructions) which, when executed on a computer, causes the computer to perform the method in any one of the aspects.

[0033] In a tenth aspect, the present application provides a chip system, comprising one or more processors for calling and executing instructions stored in a memory, so that the method in each of the aspects or any possible implementation mode of the aspects is executed. The chip system can be composed of a chip, or can include a chip and other discrete devices. The chip system can include an input circuit or interface for transmitting information or data, and an output circuit or interface for receiving information or data.

[0034] In an eleventh aspect, a communication system is provided, comprising the terminal and the network device as described above.

[0035] In one possible implementation mode, the communication system can further include other devices in communication with the terminal and / or the network device.

[0036] The second aspect to the eleventh aspect provide the technical effects of the solutions, which can be referred to the content of the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 FIG. 1 shows a schematic diagram of an architecture of a communication system provided by an embodiment of the present application;

[0038] Figure 2 A structural schematic diagram of a network device provided by an embodiment of the present application is provided.

[0039] Figure 3 and Figure 4 A structural schematic diagram of two use case examples of spatial beam prediction provided by an embodiment of the present application is provided.

[0040] Figure 5 and Figure 6 A structural schematic diagram of two use case examples of time domain beam prediction provided by an embodiment of the present application is provided.

[0041] Figure 7 A flowchart of a wireless communication method provided by an embodiment of the present application is provided.

[0042] Figure 8 A flowchart of constructing a monitoring set provided by an embodiment of the present application is provided.

[0043] Figure 9 A flowchart of sorting the probability distribution of beams in SetA provided by an embodiment of the present application is provided.

[0044] Figure 10 A structural example diagram of another communication device disclosed by an embodiment of the present application is provided.

[0045] Figure 11 A structural example diagram of another communication device disclosed by an embodiment of the present application is provided. DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. The terms used in the following embodiments are only for the purpose of describing the specific embodiments and are not intended to be limiting to the present application. As used in the specification and the appended claims of the present application, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that “one or more” in the embodiments of the present application means one, two, or more than two; “and / or” describes the association relationship of the associated objects, which means that there can be three kinds of relationships; for example, A and / or B can mean that A exists alone, A and B exist together, and B exists alone, where A and B can be singular or plural. The character “ / ” generally represents an “or” relationship between the associated objects.

[0047] Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the application. The appearances of the phrase "in one embodiment" or "in some embodiments" in various places in the specification are not necessarily all referring to the same embodiment, however, but can refer to one or more but not all embodiments. The terms "including," "comprising," "featuring," and variations thereof are meant to encompass the items listed thereafter and equivalents thereof as well as additional items. Unless otherwise noted, the terms "including" and "comprising" are used in an inclusive sense, and should be interpreted as meaning "including, but not limited to."

[0048] The plurality of embodiments related in the present application refers to greater than or equal to two. It should be noted that in the description of the embodiments of the present application, the terms "first", "second", etc. are only used for the purpose of distinguishing the description, and cannot be understood as indicating or implying relative importance, nor can it be understood as indicating or implying order.

[0049] The technical solutions provided by the embodiments of the present application can be applied to a communication system, which can include but is not limited to the following systems, for example: a second generation (2G) communication system, a third generation (3G) communication system, a long term evolution (LTE) system, a universal mobile communication system (UMTS), a worldwide interoperability for microwave access (WiMAX) communication system, a 5th generation (5G) system or new radio (NR), a 5.5G system or a 6th generation (6G) system and future mobile communication systems, vehicle to X (V2X); V2X can include vehicle to network (V2N), vehicle to vehicle (V2V), vehicle to infrastructure (V2I), vehicle to pedestrian (V2P), etc., long term evolution-vehicle (LTE-V), Internet of Vehicles, machine type communication (MTC), Internet of Things (IOT), ambient Internet of Things (AIOT), long term evolution-machine (LTE-M), machine to machine (M2M), etc.

[0050] Scenarios to which the communication system is applicable can include: terrestrial cellular communication, non-terrestrial network (NTN), satellite communication, high altitude platform station (HAPS) communication, vehicle to everything (V2X) communication, integrated access and backhaul (IAB) communication, reconfigurable intelligent surface (RIS) communication, etc.

[0051] For example,Figure 1 A schematic diagram of an architecture of a communication system is shown.

[0052] As shown in Figure 1 The communication system includes a first device 100 and a second device 200.

[0053] The first device 100 can be a device for providing network communication function on the network side, and is also called network device or network element in some cases. The network device can be a base station (including a functional unit of the base station or a combination of functional units of the base station) or a core network unit. The core network unit can be a functional unit in the core network, including but not limited to an access and mobility management function (AMF) unit or a session management function (SMF) unit.

[0054] In the embodiments of the present application, the base station can be any device with wireless transceiving function, including but not limited to: an evolved Node B (eNB or e-NodeB) in long term evolution (LTE), a base station (gNodeB or gNB) or a transmission receiving point (TRP) in new radio (NR), a base station in subsequent evolution of 3GPP, an access node in a Wi-Fi system, a wireless relay node, a wireless backhaul node, etc. The base station can be: a macro base station, a micro base station, a pico base station, a small station, a relay station, or a balloon station, etc. The base station can include one or more co-sited or non-co-sited transmission reception points (TRPs). The base station can also be a wireless controller, a centralized unit (CU), and / or a distributed unit (DU) in a cloud radio access network (CRAN) scenario. The base station can communicate with the terminal 200, or communicate with the terminal 200 through a relay station. The terminal can communicate with multiple base stations of different technologies, for example, the terminal can communicate with a base station supporting an LTE network, and can also communicate with a base station supporting a 5G network, and can also communicate with a base station supporting an LTE network and a base station supporting a 5G network in dual connectivity.

[0055] In actual application, the network device, as an access network device, can be cooperated by multiple network devices to assist the terminal to implement wireless access, and different network devices respectively implement part of functions of a base station. For example, the network device can be a central unit (CU), a distributed unit (DU), a CU-control plane (CP), a CU-user plane (UP), or a radio unit (RU), etc. The CU and the DU can be separately arranged, or can be included in the same network element, such as a baseband unit (BBU). The RU can be included in a radio frequency device or a radio frequency unit, such as a remote radio unit (RRU), an active antenna processing unit (AAU), or a remote radio head (RRH).

[0056] In different systems, the CU (or CU-CP and CU-UP), DU or RU can also have different names, but those skilled in the art can understand their meanings. For example, in an ORAN system, the CU can also be referred to as an O-CU (open CU), the DU can also be referred to as an O-DU, the CU-CP can also be referred to as an O-CU-CP, the CU-UP can also be referred to as an O-CU-UP, and the RU can also be referred to as an O-RU. Any one of the CU (or CU-CP, CU-UP), DU and RU in this application can be implemented by a software module, a hardware module, or a combination of a software module and a hardware module. The CU (or CU-CP and CU-UP), DU and RU can implement different protocol layer functions.

