Communication method and communication device

Abstract

The invention provides a communication method and a communication device. The method comprises the following steps: determining a first CSI and a second CSI; sending a first CSI report, the first CSI report comprising the first CSI and not comprising the second CSI; wherein the priority of the target CSI, such as the predicted CSI or the compressed CSI, is also the priority order; the time domain resource unit is used for acquiring a reference signal resource set of the target CSI, the prediction time unit corresponding to the target CSI, the prediction probability information or prediction confidence information included in the target CSI, the signal quality information included in the target CSI, or the acquisition mode of the signal quality information included in the target CSI; the acquisition mode comprises measurement or prediction. The target CSI comprises the first CSI or the second CSI. According to the invention, the terminal can send the CSI with higher priority.

Description

Technical Field

[0001] This application relates to the field of communications, and more specifically, to a communication method and a communication device. Background Technology

[0002] In communication systems, network devices need to determine downlink channel configuration information such as resources, modulation and coding scheme (MCS), and precoding for scheduling terminal devices based on downlink channel state information (CSI) parameters. Terminal devices calculate downlink CSI parameters by measuring downlink reference signals and feed them back to the network devices via CSI reports. CSI feedback methods include codebook-based CSI feedback and artificial intelligence (AI) model-based CSI feedback. In some scenarios, the size of the CSI report to be transmitted may exceed the channel's capacity. For example, when multiple CSI reports need to be transmitted on the same resource, the size of the CSI reports to be transmitted may exceed the channel's capacity.

[0003] Therefore, how to implement CSI feedback so that network devices can obtain CSI reports has become an urgent problem to be solved. Summary of the Invention

[0004] This application provides a communication method and a communication device. The first device can send a first CSI report according to the priority of multiple CSIs, which is beneficial for the first device to send CSIs that are more conducive to subsequent data transmission between the first device and the second device, thereby improving communication quality and / or communication efficiency.

[0005] Firstly, a communication method is provided, which can be executed by a terminal device or by components of the terminal device (such as chips, circuits, or modules).

[0006] The method includes: determining a first channel state information (CSI) and a second CSI; sending a first CSI report, which includes the first CSI but does not include the second CSI; wherein the first CSI has a higher priority than the second CSI.

[0007] The priority ranking of the target CSI is related to the first information, which includes one or more of the following: time-domain resource units of the reference signal resource set used to obtain the target CSI, prediction time units corresponding to the target CSI, prediction probability information or prediction confidence information included in the target CSI, signal quality information included in the target CSI, or the method of obtaining the signal quality information included in the target CSI; the method of obtaining the method includes measuring the reference signal resource set used to obtain the target CSI to obtain the signal quality information included in the target CSI, or predicting the reference signal resource set used to obtain the target CSI to obtain the signal quality information included in the target CSI. The target CSI includes a first CSI or a second CSI, and the reference signal resource set includes one or more reference signal resources.

[0008] Based on the above technical solution, the first device can send a first CSI report according to the priority of the CSI, which is beneficial for the first device to send a higher-priority CSI to the second device. A higher-priority CSI is more conducive to subsequent data transmission between the first and second devices, thereby improving communication quality and / or communication efficiency. For example, if the priority of the CSI is related to the prediction confidence information included in the CSI, the first device can send a CSI with a higher prediction confidence to the second device, which is beneficial for the second device to determine more accurate communication parameters required for subsequent data transmission between the first and second devices based on the higher-priority CSI.

[0009] For example, if the resources required to transmit the first CSI and the second CSI are less than or equal to the resources used to transmit the CSI report, then the first CSI report sent includes the first CSI and the second CSI; or, if the resources required to transmit the first CSI and the second CSI are greater than the resources used to transmit the CSI report, then the first CSI report sent includes the first CSI with higher priority.

[0010] For example, the target CSI includes one or more of the following: identification information of the reference signal resource corresponding to the target CSI; signal quality information corresponding to the reference signal resource corresponding to the target CSI; prediction probability information or prediction confidence information corresponding to the reference signal resource corresponding to the target CSI; or, monitoring indicator information corresponding to the reference signal resource corresponding to the target CSI.

[0011] For example, the first CSI and the second CSI correspond to different spatial resources. Spatial resources can also be referred to as beams.

[0012] In conjunction with the first aspect, in some implementations of the first aspect, the first information includes signal quality information included in the target CSI. Therefore, the higher the signal quality indicated by the signal quality information included in the target CSI, the higher the priority of the target CSI.

[0013] For example, the priority of the first CSI is higher than that of the second CSI, including: the signal quality indicated by the signal quality information included in the first CSI is higher than the signal quality indicated by the signal quality information included in the second CSI; or, the signal quality indicated by the signal quality information included in the first CSI belongs to a first signal quality range, the signal quality indicated by the signal quality information included in the second CSI belongs to a second signal quality range, and the minimum value of the first signal quality range is greater than the maximum value of the second signal quality range.

[0014] Based on the above technical solution, if the signal quality indicated by the signal quality information included in the CSI is higher, it means that the communication quality between the terminal device and the network device through the spatial resources (or beams) corresponding to the CSI is higher. Therefore, if the terminal device prioritizes sending the CSI with higher signal quality indicated by the signal quality information included to the network device, it will help improve the communication quality of subsequent communication between the terminal device and the network device.

[0015] In conjunction with the first aspect, in some implementations of the first aspect, the first information includes the prediction probability information included in the target CSI. The higher the prediction probability indicated by the prediction probability information included in the target CSI, the higher the priority of the target CSI.

[0016] For example, the priority of the first CSI is higher than that of the second CSI, including: the predicted probability indicated by the predicted probability information included in the first CSI is greater than the predicted probability indicated by the predicted probability information included in the second CSI; or, the predicted probability indicated by the predicted probability information included in the first CSI belongs to a first probability range, the predicted probability indicated by the predicted probability information included in the second CSI belongs to a second probability range, and the minimum value of the first probability range is greater than the maximum value of the second probability range.

[0017] Based on the above technical solution, the higher the predicted probability indicated by the predicted probability information included in the CSI, the higher the importance of the CSI. Therefore, if the terminal device prioritizes sending the CSI with a higher predicted probability indicated by the predicted probability information to the network device, it will help the network device determine more accurate communication parameters required for subsequent data transmission between the terminal device and the network device based on the CSI with higher importance.

[0018] In conjunction with the first aspect, in some implementations of the first aspect, the first information includes the prediction confidence information included in the target CSI. The higher the prediction confidence indicated by the prediction confidence information included in the target CSI, the higher the priority of the target CSI.

[0019] For example, the priority of the first CSI is higher than that of the second CSI, including: the predicted confidence level indicated by the predicted confidence level information included in the first CSI is greater than the predicted confidence level indicated by the predicted confidence level information included in the second CSI; or, the predicted confidence level indicated by the predicted confidence level information included in the first CSI belongs to a first confidence level range, the predicted confidence level indicated by the predicted confidence level information included in the second CSI belongs to a second confidence level range, and the minimum value of the first confidence level range is greater than the maximum value of the second confidence level range.

[0020] Based on the above technical solution, the higher the prediction confidence level indicated by the prediction confidence level information included in the CSI, the higher the accuracy of the CSI. Therefore, if the terminal device prioritizes sending the CSI with a higher prediction confidence level indicated by the prediction confidence level information to the network device, it will help the network device determine more accurate communication parameters required for subsequent data transmission between the terminal device and the network device based on the more accurate CSI.

[0021] In conjunction with the first aspect, in some implementations of the first aspect, the first information includes the method of obtaining the signal quality information contained in the target CSI. In this case, the method of obtaining the signal quality information contained in the target CSI is to measure the reference signal resource set used to obtain the target CSI, and the target CSI has a higher priority.

[0022] For example, the priority of the first CSI is higher than that of the second CSI, including: the signal quality information included in the first CSI is obtained by measuring the reference signal resource set used to obtain the first CSI, and the signal quality information included in the second CSI is obtained by predicting the reference signal resource set used to obtain the second CSI.

[0023] Based on the above technical solution, CSI obtained by measurement is more accurate than CSI obtained by prediction. Therefore, if the terminal device sends the CSI obtained by measurement to the network device first, it will help the network device to determine more accurate communication parameters required for subsequent data transmission between the terminal device and the network device based on the more accurate CSI.

[0024] In conjunction with the first aspect, in some implementations of the first aspect, the first information includes the prediction time unit corresponding to the target CSI. Therefore, the earlier the prediction time unit corresponding to the target CSI, the higher the priority of the target CSI.

[0025] For example, the priority of the first CSI is higher than that of the second CSI, including: the prediction time unit corresponding to the first CSI is earlier than the prediction time unit corresponding to the second CSI; or, the prediction time unit corresponding to the first CSI belongs to the first time unit range, the prediction time unit corresponding to the second CSI belongs to the second time unit range, and any time unit within the first time unit range is earlier than any time unit within the second time unit range.

[0026] Based on the above technical solution, when predicting the CSI of a future time using the first model, the closer the future time is to the time when the input of the first model is acquired, that is, the earlier the future time, the more accurate the CSI of the future time predicted by the first model will be. Therefore, if the terminal device prioritizes sending the CSI of the earlier prediction time unit to the network device, it will be beneficial for the network device to determine the more accurate communication parameters required for subsequent data transmission between the terminal device and the network device based on the more accurate CSI.

[0027] In conjunction with the first aspect, in some implementations of the first aspect, the first information includes time-domain resource units for obtaining the reference signal resource set of the target CSI. The later the time-domain resource unit of the reference signal resource set for obtaining the target CSI is, the higher the priority of the target CSI.

[0028] For example, the priority of the first CSI is higher than that of the second CSI, including: the time-domain resource unit used to obtain the reference signal resource set of the first CSI is later than the time-domain resource unit used to obtain the reference signal resource set of the second CSI; or, the time-domain resource unit used to obtain the reference signal resource set of the first CSI belongs to the range of the first time-domain resource unit, the time-domain resource unit used to obtain the reference signal resource set of the second CSI belongs to the range of the second time-domain resource unit, and any time-domain resource unit within the range of the first time-domain resource unit is later than any time-domain resource unit within the range of the second time-domain resource unit.

[0029] Based on the above technical solution, the closer the time of CSI acquisition is to the time of CSI usage, the more likely it is to obtain higher communication quality by using CSI. Therefore, if the terminal device prioritizes sending the CSI with a later acquisition time (i.e., the later the time domain resource unit of the corresponding reference signal resource) to the network device, it will help the network device to determine more accurate communication parameters required for subsequent data transmission between the terminal device and the network device based on the CSI with a later acquisition time.

[0030] In conjunction with the first aspect, in some implementations of the first aspect, the first information includes: the prediction time unit corresponding to the target CSI and the second information, wherein the second information includes one or more of the following: prediction probability information or prediction confidence information included in the target CSI, or signal quality information included in the target CSI; the priority of the target CSI is related to the first information, including: the priority of the target CSI is related to the first priority rule and / or the second priority rule, wherein the priority of the first priority rule is higher than the priority of the second priority rule, the first priority rule is related to the prediction time unit corresponding to the target CSI, and the second priority rule is related to the second information.

[0031] Based on the above technical solution, when determining the priority of a target CSI, the priority of the target CSI can first be determined according to the prediction time unit corresponding to the target CSI. If the priority of the target CSI cannot be determined according to the prediction time unit corresponding to the target CSI, the priority of the target CSI can be further determined based on the second information.

[0032] For example, if the prediction time unit corresponding to the first CSI is the same as that corresponding to the second CSI, or if the prediction time units corresponding to the first CSI and the second CSI belong to the same time unit range, then the priority relationship between the first CSI and the second CSI cannot be determined. In this case, for example, the priority relationship between the first CSI and the second CSI can be determined based on the prediction probability information included in the first CSI and the prediction probability information included in the second CSI.

[0033] In conjunction with the first aspect, in some implementations of the first aspect, the first information includes: a time-domain resource unit for obtaining the reference signal resource set of the target CSI and signal quality information included in the target CSI; the priority of the target CSI is related to the first information, including: the priority of the target CSI is related to a third priority rule and / or a fourth priority rule, the priority of the third priority rule is higher than the priority of the fourth priority rule, the third priority rule is related to the time-domain resource unit for obtaining the reference signal resource set of the target CSI, and the second priority rule is related to the signal quality information included in the target CSI.

[0034] Based on the above technical solution, when determining the priority of a target CSI, the priority of the target CSI can first be determined based on the time-domain resource units of the reference signal resource set used to obtain the target CSI. If the priority of the target CSI cannot be determined based on the time-domain resource units of the reference signal resource set used to obtain the target CSI, the priority of the target CSI can be further determined based on the signal quality information included in the target CSI.

[0035] For example, if the time-domain resource units of the reference signal resource set used to obtain the first CSI are the same as the time-domain resource units of the reference signal resource set used to obtain the second CSI, then it is impossible to determine the priority relationship between the first CSI and the second CSI. In this case, the priority relationship between the first CSI and the second CSI can still be determined based on the signal quality information included in the first CSI and the signal quality information included in the second CSI.

[0036] In a second aspect, a communication apparatus is provided for performing the method of the first aspect or any possible implementation thereof. Specifically, the apparatus may include units and / or modules for performing the method of the first aspect or any possible implementation thereof, such as processing units and / or communication units.

[0037] In one implementation, the device is a communication device (such as a terminal device). When the device is a communication device, the communication unit can be a transceiver or an input / output interface; the processing unit can be at least one processor. Optionally, the transceiver can be a transceiver circuit. Optionally, the input / output interface can be an input / output circuit.

[0038] In another implementation, the device is a chip, chip system, circuit, or communication module for a communication device (such as a terminal device). When the device is a chip, chip system, or circuit for a communication device, the communication unit may be an input / output interface, interface circuit, output circuit, input circuit, pin, or related circuit on the chip, chip system, or circuit; the processing unit may be at least one processor, processing circuit, or logic circuit.

[0039] Thirdly, a communication device is provided, comprising: at least one processor for executing a computer program or instructions to perform the methods described in the first aspect and any of the possible implementations thereof. Optionally, the device further comprises a memory for storing the computer program or instructions. Optionally, the device further comprises a communication interface through which the processor reads the computer program or instructions.

[0040] In one implementation, the device is a communication device (such as a terminal device).

[0041] In another implementation, the device is a chip, chip system, or circuit for communication equipment (such as terminal equipment).

[0042] Fourthly, a processor is provided for executing the method provided in the first aspect above.

[0043] Unless otherwise specified, or if it does not contradict its actual function or internal logic in the relevant description, the transmission and acquisition / reception operations involved in the processor can be understood as processor output and reception, input and other operations, or as transmission and reception operations performed by radio frequency circuits and antennas. This application does not limit them in this regard.

