Communication method and communication apparatus

Abstract

The present application provides a communication method and a communication apparatus. The method may comprise: sending or receiving first data on the basis of a first communication configuration, wherein the first communication configuration is associated with a first identifier; acquiring a data set, wherein the data set comprises at least one of the first data, second data, and a first communication metric, the second data is the first data that has nonlinearity, and the first communication metric indicates transmission performance of the first data; and determining that the data set is associated with the first identifier. On this basis, the indication overhead of a nonlinear data set can be reduced.

Description

Communication methods and communication devices

[0001] This application claims priority to Chinese Patent Application No. 202510240728.X, filed on February 28, 2025, entitled "Communication Method and Communication Device", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of communications, and more specifically, to a communication method and a communication apparatus. Background Technology

[0003] Artificial intelligence (AI) technology has been successfully applied in image processing and natural language processing, and its increasing maturity will play a significant role in driving the evolution of future mobile communication network technologies. Currently, AI technology can be applied to the network layer (e.g., network optimization, mobility management, resource allocation) or the physical layer (e.g., channel coding and decoding, channel prediction, receivers), among other things. Commonly used AI techniques include reinforcement learning, supervised learning, and unsupervised learning.

[0004] Devices such as power amplifiers (PAs) have a linear operating range for amplifying radio frequency (RF) signals. Increasing power to improve coverage may enter the nonlinear region of RF devices, thus affecting the performance of the communication link. Traditional methods include power back-off, digital pre-distortion (DPD), low peak-to-average power ratio (PAPR) waveforms, and sequence design to reduce the impact of nonlinearity on system performance. Furthermore, AI models can also be used to compensate for nonlinearity. However, AI technology is a data-driven technology, and in dynamic wireless networks, how to indicate datasets with low overhead is a pressing problem to be solved in this field. Summary of the Invention

[0005] This application provides a communication method and a communication device that can reduce the indication overhead of nonlinear datasets.

[0006] Firstly, a communication method is provided. This method can be applied to a first device (e.g., a terminal device or a network device), meaning the method can be executed by the first device or by components of the first device (e.g., a chip, chip system, circuit, communication module, or processor), and this application does not limit this. The following description primarily uses a first device as an example.

[0007] The method may include: sending or receiving first data based on a first communication configuration associated with a first identifier; obtaining a dataset including at least one of the first data, second data, and a first communication metric, wherein the second data is the first data containing nonlinearity, and the first communication metric indicates the transmission performance of the first data; and determining that the dataset is associated with the first identifier.

[0008] Based on the above technical solution, the first device can send or receive first data based on the first communication configuration associated with the first identifier, and associate the corresponding nonlinear dataset with the first identifier. It is understood that the nonlinear effect of the link is closely related to the communication configuration, and the acquisition and monitoring of nonlinear data requires association with a specific communication configuration. Based on the above technical solution, the first device can associate the first communication configuration with the corresponding nonlinear dataset through the first identifier. Subsequently, the first device or other communication devices can indicate the nonlinear dataset associated with the first communication configuration through the first identifier, thereby reducing the indication overhead of the nonlinear dataset. Conversely, if the nonlinear dataset is directly indicated through the first communication configuration, considering that the communication configuration may contain multiple parameters, the indication overhead of the nonlinear dataset is high.

[0009] In conjunction with the first aspect, in some implementations of the first aspect, the first communication configuration includes at least one of the following: the transmission power of the first data, the transmission bandwidth of the first data, the modulation order of the first data, the transmission waveform of the first data, the precoding matrix for transmitting the first data, the reference signal configuration, or the spread spectrum sequence of the first data.

[0010] Based on the above technical solution, the first communication configuration may include multiple communication configurations. The first device associates the multiple configurations with the nonlinear datasets corresponding to the multiple configurations through a first identifier. Subsequently, the first device or other communication devices can indicate the nonlinear datasets associated with the multiple configurations through the first identifier, thereby reducing the indication overhead of the nonlinear datasets.

[0011] In conjunction with the first aspect, in some implementations of the first aspect, the method can be applied to a terminal device, wherein sending or receiving first data based on the first communication configuration includes: sending the first data based on the first communication configuration; before sending the first data, the method may further include: sending first indication information, the first indication information indicating the power margin of the terminal device for sending data, the power margin including a power indication of a non-linear region; and receiving second indication information, the second indication information indicating the power for sending the first data.

[0012] In conjunction with the first aspect, in some implementations of the first aspect, the method can be applied to a network device, wherein sending or receiving first data based on the first communication configuration includes: receiving the first data based on the first communication configuration; before receiving the first data, the method further includes: receiving first indication information, the first indication information indicating the power margin of the terminal device for sending data; and sending second indication information, the second indication information indicating the power of the terminal device for sending the first data.

[0013] Based on the above technical solution, in the case of uplink transmission, the terminal device can report its own power margin by sending a first indication message, and the network device can send a second indication message to the terminal device. The second indication message can indicate the specific power of the terminal device in transmitting the first data uplink. The aforementioned power margin can include a power indication of the non-linear region, thereby causing the dataset acquired by the first device to contain non-linear distortion.

[0014] In conjunction with the first aspect, in some implementations of the first aspect, the first identifier is a cell-level identifier.

[0015] Based on the above technical solution, the first identifier can be a cell-level identifier, or in other words, the first identifier can be maintained within the cell where the terminal device is located, thereby reducing the indication overhead of the first identifier.