[0057] Figure 2 FIG. 1 is a schematic diagram of a structure of an access network device. As an implementation example, as shown in FIG. 1, the network device can include a central unit (CU) and a distributed unit (DU). The CU can be connected to the DU through an optical fiber or a cable, and the CU and the DU can be connected through an air interface to a terminal device (for example, a user equipment (UE)). Figure 2As shown, the access network device can include at least one CU and at least one DU. This design can be referred to as CU and DU separation. One CU can be connected with one or more DUs. The CU and the DU can be divided according to protocol layers of the wireless network: for example, functions of a PDCP layer and above protocol layers (for example, an RRC layer and an SDAP layer, etc.) are arranged at the CU, and functions of protocol layers below the PDCP layer (for example, an RLC layer, a media access control (MAC) layer, and a PHY layer, etc.) are arranged at the DU; for another example, functions of the PDCP layer and above protocol layers are arranged at the CU, and functions of the PDCP layer and below protocol layers are arranged at the DU, without limitation. When the CU includes a CU-CP and a CU-UP, the CU-CP is configured to implement control plane functions of the CU, and the CU-UP is configured to implement user plane functions of the CU. For example, the CU is configured to implement functions of the PDCP layer, the RRC layer, and the SDAP layer, the CU-CP is configured to implement functions of the RRC layer and control plane functions of the PDCP layer, and the CU-UP is configured to implement functions of the SDAP layer and user plane functions of the PDCP layer. The name of the CU and the DU is not limited in the present application. The above-mentioned division of processing functions of the CU and the DU according to protocol layers is only an example, and the division can also be performed in other manners.

[0058] The CU can be connected with the core network. Optionally, the CU can have part of functions of the core network.

[0059] Further, part of functions of the DU can be separately arranged. For example, Figure 2As shown, the part of the functions can be implemented by a radio unit (RU). The RU can have radio frequency functions. The name of the RU is not limited in the present application. The DU and the RU can be split or separated at the PHY layer. For example, the DU can implement high layer functions in the PHY layer, and the RU can implement low layer functions in the PHY layer or implement the low layer functions and the radio frequency functions. The high layer functions in the PHY layer include functions closer to the MAC layer, and the low layer functions in the PHY layer include functions closer to the radio frequency. For example, the high layer functions of the PHY layer include one or more of the following: forward error correction (FEC) encoding / decoding, scrambling, or modulation / demodulation. The low layer functions of the PHY layer include one or more of the following: fast Fourier transform (FFT) / inverse fast Fourier transform (IFFT), beamforming, or extraction and filtering of a physical random access channel (PRACH), and the like. The RU can communicate radio frequency signals with the terminal device through an air interface. The pre-coding function of the PHY layer code can be located in the DU or in the RU. The split manner between the DU and the RU can be various possible manners and is not limited. There is an interface between the DU and the RU. For example, according to different split manners, the interface between the DU and the RU can be a common public radio interface (CPRI) interface or an enhanced common public radio interface (eCPRI) interface.

[0060] Optionally, any of the above CU, CU-CP, CU-UP, DU, and RU can be a software module, a hardware structure, or a software module plus a hardware structure, and is not limited. The forms of existence of different entities can be the same or different. For example, the CU, the CU-CP, the CU-UP, and the DU are software modules, and the RU is a hardware structure. For the sake of brevity of description, all possible combination forms are not listed one by one here. The modules and the methods performed thereby are also within the protection scope of the embodiments of the present application. For example, when the method of the embodiments of the present application is performed by an access network device, the method can be specifically performed by at least one of the CU, the CU-CP, the CU-UP, the DU, or the RU.

[0061] The second device 200 can be a device of an access network and can generally be a terminal.

[0062] In embodiments of the present application, the terminal can be various forms, for example, a mobile phone, a tablet computer (Pad), a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal in industrial control, a vehicle-mounted terminal device, a wireless terminal in self driving, a wireless terminal in remote medical, a wireless terminal in smart grid, a wireless terminal in transportation safety, a wireless terminal in smart city, a wireless terminal in smart home, a wearable terminal device, and the like. The terminal can also be referred to as a terminal device, a user equipment (UE), an access terminal device, a vehicle-mounted terminal, an industrial control terminal, a UE unit, a UE station, a mobile station, a mobile station, a remote station, a remote terminal device, a mobile device, a UE terminal device, a wireless communication device, a UE agent, or a UE apparatus, and the like. The terminal can also be a fixed terminal or a mobile terminal.

[0063] In some embodiments, the communication system can further include other devices in communication with the first device and / or the second device, which are not limited in the present application.

[0064] For ease of understanding, the concepts involved in the present application are first described below.

[0065] 1. Spatial domain beam prediction.

[0066] Spatial domain beam prediction refers to prediction based on spatial dimensions. The terminal can use an artificial intelligence (AI) model to perform spatial domain beam prediction. For example, the spatial domain beam prediction is that the terminal predicts the measurement result of a second reference signal set (referred to as Set 2 or Set A) based on the measurement result of a first reference signal set (referred to as Set 1 or Set B). The reference signals in the first reference signal set and the second reference signal set can include channel state information reference signals (CSI-RS), synchronization signal blocks (SSB), and the like.

[0067] Different reference signals usually correspond to different beams. Optionally, the terminal predicts the signal quality (e.g., the reference signal received power (RSRP), the signal to interference plus noise ratio (SINR), etc.) of the M beams, or predicts the best beam among the M beams, or predicts the best K beams among the M beams, K being an integer greater than 1, based on the signal quality of the L beams using an AI model.

[0068] Figure 3 In one use case of the spatial domain beam prediction shown, the first set of reference signals is a subset of the second set of reference signals, i.e., the first set of reference signals contains fewer reference signals L than the second set of reference signals contains M.

[0069] Figure 4 In another use case of the spatial domain beam prediction shown, the reference signals in the first set of reference signals and the reference signals in the second set of reference signals can belong to different reference signal types, e.g., the beams corresponding to Set 1 are usually wide beams, and the beams corresponding to Set 2 are usually narrow beams. Optionally, to ensure the accuracy of the prediction, the narrow beams corresponding to Set 2 are usually located within the coverage of the wide beams corresponding to Set 1.

[0070] 2. Time domain beam prediction.

[0071] The time domain beam prediction refers to the prediction based on the time dimension. The terminal can also use an artificial intelligence (AI) model to perform the time domain beam prediction. For example, the time domain beam prediction is that the terminal predicts the measurement results of a second set of reference signals (referred to as Set 2 or Set A) in future time based on the measurement results of a first set of reference signals (referred to as Set 1 or Set B) in historical time.

[0072] In one use case, the first set of reference signals and the second set of reference signals can be the same set of reference signals, or the first set of reference signals and the second set of reference signals can be different sets of reference signals, e.g., the first set of reference signals is a subset of the second set of reference signals.

[0073] For example, Figure 5As shown, the terminal predicts, based on the measurement results of the signal quality of the first reference signal set at T1 historical time instants, the signal quality of the beams of the second reference signal set at T2 future time instants, or the optimal beam at each of the T2 time instants, or the best K beams at each of the T2 time instants, T1 and T2 being integers greater than 1, T1 can be greater than, less than or equal to T2; K is an integer greater than 1.

[0074] In another use case, the reference signals in the first reference signal set and the second reference signal set can belong to different reference signal types, for example: the beams corresponding to Set 1 are usually wide beams, and the beams corresponding to Set 2 are usually narrow beams. Optionally, the narrow beams corresponding to Set 2 are usually located in the coverage range of the wide beams corresponding to Set 1.