[0044] Optionally, the device further includes: a memory for storing a program; correspondingly, at least one processor for executing the computer program or instructions in the memory.

[0045] Optionally, the device also includes a communication interface. The communication interface is coupled to the processor and can be used to input information to the processor or output information from the processor.

[0046] Fifthly, a computer-readable storage medium is provided that stores program code for execution by a device, the program code including methods for performing the first aspect and any of the possible implementations of the first aspect described above.

[0047] In a sixth aspect, a computer program product comprising instructions is provided, which, when run on a computer, causes the computer to perform the methods described in the first aspect and any of the possible implementations of the first aspect.

[0048] In a seventh aspect, a chip is provided, the chip including a processor and a communication interface, the processor reading instructions from a memory through the communication interface and executing the method provided in the first aspect and any of the above-described implementations of the first aspect.

[0049] Optionally, as one implementation, the chip further includes a memory storing computer programs or instructions, and a processor for executing the computer programs or instructions in the memory. When the computer programs or instructions are executed, the processor is used to execute the method provided by the first aspect and any of the above implementations of the first aspect.

[0050] Eighthly, a communication system is provided, including a terminal device and / or a network device, wherein the terminal device and / or the network device are used to implement the method provided by the first aspect and any possible implementation thereof.

[0051] It should be understood that the beneficial effects of aspects two through eight and any of their implementations can be referenced in aspect one and any of its implementations. Attached Figure Description

[0052] Figure 1 This is a schematic diagram of a possible application framework in a communication system.

[0053] Figure 2This is a schematic diagram of a possible application framework in a communication system.

[0054] Figure 3 This is a schematic diagram of a communication system applicable to the communication method in the embodiments of this application.

[0055] Figure 4 This is a schematic diagram of a communication system applicable to the communication method in the embodiments of this application.

[0056] Figure 5 This is a schematic diagram of the neuron structure.

[0057] Figure 6 A schematic diagram of the prediction process for beam management scheme 1 is shown.

[0058] Figure 7 A schematic diagram of the prediction process for beam management scheme 2 is shown.

[0059] Figure 8 This is a schematic diagram of a communication method 800 provided in an embodiment of this application.

[0060] Figure 9 This is a schematic diagram of a communication method 900 provided in an embodiment of this application.

[0061] Figure 10 This is a schematic diagram of a communication method 1000 provided in an embodiment of this application.

[0062] Figure 11 This is a schematic diagram of a communication method 1100 provided in an embodiment of this application.

[0063] Figure 12 This is a schematic diagram of a communication device 2000 provided in an embodiment of this application.

[0064] Figure 13 This is a schematic diagram of another communication device 3000 provided in an embodiment of this application. Detailed Implementation

[0065] The technical solutions in this application will now be described with reference to the accompanying drawings.

[0066] The technical solutions provided in this application can be applied to various communication systems, such as: 5th generation (5G) or new radio (NR) systems, long term evolution (LTE) systems, LTE frequency division duplex (FDD) systems, LTE time division duplex (TDD) systems, wireless local area network (WLAN) systems, satellite communication systems, future communication systems, or integrated systems of multiple systems. The technical solutions provided in this application can also be applied to device-to-device (D2D) communication, vehicle-to-everything (V2X) communication, machine-to-machine (M2M) communication, machine-type communication (MTC), and Internet of Things (IoT) communication systems or other communication systems.

[0067] In a communication system, a device can send signals to or receive signals from another device. These signals can include information, signaling, or data. The term "device" can also be replaced by an entity, network entity, communication device, mobile device, network element, communication module, node, communication node, communication apparatus, etc. This disclosure uses "device" as an example. For instance, a communication system can include at least one terminal device and at least one network device. The network device can send downlink signals to the terminal device, and / or the terminal device can send uplink signals to the network device.

[0068] In the embodiments of this application, the terminal device may also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent, or user apparatus.

[0069] Terminal devices can be devices that provide voice / data, such as handheld devices with wireless connectivity, in-vehicle devices, etc. Currently, examples of terminals include: mobile phones, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, cellular phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), handheld devices with wireless communication capabilities, computing devices or other processing devices connected to a wireless modem, wearable devices, terminal devices in 5G networks, or future public land mobile communication networks. Terminal devices in a network (PLMN), etc., are not limited to this in the embodiments of this application.

[0070] By way of example and not limitation, in this embodiment, the terminal device can also be a wearable device. Wearable devices, also known as wearable smart devices, are a general term for devices that utilize wearable technology to intelligently design and develop everyday wearables, such as glasses, gloves, watches, clothing, and shoes. Wearable devices are portable devices that are worn directly on the body or integrated into the user's clothing or accessories. Wearable devices are not merely hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are feature-rich, large in size, and can achieve complete or partial functions without relying on a smartphone, such as smartwatches or smart glasses, as well as those that focus on a specific type of application function and require the use of other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0071] In this embodiment, the device for implementing the functions of the terminal device can be the terminal device itself, or it can be any device capable of supporting the terminal device in implementing those functions, such as a chip system. This device can be installed in or used in conjunction with the terminal device. In this embodiment, the chip system can be composed of chips or may include chips and other discrete components. This embodiment only uses the terminal device as an example to illustrate the device for implementing the functions of the terminal device, and does not constitute a limitation on the solution of this embodiment.

[0072] The network device in this application embodiment may include a device for communicating with a terminal device. For example, the network device may include an access network device or a wireless access network device, such as a base station. The wireless access network device in this application embodiment may refer to a radio access network (RAN) node (or device) that connects the terminal device to the wireless network. A base station can broadly encompass, or be replaced by, various names including: NodeB, evolved NodeB (eNB), next-generation NodeB (gNB), relay station, access point, transmitting and receiving point (TRP), transmitting point (TP), master station, auxiliary station, motor slide retainer (MSR) node, home base station, network controller, access node, wireless node, access point (AP), transmission node, transceiver node, baseband unit (BBU), remote radio unit (RRU), active antenna unit (AAU), remote radio head (RRH), central unit (CU), distributed unit (DU), radio unit (RU), positioning node, etc. A base station can be a macro base station, micro base station, relay node, donor node, or similar entities, or combinations thereof. A base station can also refer to a communication module, modem, or chip installed within the aforementioned equipment or apparatus. A base station can also be a mobile switching center, a device that performs base station functions in D2D, V2X, and M2M communications, or a device that performs base station functions in future communication systems. A base station can support networks using the same or different access technologies. Optionally, a RAN node can also be a server, wearable device, vehicle, or in-vehicle equipment. For example, the access network equipment in vehicle-to-everything (V2X) technology can be a roadside unit (RSU). The embodiments of this application do not limit the specific technologies or equipment forms used in the network equipment.

[0073] Base stations can be fixed or mobile. For example, a helicopter or drone can be configured to act as a mobile base station, and one or more cells can move depending on the location of the mobile base station. In other examples, a helicopter or drone can be configured as a device to communicate with another base station.

[0074] In some deployments, the network devices mentioned in the embodiments of this application may be devices including CU, DU, or CU and DU, or devices with control plane CU nodes (central unit-control plane (CU-CP)) and user plane CU nodes (central unit-user plane (CU-UP)) and DU nodes. For example, the network devices may include gNB-CU-CP, gNB-CU-UP, and gNB-DU.

[0075] In some deployments, multiple RAN nodes collaborate to assist terminals in achieving wireless access, with different RAN nodes each implementing some of the base station's functions. For example, RAN nodes can be CUs, DUs, CU-CPs, CU-UPs, or RUs. CUs and DUs can be configured separately or included in the same network element, such as a BBU. RUs can be included in radio frequency equipment or radio frequency units, such as RRUs, AAUs, or RRHs.

[0076] RAN nodes can support one or more types of fronthaul interfaces, each corresponding to a DU and RU with different functions. If the fronthaul interface between the DU and RU is a common public radio interface (CPRI), the DU is configured to implement one or more baseband functions, and the RU is configured to implement one or more radio frequency functions. If the fronthaul interface between the DU and RU is another type of interface, relative to CPRI, some downlink and / or uplink baseband functions, such as, for downlink, precoding, digital beamforming (BF), or one or more of inverse fast Fourier transform (IFFT) / cyclic prefix addition (CP), are moved from the DU to the RU; and for uplink, digital beamforming (BF), or one or more of fast Fourier transform (FFT) / cyclic prefix removal (CP), are moved from the DU to the RU. In one possible implementation, the interface can be an enhanced common public radio interface (eCPRI). Under the eCPRI architecture, the segmentation between DU and RU differs, corresponding to different categories (Cat) of eCPRI, such as eCPRI Cat A, B, C, D, E, F.

[0077] Taking eCPRI Cat A as an example, for downlink transmission, layer mapping is used as the dividing line. DU is configured to implement one or more functions preceding layer mapping (i.e., coding, rate matching, scrambling, modulation, and layer mapping), while other functions following layer mapping (e.g., RE mapping, digital beamforming (BF), or one or more inverse fast Fourier transform (IFFT) / cyclic prefix (CP) addition) are moved to RU. For uplink transmission, deRE mapping is used as the dividing line. DU is configured to implement one or more functions preceding deRE mapping (i.e., decoding, rate matching de-matching, descrambling, demodulation, inverse discrete Fourier transform (IDFT), channel equalization, and deRE mapping), while other functions following deRE mapping (e.g., digital BF or fast Fourier transform (FFT) / CP removal) are moved to RU. It is understandable that the functional descriptions of the DU and RU corresponding to various types of eCPRI can be found in the eCPRI protocol, and will not be elaborated here.

[0078] In one possible design, the processing unit in the BBU used to implement baseband functions is called the baseband high (BBH) unit, and the processing unit in the RRU / AAU / RRH used to implement baseband functions is called the baseband low (BBL) unit.

[0079] In different systems, CU (or CU-CP and CU-UP), DU, or RU may have different names, but those skilled in the art will understand their meaning. For example, in an open RAN (ORAN) system, CU can also be called O-CU (open CU), DU can also be called O-DU, CU-CP can also be called O-CU-CP, CU-UP can also be called O-CU-UP, and RU can also be called O-RU. Any of the units among CU (or CU-CP, CU-UP), DU, and RU in this application can be implemented through software modules, hardware modules, or a combination of software modules and hardware modules.

[0080] In this embodiment, the apparatus for implementing the functions of a network device can be a network device itself; it can also be an apparatus capable of supporting the network device in implementing those functions, such as a chip system, hardware circuit, software module, or a hardware circuit plus a software module. This apparatus can be installed in the network device or used in conjunction with the network device. In this embodiment, the example of a network device being used to implement the functions of a network device is provided only and does not constitute a limitation on the solutions described in this embodiment.

[0081] Network devices and / or terminal devices can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; and they can also be deployed in the air on airplanes, balloons, and satellites. This application does not limit the scenario in which the network devices and terminal devices are located. Furthermore, terminal devices and network devices can be hardware devices, or software functions running on dedicated hardware or general-purpose hardware, such as virtualization functions instantiated on a platform (e.g., a cloud platform), or entities that include dedicated or general-purpose hardware devices and software functions. This application does not limit the specific form of the terminal devices and network devices.

[0082] In wireless communication networks, such as mobile communication networks, the services supported by the networks are becoming increasingly diverse, leading to increasingly diverse requirements. For example, networks need to support ultra-high speeds, ultra-low latency, and / or massive connectivity. This characteristic makes network planning, network configuration, and / or resource scheduling increasingly complex. Furthermore, as network functions become more powerful, such as supporting higher spectrum levels, supporting higher-order multiple-input multiple-output (MIMO) technologies, supporting beamforming, and / or supporting beam management, network energy efficiency has become a hot research topic. These new requirements, new scenarios, and new characteristics bring unprecedented challenges to network planning, operation, and efficient operation. To meet these challenges, artificial intelligence technology can be introduced into wireless communication networks to achieve network intelligence.

[0083] To support artificial intelligence (AI) technology in wireless networks, AI nodes may also be introduced into the network.

[0084] Optionally, the AI ​​node can be deployed in one or more of the following locations within the communication system: access network equipment, terminal equipment, or core network equipment, etc. Alternatively, the AI ​​node can be deployed independently, for example, in a location other than any of the aforementioned devices, such as in the host or cloud server of an over-the-top (OTT) system. The AI ​​node can communicate with other devices in the communication system, which can be, for example, one or more of the following: wireless access network equipment, terminal equipment, or core network elements, etc.

[0085] It is understood that this application does not limit the number of AI nodes. For example, when there are multiple AI nodes, these nodes can be divided based on function, such as different AI nodes being responsible for different functions.

[0086] It can also be understood that AI nodes can be independent devices, or they can be integrated into the same device to achieve different functions. Alternatively, they can be network elements in hardware devices, software functions running on dedicated hardware, or virtualization functions instantiated on a platform (e.g., a cloud platform). This application does not limit the specific form of the aforementioned AI nodes.

[0087] AI nodes can be AI network elements or AI modules.

[0088] Figure 1 This is a schematic diagram of a possible application framework in a communication system. For example... Figure 1 As shown, network elements in a communication system are connected via interfaces (e.g., next-generation (NG) interfaces, Xn interfaces) or air interfaces. These network element nodes, such as core network equipment, access network nodes or equipment (RAN nodes or equipment), terminals, or one or more devices in operation administration and maintenance (OAM), are equipped with one or more AI modules (for clarity, ...). Figure 1 (Only one is shown in the image). The access network node can be a single RAN node or can include multiple RAN nodes, such as CU and DU. The CU and / or DU can also be configured with one or more AI modules. Optionally, the CU can also be split into CU-CP and CU-UP. One or more AI models are configured in CU-CP and / or CU-UP.

[0089] The AI ​​module is used to implement corresponding AI functions. AI modules deployed in different network elements can be the same or different. Depending on the parameter configuration, the AI ​​module can implement different functions. The AI ​​module model can be configured based on one or more of the following parameters: structural parameters (e.g., at least one of the following: number of neural network layers, neural network width, inter-layer connections, neuron weights, neuron activation function, or bias in the activation function), input parameters (e.g., type and / or dimension of input parameters), or output parameters (e.g., type and / or dimension of output parameters). The bias in the activation function can also be referred to as the neural network bias.

[0090] An AI module can have one or more models. A model can infer an output, which includes one or more parameters. The learning, training, or inference processes of different models can be deployed on different nodes or devices, or they can be deployed on the same node or device.