[0016] Secondly, a communication method is provided. This method can be applied to a second device (e.g., a terminal device or a network device), meaning that the method can be executed by the second device or by components of the second device (e.g., a chip, chip system, circuit, communication module, or processor), and this application does not limit this. The following description primarily uses a second device as an example.

[0017] The method may include: obtaining a dataset based on a first identifier, the first identifier being associated with a first communication configuration, the dataset including at least one of first data, second data, and a first communication metric, the first data being sent or received based on the first communication configuration, the second data being the first data containing nonlinearity, and the first communication metric indicating the transmission performance of the first data; training a first model based on the dataset to obtain a second model, the second model being used to compensate for nonlinear distortion in data transmission.

[0018] Based on the above technical solution, the second device can obtain the nonlinear dataset associated with the first communication configuration based on the first identifier. It is understood that the nonlinear effect of the link is closely related to the communication configuration, and obtaining the nonlinear dataset requires associating it with a specific communication configuration. Considering that the communication configuration may contain multiple parameters, the above technical solution can reduce the indication overhead of the dataset.

[0019] In conjunction with the second aspect, in some implementations of the second aspect, the first communication configuration includes at least one of the following: the transmission power of the first data, the transmission bandwidth of the first data, the modulation order of the first data, the transmission waveform of the first data, the precoding matrix for transmitting the first data, the reference signal configuration, or the spreading sequence of the first data.

[0020] In conjunction with the second aspect, in some implementations of the second aspect, the method may further include: associating the second model with the first identifier and / or the second identifier, the second identifier including the identifier (ID) of the terminal device and / or the ID of the group to which the terminal device belongs, the terminal device being the terminal device that sends or receives the first data.

[0021] Based on the above technical solution, the second device can associate the second model trained on the nonlinear dataset with the first identifier and / or the second identifier. It is understood that the nonlinear effect of the link is closely related to the communication configuration. Managing the model used to compensate for nonlinear distortion in data transmission requires associating it with a specific communication configuration. Considering that the communication configuration may contain multiple parameters, the above technical solution can reduce the model's indication overhead.

[0022] Furthermore, the second identifier may include UEID and / or UE group ID. It is understood that the nonlinear effect of the link is related to specific radio frequency devices. For example, the nonlinear effect of the link may be directly related to specific terminal devices. In the above technical solution, the second model is further associated with UEID and / or UE group ID, which can enable the second model to compensate for nonlinear distortion for specific UEs or UE groups and enhance the nonlinear compensation effect of the second model.

[0023] In conjunction with the second aspect, in some implementations of the second aspect, the method can be applied to a terminal device. After the second model is obtained by training the first model based on the dataset, the method may further include: sending a request message, the request message requesting the maximum transmission power of the terminal device; and receiving a third indication message, the third indication message indicating the maximum transmission power.

[0024] Based on the above technical solution, after the terminal device obtains the corresponding second model through training, it can use the second model to compensate for the nonlinear distortion generated when it transmits data with higher power. Therefore, the terminal device can request to update its maximum transmission power by sending a request message, thereby improving the transmission performance of the terminal device.

[0025] In conjunction with the second aspect, in some implementations of the second aspect, the request information includes key performance indicators (KPIs) of the first data transmission, and the maximum transmission power indicated by the third indication information is determined based on the KPIs.

[0026] Based on the above technical solution, the maximum transmission power of the terminal device can be determined based on the KPI of the first data transmission. That is, the network device can more accurately determine and indicate the updated maximum transmission power of the terminal device based on the quality of the first data transmission.

[0027] In conjunction with the second aspect, in some implementations of the second aspect, the method can be applied to network devices. After the second model is obtained by training the first model based on the dataset, the method further includes: determining the maximum transmission power based on the KPI of the first data transmission.

[0028] In conjunction with the second aspect, in some implementations of the second aspect, the maximum transmission power is the maximum transmission power of the terminal device, and the method may further include: sending third indication information to the terminal device, the third indication information indicating the maximum transmission power of the terminal device.

[0029] For some of the beneficial effects and possible designs of the second aspect, please refer to the relevant description in the first aspect, which will not be repeated here.

[0030] Thirdly, a communication method is provided. This method can be applied to a third device (e.g., a terminal device or a network device), meaning that the method can be executed by the terminal device or the network device, or by components of the third device (e.g., a chip, a chip system, a circuit, a communication module, or a processor), and this application does not limit this. The following description primarily uses a third device as an example.

[0031] The method may include: obtaining a second model based on a first identifier and / or a second identifier, wherein the first identifier is associated with a first communication configuration, the second identifier includes the ID of a terminal device and / or the ID of the group to which the terminal device belongs, the terminal device being a terminal device that sends or receives first data, the first data being sent or received based on the first communication configuration, the second model being used to compensate for nonlinear distortion in data transmission, the second model being obtained by training a first model based on a dataset, the dataset including at least one of the first data, second data, and a first communication metric, the second data being the first data containing nonlinearity, and the first communication metric indicating the transmission performance of the first data; and sending or receiving the second data through the second model.

[0032] Based on the above technical solution, the third device can obtain the second model based on the first identifier and / or the second identifier. It is understood that the nonlinear effect of the link is closely related to the communication configuration. Obtaining a model to compensate for nonlinear distortion in data transmission requires associating it with the specific communication configuration. Considering that the communication configuration may contain multiple parameters, the above technical solution can reduce the indication overhead of obtaining the model.