[0075] As shown, Figure 6 As shown, the terminal predicts, based on the measurement results of the signal quality of the first reference signal set at T1 historical time instants, the signal quality of the beams of the second reference signal set at T2 future time instants, or the optimal beam at each of the T2 time instants, or the best K beams at each of the T2 time instants, T1 and T2 being integers greater than 1, T1 can be greater than, less than or equal to T2; K is an integer greater than 1.

[0076] 3. Quasi co-location (QCL): Its main role is to allow the terminal to infer the channel characteristics of another reference signal through a known reference signal. If two reference signals have a QCL relationship, it means that they have similar propagation characteristics in space.

[0077] Among them, the related introduction of spatial beam prediction, time domain beam prediction and quasi co-location is only for the convenience of understanding the technical solutions of the present application, and does not constitute any limitation on the present application.

[0078] With the development of artificial intelligence technology, in some application scenarios, the functions of the terminal can be realized by the AI model. For example, the terminal uses the AI model to perform channel prediction. Specifically, the network device configures the terminal with a first reference signal set and a second reference signal set (i.e. Set A), the terminal can measure the first reference signal set to perform channel measurement, and obtain measurement results. The measurement results can be used as the input of the AI model, and the AI model obtains the channel prediction results of Set A based on the input information.

[0079] The terminal can also use a third reference signal set (or monitoring set) to monitor the accuracy of the prediction result of Set A. The terminal can perform channel measurement based on the monitoring set to obtain a channel measurement result, and can compare the channel measurement result with the channel prediction result of Set A as a measured label to monitor the accuracy of the channel prediction result of Set A. Set A and the monitoring set usually have a corresponding relationship, for example, the monitoring set is a subset of Set A or the monitoring set is a full set of Set A.

[0080] When the monitoring set is a subset of Set A, in some cases, the optimal beam (Top 1 beam) selected by the terminal according to the prediction result of Set A is not the same as the optimal beam selected by the terminal based on the measurement result of the monitoring set. Thus, it is indicated that the optimal beam predicted by the AI model is not the actual optimal beam, and the accuracy of the AI model prediction is not high.

[0081] To this end, the embodiments of the present application provide a wireless communication method, which can enhance the accuracy of AI model prediction.

[0082] Figure 7 A wireless communication method provided by the embodiments of the present application is shown, which can be applied to a communication system including a network device and a terminal. The description of the network device and the terminal can be referred to the foregoing content, and will not be repeated here.

[0083] As shown in Figure 7 The wireless communication method provided by the embodiments of the present application includes:

[0084] S701, the network device sends a first message to the terminal, and correspondingly, the terminal receives the first message.

[0085] The first message is used to indicate a monitoring report configuration, and the monitoring report configuration is used to indicate performance monitoring on a channel prediction result.

[0086] The channel prediction result is a channel prediction result obtained by the terminal based on the prediction report configuration, that is, the terminal can perform channel measurement based on a first reference signal set to obtain a measurement result, and the terminal invokes an AI model to obtain a channel prediction result of Set A based on the measurement result.

[0087] The prediction report configuration can include, for example, a measurement resource, i.e., a set of reference signals (or referred to as a set of beams) for beam prediction, a report content, a report time, and the like. The beam prediction can include spatial domain beam prediction and / or time domain beam prediction. The set of reference signals can include a first set of reference signals for beam measurement and a Set A for beam prediction. The report content can include a channel prediction result of channel prediction performed by the terminal, such as predicting K optimal beams in the Set A based on signal quality. The report time can include periodicity, semi-persistent, or aperiodicity.

[0088] The spatial domain beam prediction, the time domain beam prediction, the first set of reference signals, and the Set A can refer to the foregoing description, and will not be described here.

[0089] In some embodiments, the first message is a monitoring report configuration for the network device and the terminal to evaluate the AI model prediction scenario, so that the signaling between the network device and the terminal can be saved. The first message is referred to as a monitoring report configuration.

[0090] Optionally, the first message indicating the monitoring report configuration can include the first message indicating the report content, the report time, and the like.

[0091] The report content or the reporting quantity is used to indicate the content that needs to be fed back by the terminal through the monitoring report, such as that the monitoring report carries Np, Np is used to indicate the number of samples that meet the prediction accuracy condition in the monitoring window, Set A and a monitoring set are a pair of samples, and the number of samples that meet the prediction accuracy condition is the number of pairs of samples of Set A and the monitoring set that meet the prediction accuracy condition.

[0092] It can be understood that the monitoring window can include one or more monitoring reference signal occasions, and in one monitoring reference signal occasion, the terminal performs channel measurement using the monitoring set to obtain a channel measurement result, and then compares the channel measurement result with a channel prediction result of Set A to monitor the accuracy of the channel prediction result of Set A. Therefore, Np is used to indicate the number of samples that meet the prediction accuracy condition in the monitoring window, and is also used to indicate the number of monitoring reference signal occasions that meet the prediction accuracy condition in the monitoring window.

[0093] Optionally, the duration of the monitoring window (monitoringWindow) and / or the number of monitoring reference signal occasions included in the monitoring window can be included in the first message or other messages and configured by the network device to the terminal. Alternatively, the terminal can also decide the duration of the monitoring window (monitoringWindow) and / or the number of monitoring reference signal occasions included in the monitoring window.

[0094] The prediction accuracy condition, also referred to as a first condition, can include that CRI_measured_best exists in a Top K beam set predicted by the AI model, wherein:

[0095] CRI_measured_best refers to an optimal beam in a monitoring set indicated by a channel measurement result obtained by the terminal based on monitoring set channel measurement at a monitoring reference signal occasion. The channel measurement result obtained by the monitoring set channel measurement at the monitoring reference signal occasion can be referred to as a monitoring result.

[0096] The Top K beam set includes K optimal beams indicated by the channel prediction result, that is, K optimal beams in Set A indicated by the channel prediction result.

[0097] The reporting content can also include content other than Np. For details, refer to related protocol content, which will not be described here.

[0098] The reporting time can also be referred to as a time domain configuration, which is used to indicate the time at which the terminal reports the monitoring report. Alternatively, the reporting time can also not be included in the first message.

[0099] Alternatively, the first message indicating the monitoring report configuration can also include that the first message indicates a prediction report configuration associated with the monitoring report configuration. For example, the first message includes an identifier (CSI-ResourceConfigId) of the prediction report configuration, so that the monitoring report configuration is associated with the prediction report configuration indicated by the identifier.

[0100] As described above, the prediction report configuration includes measurement resources, that is, a first reference signal set for beam measurement and Set A for beam prediction. The first message indicating the monitoring report configuration associated prediction report configuration, so that the terminal can determine the resources used for channel measurement based on the monitoring set based on the measurement resources in the prediction report configuration associated with the monitoring report configuration, such as the index of the beam in the monitoring set, the time-frequency domain resources, and the like.

[0101] Alternatively, the first message indicating the monitoring report configuration can also include that the first message indicates a report size (reportSize), that is, the value of K, which is used to indicate K optimal beams in Set A predicted by the AI model. Alternatively, the first message can also indicate that the K optimal beams in Set A predicted by the AI model are used to construct the monitoring set for channel measurement.

[0102] Alternatively, the first message can also be used to indicate that the terminal feeds back a monitoring report obtained by performance monitoring on the channel prediction result. The monitoring report is a CSI (channel state information) report.