[0091] Figure 2 This is a schematic diagram of a possible application framework in a communication system. For example... Figure 2 As shown, the communication system includes a RAN intelligent controller (RIC). For example, the RIC can be... Figure 1 The AI ​​module shown is used to implement AI-related functions. The RIC includes near-real-time RIC (near-RT RIC) and non-real-time RIC (non-RT RIC). Non-real-time RIC primarily processes non-real-time information, such as data that is not sensitive to latency, with latency in the order of seconds. Real-time RIC primarily processes near-real-time information, such as data that is relatively sensitive to latency, with latency in the order of tens of milliseconds.

[0092] The near real-time RIC is used for model training and inference. For example, it is used to train an AI model and then use that AI model for inference. The near real-time RIC can obtain network-side and / or terminal-side information from RAN nodes (e.g., CU, CU-CP, CU-UP, DU, and / or RU) and / or terminals. This information can be used as training data or inference data. Optionally, the near real-time RIC can deliver the inference results to the RAN nodes and / or terminals. Optionally, inference results can be exchanged between CU and DU, and / or between DU and RU. For example, the near real-time RIC delivers the inference results to the DU, and the DU then sends the inference results to the RU.

[0093] The non-real-time RIC is also used for model training and inference. For example, it can be used to train an AI model and then use that model for inference. The non-real-time RIC can obtain network-side and / or terminal-side information from RAN nodes (e.g., CU, CU-CP, CU-UP, DU, and / or RU) and / or terminals. This information can be used as training data or inference data, and the inference results can be delivered to RAN nodes and / or terminals. Optionally, inference results can be exchanged between CU and DU, and / or between DU and RU. For example, the non-real-time RIC delivers the inference results to the DU, and the DU then sends the inference results to the RU.

[0094] The near real-time RIC and non-real-time RIC can also be set up as separate network elements. Optionally, the near real-time RIC and non-real-time RIC can also be part of other devices. For example, the near real-time RIC can be set in the RAN node (e.g., in CU, DU), while the non-real-time RIC can be set in the OAM, cloud server, core network device, or other network device.

[0095] Figure 3 This is a schematic diagram of a communication system applicable to the communication method in the embodiments of this application. For example... Figure 3 As shown, the communication system 100 may include at least one network device, such as Figure 3 The network device 110 shown; the communication system 100 may also include at least one terminal device, such as Figure 3 The terminal devices 120 and 130 are shown. Network device 110 can communicate with the terminal devices (such as terminal devices 120 and 130) via a wireless link. Communication devices in this communication system, for example, network device 110 and terminal device 120, can communicate via multi-antenna technology.

[0096] Figure 4 This is a schematic diagram of a communication system applicable to the communication method in the embodiments of this application. Compared to Figure 3 Regarding the communication system 100 shown, Figure 4 The communication system 200 shown also includes an AI network element 140. The AI ​​network element 140 is used to perform AI-related operations, such as building training datasets or training AI models.

[0097] In one possible implementation, network device 110 can send data related to the training of the AI ​​model to AI network element 140, which then constructs a training dataset and trains the AI ​​model. For example, the data related to the training of the AI ​​model may include data reported by the terminal device. AI network element 140 can send the results of operations related to the AI ​​model to network device 110, which then forwards them to the terminal device. For example, the results of operations related to the AI ​​model may include at least one of the following: a trained AI model, model evaluation results, or test results. Exemplarily, a portion of the trained AI model may be deployed on network device 110, and another portion on the terminal device. Alternatively, the trained AI model may be deployed on network device 110. Or, the trained AI model may be deployed on the terminal device.

[0098] It should be understood that Figure 4 This explanation only uses the direct connection between AI network element 140 and network device 110 as an example. In other scenarios, AI network element 140 can also be connected to a terminal device. Alternatively, AI network element 140 can be connected to both network device 110 and a terminal device simultaneously. Alternatively, AI network element 140 can also be connected to network device 110 through a third-party network element. This application embodiment does not limit the connection relationship between AI network element and other network elements.

[0099] The AI ​​Network Element 140 can also be configured as a module in network devices and / or terminal devices, for example, configured in Figure 3 In the network device 110 or terminal device shown.

[0100] It should be noted that, Figure 3 and Figure 4 This is a simplified illustration for ease of understanding only. For example, the communication system may also include other devices, such as wireless relay devices and / or wireless backhaul devices. Figure 3 and Figure 4 The figures are not shown. In practical applications, this communication system may include multiple network devices or multiple terminal devices. This application does not limit the number of network devices and terminal devices included in the communication system.

[0101] To facilitate understanding of the solutions in the embodiments of this application, the terms that may be involved in the embodiments of this application are explained below.

[0102] (1) Artificial Intelligence: This refers to enabling machines to learn, accumulate experience, and solve problems that humans can solve through experience, such as natural language understanding, image recognition, and chess. Artificial intelligence can be understood as the intelligence exhibited by machines created by humans. Generally, artificial intelligence refers to the technology of presenting human intelligence through computer programs. The goals of artificial intelligence include understanding intelligence by constructing computer programs that demonstrate symbolic reasoning or reasoning.

[0103] (2) Machine learning (ML): This is a method of implementing artificial intelligence. Machine learning is a method that endows machines with the ability to perform functions that cannot be accomplished through direct programming. In practical terms, machine learning is a method that uses data to train a model and then uses the model to make predictions. There are many methods of machine learning, such as neural networks (NN), decision trees, and support vector machines. Machine learning theory mainly involves designing and analyzing algorithms that enable computers to learn automatically. Machine learning algorithms are a class of algorithms that automatically analyze data to obtain patterns and use these patterns to predict unknown data.

[0104] (3) Neural Networks: Neural networks are a specific manifestation of machine learning methods. A neural network is a mathematical model that mimics the behavioral characteristics of animal neural networks to process information. For example... Figure 5 As shown, a neural network can be composed of three types of computational layers: input layer, hidden layer, and output layer. Each layer has one or more logical decision units, called neurons. Common neural network structures include feedforward neural networks (FNN), convolutional neural networks (CNN), and recurrent neural networks (RNN), all of which are based on neurons. Each neuron performs a weighted summation operation on its input values ​​and outputs the result through a nonlinear function. The weights of the neuron's weighted summation operation and the nonlinear function are called the parameters of the neural network. The connections between neurons in the neural network are called the structure of the neural network, and the parameters of all neurons constitute the parameters of the neural network.

[0105] (4) Deep neural network: A neural network with multiple hidden layers.

[0106] (5) Deep learning: Machine learning using deep neural networks.

[0107] (6) AI Model: An AI model is an algorithm or computer program that can implement AI functions. An AI model represents the mapping relationship between the model's input and output; in other words, an AI model is a function model that maps an input of a certain dimension to an output of a certain dimension. The parameters of the function model can be obtained through machine learning training. For example, f(x) = ax 2 +b is a quadratic function model, which can be viewed as an AI model. a and b are the parameters of this AI model, and a and b can be obtained through machine learning training. For example, the AI ​​model mentioned in the following embodiments of this application is not limited to neural networks, linear regression models, decision tree models, support vector machines (SVM), Bayesian networks, Q-learning models, or other machine learning (ML) models.

[0108] The implementation of an AI model can be a hardware circuit, software, or a combination of both; there are no restrictions. Non-restrictive examples of software include: program code, program, subroutine, instruction, instruction set, code, code segment, software module, application program, or software application, etc.

[0109] (7) Beams and Beam Management:

[0110] In this application, a beam refers to the energy distribution of an electromagnetic wave emitted by an antenna in a specific shape and direction in space. Therefore, K beams refer to K energy distributions of different shapes and / or different directions. One way to implement a beam is to use a sensor array (such as an antenna array) to achieve directional signal transmission and reception. Specifically, by adjusting the phase and amplitude of each element (such as an antenna) in the sensor array, signals at certain angles undergo constructive interference (i.e., peaks add to peaks, enhancing the signal), while signals at other angles undergo destructive interference (i.e., peaks cancel out troughs, weakening the signal), thereby forming a beam with a specific shape and direction. A beam is a communication resource. A beam can be a wide beam, a narrow beam, or other types of beams. The technology for forming a beam can be beamforming or other techniques. Beamforming technology can specifically be digital beamforming, analog beamforming, or hybrid digital / analog beamforming. Different beams can be considered different resources. The same information or different information can be transmitted through different beams. Optionally, multiple beams with the same or similar communication characteristics can be considered as a single beam. A beam may include one or more antenna ports for transmitting at least one data channel, control channel, and probe signal. A beam can also be understood as a spatial resource, referring to a transmit or receive precoding vector with energy transmission directionality. Energy transmission directionality can mean that within a certain spatial location, the received signal after precoding processing by the precoding vector has good received power, such as meeting the received demodulation signal-to-noise ratio. Energy transmission directionality can also mean that the same signal transmitted from different spatial locations has different received power through the precoding vector. The same device (e.g., network device or terminal device) can have different precoding vectors, and different devices can also have different precoding vectors, corresponding to different beams. Depending on the device's configuration or capabilities, a device can use one or more different precoding vectors at the same time, that is, it can simultaneously form one or more beams. From the perspectives of transmission and reception, beams can be divided into transmit beams and receive beams.

[0111] Optionally, the beam can also be replaced by a first signal, downlink beam, transmit beam, transmit beam, thin beam, narrow beam, wide beam, spatial filter, spatial filter, spatial parameters, spatial transmit filter, port, etc. The beam used to transmit signals can be called a transmission beam (Tx beam), a spatial domain transmit filter, or a spatial domain transmit parameter; the beam used to receive signals can be called a reception beam (Rx beam), a spatial domain receiver filter, or a spatial domain receive parameter.

[0112] In this application, the information used to indicate the beam used for transmission can be called beam indication information. Beam indication information can be one or more of the following: beam number (or number, index, identity, ID, etc.), uplink signal resource number, downlink signal resource number, absolute index of the beam, relative index of the beam, logical index of the beam, index of the antenna port corresponding to the beam, index of the antenna port group corresponding to the beam, index of the downlink signal corresponding to the beam, time index of the downlink synchronization signal block corresponding to the beam, beam pair link (BPL) information, transmit parameters (Tx parameter) corresponding to the beam, receive parameters (Rx parameter) corresponding to the beam, transmit weight corresponding to the beam, weight matrix corresponding to the beam, weight vector corresponding to the beam, receive weight corresponding to the beam, index of transmit weight corresponding to the beam, index of weight matrix corresponding to the beam, index of weight vector corresponding to the beam, index of receive weight corresponding to the beam, receive codebook corresponding to the beam, transmit codebook corresponding to the beam, index of receive codebook corresponding to the beam, and index of transmit codebook corresponding to the beam. Beam indication information can also be represented as a transmission configuration index (TCI) or a TCI state. A TCI state includes one or more quasi-co-location (QCL) information, each QCL including a reference signal (or synchronization block) ID and a QCL type. For example, a terminal device may need to determine the beam to receive the physical downlink shared channel (PDSCH) based on the TCI state indicated by the network device (typically carried by the physical downlink control channel (PDCCH)). In this application, the beam index information is a typical example of beam indication information; the beam index can also be replaced with other beam indication information that can indicate a beam.

[0113] The reference signal resources and beams described in the embodiments of this application can have a corresponding relationship, such as a one-to-one correspondence, a many-to-one relationship, or a one-to-many relationship. In one possible approach, the reference signal resources may include spatial domain resources, and the spatial domain resources included in the reference signal resources are the beams corresponding to the reference signal resources. In another possible approach, the reference signal resources may not include spatial domain resources, but may include time domain resources and / or frequency domain resources.

[0114] The reference signal transmitted on the reference signal resource is used to determine the signal quality of the beam corresponding to the reference signal resource.

[0115] To achieve beam management, methods such as layered scanning can be used to reduce beam scanning overhead. For example, a wide beam can be scanned first, followed by a narrow beam within the wide beam. Beam selection is primarily accomplished through reference signals and corresponding beam measurements. Reference signals mainly include synchronization signal blocks (SSBs or SS / PBCH blocks) and / or channel state information-reference signals (CSI-RS) or similar reference signals, which are not limited here. SSBs are cell broadcast signals, including the primary synchronization signal (PSS), secondary synchronization signal (SSS), physical broadcast channel (PBCH), and demodulation reference signal (DMRS). SSBs can be periodically transmitted according to cell configuration, and their function extends beyond beam management to include initial access, time-frequency synchronization, etc. Simply put, SSB signals can be considered wide-beam signals. Correspondingly, CSI-RS are UE-level signals; the network configures one or more CSI-RS signals for the UE based on actual conditions. Similarly, CSI-RS is not only used for beam management, but also for channel quality measurement, etc. A CSI-RS signal can be understood as a narrow-beam signal.

[0116] Traditional beam management systems perform a two-step beam scan during the serving beam selection phase: The first phase scans the Service SSB (i.e., wide beams), where the UE measures and reports the reference signal received power (RSRP) of the SSB beam to the network side. The second phase involves the network side selecting the SSB beam with the highest RSRP based on the RSRP reported by the UE and configuring a CSI-RS signal for the terminal device to scan the narrow beams covered by the SSB beam with the highest RSRP to determine the optimal beam (or the best beam). The optimal beam can refer to the beam that maximizes received or transmitted energy. For example, if the receiver uses different receive beams to receive signals, the optimal beam can include the beam with the highest RSRP (or SINR) of the signals received from multiple different receive beams. Similarly, if the transmitter uses different transmit beams to transmit signals, the optimal beam can include the beam with the highest RSRP (or SINR) of the signal measured by the receiver when the transmitted signal arrives at the receiver. In recent years, artificial intelligence (AI) technology has played a significant role in beam management, particularly in reducing beam scanning overhead. Typically, the AI ​​model takes the received power of a wide beam or a sparsely scanned narrow beam measured by the UE as input. The AI ​​model infers and outputs K candidate narrow beams, referred to as the Top-K candidate beams. For example, it can output the RSRP value or ID of the beams in the beam set (including the K best narrow beams). The network side performs a scan based on the Top-K candidate beams to ultimately determine the optimal beam, where K is a positive integer equal to or greater than 1. The AI ​​model can typically be deployed on either the UE side or the network side.

[0117] Currently, AI beam management (BM) is mainly applied in two aspects: spatial prediction and temporal prediction, which can be referred to as beam management scheme 1 (BM case 1) and beam management scheme 2 (BM case 2) respectively.

[0118] Figure 6 This is a schematic diagram of the prediction process for BM case 1. The input to the AI ​​model is the beam information (usually RSRP value) of a specific pattern scanned at a certain time. The set corresponding to this beam information is called set B. After prediction by the AI ​​model, the set corresponding to the output beam information is called set A. The terminal can select the top-K beams from set A and report the relevant information of the top-K beams (such as RSRP or the probability value as the best beam) to the network side. It should be noted that set B belongs to set A, and the top-K beams belong to set A.