[0033] In conjunction with the third aspect, in some implementations of the third aspect, the method can be applied to a network device. Before obtaining the second model based on the first identifier and / or the second identifier, the method may further include: sending a third identifier, the third identifier including the ID of the terminal device currently maintained by the network device and / or the ID of the group to which the terminal device belongs; and receiving the second identifier.

[0034] Based on the above technical solution, the network device can request a second identifier associated with the second model by sending the currently maintained UEID and / or UE group ID. It is understood that the UEID or UE group ID may not be a fixed value for the cell; for example, the network device may not be able to obtain the second identifier associated with the second model due to security or privacy issues. Based on the above technical solution, the mapping from the network device's currently maintained UEID and / or UE group ID to the second identifier can be completed on other communication devices (e.g., the core network). For example, the second identifier can be the UEID and / or UE group ID used during model training, and the other communication device can indicate the second identifier to the network device.

[0035] In conjunction with the third aspect, in some implementations of the third aspect, the method can be applied to a terminal device, and the method may further include: sending a fourth identifier associated with a second communication configuration, the second communication configuration not used to train a model associated with the terminal device for compensating for nonlinear distortion in data transmission; and receiving the first identifier.

[0036] Based on the above technical solution, when a terminal device requests to obtain a model associated with the terminal device that is not used for training to compensate for nonlinear distortion in data transmission, the network device can indicate a first identifier to the terminal device. This first identifier can be associated with a trained model, thereby achieving nonlinear compensation without retraining the model and saving model training time.

[0037] Fourthly, a communication apparatus is provided for performing the methods of any one of the first to third aspects and any possible implementation thereof. Specifically, the apparatus may include units and / or modules for performing the methods of any one of the first to third aspects and any possible implementation thereof, such as processing units and / or communication units.

[0038] In one implementation, the device is a communication device (such as a terminal device or a network 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.

[0039] In another implementation, the device is a chip, chip system, circuit, or communication module for communication equipment (such as terminal equipment or network equipment). When the device is a chip, chip system, or circuit for communication equipment, 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.

[0040] Fifthly, a communication device is provided, the device comprising: at least one processor configured to cause the device to perform the methods of any one of the first to third aspects and any possible implementation thereof.

[0041] Optionally, the at least one processor is configured to execute computer programs or instructions to perform the methods of any one of the first to third aspects and any possible implementation thereof.

[0042] Optionally, the device further includes a memory for storing the computer program or instructions.

[0043] Optionally, the at least one processor is coupled to a memory for storing the computer program or instructions. The memory may be located externally to the device.

[0044] Optionally, the device also includes a communication interface through which the processor reads instructions from memory. This can be understood as the communication interface being coupled to the processor and used to input computer programs or instructions to the processor, or to output information from the processor.

[0045] Unless otherwise specified, or if the transmission and acquisition / reception operations involved do not contradict their actual function or internal logic in the relevant description, they can be understood as output, input, or other operations, or as transmission and reception operations performed by radio frequency circuits and antennas. This application does not limit them in this regard.

[0046] In one implementation, the device is a communication device (such as a terminal device or a network device).

[0047] In another implementation, the device is a chip, chip system, circuit, or communication module for communication equipment (such as terminal equipment or network equipment). Optionally, the chip is a modem chip, also known as a baseband chip, or a system-on-chip (SoC) chip containing a modem core, or a system-in-package (SIP) chip.

[0048] In a sixth aspect, a computer-readable storage medium is provided, on which a computer program (e.g., program code) or instructions are stored, which, when executed on a communication device, cause the communication device to perform the methods of any one of the first to third aspects and any possible implementation thereof.

[0049] In a seventh aspect, a computer program product comprising instructions is provided, which, when run on a computer, causes the computer to perform the methods of any one of the first to third aspects and any possible implementation thereof.

[0050] Eighthly, a communication system is provided, including a first communication device and a second communication device. The first communication device is used to execute the method provided in any one of the implementations of the first to third aspects, and the second communication device is used to execute the method provided in any one of the implementations of the first to third aspects. Attached Figure Description

[0051] Figure 1 is a schematic diagram of a communication system applicable to an embodiment of this application.

[0052] Figure 2 is a schematic diagram of another communication system applicable to the embodiments of this application.

[0053] Figure 3 is a schematic diagram of link nonlinearity compensation using an AI model applicable to an embodiment of this application.

[0054] Figure 4 is a schematic diagram of a communication method 400 provided in an embodiment of this application.

[0055] Figure 5 is a schematic diagram of a communication method 500 provided in an embodiment of this application.

[0056] Figure 6 is a schematic diagram of a communication method 600 provided in an embodiment of this application.

[0057] Figure 7 is a schematic diagram of a communication method 700 provided in an embodiment of this application.

[0058] Figure 8 is a schematic diagram of a communication method 800 provided in an embodiment of this application.

[0059] Figure 9 is a schematic diagram of a communication method 900 provided in an embodiment of this application.

[0060] Figure 10 is a schematic diagram of a communication method 1000 provided in an embodiment of this application.

[0061] Figure 11 is a schematic diagram of a communication method 1100 provided in an embodiment of this application.

[0062] Figure 12 is a schematic diagram of a communication method 1200 provided in an embodiment of this application.

[0063] Figure 13 is a schematic diagram of a communication method 1300 provided in an embodiment of this application.