[0103] In some embodiments, the first message and the monitoring report configuration in the predicted scenario of the evaluation AI model are two messages independent of each other, and the first message belongs to the added message and is also applied to the network device and the terminal to evaluate the predicted scenario of the evaluation AI model, so as to enhance the flexibility of the network device configuration.

[0104] Optionally, the first message indicating the monitoring report configuration can include: the first message indicating the report content, the report time, and optionally, the first message indicating the prediction report configuration associated with the monitoring report configuration, and optionally, the first message indicating the report size (reportSize).

[0105] The report content, the report time, the first message indicating the prediction report configuration associated with the monitoring report configuration, and the first message indicating the report size are described above and will not be repeated here.

[0106] Further optionally, in order to reduce the content carried by the first message, in the scenario that the first message and the monitoring report configuration in the predicted scenario of the evaluation AI model are two messages independent of each other, the content included in the monitoring report configuration in the predicted scenario of the evaluation AI model can not be included in the first message.

[0107] For example, in the case that one or more of the report content, the report time, the prediction report configuration associated with the monitoring report configuration, and the report size is included in the monitoring report configuration in the predicted scenario of the evaluation AI model, the first message does not include the content included in the monitoring report configuration in the predicted scenario of the evaluation AI model, and only includes the content not included in the monitoring report configuration in the predicted scenario of the evaluation AI model.

[0108] Further optionally, the first message indicating the monitoring report configuration can further include: the first message indicating a parameter, such as a dynamic monitoring-enabled, which is used to activate the method provided in the present application, i.e., to perform performance monitoring on the channel prediction result and send the prediction report by using the method provided in the present application.

[0109] For example, the first message can include a radio resource control reconfiguration (RRC signaling for short). That is, the network device sends the RRC signaling, and the RRC signaling is used to instruct the terminal to perform performance monitoring on the channel prediction result.

[0110] For another example, the first message can comprise a medium access control control element (MAC CE). That is, the network device sends the MAC CE, which is used to instruct the terminal to perform performance monitoring on the channel prediction result.

[0111] S702, the terminal sends a monitoring report to the network device, and correspondingly, the network device receives the monitoring report.

[0112] The monitoring report is used to indicate the number of monitoring reference signal occasions that satisfy the first condition in the monitoring window.

[0113] The first condition is as described above, including: the optimal beam in the monitoring set indicated by the monitoring result is included in the K optimal beams indicated by the channel prediction result, the monitoring result is based on the channel measurement result obtained by the monitoring set at the monitoring reference signal occasion; the monitoring set comprises the K optimal beams indicated by the channel prediction result and N first beams, the first beam has continuity with the spatial distribution of any beam in the K optimal beams indicated by the channel prediction result, and K and N are positive integers.

[0114] In some embodiments, after the network device sends the first message, it can also transmit reference signals to the terminal in the beam directions included in the beam set Set A at the monitoring reference signal occasion, and the terminal can obtain the monitoring result of the monitoring reference signal occasion based on the reference signals transmitted by the network device in the beam directions included in Set A.

[0115] The monitoring result can indicate the signal quality of the reference signal in each beam direction included in the monitoring set, such as the RSRP of the reference signal in each beam direction included in the monitoring set.

[0116] Optionally, the monitoring result can also indicate the optimal beam in the monitoring set. For example, the terminal measures the RSRP of the reference signal in each beam direction included in the monitoring set, and takes the beam in the monitoring set corresponding to the maximum value of the RSRP of the reference signal as the optimal beam in the monitoring set. That is, the reference signal transmitted by the optimal beam in the monitoring set has the maximum RSRP measured by the terminal.

[0117] In the embodiments of the present application, the monitoring set comprises the K optimal beams indicated by the channel prediction result and the N first beams, which expands the number of beams in the monitoring set, increases the spatial dimension of the monitoring, and realizes more accurate monitoring of the channel prediction result, effective monitoring of the AI model, and through fast and sensitive monitoring of whether the performance of the AI model decreases, measures can be taken in time to improve the robustness of the AI model and enhance the accuracy of the AI model prediction.

[0118] And, since the first beam has continuity with the spatial distribution of any one of the K optimal beams indicated by the channel prediction result, it is also ensured that the beams expanded to the monitoring set also belong to beams with better channel quality, improving the efficiency of monitoring the channel prediction result by the monitoring set.

[0119] In some embodiments, the terminal can obtain the monitoring result of the monitoring reference signal occasion based on the reference signal transmitted by the network device in the beam direction included in Set A in the following manner:

[0120] Implementation 1. At the monitoring reference signal occasion, the network device transmits a reference signal to the terminal in the beam direction included in Set A; the terminal obtains the index and time-frequency domain resource of the beam in the monitoring set based on the prediction report configuration associated with the monitoring report configuration indicated by the first message; the terminal measures the signal quality (such as RSRP) of the reference signal in each beam direction included in the monitoring set based on the index and time-frequency domain resource of the beam in the monitoring set; and the terminal can also obtain the optimal beam in the monitoring set based on the signal quality of the reference signal in each beam direction included in the monitoring set.

[0121] Implementation 2. The terminal can send the beam (such as the index of the beam) included in the monitoring set to the network device; at the monitoring reference signal occasion, the network device transmits a reference signal to the terminal in the beam direction included in the monitoring set; the terminal obtains the index and time-frequency domain resource of the beam in the monitoring set based on the prediction report configuration associated with the monitoring report configuration indicated by the first message; the terminal measures the signal quality (such as RSRP) of the reference signal in each beam direction included in the monitoring set based on the index and time-frequency domain resource of the beam in the monitoring set; and the terminal can also obtain the optimal beam in the monitoring set based on the signal quality of the reference signal in each beam direction included in the monitoring set.

[0122] In some embodiments, the terminal can also construct the monitoring set.

[0123] For example, after the terminal obtains the channel prediction result of Set A, such as the K optimal beams in Set A, the terminal can also construct a monitoring set, which, as described above, includes the K optimal beams (referred to as Top-K beams) in Set A and the N first beams.

[0124] Figure 8 A flowchart for constructing the monitoring set by the terminal is shown.

[0125] As shown in Figure 8 the method for constructing the monitoring set includes:

[0126] S801. The terminal obtains the channel prediction result of Set A output by the AI model.

[0127] S802. Based on the probability distribution of beams in Set A indicated by the channel prediction results, obtain the probability ranking of the beams.

[0128] Optionally, the channel prediction results of Set A can be used to indicate the probability distribution of beams in Set A, which includes the probability that each beam in Set A is predicted as the optimal beam by the AI ​​model.

[0129] The Top-K beams predicted by the AI ​​model are the top K beams ranked according to the probability that the AI ​​model predicts them as the optimal beams.

[0130] For example, Figure 9 This demonstrates how the terminal obtains the probability that the beams in Set A, sorted by probability, are the optimal beams.

[0131] like Figure 9 As shown in (a), the terminal uses the measurement results of the first reference signal set as input to the AI ​​model. Based on the measurement results of the first reference signal set, the AI ​​model predicts the channel prediction result for Set A. Optionally, the channel prediction result for Set A may include the probability distribution of beams in Set A, which includes the probability that a beam in Set A is the optimal beam in Set A.