[0119] Figure 7 This is a schematic diagram of the prediction process in BM case 2. A sliding time window is used to collect input information from the AI ​​model, such as... Figure 7 The RSRP of set B from time (t-N+1) to time (t) is shown. Set B's RSRP includes the RSRP corresponding to each beam in set B. Time (t-N+1) to time (t) corresponds to the observation time window T1. The AI ​​model processes the input information and outputs the prediction results for future time windows. The future time windows are shown below. Figure 7 The time interval from (t+1) to (t+M) shown is also represented as time window T2. If the AI ​​model is a regression model, the prediction result is the RSRP of set A, which includes the RSRP corresponding to each beam in set A; if the AI ​​model is a classification model, the prediction result is the IDs of the top-K beams. Accordingly, the terminal device ultimately selects the top-K beams and their related information from set A, or selects the beam IDs of the top-K beams to report to the network side. top-K(t+1) represents the prediction result at time (t+1), which can be the beam IDs of the top-K beams output by the AI ​​model.

[0120] Here, "time" can be understood as any one or more of the following: time slot, subframe, frame, and OFDM symbol. For example, the time corresponding to A represents the time slot, subframe, frame, or OFDM symbol in which A is located, or the first time slot, subframe, frame, or OFDM symbol in which A is located, or the last time slot, subframe, frame, or OFDM symbol in which A is located.

[0121] In codebook-based CSI feedback, for some codebooks with high overhead, such as release (R) 15 type II, R16 type II, and R17 type II, the CSI report content can be divided into two parts: Part 1 and Part 2. Part 1 can also be called Part 1, and Part 2 can also be called Part 2. CQI and RI belong to Part 1, while PMI belongs to Part 2. Part 2 can be transmitted via the Physical Uplink Shared Channel (PUSCH) or the Physical Uplink Control Channel (PUCCH). Since the size of Part 2 is not fixed, and multiple CSI reports may need to be transmitted on the same resource, the size of the Part 2 to be transmitted in each of the multiple CSI reports may exceed the channel's capacity. In related schemes, when the number of coded modulation symbols (or modulation symbols) in the Part 2 to be transmitted exceeds a set threshold, the terminal device will discard lower-priority parts of the report content according to their priority order until the number of coded modulation symbols in the Part 2 to be transmitted does not exceed the set threshold. The number of encoded modulation symbols in the second part to be transmitted and the set threshold can be calculated using formulas and parameters defined in the protocol.

[0122] With the development of artificial intelligence (AI) technology, a CSI feedback method based on AI models has emerged. For example, the UE feeds back the IDs of the top-K beams predicted by the AI ​​model to the base station. Correspondingly, various types of AI-related CSI reports have appeared in the CSI feedback process. The content of AI-related CSI reports differs from that of codebook-based CSI reports, and the above approach is no longer applicable to the AI ​​model-based CSI feedback method.

[0123] For example, the CSI report in this application embodiment may include one or more CSIs. The CSI may include one or more of the following: identification information of the reference signal resource corresponding to the CSI, signal quality information of the reference signal resource corresponding to the CSI, prediction probability information or prediction confidence information of the reference signal resource corresponding to the CSI, or monitoring indicator information of the reference signal resource corresponding to the CSI.

[0124] In view of this, this application provides a communication method and a communication apparatus that determines the priority of CSI based on one or more of the following: a time-domain resource unit for obtaining the reference signal resource set of CSI, a prediction time unit corresponding to the CSI, prediction probability information or prediction confidence information included in the CSI, signal quality information included in the CSI, or a method for obtaining the signal quality information included in the CSI. When the size of the CSI report to be transmitted exceeds a set threshold, the terminal device can discard the lower-priority CSIs according to the CSI priority, so as to enable the network device to obtain the higher-priority CSIs, which is beneficial to the subsequent data transmission between the network device and the terminal device. This communication method can be applied to the above-mentioned communication system, such as FDD communication scenarios. Optionally, this communication method can also be used in TDD communication scenarios, which is not limited in this disclosure.

[0125] Before introducing the scheme of this application, the following points should be noted.

[0126] (1) In this application, “instruction” may include direct instruction, indirect instruction, explicit instruction, and implicit instruction. When describing a certain instruction information for the purpose of instructing A, it can be understood that the instruction information carries A, directly instructs A, or indirectly instructs A.

[0127] In this application, the information indicated by the instruction information is called the information to be instructed. In specific implementations, there are many ways to indicate the information to be instructed, such as, but not limited to, directly indicating the information to be instructed, such as the information to be instructed itself or its index. It can also indirectly indicate the information to be instructed by indicating other information, where there is a relationship between the other information and the information to be instructed. It can also indicate only a part of the information to be instructed, while the other parts are known or pre-agreed upon. For example, the instruction of specific information can be achieved by using a pre-agreed (e.g., protocol-defined) arrangement of various pieces of information, thereby reducing instruction overhead to some extent. Furthermore, the information to be instructed can be sent as a whole or divided into multiple sub-information pieces, and the sending period and / or timing of these sub-information pieces can be the same or different.

[0128] (2) In this application, "send" and "receive" indicate the direction of signal transmission. For example, "send information to XX" can be understood as the destination of the information being XX, which may include direct transmission via the air interface or indirect transmission via the air interface by other units or modules. "Receive information from YY" can be understood as the source of the information being YY, which may include direct reception from YY via the air interface or indirect reception from YY via the air interface by other units or modules. "Send" can also be understood as the "output" of the chip interface, and "receive" can also be understood as the "input" of the chip interface. In other words, sending and receiving can occur between devices, such as between network devices and terminal devices, or within a device, such as between components, modules, chips, software modules, or hardware modules within the device via a bus, wiring, or interface.

[0129] (3) In the various embodiments of this application, unless otherwise specified or logically conflicting, the terms and / or descriptions of different embodiments are consistent and can be referenced by each other. The technical features of different embodiments can be combined to form new embodiments according to their inherent logical relationship.

[0130] (4) In this application, "first," "second," and "#1," "#2," etc., are merely for descriptive convenience and are used to distinguish objects, and are not intended to limit the scope of the embodiments of this application. They are not used to describe the order or sequence of features. It should be understood that such described objects can be interchanged where appropriate so as to describe solutions other than those in the embodiments of this application.

[0131] (5) In this application, “predefined” may mean a standard protocol predefined, or it may mean that the devices have agreed or negotiated in advance.

[0132] (6) In this application, the words “exemplary,” “for example,” etc., are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as an “example” in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word “example” is intended to present the concept in a concrete manner. In the embodiments of this application, “of,” “corresponding, relevant,” and “corresponding” can sometimes be used interchangeably, and it should be noted that their intended meanings are consistent when their distinctions are not emphasized. Furthermore, “corresponding to” in this application can also be replaced with “for,” “determined according to xx,” or “used to determine.”

[0133] (7) In this document, "at least one" means one or more. "More than one" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, or B exists alone, where A and B can be singular or plural. In the textual description of this application, the character " / " generally indicates that the related objects before and after are in an "or" relationship; in the formula of this application, the character " / " indicates that the related objects before and after are in a "division" relationship. "Including at least one of A, B and C" can mean: including A; including B; including C; including A and B; including A and C; including B and C; including A, B and C.

[0134] (8) The arrows or boxes indicated by dashed lines in the schematic diagrams in the accompanying drawings of this application indicate optional steps or optional modules.

[0135] The communication method provided in the embodiments of this application will be described in detail below with reference to the accompanying drawings. The embodiments provided in this application can be applied to the above-described embodiments. Figure 3 or Figure 4 The communication system shown is not limited.

[0136] It should be noted that the first device in the following embodiments can be a terminal device, or a component of a terminal device, such as a chip or circuit. The second device in the following embodiments can be a network device, or a component of a network device, such as a chip or circuit. Alternatively, the second device in the following embodiments can be an access network node, such as a RIC, CU, DU, RU, etc., or the second device can be a component of an access network node, such as a chip or circuit.

[0137] It should also be noted that the first device and the second device in the following embodiments are different. For example, the first device is a terminal device and the second device is a network device.

[0138] Figure 8 A schematic flowchart of the communication method provided in an embodiment of this application is shown, such as... Figure 8 As shown, method 800 may include the following steps.

[0139] S810, the first device determines the first CSI and the second CSI.

[0140] Optionally, the first device can determine multiple CSIs, including a first CSI and a second CSI. The following explanation uses the example of the first device determining multiple CSIs.

[0141] Optionally, multiple CSIs may correspond to the first model.

[0142] For example, multiple CSIs corresponding to the first model means that one of the multiple CSIs is an input or output of the first model.

[0143] For example, the first model is deployed on the first device side (the first model is deployed in the first device, or the first model is deployed on another device different from the first device, such as a server), each of the multiple CSIs is the output of the first model, or some of the multiple CSIs are the input of the first model or are used for monitoring the output of the first model, and the remaining CSIs of the multiple CSIs are the output of the first model.

[0144] For example, the first model is a classification model for beam management, and multiple CSIs can include the IDs of the top-K beams output by the first model (and further, the probability value of each of the top-K beams as the best beam), that is, each CSI in the multiple CSIs is the output of the first model.

[0145] For another example, the first model is a regression model used for beam management. Multiple CSIs may include the RSRP corresponding to each beam in the set A predicted by the first model. Optionally, they may also include the prediction confidence of the RSRP corresponding to each beam predicted by the first model. That is, each CSI in the multiple CSIs is the output of the first model.

[0146] For another example, the first model is a regression model for beam management. This model outputs the RSRP (Responsible RSRP) for each beam in set A. Optionally, it can also output the predicted confidence level of the RSRP for each beam in set A. Set A includes set B, meaning the output of the first model includes the RSRP (or the predicted confidence level of the RSRP) for each beam in set B. Since the first device obtains the RSRP for each beam in set B by measuring at least one reference signal, and the RSRP obtained by the first device through measuring the reference signal is more accurate than the RSRP predicted by the first model, the first device can carry the measured RSRP for each beam in set B in the CSI (Cost Indicator Signal) for each beam in set B. This allows for better beam management. In other words, the RSRP obtained through inference for a beam is replaced with the RSRP obtained through measurement for that beam. In this case, the multiple CSIs determined by the first device may include CSIs corresponding to each beam in set B, and CSIs corresponding to each beam in set A other than those in set B. The CSIs corresponding to each beam in set B include the measured RSRP value for that beam, and these measured RSRP values ​​are actually the input to the first model. The CSIs corresponding to each beam in set A other than those in set B include the predicted RSRP value for that beam, and these predicted RSRP values ​​are the output of the first model.

[0147] Optionally, the CSI corresponding to each beam in set B, including the measured RSRP of the corresponding beam, can be obtained by processing the actual measured RSRP of each beam in set B based on the predicted RSRP of each beam in set A (e.g., compensation, quantization, normalization, etc.). Alternatively, the predicted RSRP of each beam in set A other than the beams in set B can be obtained by processing the actual predicted RSRP of each beam in set B based on the actual predicted RSRP of each beam in set B (e.g., compensation, quantization, normalization, etc.).

[0148] Here, set A includes all beams associated with the network device in a single beam management inference task, and set B is a subset of set A. For example, the reference signal resource set corresponding to set B is used to obtain the model input corresponding to the beam management inference task. The reference signal resource set corresponding to set B refers to the set of reference signal resources composed of the reference signal resources corresponding to each beam in set B.

[0149] For example, if the first model is deployed on the second device side (either the first model is deployed in the second device, or the first model is deployed on another device different from the second device, such as a server), then each of the multiple CSIs is an input to the first model.

[0150] For example, the first model is a model for beam management, and the multiple CSIs may include the RSRP corresponding to each beam in set B, with each CSI being an input to the first model.

[0151] In one possible implementation, different CSIs among the multiple CSIs correspond to different spatial resources. Spatial resources can be interchanged with beams. For example, if the reference signal resources corresponding to the spatial resources (or beams) include spatial resources, then different CSIs among the multiple CSIs correspond to different reference signal resources. It can be understood that the first CSI and the second CSI correspond to different spatial resources.

[0152] In this application, the predicted value can be the prediction result directly output by the AI ​​model, or the result obtained after data processing of the prediction result directly output by the AI ​​model. A predicted value can be the prediction result directly output by the AI ​​model in a prediction process, or the result obtained after processing the prediction result. The AI ​​model can be deployed on a terminal device or on an OTT device on the terminal device side. When the AI ​​model is deployed on an OTT device, the terminal device can receive the prediction result output by the AI ​​model from the OTT device.

[0153] The information contained in the target CSI is described below. The target CSI is any one of multiple CSIs. For example, the target CSI is either the first CSI or the second CSI.

[0154] The target CSI may include one or more of the following: the identification information of the reference signal resource corresponding to the target CSI, the signal quality information of the reference signal resource corresponding to the target CSI, the prediction probability information or prediction confidence information of the reference signal resource corresponding to the target CSI, or the monitoring indicator information of the reference signal resource corresponding to the target CSI.

[0155] For example, if the first model is deployed on the first device side, the target CSI may include one or more of the following: identification information of the reference signal resource corresponding to the target CSI, signal quality information of the reference signal resource corresponding to the target CSI, prediction probability information or prediction confidence information of the reference signal resource corresponding to the target CSI, or monitoring indicator information of the reference signal resource corresponding to the target CSI.

[0156] For example, if the first model is deployed on the second device side, the target CSI may include one or more of the following: identification information of the reference signal resource corresponding to the target CSI, or signal quality information corresponding to the reference signal resource corresponding to the target CSI.

[0157] If CSI#1 includes information related to reference signal resource #1, such as the identification information of reference signal resource #1, the signal quality information corresponding to reference signal resource #1, the prediction probability information or prediction confidence information corresponding to reference signal resource #1, or the monitoring indicator information corresponding to reference signal resource #1, then it means that CSI#1 corresponds to reference signal resource #1.

[0158] The identification information may include one or more of the following: the identifier (ID) of the beam corresponding to the reference signal resource corresponding to the target CSI, the ID of the reference signal resource corresponding to the target CSI, or the sequence number of the reference signal resource corresponding to the target CSI in the set of reference signal resources to which the reference signal resource corresponding to the target CSI belongs. For ease of description, the beam corresponding to the reference signal resource corresponding to the target CSI will be referred to as the beam corresponding to the target CSI below. The reference signal resource includes time-domain resources and / or frequency-domain resources, then the ID of the reference signal resource may include the ID of the time-domain resources and / or the ID of the frequency-domain resources included in the reference signal resource, or the IDs of the time-domain resources and the frequency-domain resources. The reference signal resource may also include spatial-domain resources, then the ID of the reference signal resource may also include the ID of the spatial-domain resources included in the reference signal resource. The ID of the spatial-domain resources included in the reference signal resource may be equivalent to the ID of the beam corresponding to the reference signal resource.