[0064] Figure 14 is a schematic diagram of a communication method 1400 provided in an embodiment of this application.

[0065] Figure 15 is a schematic diagram of a communication device 1500 provided in an embodiment of this application.

[0066] Figure 16 is a schematic diagram of another communication device 1600 provided in an embodiment of this application.

[0067] Figure 17 is a schematic diagram of a chip system 1700 provided in an embodiment of this application. Detailed Implementation

[0068] To facilitate understanding of the above embodiments provided in this application, the following points are made:

[0069] 1) In this application, unless otherwise specified or in case of logical conflict, 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.

[0070] 2) In this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. 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 preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, and c can mean: a, or, b, or, c, or, a and b, or, a and c, or, b and c, or, a, b, and c. Here, a, b, and c can each be single or multiple.

[0071] 3) In this application, the terms "first," "second," and various numerical designations (e.g., #1, #2, etc.) indicate distinctions made for ease of description and are not intended to limit the scope of the embodiments of this application. For example, they may distinguish different messages, rather than describing a specific order or sequence. It should be understood that such descriptions can be interchanged where appropriate to describe solutions other than those in the embodiments of this application.

[0072] 4) In this application, descriptions such as “when…”, “under the circumstances of…” and “if” all refer to the fact that the device will make corresponding processing under certain objective circumstances. They are not time limits, nor do they require the device to make a judgment action when it is implemented, nor do they mean that there are other limitations.

[0073] 5) In this application, "instruction" or "for instruction" can include both direct and indirect instruction. When describing an instruction as being used to instruct A, it may include whether the instruction directly instructs A or indirectly instructs A, but does not necessarily mean that the instruction carries A.

[0074] The indication methods involved in the embodiments of this application should be understood to cover various methods that enable the party to be indicated to obtain the information to be indicated. The information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately. Moreover, the sending period and / or sending time of these sub-information can be the same or different. This application does not limit the sending method, for example.

[0075] The "instruction information" in the embodiments of this application can be an explicit instruction, that is, a direct instruction through signaling, or an instruction obtained by combining other rules or parameters with the parameters indicated by the signaling, or by deduction. It can also be an implicit instruction, that is, an instruction obtained based on rules or relationships, or based on other parameters, or by deduction. This application does not specifically limit it in this regard.

[0076] 6) In this application, "protocol" can refer to a standard protocol in the field of communications, such as the 5G protocol, the new radio (NR) protocol, and related protocols applied to future communication systems. This application does not limit this term. "Predefined" can include predefined terms, such as protocol definitions. "Preconfiguration" can be implemented by pre-storing corresponding codes, tables, or other means that can be used to indicate relevant information in the device. This application does not limit the implementation method, for example.

[0077] 7) In this application, "communication" can also be described as "data transmission", "information transmission", "data processing", etc. "Transmission" includes "sending" and "receiving". "Transmission" can be described as "output".

[0078] 8) In this application, "sending information to XX (device)" can be understood as the destination of the information being that device. This can include sending information directly or indirectly to that device. "Receiving information from XX (device), or receiving information from XX (device)" can be understood as the source of the information being that device, and can include receiving information directly or indirectly from that device. Information may undergo necessary processing between the source and destination, such as format changes, but the destination can understand the valid information from the source. Similar expressions in this application can be interpreted similarly, and will not be elaborated further here.

[0079] 9) In this application, the terms "exemplarily," "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 term "example" is intended to present concepts in a concrete manner. In the embodiments of this application, "of," "corresponding, relevant," and "corresponding" may sometimes be used interchangeably, and it should be noted that their intended meanings are consistent unless their distinction is emphasized.

[0080] The technical solutions in this application will now be described with reference to the accompanying drawings.

[0081] The technical solutions of this application can be applied to various communication systems, such as: Long Term Evolution (LTE) systems, LTE Frequency Division Duplex (FDD) systems, LTE Time Division Duplex (TDD) systems, 5th Generation (5G) systems or NR systems, and future communication systems, such as future mobile communication 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.

[0082] Furthermore, the embodiments of this application are applicable to both homogeneous and heterogeneous network scenarios, and there are no restrictions on the transmission points. They can be applied to systems such as multi-point collaborative transmission between macro base stations, micro base stations, and macro base stations. The embodiments of this application are applicable to both low-frequency and high-frequency scenarios, including terahertz and optical communications.

[0083] In a communication system, a device can send signals to or receive signals from another device. These signals may include reference signals, information, signaling, or data. In this application, "device" can be replaced by an entity, network entity, communication equipment, communication module, node, or communication node.

[0084] Referring to Figure 1, as an example, Figure 1 is a schematic diagram of a communication system applicable to an embodiment of this application. As shown in Figure 1, the communication system 10 includes a radio access network (RAN) 100 and a core network (CN) 200. RAN 100 includes at least one RAN node (110a and 110b in Figure 1, collectively referred to as 110) and at least one terminal (120a-120j in Figure 1, collectively referred to as 120). RAN 100 may also include other RAN nodes, such as wireless relay devices and / or wireless backhaul devices (not shown in Figure 1). Terminal 120 is wirelessly connected to RAN node 110. RAN node 110 is wirelessly or wired connected to core network 200. The core network devices in core network 200 and RAN node 110 in RAN 100 can be different physical devices, or they can be the same physical device integrating core network logical functions and radio access network logical functions.