[0132] Taking the channel prediction result of Set A, which includes the RSRP of the reference signal in each beam direction contained in Set A, as an example, the optimal beam in Set A is the beam in Set A corresponding to the maximum value of the RSRP of the reference signal. That is, the reference signal transmitted by the optimal beam in Set A has the maximum RSRP measured by the terminal.

[0133] Figure 9 In example (b), the probability distribution of beams in Set A is shown. In this example, the beams in Set A include 6 beams with indices #1 to #6, and each beam has a probability of being the optimal beam of any value in the interval [0,1].

[0134] Depend on Figure 9 As shown in (b): the probability of beam #1 being the optimal beam is 0.15, the probability of beam #2 being the optimal beam is 0.2, the probability of beam #3 being the optimal beam is 0.5, the probability of beam #4 being the optimal beam is 0.8, the probability of beam #5 being the optimal beam is 0.03, and the probability of beam #6 being the optimal beam is 0.01.

[0135] The six beams in Set A, sorted by probability, are as follows: Figure 9 As shown in (c), the beams are: beam #4, beam #3, beam #2, beam #1, beam #5 and beam #6.

[0136] S803, obtaining confidence information based on the probability ranking of the beams in Set A.

[0137] In some embodiments, the terminal can obtain the confidence information in the following manner:

[0138] Implementation 1. The confidence information comprises the difference between the probability that the Kth optimal beam indicated by the channel prediction result is the optimal beam and the probability that the K+1th beam indicated by the channel prediction result is the optimal beam.

[0139] Suppose K is 4, and K+1 is 5, in the example shown in (c) of Figure 9 the confidence information is 0.15-0.03=0.12.

[0140] In this implementation, the greater the confidence information value, the more clear the probability boundary of the Top K beams, and the higher the confidence level of the channel prediction result of Set A, and vice versa.

[0141] Implementation 2. The confidence information comprises the difference between the probability that the first optimal beam indicated by the channel prediction result is the optimal beam and the sum of the first probability and the confidence information, and the first probability sum is the sum of the probability that the second optimal beam indicated by the channel prediction result is the optimal beam to the probability that the Kth optimal beam is the optimal beam.

[0142] Suppose K is 4, in the example shown in (c) of Figure 9 the confidence information is 0.8-0.85=-0.05.

[0143] In the present implementation, the confidence information being a negative value or a value close to 0 indicates that the Top 1 advantage indicated by the channel prediction result is very weak, and the difference with the following several beams is small, and the confidence degree of the channel prediction result of Set A is low; on the contrary, the confidence information being a larger value indicates that the Top 1 advantage indicated by the channel prediction result is very significant, and the confidence degree of the channel prediction result of Set A is high.

[0144] In the present implementation, the confidence information includes a KL divergence of distribution P with respect to distribution Q, that is:

[0145] Formula 1

[0146] In Formula 1, distribution P is a probability distribution of the multiple beams in Set A being the optimal beam indicated by the channel prediction result, and distribution Q is an ideal probability distribution of the multiple beams being the optimal beam.

[0147] Distribution Q is an ideal probability distribution of the multiple beams being the optimal beam defined by distribution Q, and optionally, in distribution Q, the probability of the optimal beam in Set A is 1, and the probabilities of the remaining beams are 0, that is, the probability corresponding to the first beam in the beam sequence in Set A sorted according to the probability size is 1, and the probabilities of the remaining beams are 0.

[0148] Based on this, because Q(x) is only 1 at the optimal beam, the KL divergence of distribution P with respect to distribution Q can be simplified as:

[0149] Formula 2

[0150] In Formula 2, P(TOP1) is the probability corresponding to the first beam in the beam sequence in Set A sorted according to the probability size.

[0151] In the example shown in (c) in Figure 9 , the probability of the first optimal beam indicated by the channel prediction result being the optimal beam is then the probability corresponding to the first beam in the sequence of the 6 beams in Set A sorted according to the probability size, that is, the probability of beam #4 is 0.8; P(TOP1) = 0.8, and the confidence information = -log(0.8) 0.097.

[0152] In the present implementation, the confidence information is inversely proportional to the KL divergence, the smaller the KL divergence is, the higher the confidence information is, that is, the higher the confidence degree of the channel prediction result of Set A is.

[0153] S804, filtering out the number N of the first beams corresponding to the confidence information in the mapping relationship.

[0154] In some embodiments, the implementation of the terminal to determine the value of N includes:

[0155] The number of first beams corresponding to the confidence information is screened in the mapping relationship, wherein the confidence information is used to indicate the confidence degree of the channel prediction result of Set A.

[0156] The mapping relationship includes a plurality of confidence information and the number of first beams corresponding to each confidence information.

[0157] Optionally, the mapping relationship can be included in the first message, that is, the first message sent by the network device can indicate the mapping relationship. The confidence information included in the mapping relationship and the number of first beams corresponding thereto can be negatively correlated, that is, the higher the confidence information, the smaller the number of first beams corresponding thereto.

[0158] When the robust network is the purpose, the number of first beams corresponding to the confidence information in the mapping relationship can be set to a large value, and when the efficiency is the purpose, the number of first beams corresponding to the confidence information in the mapping relationship can be set to a small value.

[0159] As described above, the mapping relationship includes a plurality of confidence information and the number of first beams corresponding to each confidence information. After the terminal obtains the confidence information based on any one of the three implementation manners described above, the terminal can screen the mapping relationship to obtain the N value corresponding to the confidence information calculated by the terminal.

[0160] An example of the mapping relationship is as follows:

[0161] {threshold: 15, numSpace: 2};

[0162] {threshold: 5, numSpace: 4};

[0163] {threshold: 0, numSpace: 8}.

[0164] Wherein, threshold indicates the confidence information, and numSpace is used to indicate the number N of first beams.

[0165] Taking the confidence information obtained through implementation method 1 as an example, in the above mapping example, 15 can refer to the integer corresponding to the confidence information. For example, 15 is the integer corresponding to 0.15. It can be understood that: {threshold: 15, numSpace: 2} means: P(TopK) – P(Top K+1) > 0.15, and the number of the first beam N is 2; {threshold: 5, numSpace: 4} means: 0.15≥P(Top K) – P(Top K+1)>0.05, and the number of the first beam N is 4; {threshold: 0, numSpace: 8} means: 0.05≥P(Top K) – P(Top K+1)>0, and the number of the first beam N is 8.

[0166] The threshold shown in the above example is merely an example and does not constitute a limitation on the confidence information in the mapping relationship.

[0167] exist Figure 9 In the example shown in (c), the confidence level obtained according to implementation method 1 is 0.12. Based on this confidence level, the number of first beams N obtained by filtering in the mapping relationship is 2.

[0168] S805. The monitoring set is constructed including K optimal beams indicated by the channel prediction results and N first beams. The spatial distribution of the first beams is continuous with that of any one of the K optimal beams indicated by the channel prediction results.

[0169] The principle behind the terminal constructing N first beams as part of the monitoring set is:

[0170] In the field of wireless communication technology, the channel state of a wireless channel is not independently and randomly distributed in space, but has a high degree of spatial correlation. That is, the quality of the reference signal transmitted by multiple beams that are spatially continuous is basically the same. Simply put, the optimal beam rarely exists in isolation; usually, multiple optimal beams exist in spatial continuity.