[0159] Signal quality information indicating signal quality may include one or more of the following: RSRP (Reference Signal Receiving Quality Ratio) of the reference signal resource corresponding to the target CSI, Reference Signal Receiving Quality (RSRQ), or Signal to Interference Plus Noise Ratio (SINR). Signal quality information may include signal quality itself, quantized values ​​of signal quality, or relative values ​​of signal quality, such as difference values ​​or ratios. For example, if CSI#1 among multiple CSIs has the highest signal quality corresponding to the reference signal resource, then the signal quality information included in CSI#1 may include the signal quality corresponding to the reference signal resource corresponding to CSI#1. Similarly, the signal quality information included in CSI#2 among multiple CSIs may include the difference or ratio between the signal quality corresponding to the reference signal resource corresponding to CSI#1 and the signal quality corresponding to the reference signal resource corresponding to CSI#2.

[0160] The signal quality indicated by the signal quality information can be a predicted value obtained by measuring a set of reference signal resources used to obtain the target CSI, or a predicted value obtained by predicting through a first model whose input parameters are measured with respect to the set of reference signal resources used to obtain the target CSI.

[0161] The reference signal resource set used to obtain the target CSI may or may not include the reference signal resource corresponding to the target CSI. That is, if the reference signal resource set used to obtain the target CSI does not include the reference signal resource corresponding to the target CSI, then during the measurement process (referring to measurement of the reference signal resource set used to obtain the target CSI, hereinafter "performing measurement" has the same meaning), the first device cannot obtain the measured value of the signal quality corresponding to the reference signal resource of the target CSI. Therefore, the signal quality indicated by the signal quality information carried by the first device in the target CSI is the signal quality predicted by the first model. The input parameters of the first model are obtained by measuring the reference signal resource set used to obtain the target CSI.

[0162] If the set of reference signal resources used to obtain the target CSI includes the reference signal resources corresponding to the target CSI, then during the measurement process, the first device can obtain the measured value of the signal quality corresponding to the reference signal resources corresponding to the target CSI. Furthermore, the signal quality indicated by the first device carrying signal quality information in the target CSI can be either the measured value of the signal quality or the signal quality predicted by the first model.

[0163] For example, the reference signal resource set corresponding to set B is used to obtain multiple CSIs. Among these multiple CSIs, the beam corresponding to CSI#1 (an example of the target CSI) belongs to set B; in other words, the reference signal resource set corresponding to set B includes the reference signal resource corresponding to CSI#1. The beam corresponding to CSI#2 (another example of the target CSI) belongs to set A and not to set B; in other words, the reference signal resource set corresponding to set B does not include the reference signal resource corresponding to CSI#2.

[0164] The first device measures the signal quality of the reference signal resource set corresponding to set B to obtain the measured value of set B. The measured value of the signal quality of set B includes the measured value of the signal quality corresponding to each beam in set B. Then, the first device uses the signal quality of set B as the input of a first model, and the output of the first model is the predicted value of the signal quality of set A. The predicted value of the signal quality of set A includes the predicted value of the signal quality corresponding to each beam in set A.

[0165] Assuming beam #1 belongs to set B, and beam #2 belongs to set A but not to set B, then the CSI #1 corresponding to beam #1 determined by the first device can include the measured and / or predicted values ​​of the signal quality corresponding to beam #1, and the CSI #1 corresponding to beam #2 includes the predicted value of the signal quality corresponding to beam #2. It can be understood that if beam #1 belongs to set B, then the reference signal resource corresponding to beam #1 (or the reference signal resource corresponding to CSI #1) belongs to the set of reference signal resources corresponding to set B. If beam #2 does not belong to set B, then the reference signal resource corresponding to beam #2 (or the reference signal resource corresponding to CSI #2) does not belong to the set of reference signal resources corresponding to set B.

[0166] The prediction probability information is used to indicate the prediction probability of the prediction result corresponding to the target CSI predicted by the first device through the first model. For example, if the first model is a model for beam management and is a classification model, then the prediction probability information is used to indicate the prediction probability that the beam corresponding to the target CSI predicted by the first device through the first model will become the optimal beam.

[0167] The prediction probability information may include the prediction probability corresponding to the reference signal resource corresponding to the target CSI, or it may include the quantized value of the prediction probability corresponding to the reference signal resource corresponding to the target CSI, and it may also include a relative value of the prediction probability, such as a difference value or a ratio. For example, if the prediction probability corresponding to the reference signal resource corresponding to CSI#1 among multiple CSIs is the highest, then the prediction probability information included in CSI#1 may include the prediction probability corresponding to the reference signal resource corresponding to CSI#1. The prediction probability information included in CSI#2 among multiple CSIs may include the difference or ratio between the prediction probability corresponding to the reference signal resource corresponding to CSI#1 and the prediction probability corresponding to the reference signal resource corresponding to CSI#2.

[0168] The prediction confidence information is used to indicate the prediction confidence of the prediction result corresponding to the target CSI predicted by the first device through the first model. For example, if the first model is a model for beam management and is a regression model, then the prediction confidence information is used to indicate the prediction confidence of the signal quality information corresponding to the reference signal resource for which the CSI is predicted by the first device through the first model.

[0169] The prediction confidence information may include the prediction confidence of the reference signal resource corresponding to the target CSI, or it may include the quantized value of the prediction confidence of the reference signal resource corresponding to the target CSI, and it may also include a relative value of the prediction confidence, such as a difference value or a ratio. For example, if the reference signal resource corresponding to CSI#1 among multiple CSIs has the highest prediction confidence, then the prediction confidence information included in CSI#1 may include the prediction confidence of the reference signal resource corresponding to CSI#1. The prediction confidence information included in CSI#2 among multiple CSIs may include the difference or ratio between the prediction confidence of the reference signal resource corresponding to CSI#1 and the prediction confidence of the reference signal resource corresponding to CSI#2.

[0170] The monitoring indicator information is used to monitor the first model. The monitoring indicator information may include one or more of the following: the difference or ratio between the predicted confidence level and the confidence level threshold indicated by the predicted confidence level information included in the target CSI, or the difference or ratio between the signal quality indicated by signal quality information #1 corresponding to the target CSI and the signal quality indicated by signal quality information #2 corresponding to the target CSI. Wherein, the signal quality indicated by signal quality information #1 is obtained by the first device by measuring the reference signal on the reference signal resource corresponding to the target CSI, and the signal quality indicated by signal quality information #2 is obtained by the first device through the first model. The monitoring indicator information can also be referred to as monitoring result information.

[0171] S820, the first device sends the first CSI report.

[0172] Correspondingly, the second device receives the first CSI report.

[0173] For example, if the resources used to transmit the CSI report are sufficient to transmit multiple CSIs, in other words, the resources required to transmit multiple CSIs are less than or equal to the resources used to transmit the CSI report, then the first CSI report sent by the first device includes multiple CSIs, for example, including a first CSI and a second CSI.

[0174] For example, if the resources available for transmitting CSI reports are insufficient to transmit multiple CSIs—in other words, the resources required to transmit multiple CSIs exceed the resources available for transmitting CSI reports—the first device transmits a first CSI report according to the priority of the multiple CSIs. The first CSI report includes one or more of the multiple CSIs. For instance, the first CSI report includes the first CSI but does not include the second CSI. The first CSI has a higher priority than the second CSI.

[0175] Specifically, the priority of any CSI included in the first CSI report is higher than or equal to the priority of any CSI that is not included in the first CSI report. In other words, if the resources used to transmit the CSI report are insufficient to transmit multiple CSIs, the first device will send one or more CSIs with higher priority from the multiple CSIs according to their priority, i.e., priority order. It should be noted that the resources required to transmit the first CSI report are less than or equal to the resources used to transmit the CSI report.

[0176] For example, if the number of CSIs is N, and the CSIs are sorted in descending order of priority, then the number M of CSIs included in the first CSI report satisfies the following condition: Where, r m R represents the resources required to transmit the CSI ordered m out of multiple CSIs, where R represents the resources used to transmit the CSI report, m = 1, 2, ..., M, M is a positive integer, and M is less than or equal to N.

[0177] For example, the first device can group multiple CSIs according to a certain ratio and priority order. For instance, the multiple CSIs can be divided into two groups, where the priority of any CSI in the first group is not lower than the priority of any CSI in the second group. Furthermore, if the resources for transmitting CSI reports are insufficient to transmit multiple CSIs, the first device can prioritize sending the first group of CSIs, meaning the first CSI report includes the first group of CSIs.

[0178] If the codebook reported by the CSI is release type 15, type 2, type 2, type 2, or type 2, then the first and second groups of CSI mentioned above can be compared to group 1 and group 2 CSI, respectively. Alternatively, if the codebook reported by the CSI is a different codebook than those mentioned above, then the first and second groups of CSI mentioned above can be compared to even subbands CSI and odd subband CSI, respectively.

[0179] The following describes how the first device determines the priority of the target CSI.

[0180] For example, the priority of the target CSI is related to the first information, which includes one or more of the following: a time-domain resource unit for obtaining the reference signal resource set of the target CSI, a prediction time unit corresponding to the target CSI, prediction probability information or prediction confidence information included in the target CSI, signal quality information included in the target CSI, or the method of obtaining the signal quality information included in the target CSI.

[0181] The set of reference signal resources used to obtain the target CSI includes one or more reference signal resources. The first device can obtain at least one CSI, including the target CSI, through the set of reference signal resources used to obtain the target CSI.

[0182] As described above, the set of reference signal resources used to obtain the target CSI may or may not include the reference signal resources corresponding to the target CSI. For example, the set of reference signal resources used to obtain the target CSI may include reference signal resource #1 and reference signal resource #2. The first device can obtain CSI#1, CSI#2, and CSI#3 based on the set of reference signal resources used to obtain the target CSI. CSI#1 (an example of the target CSI) and CSI#2 (another example of the target CSI) correspond to reference signal resources #1 and #2, respectively; that is, the reference signal resources used to obtain the target CSI include the reference signal resources corresponding to the target CSI. CSI#3 (another example of the target CSI) corresponds to reference signal resource #3; that is, the reference signal resources used to obtain the target CSI do not include the reference signal resources corresponding to the target CSI. In other words, as... Figure 6 As shown in the right figure, the scanning beam and the top-K candidate beams include some of the same beams.

[0183] For example, if the first device obtains the target CSI by measuring the reference signal resource set used to obtain the target CSI, then the time-domain resource unit of the reference signal resource set used to obtain the target CSI can be called the measurement time unit corresponding to the target CSI.

[0184] If the signal quality information included in the target CSI is used to indicate the signal quality of the reference signal resource corresponding to the target CSI in a future time unit, for example, if the first device predicts the signal quality information included in the target CSI using a first model, and the signal quality information predicted by the first device using the first model is used to indicate the signal quality of the reference signal resource corresponding to the target CSI in a future time unit, then this future time unit can be called the prediction time unit corresponding to the target CSI. The prediction time unit corresponding to the target CSI can be the time unit in which the target CSI is applied in the future.

[0185] The prediction probability information included in the target CSI can be found in the description of the prediction probability information corresponding to the reference signal resource corresponding to the target CSI in S810 above.

[0186] The prediction confidence information included in the target CSI can be found in the description of the prediction confidence information corresponding to the reference signal resource corresponding to the target CSI in S810 above.

[0187] The signal quality information included in the target CSI can be found in the description of the signal quality information corresponding to the reference signal resource for the target CSI in S810 above.

[0188] The signal quality information included in the target CSI can be obtained in one of the following ways: by measuring the reference signal resource set used to obtain the target CSI, or by predicting the signal quality information included in the target CSI using the reference signal resource set used to obtain the target CSI. Here, measuring the reference signal resource set used to obtain the target CSI refers to measuring the reference signal on the reference signal resource set used to obtain the target CSI. The method of obtaining the signal quality information included in the target CSI can be replaced with the method of obtaining the signal quality indicated by the signal quality information included in the target CSI.

[0189] It is understandable that the first device determines the priority of the target CSI in different ways depending on the different first pieces of information. The different ways in which the first device determines the priority of the target CSI are explained below.

[0190] Method 1, the first information includes: signal quality information included in the target CSI, and the first device determines the priority of the target CSI based on the signal quality indicated by the signal quality information included in the target CSI.

[0191] For example, the higher the signal quality indicated by the signal quality information included in the target CSI, the higher the priority of the target CSI. Alternatively, the larger the minimum (or maximum) value of the signal quality range to which the signal quality indicated by the signal quality information included in the target CSI belongs, the higher the priority of the target CSI.

[0192] For example, if multiple CSIs include a first CSI and a second CSI, then the first CSI has a higher priority than the second CSI, including: the signal quality indicated by the signal quality information included in the first CSI is higher than the signal quality indicated by the signal quality information included in the second CSI; or, the signal quality indicated by the signal quality information included in the first CSI belongs to a first signal quality range, the signal quality indicated by the signal quality information included in the second CSI belongs to a second signal quality range, and the minimum value of the first signal quality range is greater than the maximum value of the second signal quality range.

[0193] The signal quality range includes multiple consecutive signal quality values. For example, signal quality range #1 is represented as [signal quality value #1, signal quality value #2], which includes all signal quality values ​​greater than or equal to signal quality value #1 and less than or equal to signal quality value #2. A signal quality belonging to the signal quality range means that the signal quality is greater than or equal to the minimum value of the signal quality range and less than or equal to the maximum value of the signal quality range.

[0194] Method 2, the first information includes: the predicted probability information included in the target CSI, and the predicted probability indicated by the predicted probability information included in the target CSI by the first device determines the priority of the target CSI.

[0195] For example, the higher the predicted probability indicated by the predicted probability information included in the target CSI, the higher the priority of the target CSI. Alternatively, the larger the minimum (or maximum) value of the probability range to which the predicted probability indicated by the predicted probability information included in the target CSI belongs, the higher the priority of the target CSI.

[0196] For example, multiple CSIs include a first CSI and a second CSI, where the first CSI has a higher priority than the second CSI. This includes situations where the predicted probability indicated by the prediction probability information included in the first CSI is greater than the predicted probability indicated by the prediction probability information included in the second CSI; or, the predicted probability indicated by the prediction probability information included in the first CSI belongs to a first probability range, the predicted probability indicated by the prediction probability information included in the second CSI belongs to a second probability range, and the minimum value of the first probability range is greater than the maximum value of the second probability range.