[0085] RAN 100 can be a cellular system related to the 3rd Generation Partnership Project (3GPP), such as a 4G mobile communication system, a 5G mobile communication system, or a future-oriented evolution system (such as a future mobile communication system). RAN 100 can also be an open access network (open RAN, O-RAN, or ORAN), a cloud radio access network (CRAN), or a wireless fidelity (WiFi) system. RAN 100 can also be a communication system that integrates two or more of the above systems.

[0086] RAN node 110, sometimes also referred to as network equipment, access network equipment, RAN entity, or access node, constitutes part of the communication system and is used to help terminals achieve wireless access. Multiple RAN nodes 110 in communication system 10 can be of the same type or different types. In some scenarios, the roles of RAN node 110 and terminal 120 are relative. For example, network element 120i in Figure 1 can be a helicopter or drone, which can be configured as a mobile base station. For terminals 120j accessing RAN 100 through network element 120i, network element 120i is a base station; but for base station 110a, network element 120i is a terminal. RAN node 110 and terminal 120 are sometimes both referred to as communication devices. For example, network elements 110a and 110b in Figure 1 can be understood as communication devices with base station functions, and network elements 120a-120j can be understood as communication devices with terminal functions.

[0087] In one possible scenario, a RAN node can be a base station (BS), an evolved NodeB (eNodeB), an access point (AP), a transmission reception point (TRP), a next-generation NodeB (gNB), a next-generation base station in a future mobile communication system, a base station in a future mobile communication system, or an access node in a WiFi system. A RAN node can be a macro base station (as shown in Figure 1, 110a), a micro base station or indoor station (as shown in Figure 1, 110b), a relay node or donor node, or a radio controller in a CRAN scenario. 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).

[0088] In another possible scenario, multiple RAN nodes collaborate to assist the terminal in achieving wireless access, with different RAN nodes each implementing a portion of the base station's functions. For example, RAN nodes can be central units (CUs), distributed units (DUs), CU-control planes (CU-CPs), CU-user planes (CU-UPs), radio units (RUs), or CU-radio units (CU-RUs), etc. CUs and DUs can be configured separately or included in the same network element, such as a baseband unit (BBU). RUs can be included in radio equipment or radio units, such as remote radio units (RRUs), active antenna units (AAUs), or remote radio heads (RRHs).

[0089] In different systems, CU (including open CU-CP (O-CU-CP) and open CU-UP (O-CU-UP), DU, or RU may have different names, but those skilled in the art will understand their meaning. For example, in an ORAN system, CU can also be called an open central unit (O-CU), DU can also be called an open distributed unit (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. For ease of description, this application uses CU, CU-CP, CU-UP, DU, and RU as examples. 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 and hardware modules.

[0090] Terminal 120 can be a device or module that accesses the aforementioned communication system and has corresponding communication functions. A terminal can also be referred to as user equipment (UE), terminal, user device, access terminal, user unit, user station, mobile station, mobile station (MS), remote station, remote terminal, mobile device, user terminal, terminal unit, terminal station, terminal device, wireless communication equipment, user agent, or user device. A terminal typically contains a communication module, circuit, or chip that performs the corresponding communication functions. The terminal may also be configured with program instructions for performing these communication functions.

[0091] For example, the terminal in this application embodiment can be a mobile phone, a personal digital assistant (PDA) computer, a laptop computer, a tablet computer, a drone, a computer with wireless transceiver capabilities, a machine type communication (MTC) terminal, a virtual reality (VR) terminal, an augmented reality (AR) terminal, an Internet of Things (IoT) terminal, a wireless terminal in industrial control, a wireless terminal in self-driving, a wireless terminal in remote medical care, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, a wireless terminal in a smart home (e.g., game consoles, smart TVs, smart speakers, smart refrigerators, and fitness equipment), a transport vehicle with wireless communication capabilities, a communication module, or a roadside unit (RSU) with terminal capabilities.

[0092] RAN 100 and terminal 120 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 aircraft, balloons, and satellites. The embodiments of this application do not limit the scenarios in which RAN 100 and terminal 120 are located.

[0093] Communication between access network devices and terminal devices follows a specific protocol layer structure. This protocol layer may include a control plane protocol layer and a user plane protocol layer. The control plane protocol layer may include at least one of the following: radio resource control (RRC) layer, packet data convergence protocol (PDCP) layer, radio link control (RLC) layer, medium access control (MAC) layer, or physical (PHY) layer, etc. The user plane protocol layer may include at least one of the following: service data adaptation protocol (SDAP) layer, PDCP layer, RLC layer, MAC layer, or physical layer, etc.

[0094] The correspondence between network elements and their achievable protocol layer functions in the ORAN system can be found in Table 1 below.

[0095] Table 1

[0096] CN 200 can be the core network of a future communication system, a 5G core network, or an evolved 5G core network. Taking a 5G core network as an example, CN 200 includes access and mobility management (AMF) network elements responsible for mobility management and access management services; session management (SMF) network elements responsible for session management; user plane (UPF) network elements responsible for user plane packet routing and forwarding and quality of service (QoS) control; and policy control (PCF) network elements. These core network elements can work independently or be combined to implement certain control functions. For example, AMF, SMF, and PCF can be combined into a single core network device.