[0171] Therefore, the rule for constructing the monitoring set is the Top-K beam and the beam with spatial correlation to it (i.e., the first beam), as follows:

[0172] The monitoring set = Top-K beams predicted by the AI ​​model + N first beams.

[0173] Optionally, as mentioned above, the first message indicates the value of K. Based on this, the value of K in the Top-K beam predicted by the AI ​​model used by the terminal to construct the monitoring set can be specified by the terminal through the first message. Of course, this does not constitute a limitation on the terminal specifying the value of K, and the terminal can also choose the value of K on its own.

[0174] In some embodiments, the terminal determines the implementation manner of the index (or called identification) of the first beam, including:

[0175] The terminal selects a beam having continuity with the spatial distribution of any one of the K optimal beams indicated by the channel prediction result as the first beam, that is, the first beam has continuity with the spatial distribution of any one of the K optimal beams indicated by the channel prediction result, that is, the first beam has continuity with the spatial distribution of any one of the Top-K beams, and of course, the first beam can have continuity with the spatial distribution of multiple beams in the Top-K beams.

[0176] Optionally, the first beam is included in Set A, that is, the terminal selects a beam having continuity with the spatial distribution of any one of the K optimal beams indicated by the channel prediction result from the beams in Set A as the first beam.

[0177] From the foregoing, it can be seen that the number of the first beam is N, and in the case that the number of the beam selected by the terminal and having continuity with the spatial distribution of any one of the Top-K beams is greater than N, the terminal can randomly select N first beams, or preferentially select a beam having continuity with the spatial distribution of a beam with a high ranking in the Top-K beams as the first beam. The embodiments of the present application do not limit this.

[0178] Optionally, one implementation manner in which the first beam has continuity with the spatial distribution of any one of the K optimal beams indicated by the channel prediction result includes:

[0179] The reference signal transmitted by the first beam has a QCL relationship with the reference signal transmitted by any one of the K optimal beams indicated by the channel prediction result. That is, the reference signal transmitted by the first beam has a QCL relationship with the reference signal transmitted by any one of the Top-K beams, or has a QCL relationship with the reference signal transmitted by multiple beams in the Top-K beams.

[0180] Optionally, the prediction report configuration proposed in the foregoing can also indicate the QCL relationship of the beams in Set A; based on this, the terminal can select a beam having continuity with the spatial distribution of any one of the Top-K beams as the first beam based on the prediction report configuration.

[0181] In some embodiments, before the terminal receives the first message, the terminal can also perform step S703 of sending a prediction report to the network device, and correspondingly, the network device can receive the prediction report.

[0182] The prediction report is obtained by the terminal performing channel prediction according to the prediction report configuration, and can include a channel prediction result, such as K optimal beams in Set A, where the K optimal beams in the Set A can be indicated by beam indexes.

[0183] In some other embodiments, before the terminal performs step S702, the terminal can also perform step S704, and the network device sends a second message to the terminal, and correspondingly, the terminal receives the second message, where the second message is used to trigger the terminal to perform performance monitoring on the channel prediction result; optionally, the second message can also be used to trigger the terminal to send a monitoring report.

[0184] Optionally, the reporting time indicated by the first message is non-periodic, and the network device can trigger the terminal to perform performance monitoring on the channel prediction result based on the second message, and also trigger the terminal to report the monitoring report.

[0185] Optionally, the second message can also indicate that the second message is associated with the monitoring report configuration indicated by the first message, for example, the second message includes an identifier of the first message or an identifier of the monitoring report configuration indicated by the first message, so that the second message is associated with the monitoring report configuration indicated by the first message. The terminal can perform performance monitoring on the channel prediction result based on the second message, and specifically, perform performance monitoring on the channel prediction result based on the monitoring report configuration associated with the second message, and send a monitoring report to the network device after the performance monitoring is completed.

[0186] For example, the second message can include downlink control information (DCI).

[0187] Figure 10 is a schematic block diagram of a communication device provided by an embodiment of the present application.

[0188] As shown in Figure 10 , the communication device 1000 can include a communication module 1020. The communication module 1020 can implement a corresponding communication function, which can be an internal communication function of the communication device 1000, or a communication function of the communication device 1000 and other devices. Optionally, the communication module 1020 can also be referred to as a communication interface or a transceiver module.

[0189] Optionally, the communication device 1000 further includes a processing module 1010. The processing module 1010 can implement a corresponding processing function, and optionally, the processing module 1010 can also be referred to as a processing unit.

[0190] Optionally, the communication device 1000 further includes a storage module, which can be used to store instructions and / or data; the processing module 1010 can read the instructions and / or data in the storage module, so that the communication device 1000 implements the foregoing method embodiments.

[0191] In a possible design, the communication apparatus 1000 can correspond to a terminal in the above method embodiments, or a component (such as a circuit, a chip, or a chip system, etc.) configured in the terminal. The communication apparatus 1000 can be used to perform steps or procedures performed by the terminal in any of the above method embodiments.

[0192] For example, the communication module 1020 is configured to receive a first message, the first message being used to indicate a monitoring report configuration, the monitoring report configuration being used to indicate performance monitoring on a channel prediction result; and send a monitoring report, the monitoring report being used to indicate a number of monitoring reference signal occasions that satisfy a first condition in a monitoring window; and wherein: the first condition comprises that an optimal beam in a monitoring set indicated by a monitoring result comprises in K optimal beams indicated by the channel prediction result, the monitoring result is based on a channel measurement result obtained by the monitoring set at the monitoring reference signal occasion, the monitoring set comprises the K optimal beams indicated by the channel prediction result and N first beams, the first beam has continuity with a spatial distribution of any one of the K optimal beams indicated by the channel prediction result, and K and N are positive integers.

[0193] For example, the continuity of the first beam with the spatial distribution of any one of the K optimal beams indicated by the channel prediction result comprises that a reference signal transmitted by the first beam has a quasi co-location (QCL) relationship with a reference signal transmitted by any one of the K optimal beams indicated by the channel prediction result.

[0194] For example, the determination manner of N comprises: screening out the number of the first beams corresponding to the confidence information in a mapping relationship, the mapping relationship comprising a plurality of confidence information and the number of the first beams corresponding to each confidence information; and the confidence information being used to indicate a confidence degree of the channel prediction result.

[0195] For example, the confidence information comprises a difference between a probability that a Kth optimal beam indicated by the channel prediction result is an optimal beam and a probability that a K+1th beam indicated by the channel prediction result is the optimal beam.

[0196] Or, the confidence information comprises a difference between a probability that a first optimal beam indicated by the channel prediction result is an optimal beam and a sum of a first probability and a second probability, the first probability being a probability that a second optimal beam indicated by the channel prediction result is the optimal beam, and the second probability being a probability that a Kth optimal beam indicated by the channel prediction result is the optimal beam.

[0197] Or, the confidence information comprises a KL divergence of a distribution P with respect to a distribution Q, the distribution P being a probability distribution of a plurality of beams indicated by the channel prediction result being optimal beams, and the distribution Q being an ideal probability distribution of the plurality of beams being the optimal beams.

[0198] For example, the mapping relationship is comprised in the first message.

[0199] The above is only an example, and detailed steps or processes can refer to the description of the foregoing embodiments.