[0197] The probability range includes multiple consecutive predicted probability values. For example, if probability range #1 is represented as [predicted probability value #1, predicted probability value #2], then probability range #1 includes all predicted probability values ​​that are greater than or equal to predicted probability value #1 and less than or equal to predicted probability value #2. A predicted probability belonging to a probability range means that the predicted probability is greater than or equal to the minimum value of the probability range and less than or equal to the maximum value of the probability range.

[0198] Method 3, the first information includes: prediction confidence information included in the target CSI, and the first device determines the priority of the target CSI based on the prediction confidence indicated by the prediction confidence information included in the target CSI.

[0199] For example, the higher the predicted confidence level indicated by the predicted confidence level information included in the target CSI, the higher the priority of the target CSI. Alternatively, the larger the minimum (or maximum) value of the confidence level range to which the predicted confidence level indicated by the predicted confidence level information included in the target CSI belongs, the higher the priority of the target CSI.

[0200] For example, multiple CSIs include a first CSI and a second CSI, where the first CSI has a higher priority than the second CSI. This includes situations where: the predicted confidence level indicated by the predicted confidence level information included in the first CSI is greater than the predicted confidence level indicated by the predicted confidence level information included in the second CSI; or, the predicted confidence level indicated by the confidence level information included in the first CSI falls within a first confidence level range, the predicted confidence level indicated by the predicted confidence level information included in the second CSI falls within a second confidence level range, and the minimum value of the first confidence level range is greater than the maximum value of the second confidence level range.

[0201] The confidence range includes multiple consecutive predicted confidence values. For example, if confidence range #1 is represented as [predicted confidence value #1, predicted confidence value #2], then confidence range #1 includes all predicted confidence values ​​that are greater than or equal to predicted confidence value #1 and less than or equal to predicted confidence value #2. A predicted confidence value belonging to the confidence range means that the predicted confidence value is greater than or equal to the minimum value of the confidence range and less than or equal to the maximum value of the confidence range.

[0202] Method 4, the first information includes: the method of acquiring the signal quality information included in the target CSI, and the first device determines the priority of the target CSI according to the method of acquiring the signal quality information included in the target CSI.

[0203] For example, if the signal quality information included in the target CSI is obtained by measuring a set of reference signal resources used to obtain the target CSI, then the target CSI has a higher priority.

[0204] For example, multiple CSIs include a first CSI and a second CSI, where the first CSI has a higher priority than the second CSI. The first CSI is obtained by measuring a set of reference signal resources used to obtain the first CSI. The second CSI is obtained by predicting a set of reference signal resources used to obtain the second CSI.

[0205] The reference signal resource set used to obtain the first CSI may be the same as or different from the reference signal resource set used to obtain the second CSI. If the reference signal resource set used to obtain the first CSI and the reference signal resource set used to obtain the second CSI are different, the time-domain resource units of the reference signal resource set used to obtain the first CSI are different from the time-domain resource units of the reference signal resource set used to obtain the second CSI.

[0206] Method 5, the first information includes: the prediction time unit corresponding to the target CSI, and the first device determines the priority of the target CSI based on the prediction time unit corresponding to the target CSI.

[0207] For example, the earlier the prediction time unit corresponding to the target CSI, the higher the priority of the target CSI. Alternatively, the earlier the time unit range to which the prediction time unit corresponding to the target CSI belongs, the higher the priority of the target CSI. It can be understood that the earlier the prediction time unit corresponding to the target CSI, the smaller the interval between the prediction time unit and the observation time unit. The observation time unit is the time unit in which the first device measures the set of reference signal resources used to obtain the target CSI. For example, the observation time unit is the time unit in which the first device acquires the input of the first model; that is, the input of the first model acquired by the first device in the observation time unit is used to determine the target CSI.

[0208] For example, multiple CSIs include a first CSI and a second CSI, where the first CSI has a higher priority than the second CSI. This includes situations where the prediction time unit corresponding to the first CSI is earlier than the prediction time unit corresponding to the second CSI; or, the prediction time unit corresponding to the first CSI belongs to the first time unit range, the prediction time unit corresponding to the second CSI belongs to the second time unit range, and any time unit within the first time unit range is earlier than any time unit within the second time unit range.

[0209] The time unit range includes multiple consecutive time units. For example, if time unit range #1 is represented as [time unit #1, time unit #2], then time unit range #1 includes time unit #1, time unit #2, and all time units between time unit #1 and time unit #2. A time unit can be one of the following: a slot, a subframe, a frame, an orthogonal frequency division multiplexing (OFDM) symbol, a second (s), or a millisecond (ms), etc.

[0210] Method 6, the first information includes: a time-domain resource unit for obtaining a reference signal resource set for the target CSI, and the first device determines the priority of the target CSI based on the time-domain resource unit for obtaining the reference signal resource set for the target CSI.

[0211] For example, the later the time-domain resource unit of the reference signal resource set used to obtain the target CSI, the higher the priority of the target CSI. Alternatively, the later the time-domain resource unit range to which the time-domain resource unit of the reference signal resource set used to obtain the target CSI belongs, the higher the priority of the target CSI. It can be understood that the later the time-domain resource unit of the reference signal resource set used to obtain the target CSI, the smaller the interval between the time-domain resource unit of the reference signal resource set used to obtain the target CSI and the time-domain resource unit of the resource used to send the first CSI report.

[0212] For example, multiple CSIs include a first CSI and a second CSI, where the first CSI has a higher priority than the second CSI. This includes situations where: the time-domain resource units used to obtain the reference signal resource set for the first CSI are later than the time-domain resource units used to obtain the reference signal resource set for the second CSI; or, the time-domain resource units used to obtain the reference signal resource set for the first CSI belong to the range of the first time-domain resource units, the time-domain resource units used to obtain the reference signal resource set for the second CSI belong to the range of the second time-domain resource units, and any time-domain resource unit within the range of the first time-domain resource units is later than any time-domain resource unit within the range of the second time-domain resource units.

[0213] The time-domain resource unit range includes multiple consecutive time-domain resource units. For example, if the time-domain resource unit range #1 is represented as [time-domain resource unit #1, time-domain resource unit #2], then the time-domain resource unit range #1 includes time-domain resource unit #1, time-domain resource unit #2, and all time units between time-domain resource unit #1 and time-domain resource unit #2. A time-domain resource unit can be one of the following: a slot, a subframe, a frame, an orthogonal frequency division multiplexing (OFDM) symbol, a second (s), or a millisecond (ms), etc.

[0214] Method 7, where the first information includes at least two of the following: signal quality information included in the target CSI, prediction confidence information or prediction probability information included in the target CSI, prediction time unit corresponding to the target CSI, time-domain resource unit for obtaining the reference signal resource set of the target CSI, and acquisition method of the signal quality information included in the target CSI, then the first device determines the priority of the target CSI according to one or more priority rules among at least two priority rules.

[0215] The number of items in the priority rule is related to the number of items in the first information, which includes at least two of the above items. For example, the number of items in the priority rule is the same as the number of items in the first information, which includes at least two of the above items.

[0216] For example, in the process of determining the priority of a target CSI according to at least two priority rules, the first device first determines the priority of the target CSI according to the priority rule with higher priority; if the first device cannot determine the priority of the target CSI according to the priority rule with higher priority, then the first device determines the priority of the target CSI according to the priority rule with lower priority. Alternatively, in the process of determining the priority of the target CSI according to at least two priority rules, the priority rule with higher priority has a higher proportion among the at least two priority rules; for example, the priority of the target CSI is equal to the weighted sum of the priorities determined according to each priority rule.

[0217] For example, the first information includes: the prediction time unit corresponding to the target CSI and second information, wherein the second information includes one or more of the following: prediction probability information or prediction confidence information included in the target CSI, or signal quality information included in the target CSI. The priority of the target CSI is related to the first information, including: the priority of the target CSI is related to a first priority rule and / or a second priority rule, wherein the priority of the first priority rule is higher than the priority of the second priority rule. The first priority rule is related to the prediction time unit corresponding to the target CSI, and the second priority rule is related to the second information.

[0218] Optionally, if the second information includes multiple items, the second priority rule may include multiple sub-priority rules. For example, if the second information includes the prediction confidence information and the signal quality information included in the target CSI, then the second priority rule may include sub-priority rule #1 and sub-priority rule #2, where sub-priority rule #1 has a higher priority than sub-priority rule #2. Sub-priority rule #1 is related to the prediction confidence information included in the target CSI, and sub-priority rule #2 is related to the signal quality information included in the target CSI.

[0219] For example, if multiple CSIs include a first CSI and a second CSI, the first device first determines the relationship between the priorities of the first CSI and the second CSI according to a first priority rule. If the prediction time unit corresponding to the first CSI is different from that corresponding to the second CSI, or if the prediction time unit corresponding to the first CSI and the prediction time unit corresponding to the second CSI belong to different time unit ranges, the method by which the first device determines the relationship between the priorities of the first CSI and the second CSI according to the first priority rule can refer to method 5 described above. If the prediction time unit corresponding to the first CSI is the same as that corresponding to the second CSI, or if the prediction time unit corresponding to the first CSI and the prediction time unit corresponding to the second CSI belong to the same time unit range, the first device continues to determine the relationship between the priorities of the first CSI and the second CSI according to the second priority rule. For example, if the second priority rule is related to the prediction confidence information included in the target CSI, the method by which the first device determines the relationship between the priorities of the first CSI and the second CSI according to the second priority rule can refer to method 3 described above.

[0220] For example, the first information includes: time-domain resource units for obtaining the reference signal resource set of the target CSI and signal quality information included in the target CSI. The priority of the target CSI is related to the first information, including: the priority of the target CSI is related to a third priority rule and / or a fourth priority rule, wherein the priority of the third priority rule is higher than the priority of the fourth priority rule. The third priority rule is related to the time-domain resource units for obtaining the reference signal resource set of the target CSI, and the second priority rule is related to the signal quality information included in the target CSI.

[0221] For example, if multiple CSIs include a first CSI and a second CSI, the first device first determines the relationship between the priorities of the first CSI and the second CSI according to the third priority rule. If the time-domain resource units of the reference signal resource set used to obtain the first CSI are different from those of the reference signal resource set used to obtain the second CSI, or if the time-domain resource units of the reference signal resource set used to obtain the first CSI and the time-domain resource units of the reference signal resource set used to obtain the second CSI belong to different time-domain resource unit ranges, then the method by which the first device determines the relationship between the priorities of the first CSI and the second CSI according to the third priority rule can refer to the method 6 described above. If the time-domain resource units of the reference signal resource set used to obtain the first CSI are the same as those of the reference signal resource set used to obtain the second CSI, or if the time-domain resource units of the reference signal resource set used to obtain the first CSI and the time-domain resource units of the reference signal resource set used to obtain the second CSI belong to the same time-domain resource unit range, then the first device continues to determine the relationship between the priorities of the first CSI and the second CSI according to the fourth priority rule. The method by which the first device determines the relationship between the priority of the first CSI and the priority of the second CSI according to the fourth priority rule can refer to the above method 1.

[0222] For example, the first information includes: the method of acquiring the signal quality information included in the target CSI and the prediction confidence information included in the target CSI. The priority of the target CSI is related to the first information, including: the priority of the target CSI is related to the fifth priority rule and / or the sixth priority rule, where the fifth priority rule has a higher priority than the sixth priority rule. The fifth priority rule is related to the method of acquiring the signal quality information included in the target CSI, and the second priority rule is related to the prediction confidence information included in the target CSI.

[0223] For example, if multiple CSIs include a first CSI and a second CSI, the first device first determines the relationship between the priorities of the first CSI and the second CSI according to the fifth priority rule. If the acquisition method of the signal quality information included in the first CSI is different from that of the second CSI, the method by which the first device determines the relationship between the priorities of the first CSI and the second CSI according to the fifth priority rule can refer to method 4 above. If the acquisition method of the signal quality information included in the first CSI is the same as that of the second CSI, and both are obtained by prediction of the reference signal resource set used to obtain the target CSI, the first device continues to determine the relationship between the priorities of the first CSI and the second CSI according to the sixth priority rule. The method by which the first device determines the relationship between the priorities of the first CSI and the second CSI according to the sixth priority rule can refer to method 3 above.

[0224] It should be noted that the priority order of each priority rule in Method 7 is only an example, and this application does not limit it.

[0225] It should be noted that the methods 1 to 7 described above for determining the priority of the target CSI are merely examples, and this application does not limit the method by which the first device determines the priority of the target CSI. For example, based on the same inventive concept, the first device may determine the priority of the target CSI in a manner opposite to any of the methods 1 to 7 described above. For instance, if the first device determines the priority of the target CSI in a manner opposite to method 1 described above, then the lower the signal quality indicated by the signal quality information included in the target CSI, the higher the priority of the target CSI. Correspondingly, if the first device determines the priority of the target CSI in a manner opposite to the above, then the priority of any CSI in the first CSI report sent by the first device is not higher than (i.e., lower than or equal to) the priority of any CSI not belonging to the first CSI report.

[0226] In this embodiment, the first device can send a first CSI report based on the priority of the CSI, which facilitates the first device sending a higher-priority CSI to the second device. A higher-priority CSI is more beneficial for subsequent data transmission between the first and second devices, thereby improving communication quality and / or efficiency. For example, if the priority of the CSI is related to the prediction confidence information included in the CSI, the first device can send a CSI with a higher prediction confidence to the second device, which helps the second device determine more accurate communication parameters required for subsequent data transmission between the first and second devices based on the higher-priority CSI.

[0227] The following is combined Figures 9 to 11 Taking the first model for beam management as an example, the above text... Figure 8 The communication method shown is described in detail. Figures 9 to 11 The network device in the example is the second device, and the UE is the first device.

[0228] Example, Figure 9 and Figure 10 The first model in the series is deployed on the UE side. Figure 9 The beam management scheme corresponding to the first model in the model is beam management scheme 1 (or in other words, the first model supports spatial prediction). Figure 10 The beam management scheme corresponding to the first model in the model is beam management scheme 2 (or the first model supports time-domain prediction). Figure 11 The first model is deployed on the network device side.

[0229] Figure 9 A schematic flowchart of the communication method provided in an embodiment of this application is shown, such as... Figure 9 As shown, method 900 may include the following steps.

[0230] S901, UE reports capability information.

[0231] Capability information is used to indicate the type of prediction task supported by the first model deployed on the UE side. As an example, if the first model deployed on the UE side supports both spatial and temporal prediction, the capability information reported by the UE can indicate both types of prediction simultaneously.