[0097] The communication system 10 provided in this application may further include AI network elements for implementing some or all AI-related operations. AI network elements may also be referred to as AI nodes, AI devices, AI entities, AI modules, AI models, or AI units, etc. The AI ​​network elements may be built into the network elements of the communication system. For example, an AI network element may be an AI module built into access network equipment, core network equipment, cloud servers, or operation, administration and maintenance (OAM) management systems to implement AI-related functions. The OAM may be the management system for core network equipment and / or the management system for access network equipment. Alternatively, the AI ​​network element may be an independently configured network element in the communication system. Optionally, the terminal or its built-in chip may also include an AI entity for implementing AI-related functions.

[0098] Referring to Figure 2, as an example, Figure 2 is a schematic diagram of another communication system applicable to embodiments of this application. As shown in Figure 2, network elements in the communication system are connected through interfaces (e.g., NG, Xn) or air interfaces. These network element nodes, such as core network equipment, access network nodes (RAN nodes), terminals, or one or more devices in OAM, are equipped with one or more AI modules (only one is shown in Figure 5 for clarity). The access network node can be a single RAN node or can include multiple RAN nodes, for example, including CU and DU. The CU and / or DU can also be equipped 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 set in CU-CP and / or CU-UP.

[0099] 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.

[0100] 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.

[0101] AI technology has been successfully applied in image processing and natural language processing, and its increasing maturity will significantly drive the evolution of future mobile communication network technologies. Currently, AI technology can be applied to the network layer (e.g., network optimization, mobility management, resource allocation) or the physical layer (e.g., channel coding and decoding, channel prediction, receivers). Commonly used AI techniques include reinforcement learning, supervised learning, and unsupervised learning.

[0102] Devices such as power amplifiers (PAs) have a linear operating range for amplifying radio frequency (RF) signals. Increasing power to improve coverage may enter the nonlinear region of RF devices, thus affecting the performance of the communication link. Traditional methods include power back-off, digital pre-distortion (DPD), low peak-to-average power ratio (PAPR) waveforms, and sequence design to reduce the impact of nonlinearity on system performance. Furthermore, AI models can also be used to compensate for nonlinearity. However, AI technology is a data-driven technology. In dynamic wireless networks, collecting real-world data and using that data for model training is one of the important ways to improve the performance of wireless AI models.

[0103] Referring to Figure 3, as an example, Figure 3 is a schematic diagram of link nonlinear compensation using an AI model applicable to an embodiment of this application.

[0104] As an example, as shown in Figure 3, an AI compensation link, or rather, an AI compensation model, can be set up between the transmitting and receiving sides of a communication system to compensate for nonlinear distortion in the link. In Figure 3, the location of the AI ​​compensation model can be indicated by dashed lines. For example, the AI ​​compensation model can be deployed on the transmitting side, or it can be deployed on the receiving side.

[0105] The nonlinear effects of a link are highly dependent on communication configuration. The acquisition and monitoring of nonlinear data require association with specific communication configurations. If the nonlinear dataset is directly indicated through the communication configuration, the overhead of indicating the nonlinear dataset is high, considering that the communication configuration may contain multiple parameters. Therefore, this application proposes that first data can be sent or received based on a first communication configuration associated with a first identifier, and the corresponding nonlinear dataset can be associated with the first identifier, thereby reducing the overhead of indicating subsequent nonlinear datasets.

[0106] The methods provided by the embodiments of this application will be described in detail below with reference to the accompanying drawings. The embodiments provided by this application can be applied to the scenarios shown in the above figures, and are not limited thereto.

[0107] Referring to Figure 4, as an example, Figure 4 is a schematic diagram of a communication method 400 provided in an embodiment of this application. For ease of description, the following illustrative example uses a first device (e.g., a terminal device or a network device) and device #A (e.g., a network device or a terminal device). The first device can be replaced by a component of the first device (e.g., a chip, a chip system, a circuit, a communication module, or a processor), and device #A can be replaced by a component of device #A (e.g., a chip, a chip system, a circuit, a communication module, or a processor). Furthermore, the steps described below as being performed by a single execution entity can also be divided into steps performed by multiple execution entities, which can be logically and / or physically separated. The method 400 shown in Figure 4 may include the following steps.

[0108] S410, the first device sends or receives first data based on a first communication configuration. Accordingly, device #A receives or sends the first data based on the first communication configuration.

[0109] As an example, the first device can be a terminal device or a network device. Accordingly, device #A can be a network device or a terminal device. For example, if the first device is a terminal device, then device #A is a network device; if the first device is a network device, then device #A is a terminal device. Thus, S410 can be understood as the terminal device sending first data, and correspondingly, the network device receiving the first data; or, the terminal device receiving the first data, and correspondingly, the network device sending the first data.

[0110] It should be understood that the above description of the first device and device #A is only an example. For examples of terminal equipment and network equipment, please refer to the above text. The embodiments of this application will not repeat the description.

[0111] As an example, the first data can be understood as the data transmitted between the first device and device #A. Data can also be replaced with signals, etc., and its name does not limit the scope of protection of this application embodiment. Furthermore, considering the nonlinear background of data transmission described above, the first data can be further understood as data before nonlinear distortion occurs, or real data, or data to be sent, or data without nonlinearity, or tag data, etc., and this application embodiment does not limit it.

[0112] As an example, communication configuration can be understood as parameters used by a communication device to send or receive data. Communication configuration can also be called communication parameters or configuration parameters, etc. The name does not limit the scope of protection of the embodiments of this application, as long as it can express the same meaning.