[0200] In a possible design, the communication apparatus 1000 can correspond to a network device (which can be a RAN, or a core network device or a functional unit in a core network device) in the foregoing method embodiments, or a component (such as a circuit, a chip, or a chip system, etc.) configured in the network device. The communication apparatus 1000 can be used to execute steps or processes performed by the network device in any of the foregoing method embodiments.

[0201] For example, the communication module 1020 is configured to send a first message, the first message being used to indicate a monitoring report configuration, the monitoring report configuration being used to indicate performance monitoring on a channel prediction result; and receive a monitoring report, the monitoring report being used to indicate a number of monitoring reference signal occasions that satisfy a first condition in a monitoring window; wherein: the first condition includes that an optimal beam in a monitoring set indicated by a monitoring result is included in K optimal beams indicated by the channel prediction result, the monitoring result is based on a channel measurement result obtained by the monitoring set at the monitoring reference signal occasion, the monitoring set includes the K optimal beams indicated by the channel prediction result and N first beams, a first beam has continuity with a spatial distribution of any one of the K optimal beams indicated by the channel prediction result, and K and N are positive integers.

[0202] For example, the first beam having the continuity with the spatial distribution of any one of the K optimal beams indicated by the channel prediction result includes that a reference signal transmitted by the first beam has a quasi co-location (QCL) relationship with a reference signal transmitted by any one of the K optimal beams indicated by the channel prediction result.

[0203] For example, the determination manner of N includes: screening out the number of the first beams corresponding to the confidence information in a mapping relationship, the mapping relationship including a plurality of confidence information and the number of the first beams corresponding to each confidence information; and the confidence information being used to indicate a confidence degree of the channel prediction result.

[0204] For example, the confidence information includes: a difference between a probability that a Kth optimal beam indicated by the channel prediction result is an optimal beam and a probability that a K+1th beam indicated by the channel prediction result is the optimal beam.

[0205] Alternatively, the confidence information includes: a difference between a probability that a first optimal beam indicated by the channel prediction result is an optimal beam and a sum of a first probability and a second probability, the first probability being a probability that a second optimal beam indicated by the channel prediction result is the optimal beam, and the second probability being a probability that a Kth optimal beam indicated by the channel prediction result is the optimal beam.

[0206] Alternatively, the confidence information comprises a KL divergence of a distribution P relative to a distribution Q, the distribution P being a probability distribution of the plurality of beams being the optimal beam indicated by the channel prediction result, and the distribution Q being an ideal probability distribution of the plurality of beams being the optimal beam.

[0207] For example, the mapping relationship is included in the first message.

[0208] The above is only an example, and detailed steps or processes can refer to the description of the foregoing embodiments.

[0209] Figure 11 is another schematic block diagram of the communication apparatus 1100 provided by the embodiments of the present application.

[0210] The communication apparatus 1100 can be a terminal, a network device, a chip, a chip system or a processor, etc. that implements the method described above. The communication apparatus 1100 can be used to implement the method described in the method embodiments described above, and specific implementation can refer to the description in the method embodiments described above.

[0211] As shown in Figure 11 The communication apparatus 1100 can include one or more processors 1110, which can also be referred to as processing units or processing modules, and can implement certain control functions. The processor 1110 can be a general-purpose processor or a special-purpose processor, etc., for example, a baseband processor or a central processing unit. The baseband processor can be used to process communication protocols and communication data, and the central processing unit can be used to control the communication apparatus 1100 (such as a base station, a baseband chip, a user, and a user chip), execute software programs, and process data of software programs.

[0212] In an optional design, the processor 1110 can also store instructions and / or data, which can be executed by the processor 1110, so that the communication apparatus 1100 executes the method described in the method embodiments described above.

[0213] In another optional design, the communication apparatus 1100 can include a communication interface 1120 for implementing receiving and sending functions. For example, the communication interface 1120 can be a transceiver circuit, an interface, an interface circuit or a transceiver, etc. The transceiver circuit, the interface, the interface circuit or the transceiver for implementing the receiving and sending functions can be separate or integrated together. The transceiver circuit, the interface, the interface circuit or the transceiver described above can be used for reading and writing of code / data, or the transceiver circuit, the interface, the interface circuit or the transceiver described above can be used for transmission or transfer of signals.

[0214] Optionally, one or more memories 1130 are included in the communications device 1100, which can store instructions thereon that are executable by the processor 1110 to cause the communications device 1100 to perform the methods described in the above method embodiments. Optionally, the memories 1130 can also store data. Optionally, the processor 1110 can also store instructions and / or data. The processor 1110 and the memories 1130 can be separately provided, or integrated together.

[0215] It should be understood that, in a possible design, the steps in the method embodiments provided in the present application can be completed by integrated logic circuits of hardware in the processor or instructions in the form of software. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as completed by a hardware processor, or completed by a combination of hardware and software modules in the processor. The software modules can be located in random access memories, flash memories, read-only memories, programmable read-only memories or electrically erasable programmable memories, registers, or other mature storage mediums in the art. The storage medium is located in the storage, and the processor reads information in the storage medium, and combines the hardware to complete the steps of the above method. To avoid repetition, they will not be described in detail here.

[0216] In one implementation, the communications device 1100 can correspond to the terminal in the above method embodiments, and can be used to perform the steps and / or procedures performed by the terminal in the above method embodiments. The processor 1110 can be used to execute the instructions stored in the memories 1130, and when the processor 1110 executes the instructions stored in the memories, the processor 1110 is used to perform the steps and / or procedures of the above method embodiments corresponding to the terminal.

[0217] In another implementation, the communications device 1100 can correspond to the network device in the above method embodiments, and can be used to perform the steps and / or procedures performed by the network device in the above method embodiments. The processor 1110 can be used to execute the instructions stored in the memories 1130, and when the processor 1110 executes the instructions stored in the memories, the processor 1110 is used to perform the steps and / or procedures of the above method embodiments corresponding to the network device.

[0218] It can be understood that the processor described above can be one or more chips. For example, the processor can be a field programmable gate array (FPGA), can be an application specific integrated chip (ASIC), can also be a system chip (SoC), can also be a central processor unit (CPU), can also be a network processor (NP), can also be a digital signal processing circuit (digital signal processor, DSP), can also be a micro controller (MCU), can also be a programmable logic device (programmable logic device, PLD) or other integrated chip.

[0219] It can be understood that the memory in the embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (read-only memory, ROM), a programmable read-only memory (programmable ROM, PROM), an erasable programmable read-only memory (erasable PROM, EPROM), an electrically erasable programmable read-only memory (electrically EPROM, EEPROM) or a flash memory. The volatile memory can be a random access memory (random access memory, RAM) used as an external cache. By way of example, but not by way of limitation, many forms of RAM are available, such as 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, DDR SDRAM), enhanced synchronous dynamic random access memory (enhanced SDRAM, ESDRAM), synchronous link dynamic random access memory (synchlink DRAM, SLDRAM) and direct memory bus random access memory (direct rambus RAM, DR RAM). It should be noted that the memory of the system and method described herein is intended to include, but not limited to, these and any other suitable types of memory.

[0220] The embodiment of the present application further provides a computer readable storage medium, which stores instructions, and when the instructions are run on one or more computing devices, the one or more computing devices execute the data indication method described in the above embodiment.