[0232] Optionally, the UE can also send a request message. The request message is used to indicate to the UE that it can begin executing the prediction task. Thus, the network device can issue prediction tasks supported by the AI ​​model on the UE side based on the UE's request message.

[0233] S901 is an optional step. For example, when the UE has reported capability information to the network side, the network device saves the UE's capability information. Before subsequent prediction tasks based on the first model are issued, the UE does not need to report its capability information each time. Unless the type of prediction task supported by the UE changes, the UE can indicate the changed capability information to the network device.

[0234] S902, a set of reference signal resources transmitted by network devices.

[0235] The reference signal resource set is used by the UE to perform measurements on the reference signal resource set.

[0236] Alternatively, the reference signal resources included in the reference signal resource set can also be referred to as beams, or beam resources. The process by which the UE measures the reference signal resource set can also be called beam scanning.

[0237] S903, the UE performs beam scanning to obtain the first set of measurement information.

[0238] The first set of measurement information consists of the measurement information of the scanned beams obtained by the UE during beam scanning, such as RSRP. The set of beams composed of the scanned beams can be called set B. The measurement information of the scanned beams can also be called the signal quality information of the scanned beams.

[0239] S904, the UE obtains multiple CSIs based on the first model and the first set of measurement information.

[0240] For example, if the first model is a classification model, the UE uses the first set of measurement information as input to the first model, thereby obtaining the output of the first model as the IDs of the top-K beams and the predicted probability that each of the top-K beams will become the optimal beam. Furthermore, the UE can determine that the number of multiple CSIs is K, with each of the K CSIs corresponding one-to-one with the top-K beams. Each CSI can include the ID of one of the top-K beams and the predicted probability that the beam will become the optimal beam. Different CSIs among the K CSIs include the IDs of different beams among the top-K beams.

[0241] For example, if the first model is a regression model, the UE uses the first set of measurement information as input to the first model, thereby obtaining the output of the first model as the signal quality information of each beam in the predicted set A, such as RSRP, and the prediction confidence of the signal quality information of each beam in set A. Set A includes all beams associated with a single beam management inference task, and set B is a subset of set A. Assuming that the number of beams included in set A is L, the UE can determine that the number of multiple CSIs is L, and the L CSIs correspond one-to-one with the L beams in set A. If the beam #x corresponding to CSI#x among the L CSIs belongs to set B, then CSI#x includes the measurement information of beam #x. If the beam #y corresponding to CSI#y among the L CSIs belongs to set A and not to set B, then CSI#y includes the signal quality information of beam #y predicted by the first model and the prediction confidence of the signal quality information of beam #y.

[0242] S905, the UE determines the priority order of multiple CSIs.

[0243] In one possible implementation, if the multiple CSIs are the K CSIs described in S904, the UE determines the priority or priority order of the K CSIs based on the prediction probability included in each of the K CSIs. For example, the priority order of the K CSIs is determined by determining the priority of each CSI. For instance, the higher the prediction probability included in a CSI, the higher the priority of the CSI.

[0244] In one possible implementation, if the multiple CSIs are L CSIs as described in S904, the UE first sets the priority of the L1 CSIs among the L CSIs to the highest, where each of the L1 CSIs includes measurement information. Then, the UE determines the priority of each of the L2 CSIs among the L CSIs based on the prediction confidence level included in the CSIs, thereby determining the priority order of the L CSIs. Each of the L2 CSIs includes predicted signal quality information. For example, if the signal quality information included in the CSI indicates a higher signal quality, then the CSI has a higher priority.

[0245] For example, if L CSIs include CSI#x1, CSI#x2, CSI#y1, and CSI#y2, where CSI#x1 includes measurement information for beam #x1, CSI#x2 includes measurement information for beam #x2, CSI#y1 includes predicted signal quality information for beam #y1 and its predicted confidence level, and CSI#y2 includes predicted signal quality information for beam #y2 and its predicted confidence level, then the UE first determines that CSI#x1 and CSI#x2 have a higher priority than CSI#y1 and CSI#y2. Furthermore, if the predicted confidence level of the signal quality information for beam #y1 is higher than the predicted confidence level of the signal quality information for beam #y2, then the UE determines that CSI#y1 has a higher priority than CSI#y2.

[0246] It should be noted that S905 is an optional step. For example, if method 900 executes S906 first, and in S906 the UE determines that the transmission resources are sufficient to transmit multiple CSIs, then method 900 may not execute S905.

[0247] S906, the UE determines whether to drop the data due to insufficient transmission resources.

[0248] For example, if the transmission resources are less than the resources required to transmit multiple CSIs, the UE performs a drop. Then, method 900 continues to execute S908 and S909. If the transmission resources are greater than or equal to the resources required to transmit multiple CSIs, the UE does not perform a drop. Then, method 900 continues to execute S907.

[0249] In the process of discarding some CSIs among multiple CSIs, the UE discards the lower-priority CSIs according to the priority order of the multiple CSIs. When the UE discards CSIs due to insufficient transmission resources, it is equivalent to the UE reporting the higher-priority CSIs due to insufficient transmission resources.

[0250] S907, UE reports multiple CSIs.

[0251] S908: The UE discards CSIs from high to low priority until the transmission resource requirements are met.

[0252] That is, the UE discards some of the multiple CSIs in order of priority from high to low, until the resources required to transmit the reserved CSIs (i.e. the CSIs that have not been discarded) are less than or equal to the transmission resources.

[0253] S909, the UE reports the CSI that is retained among multiple CSIs.

[0254] In this embodiment, if the transmission resources are insufficient to transmit all prediction results (i.e., multiple CSIs) of the first model, the UE can prioritize reporting prediction results with higher prediction probabilities or prediction results with higher prediction confidence. Compared to discarding all prediction results of the first model or randomly discarding some prediction results from all prediction results of the first model, this application can save air interface overhead more scientifically and efficiently, and ensure that high-quality prediction results are not erroneously discarded, thereby improving the communication quality between the UE and the network device.

[0255] Figure 10 A schematic flowchart of the communication method provided in an embodiment of this application is shown, such as... Figure 10 As shown, method 1000 may include the following steps.

[0256] S1001, UE reports capability information.

[0257] For a more detailed description of S1001, please refer to S901 in Method 900 above.

[0258] S1002, the UE repeats beam scanning within N time windows.

[0259] The procedure for the UE to perform beam scanning within each time window can be referred to S902 and S903 in method 900 above. N is a positive integer.

[0260] It should be noted that in S1002, the UE can obtain N sets of measurement information, and the N sets of measurement information correspond one-to-one with N time windows.

[0261] S1004, the UE obtains multiple CSIs based on the first model and N sets of measurement information.

[0262] The UE can use N sets of measurement information as input to the first model, thereby obtaining multiple CSIs as the output of the first model.

[0263] Multiple CSIs can be divided into T groups of CSIs, and each of the T groups of CSIs corresponds one-to-one with T future prediction time units. T is a positive integer.

[0264] The following description uses the t-th CSI in group T as an example to illustrate multiple CSIs. t is a positive integer, and 1 ≤ t ≤ T.

[0265] For example, if the first model is a classification model, the UE uses N sets of measurement information as input to the first model, thereby obtaining the output of the first model as the IDs of the top-K beams corresponding to each of the T prediction time units, and the prediction probability that each of the top-K beams will become the optimal beam. Furthermore, the UE can determine that the number of CSIs in the t-th group is K, with each of the K CSIs corresponding one-to-one with the top-K beams. Each of the K CSIs can include the ID of one of the top-K beams and the prediction probability that the beam will become the optimal beam. Different CSIs among the K CSIs include the IDs of different beams among the top-K beams.

[0266] For example, if the first model is a regression model, the UE uses N sets of measurement information as input to the first model, thereby obtaining the output of the first model as the signal quality information of set A corresponding to each prediction time in T prediction time units, such as RSRP, and the prediction confidence of the signal quality information of set A. Set A includes all beams associated with a beam management task, and the signal quality information of set A includes the quality information of each beam in set A. Assuming that the number of beams included in set A is L, the UE can determine that the number of CSIs in the t-th group is L, and the L CSIs correspond one-to-one with the L beams in set A. CSI#l in the L CSIs includes the signal quality information of beam#l predicted by the first model and the prediction confidence of the signal quality information of beam#l.

[0267] S1004, the UE determines the priority order of multiple CSIs.

[0268] In one possible implementation, the t-th group of CSIs in the T-group consists of the K CSIs described in S1003. The UE determines the priority or priority order of the multiple CSIs based on the prediction probability included in each CSI. For example, the priority order of the multiple CSIs is determined by determining the priority of each CSI. For instance, the higher the prediction probability included in a CSI, the higher the priority of that CSI.

[0269] In one possible implementation, the t-th group of CSIs in the T groups consists of the L CSIs described in S1003. The UE then determines the priority or priority order of the multiple CSIs based on the prediction confidence level included in each CSI. For example, the priority order of the multiple CSIs is determined by determining the priority of each CSI. For instance, the higher the prediction confidence level included in a CSI, the higher the priority of that CSI.

[0270] In one possible implementation, the UE determines the priority or priority order of multiple CSIs based on the prediction time unit corresponding to each CSI. For example, the priority order of multiple CSIs is determined by determining the priority of each CSI. For instance, the earlier the prediction time unit corresponding to a CSI, the higher the priority of the CSI.

[0271] It can be understood that in this implementation, all CSIs in the t-th group of CSIs correspond to the same prediction time unit, and therefore the different CSIs in the t-th group of CSIs have the same priority.

[0272] Optionally, if the t-th group of CSIs comprises the K CSIs described in S1003, the UE can further determine the priority or priority order of the K CSIs in the t-th group of CSIs based on the prediction probability included in each CSI. For example, by determining the priority of each CSI, the priority order of the K CSIs in the t-th group of CSIs can be determined. Alternatively, if the t-th group of CSIs comprises the L CSIs described in S1003, the UE can determine the priority or priority order of the L CSIs in the t-th group of CSIs based on the prediction confidence included in each CSI. For example, by determining the priority of each CSI, the priority order of the L CSIs in the t-th group of CSIs can be determined.

[0273] It should be noted that S1004 is an optional step. For example, if method 1000 executes S1005 first, and in S1005 the UE determines that the transmission resources are sufficient to transmit multiple CSIs, then method 1000 may not execute S1004.

[0274] S1005, the UE determines whether to drop the data due to insufficient transmission resources.

[0275] S1005 can be referenced from S906 in method 900 above.

[0276] S1006, UE reports multiple CSIs.

[0277] S1007, the UE discards CSIs from high to low priority until the transmission resource requirements are met.

[0278] That is, the UE discards some of the multiple CSIs in order of priority from high to low, until the resources required to transmit the reserved CSIs (i.e. the CSIs that have not been discarded) are less than or equal to the transmission resources.

[0279] S1008, the UE reports the CSI that is retained among multiple CSIs.

[0280] In this embodiment, if the transmission resources are insufficient to transmit all prediction results (i.e., multiple CSIs) of the first model, the UE can prioritize reporting prediction results with higher prediction probabilities, or prioritize reporting prediction results with higher prediction confidence, or prioritize reporting prediction results with earlier prediction time units. Compared to discarding all prediction results of the first model, or randomly discarding some prediction results from all prediction results of the first model, this application can save air interface overhead more scientifically and efficiently, ensuring that high-quality prediction results and / or prediction results that have a significant impact on all prediction results are not erroneously discarded, thereby improving the communication quality between the UE and the network device.

[0281] Figure 11 A schematic flowchart of the communication method provided in an embodiment of this application is shown, such as... Figure 11 As shown, method 1100 may include the following steps.

[0282] S1101, the network device sends a data collection command to the UE.

[0283] The data collection command is used to instruct the UE to perform beam scanning and report the measurement information obtained by scanning the beam.

[0284] S1101 can be an optional step. For example, if the network device pre-configures the UE to perform beam scanning in a specified reference signal resource and / or time period and report measurement information, then method 1100 may not execute S1101.

[0285] S1102, the UE repeats beam scanning within N time windows.

[0286] The procedure for the UE to perform beam scanning within each time window can be referred to S902 and S903 in method 900 above. N is a positive integer.

[0287] It should be noted that in S1002, the UE can obtain N sets of CSIs, each corresponding to one of the N time windows. The nth CSI set in the N sets includes M CSIs, each corresponding to one of the M scanning beams. Each CSI in the nth CSI set includes measurement information from one of the M scanning beams. Different CSIs in the nth CSI set include measurement information from different scanning beams within the M scanning beams. Measurement information can also be referred to as signal quality information. M is a positive integer. n is a positive integer, and 1 ≤ n ≤ N.

[0288] S1103, the UE determines the priority order of multiple CSIs.

[0289] For example, the UE determines the priority or priority order of multiple CSIs based on the time window corresponding to each CSI. For instance, the priority order of multiple CSIs is determined by determining the priority of each CSI. For example, the later the time window corresponding to a CSI, the higher the priority of the CSI. The time window corresponding to a CSI can also be referred to as a time-domain resource unit used to obtain the reference signal resource set for the CSI.

[0290] It is understandable that in this implementation, all CSIs in the nth group of CSIs correspond to the same time window, so different CSIs in the nth group of CSIs have the same priority.

[0291] Optionally, the UE can also determine the priority or priority order of the M CSIs in the nth CSI group based on the measurement information included in each CSI. For example, by determining the priority of each CSI, the priority order of the M CSIs in the nth CSI group can be determined. For instance, if the signal quality indicated by the measurement information included in the CSI is higher, then the priority of the CSI is higher.

[0292] It should be noted that S1103 is an optional step. For example, if method 1100 executes S1104 first, and in S1104 the UE determines that the transmission resources are sufficient to transmit multiple CSIs, then method 1100 may not execute S1103.

[0293] S1104, the UE determines whether to drop the data due to insufficient transmission resources.

[0294] S1104 can be referenced from S906 in method 900 above.

[0295] S1105, UE does not report multiple CSIs.

[0296] S1106, the UE discards CSIs from high to low priority until the transmission resource requirements are met.

[0297] That is, the UE discards some of the multiple CSIs in order of priority from high to low, until the resources required to transmit the reserved CSIs (i.e. the CSIs that have not been discarded) are less than or equal to the transmission resources.

[0298] S1107, the UE reports the CSI that is retained among multiple CSIs.