[0113] Specifically, the first communication configuration may include / indicate at least one of the following: the transmission power of the first data, the transmission bandwidth of the first data, the modulation order of the first data, the transmission waveform of the first data, the precoding matrix for transmitting the first data, the reference signal configuration, or the spread spectrum sequence of the first data, etc.

[0114] For example, #1, the first communication configuration can indicate: the first data transmission power is 46dBm, the first data transmission bandwidth is 20MHz, the first data modulation order is 64 quadrature amplitude modulation (QAM), the first data transmission waveform is cyclic prefix orthogonal frequency division multiplexing (CP-OFDM), and the precoding matrix for transmitting the first data is... The reference signal is configured as a demodulation reference signal (DMRS), and the spread spectrum sequence of the first data is a Zadoff-Chu (ZC) sequence, etc.

[0115] The first communication configuration is associated with the first identifier. For example, a first table can be configured in the first device, and the first identifier can be associated with the first communication configuration through the first table. The association of the first communication configuration with the first identifier can also be replaced by the correspondence between the first communication configuration and the first identifier, or the first device can determine the first communication configuration through the first identifier, etc., which is not limited in the embodiments of this application.

[0116] It should be understood that the configuration of the first table in the first device described above is merely one possible example. This application does not limit the configuration of the first table to the first device. For example, the first table can be configured in other communication devices, and the first device can request the first communication configuration corresponding to the first identifier from other communication devices through the first identifier. Furthermore, this application does not limit the association method between the first identifier and the first communication configuration.

[0117] As an example, in light of the nonlinear background of data transmission described above, the first communication configuration associated with the first identifier can cause the link between the first device and device #A to become nonlinear. Therefore, the first identifier can also be called a nonlinear identifier, or a nonlinear configuration identifier, or a nonlinear configuration ID, etc., and its name does not limit the scope of protection of the embodiments of this application.

[0118] For example, the first identifier is "1", which is associated with a set of communication configurations in example #1 above.

[0119] As an example, the first device sending or receiving first data based on the first communication configuration can be understood as the first device sending or receiving first data using the communication parameters indicated / included by the first communication configuration, or in other words, the first device sending or receiving first data using the communication parameters associated / corresponding to the first identifier, etc. Correspondingly, device #A receiving or sending first data based on the first communication configuration can be understood as device #A receiving or sending first data using the communication parameters indicated / included by the first communication configuration, or in other words, device #A receiving or sending first data using the communication parameters associated / corresponding to the first identifier, etc. The embodiments of this application do not limit this.

[0120] For example, the first device determines that the first identifier is "1", which is associated with a set of communication configurations in Example #1 above. Then the first device can use the set of communication configurations in Example #1 above to send or receive the first data. Correspondingly, device #A can use the set of communication configurations in Example #1 above to receive or send the first data.

[0121] As an example, the first identifier can be a cell-level identifier. This can also be understood as the first identifier being maintained within the cell where the terminal device is located, or, in other words, the identifier associated with the first communication configuration being fixed within the cell where the terminal device is located, etc. This embodiment of the application does not impose such limitations. The terminal device can be a first device or device #A.

[0122] In this embodiment of the application, by maintaining the first identifier within the cell where the terminal device is located, the indication overhead of the first identifier can be reduced.

[0123] S420, the first device acquires a dataset. The dataset may include at least one of first data, second data, and a first communication indicator.

[0124] As an example, the second data can be the first data that includes nonlinearity. It can also be understood as the second data being the first data after nonlinear distortion, or the first data being transformed into the second data after nonlinearity in the link between the first device and device #A, etc. Alternatively, the second data can be the data obtained after the first data undergoes nonlinear distortion and then passes through a signal processing module; or the second data can be the data obtained after the first data undergoes signal processing and then nonlinear distortion, etc. This application does not limit the specific implementation.

[0125] For example, considering the nonlinear background of data transmission described above, when the first device transmits the first data at a higher power, it enters the nonlinear region of the radio frequency device. As a result, there is nonlinearity in the link between the first device and device #A. Therefore, the data actually transmitted in this link is the second data after the nonlinear distortion of the first data.

[0126] As an example, the first communication indicator can indicate the transmission performance of the first data. It can also be understood as the first communication indicator indicating the degree of nonlinear distortion of the first data, or the first communication indicator indicating the degree of change of the nonlinearized second data relative to the first data, etc., which is not limited in the embodiments of this application.

[0127] Optionally, the first communication indicator can be a key performance indicator (KPI), specifically a KPI for the communication system or a KPI for the current transmission of the first data. As an example, the KPI may include the bit error rate and / or signal-to-interference-plus-noise ratio of the first data transmission. This application embodiment does not limit the specific indicators included, as long as they can indicate the performance of one or more transmissions of the first data.

[0128] For example, when the change of the second data relative to the first data is small, the first communication indicator indicates that the transmission performance of the first data is good, indicating that the nonlinearity of the transmission of the first data in the link between the first device and device #A using the first communication configuration is small; conversely, when the change of the second data relative to the first data is large, the first communication indicator indicates that the transmission performance of the first data is poor, indicating that the nonlinearity of the transmission of the first data in the link between the first device and device #A using the first communication configuration is large.

[0129] It is understandable that, considering that the dataset may contain first data (excluding nonlinearity) and second data after nonlinearity, as well as a first communication metric, the dataset can be used to train an AI model that can be used to compensate for nonlinear distortion in data transmission.