[0221] The computer readable storage medium can be a non-transitory computer readable storage medium, for example, the non-transitory computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0222] The embodiment of the present application further provides a computer program product, and when the computer program product is executed by one or more computing devices, the one or more computing devices execute any of the data indication methods described above. The computer program product can be a software installation package, and when any of the data indication methods described above is needed, the computer program product can be downloaded and executed on a computer.

[0223] The embodiment of the present application further provides a processor, which comprises an input circuit, an output circuit and a processing circuit. The processing circuit is configured to receive a signal through the input circuit and transmit a signal through the output circuit, so that the processor executes the data indication method described in the above embodiment.

[0224] In the implementation process, the processor can be one or more chips, the input circuit can be an input pin, the output circuit can be an output pin, and the processing circuit can be a transistor, a gate circuit, a flip-flop and various logic circuits, etc. The input signal received by the input circuit can be received and input by, for example but not limited to, a receiver, the signal output by the output circuit can be output to and transmitted by, for example but not limited to, a transmitter, and the input circuit and the output circuit can be the same circuit, which is used as the input circuit and the output circuit at different times. The embodiment of the present application does not limit the specific implementation of the processor and various circuits.

[0225] The embodiment of the present application further provides a chip system, which comprises one or more processors for calling and running instructions stored in a memory, so that the data indication method described in the above embodiment is executed. The chip system can be composed of a chip, or can include a chip and other discrete devices. The chip system can comprise an input circuit or an interface for transmitting information or data, and an output circuit or an interface for receiving information or data.

[0226] In the embodiments of the present application, each term and English abbreviation is an exemplary example given for convenience of description, and should not constitute any limitation on the present application. The present application does not exclude the possibility of defining other terms capable of achieving the same or similar functions in existing or future protocols.

[0227] In the above embodiments, all or part of the embodiments can be realized by software, hardware, firmware or any combination thereof. When realized by software, all or part of the embodiments can be realized in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated.

[0228] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented by other ways. For example, the above-described device embodiments are merely illustrative, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0229] It should be understood that in various embodiments of the present application, the size of the serial number of each process does not mean the execution order, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0230] In summary, the above description is only the preferred embodiment of the technical scheme of the present application, and is not used to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A wireless communication method, characterized in that, include: Receive a first message, the first message being used to instruct monitoring report configuration, the monitoring report configuration being used to instruct performance monitoring of channel prediction results; A monitoring report is sent, which indicates the number of monitoring reference signal moments that meet a first condition within the monitoring window; wherein: the first condition includes: the optimal beams in the monitoring set indicated by the monitoring results are included in the K optimal beams indicated by the channel prediction results, the monitoring results are channel measurement results obtained based on the monitoring set at the monitoring reference signal moment, the monitoring set includes the K optimal beams indicated by the channel prediction results and N first beams, the spatial distribution of the first beams and any one of the K optimal beams indicated by the channel prediction results is continuous, and K and N are both positive integers.

2. The method according to claim 1, characterized in that, The spatial distribution of the first beam and any of the K optimal beams indicated by the channel prediction result is continuous, including: The reference signal transmitted by the first beam has a quasi-co-located (QCL) relationship with the reference signal transmitted by any of the K optimal beams indicated by the channel prediction result.

3. The method according to claim 1 or 2, characterized in that, The methods for determining N include: The number of first beams corresponding to confidence information is screened out in the mapping relationship, which includes multiple confidence information and the number of first beams corresponding to each confidence information; the confidence information is used to indicate the credibility of the channel prediction result.

4. The method according to claim 3, characterized in that, The confidence information includes: the difference between the probability that the Kth optimal beam indicated by the channel prediction result is the optimal beam and the probability that the (K+1)th beam indicated by the channel prediction result is the optimal beam; Alternatively, the confidence information includes: the difference between the probability that the first optimal beam indicated by the channel prediction result is the optimal beam and the first probability sum, where the first probability sum is the sum of the probabilities that the second optimal beam indicated by the channel prediction result is the optimal beam up to the Kth optimal beam being the optimal beam. Alternatively, the confidence information includes: the KL divergence of distribution P relative to distribution Q, where distribution P is the probability distribution of multiple beams indicating that they are the optimal beams according to the channel prediction results, and distribution Q is the ideal probability distribution of the multiple beams being the optimal beams.

5. The method according to claim 3, characterized in that, The mapping relationship is included in the first message.

6. A wireless communication method, characterized in that, include: Send a first message, the first message being used to instruct the monitoring report configuration, the monitoring report configuration being used to instruct performance monitoring of the channel prediction results; A monitoring report is received, the monitoring report being used to indicate the number of monitoring reference signal opportunities that meet a first condition within the monitoring window; wherein: the first condition includes: the optimal beams in the monitoring set indicated by the monitoring results are included in the K optimal beams indicated by the channel prediction results, the monitoring results are channel measurement results obtained based on the monitoring set at the monitoring reference signal opportunity, the monitoring set includes the K optimal beams indicated by the channel prediction results and N first beams, the spatial distribution of the first beams and any one of the K optimal beams indicated by the channel prediction results is continuous, and K and N are both positive integers.

7. The method according to claim 6, characterized in that, The spatial distribution of the first beam and any of the K optimal beams indicated by the channel prediction result is continuous, including: The reference signal transmitted by the first beam has a quasi-co-located (QCL) relationship with the reference signal transmitted by any of the K optimal beams indicated by the channel prediction result.

8. The method according to claim 6 or 7, characterized in that, The methods for determining N include: The number of first beams corresponding to confidence information is screened out in the mapping relationship, which includes multiple confidence information and the number of first beams corresponding to each confidence information; the confidence information is used to indicate the credibility of the channel prediction result.

9. The method according to claim 8, characterized in that, The confidence information includes: the difference between the probability that the Kth optimal beam indicated by the channel prediction result is the optimal beam and the probability that the (K+1)th beam indicated by the channel prediction result is the optimal beam; Alternatively, the confidence information includes: the difference between the probability that the first optimal beam indicated by the channel prediction result is the optimal beam and the first probability sum, where the first probability sum is the sum of the probabilities that the second optimal beam indicated by the channel prediction result is the optimal beam up to the Kth optimal beam being the optimal beam. Alternatively, the confidence information includes: the KL divergence of distribution P relative to distribution Q, where distribution P is the probability distribution of multiple beams indicating that they are the optimal beams according to the channel prediction results, and distribution Q is the ideal probability distribution of the multiple beams being the optimal beams.

10. The method according to claim 8, characterized in that, The mapping relationship is included in the first message.

11. A communication device, characterized in that, The communication device includes a processing module and a transceiver module, and is used to perform the method as described in any one of claims 1 to 5, or the method as described in any one of claims 6 to 10.

12. A communication device, characterized in that, include: Memory, used to store computer instructions; A processor for executing a computer program or computer instructions stored in the memory, causing the communication device to perform the method as described in any one of claims 1 to 5, or the method as described in any one of claims 6 to 10.

13. A communication system, characterized in that, Includes the communication device as described in claim 12.

14. A computer storage medium, characterized in that, Used to store a computer program, which, when executed, is used to implement the method as described in any one of claims 1 to 5, or the method as described in any one of claims 6 to 10.

15. A computer program product, characterized in that, The computer program thereunder, when the computer program is run, causes the method as described in any one of claims 1 to 5, or the method as described in any one of claims 6 to 10, to be performed.

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