[0299] In this embodiment, the first model is deployed on the network device side, and the CSI reported by the UE is used by the network device for beam management. For example, if the first model is a classification model, after receiving the CSI from the UE, the network device can use the CSI from the UE as input to the first model, and then obtain the predicted top-K beams through the first model. Optionally, it can also obtain the predicted probability of each of the top-K beams being the optimal beam. For example, if the first model is a regression model, after receiving the CSI from the UE, the network device can use the CSI from the UE as input to the first model, and then obtain the predicted RSRP of each beam in the predicted set A through the first model. Optionally, it can also obtain the predicted confidence of the RSRP of each beam. Set A includes all beams associated with a single beam management inference task.

[0300] In this embodiment of the application, if the transmission resources are insufficient to transmit all measurement information (i.e., multiple CSIs), the UE can prioritize reporting measurement information with later measurement times, which is beneficial for the second device to obtain more accurate prediction results based on the measurement information reported by the first device.

[0301] In the above embodiments, the deployment of the first model on the first device side can be implemented on a chip inside the first device, or it can be located outside the first device, such as in the host of an OTT system or a cloud server.

[0302] If the first model is deployed at a location other than the first device, the following steps in the above embodiments can be performed by the device or equipment that deploys the first model: determining multiple CSIs.

[0303] Taking the first device as an example, the deployment of the first model on the UE side can be implemented on the chip inside the UE, or it can be located outside the UE, such as in the host of the OTT system or in the cloud server.

[0304] If the first model on the UE side is deployed on the host or cloud server of the OTT system, then in Figure 8 The method shown is 800. Figure 9 Method 900 or shown Figure 10 In method 1000, the UE obtains the input of the first model (e.g., the RSRP corresponding to each beam in set B) and sends it to the OTT. The OTT then obtains the output of the first model (e.g., the RSRP corresponding to each beam in set A or the IDs of the top-K beams) based on the input and the first model and sends it to the UE. The UE can determine the priority of each of the multiple CSIs and report one or more CSIs from the multiple CSIs according to the priority of each CSI.

[0305] It should be understood that the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0306] It should also be understood that, in the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced by each other, and the technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationships.

[0307] It is understood that, in the above-described method embodiments, the methods and operations implemented by the apparatus (such as the first apparatus or the second apparatus) can also be implemented by components of the apparatus (such as chips or circuits).

[0308] The above, combined with Figures 8 to 11 The communication method provided in the embodiments of this application is described in detail. The above communication method is mainly described from the perspective of the interaction between the first device and the second device. It is understood that, in order to achieve the above functions, the first device and the second device include hardware structures and / or software modules corresponding to the execution of each function.

[0309] It is understood that, in order to achieve the functions in the above embodiments, the first device and the second device include hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and method steps of the various examples described in conjunction with the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application scenario and design constraints of the technical solution.

[0310] Figure 12 and Figure 13 This is a schematic block diagram of a communication device provided in an embodiment of this application. These communication devices can be used to implement the functions of the first or second device in the above method embodiments, and therefore can also achieve the beneficial effects of the above method embodiments.

[0311] Figure 12 This is a schematic block diagram of the communication device 2000 provided in an embodiment of this application. Figure 12 As shown, the communication device 2000 includes a transceiver unit (or communication unit) 2020. Optionally, the communication device 2000 further includes a processing unit 2010. The communication device 2000 is used to implement the above-mentioned... Figure 8 , Figure 9 , Figure 10 or Figure 11 The function of the first or second device in the method embodiments shown.

[0312] When the communication device 2000 is used to achieve Figure 8 , Figure 9 , Figure 10 or Figure 11 In the method embodiment shown, the first device functions as follows: Processing unit 2010 is used to determine a first CSI and a second CSI. Transceiver unit 2020 is used to send a first CSI report, which includes the first CSI but does not include the second CSI, and the first CSI has a higher priority than the second CSI.

[0313] For a more detailed description of the aforementioned processing unit 2010 and transceiver unit 2020, please refer to [link / reference needed]. Figure 8 , Figure 9 , Figure 10 or Figure 11 The relevant descriptions in the method embodiments shown.

[0314] The apparatus 2000 of each of the above-described schemes has the function of implementing the corresponding steps performed by the first apparatus in the above-described method, or the apparatus 2000 of each of the above-described schemes has the function of implementing the corresponding steps performed by the second apparatus in the above-described method. The function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions; for example, the transceiver unit can be replaced by a transceiver (e.g., the transmitting unit in the transceiver unit can be replaced by a transmitter, and the receiving unit in the transceiver unit can be replaced by a receiver), and other units, such as processing units, can be replaced by processors, respectively executing the transceiver operations and related processing operations in each method embodiment.

[0315] Furthermore, the aforementioned transceiver unit can also be a transceiver circuit (e.g., it may include a receiving circuit and a transmitting circuit), and the processing unit can be a processing circuit. The processing circuit can be one or more processors, or all or part of the circuitry within one or more processors used for control or processing functions. In embodiments of this application, Figure 12 The device mentioned can be the first or second device in the foregoing embodiments, or it can be a chip or a chip system, such as a system on a chip (SoC). The transceiver unit can be an input / output circuit or a communication interface; the processing unit is a processor, microprocessor, or integrated circuit integrated on the chip. No limitations are imposed here.

[0316] Figure 13 This is a schematic block diagram of a communication device 3000 provided in an embodiment of this application. The device 3000 includes a processing circuit. The device may also include a communication circuit. The processing circuit and the communication circuit communicate with each other via an internal connection path. The processing circuit executes instructions to control the communication circuit to send and / or receive signals.

[0317] Taking a processing circuit that includes one or more processors and a communication circuit that is a transceiver as an example, such as Figure 13 As shown, the communication device 3000 includes a processor 3010 and a transceiver 3020. The processor 3010 and the transceiver 3020 are coupled to each other. It is understood that the transceiver 3020 can be a transceiver or an input / output interface. Optionally, the communication device 3000 may also include a memory 3030 for storing instructions executed by the processor 3010, or storing input data required by the processor 3010 to execute instructions, or storing data generated after the processor 3010 executes instructions. Sometimes, the transceiver 3020 can also be understood as part of the processor 3010, in which case the communication device 3000 includes the processor 3010.

[0318] In one possible implementation, the apparatus 3000 is used to implement the various processes and steps corresponding to the first apparatus in the above method embodiments. In another possible implementation, the apparatus 3000 is used to implement the various processes and steps corresponding to the second apparatus in the above method embodiments.

[0319] It is understood that device 3000 can specifically be the first device or the second device in the above embodiments, or it can be a chip or a chip system. Correspondingly, the communication circuit can be the interface circuit of the chip, or an input / output circuit, which is not limited here. Specifically, device 3000 can be used to execute the various steps and / or processes corresponding to the first device or the second device in the above method embodiments.

[0320] When the communication device 3000 is used to achieve Figure 8 , Figure 9 , Figure 10 or Figure 11 In the method shown, the processor 3010 is used to implement the functions of the processing unit 2010, and the transceiver 3020 is used to implement the functions of the transceiver unit 2020.

[0321] When the aforementioned communication device is a chip or OTT device applied to the first device, the chip or OTT device of the first device implements the functions of the first device in the above method embodiments, for example, implementing the processing functions of the first device. The chip or OTT device of the first device receiving information from the second device can be understood as the information being first received by other modules (such as radio frequency modules or antennas) in the first device, and then sent by these modules to the chip or OTT device of the first device. The chip or OTT device of the first device sending information to the second device can be understood as the information being first sent by the chip or OTT device of the first device to other modules (such as radio frequency modules or antennas) in the first device, and then sent by these modules to the second device.

[0322] When the aforementioned communication device is a chip or OTT device applied to the second device, the chip or OTT device of the second device implements the functions of the second device in the above method embodiments, for example, implementing the processing functions of the second device. The chip or OTT device of the second device receiving information from the first device can be understood as the information being first received by other modules (such as radio frequency modules or antennas) in the second device, and then sent by these modules to the chip or OTT device of the second device. The chip or OTT device of the second device sending information to the first device can be understood as the information being first sent by the chip or OTT device of the second device to other modules (such as radio frequency modules or antennas) in the second device, and then sent by these modules to the first device.

[0323] It is understood that, in order to achieve the functions in the above embodiments, the first device and the second device include hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and method steps of the various examples described in conjunction with the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application scenario and design constraints of the technical solution.

[0324] It is understood that the processor in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), image processors, artificial intelligence processors, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0325] The method steps in the embodiments of this application can be implemented in hardware or in software instructions executable by a processor. The software instructions can consist of corresponding software modules, which can be stored in random access memory, flash memory, read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. The storage medium can also be a component of the processor. The processor and the storage medium can reside in an ASIC. Alternatively, the ASIC can reside in a first device or a second device. The processor and the storage medium can also exist as discrete components in the first device or the second device.

[0326] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this application are performed entirely or partially. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user equipment, or other programmable device. The computer program or instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; it can also be an optical medium, such as a digital video optical disc; or it can be a semiconductor medium, such as a solid-state drive. The computer-readable storage medium may be a volatile or non-volatile storage medium, or may include both types of storage media.

[0327] In the above embodiments, unless otherwise specified or there is a logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced by each other. The technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationships.

[0328] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0329] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0330] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0331] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0332] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0333] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0334] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A communication method characterized by comprising: Comprising: determining first channel state information, CSI, and second CSI; sending a first CSI report, the first CSI report comprising the first CSI and not comprising the second CSI; wherein a priority of the first CSI is higher than a priority of the second CSI; a priority of a target CSI is related to first information, the first information comprising one or more of: a time domain resource unit of a reference signal resource set used to obtain the target CSI, a prediction time unit corresponding to the target CSI, prediction probability information or prediction confidence information included in the target CSI, signal quality information included in the target CSI, or a way of obtaining the signal quality information included in the target CSI; the way of obtaining comprising measuring the signal quality information included in the target CSI with respect to the reference signal resource set used to obtain the target CSI, or predicting the signal quality information included in the target CSI with respect to the reference signal resource set used to obtain the target CSI; the target CSI comprising the first CSI or the second CSI, the reference signal resource set comprising one or more reference signal resources.

2. The method of claim 1, wherein, the first information comprising signal quality information included in the target CSI; the priority of the first CSI being higher than the priority of the second CSI comprises: a signal quality indicated by the signal quality information included in the first CSI is higher than a signal quality indicated by the signal quality information included in the second CSI; or, a signal quality indicated by the signal quality information included in the first CSI belongs to a first signal quality range, a signal quality indicated by the signal quality information included in the second CSI belongs to a second signal quality range, and a minimum value of the first signal quality range is greater than a maximum value of the second signal quality range.

3. The method of claim 1, wherein, the first information comprising prediction probability information included in the target CSI; the priority of the first CSI being higher than the priority of the second CSI comprises: a prediction probability indicated by the prediction probability information included in the first CSI is greater than a prediction probability indicated by the prediction probability information included in the second CSI; or, a prediction probability indicated by the prediction probability information included in the first CSI belongs to a first probability range, a prediction probability indicated by the prediction probability information included in the second CSI belongs to a second probability range, and a minimum value of the first probability range is greater than a maximum value of the second probability range.

4. The method of claim 1, wherein, the first information comprising prediction confidence information included in the target CSI; the priority of the first CSI being higher than the priority of the second CSI comprises: a prediction confidence indicated by the prediction confidence information included in the first CSI is greater than a prediction confidence indicated by the prediction confidence information included in the second CSI; or, a prediction confidence indicated by the prediction confidence information included in the first CSI belongs to a first confidence range, a prediction confidence indicated by the prediction confidence information included in the second CSI belongs to a second confidence range, and a minimum value of the first confidence range is greater than a maximum value of the second confidence range.

5. The method of claim 1, wherein, The first information comprises: an acquisition manner of signal quality information included in the target CSI; The priority of the first CSI is higher than the priority of the second CSI, comprising: The acquisition manner of signal quality information included in the first CSI is measuring the signal quality information included in the first CSI on a reference signal resource set used for obtaining the first CSI, and the acquisition manner of signal quality information included in the second CSI is predicting the signal quality information included in the second CSI on a reference signal resource set used for obtaining the second CSI.

6. The method of claim 1, wherein, The first information comprises: a prediction time unit corresponding to the target CSI; The priority of the first CSI is higher than the priority of the second CSI, comprising: The prediction time unit corresponding to the first CSI is earlier than the prediction time unit corresponding to the second CSI; or, The prediction time unit corresponding to the first CSI belongs to a first time unit range, the prediction time unit corresponding to the second CSI belongs to a second time unit range, and any time unit in the first time unit range is earlier than any time unit in the second time unit range.

7. The method of claim 1, wherein, The first information comprises: a time domain resource unit of a resource set used for obtaining the target CSI; The priority of the first CSI is higher than the priority of the second CSI, comprising: The time domain resource unit of the reference signal resource set used for obtaining the first CSI is later than the time domain resource unit of the reference signal resource set used for obtaining the second CSI; or, The time domain resource unit of the reference signal resource set used for obtaining the first CSI belongs to a first time domain resource unit range, the time domain resource unit of the reference signal resource set used for obtaining the second CSI belongs to a second time domain resource unit range, and any time domain resource unit in the first time domain resource unit range is later than any time domain resource unit in the second time domain resource unit range.

8. The method of claim 1, wherein, The first information comprises: a prediction time unit corresponding to the target CSI and second information; the second information comprises one or more of: prediction probability information or prediction confidence information included in the target CSI, or signal quality information included in the target CSI; The priority of the target CSI is related to the first information, comprising: The priority of the target CSI is related to a first priority rule and / or a second priority rule, the priority of the first priority rule is higher than the priority of the second priority rule, the first priority rule is related to a prediction time unit corresponding to the target CSI, and the second priority rule is related to the second information.

9. The method of claim 1, wherein, The first information comprises: a time domain resource unit of a reference signal resource set used for obtaining the target CSI and signal quality information included in the target CSI; The priority of the target CSI is related to the first information, comprising: The priority of the target CSI is related to a third priority rule and / or a fourth priority rule, a priority of the third priority rule is higher than a priority of the fourth priority rule, the third priority rule is related to a time domain resource unit of a reference signal resource set used for obtaining the target CSI, and the fourth priority rule is related to signal quality information included in the target CSI.

10. The method according to any one of claims 1 to 9, characterized in that, The target CSI includes one or more of the following: identification information of a reference signal resource corresponding to the target CSI; signal quality information corresponding to the reference signal resource corresponding to the target CSI; prediction probability information or prediction confidence information corresponding to the reference signal resource corresponding to the target CSI; or monitoring index information corresponding to the reference signal resource corresponding to the target CSI.

11. The method according to any one of claims 1 to 10, characterized in that, The first CSI and the second CSI correspond to different spatial domain resources.

12. A communications device, characterized by A module or unit for performing the method of any one of claims 1 to 11.

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