[0130] It should be understood that, for the sake of consistency in the specification, specific descriptions of the first device acquiring the dataset can be found in Examples 1 to 4 below, and the embodiments of this application will not be elaborated here.

[0131] S430, the first device determines that the dataset is associated with the first identifier.

[0132] As an example, S430 can also be understood as the first device associating the dataset obtained in S420 with the first identifier, or the first device associating the first communication configuration with the dataset obtained under the first communication configuration through the first identifier, or the first device associating the first identifier, the first communication configuration and the dataset. This application embodiment does not limit this.

[0133] For example, the first device sends or receives first data according to the first identifier "1" using the first communication configuration of example #1 mentioned above, thereby obtaining dataset #1. Then, in S430, the first device can further associate the first identifier "1" with dataset #1.

[0134] In this embodiment, the first device can send or receive first data based on a first communication configuration associated with a first identifier, and associate the corresponding nonlinear dataset with the first identifier. It is understood that the nonlinear effect of the link is closely related to the communication configuration, and the acquisition and monitoring of nonlinear data requires association with a specific communication configuration. Based on the above technical solution, the first device can associate the first communication configuration with the corresponding nonlinear dataset through the first identifier. Subsequently, the first device or other communication devices can indicate the nonlinear dataset associated with the first communication configuration through the first identifier, thereby reducing the indication overhead of the nonlinear dataset. Conversely, if the nonlinear dataset is directly indicated through the first communication configuration, considering that the communication configuration may contain multiple parameters, the indication overhead of the nonlinear dataset is high.

[0135] The following examples 1 to 4 illustrate four possible processes corresponding to method 400 during downlink transmission, based on the location of data collection and the location where the model to be trained will be deployed.

[0136] Example 1: The model is deployed on a network device, and data collection occurs on the network device.

[0137] Referring to Figure 5, as an example, Figure 5 is a schematic diagram of a communication method 500 provided in an embodiment of this application. In method 500, the network device can correspond to the first device in method 400, and the terminal device can correspond to device #A in method 400. The method 500 shown in Figure 5 may include the following steps.

[0138] S510, the network device sends a data collection instruction. Correspondingly, the terminal device receives the data collection instruction. As an example, the data collection instruction can be used to instruct the terminal device to prepare to start / before starting data collection, or to instruct the terminal device to subsequently provide data feedback.

[0139] Optionally, the data collection instruction may include a first identifier from method 400.

[0140] It is understandable that after receiving the first identifier in the data collection instruction, the terminal device can determine the data corresponding to the first identifier to be received subsequently, which is beneficial for the terminal device to manage the data.

[0141] In S520, the network device sends the first data. Correspondingly, the terminal device receives the first data.

[0142] Specifically, the network device may send the first data using the first communication configuration associated with the first identifier. For a detailed explanation, please refer to the relevant explanation in S410. This application embodiment will not repeat the explanation.

[0143] S530, the terminal device sends second data and / or the first communication indicator. Accordingly, the network device receives the second data and / or the first communication indicator.

[0144] It should be noted that the explanation of the second data and the first communication indicator can be found in the relevant content in S420 above. For example, the second data can be the data after the first data has been affected by the nonlinearity of the link between the network device and the terminal device. This application embodiment will not repeat the explanation here.

[0145] It is understood that the first data can be data known to both the network device and the terminal device prior to method 500. For example, the first data could be a pilot signal. Thus, the terminal device can determine and feedback a first communication indicator based on the received second data and the known first data.

[0146] S540, network devices acquire datasets.

[0147] As an example, as described above in S420, the network device can acquire a dataset. This dataset may include at least one of first data, second data, and a first communication metric.

[0148] The first data is acquired by the network device before it sends the first data, while the second data or the first communication indicator can be received by the network device through S530.

[0149] In step S550, the network device determines that the dataset is associated with the first identifier. For a detailed explanation, please refer to the relevant content in step S430 above; this embodiment will not repeat the explanation here.

[0150] Example 2: The model is deployed on network devices, and data collection occurs on terminal devices.

[0151] Referring to Figure 6, as an example, Figure 6 is a schematic diagram of a communication method 600 provided in an embodiment of this application. In method 600, the network device can correspond to the first device in method 400, and the terminal device can correspond to device #A in method 400. The method 600 shown in Figure 6 may include the following steps.

[0152] S610, the network device sends a data collection instruction. Accordingly, the terminal device receives the data collection instruction.

[0153] In S620, the network device sends the first data. Correspondingly, the terminal device receives the first data.

[0154] It should be noted that the descriptions of S610 and S620 can be found in the relevant content of S510 and S520 above, and will not be repeated here in the embodiments of this application.

[0155] S630, the terminal device collects data.

[0156] As an example, the terminal device can determine second data and / or a first communication indicator. The second data may be data received by the terminal device after the first data has been affected by the non-linearity of the link between the network device and the terminal device, and the first communication indicator may be determined by the terminal device based on the received second data and the known first data.

[0157] In step S640, the terminal device sends second data and / or the first communication indicator. Correspondingly, the network device receives the second data and / or the first communication indicator. For a detailed explanation, please refer to the relevant content in step S530; this embodiment will not be repeated here.

[0158] S650, network devices acquire datasets.

[0159] S660, the network device determines that the dataset is associated with the first identifier.

[0160] It should be noted that the descriptions of S650 and S660 can be found in the relevant content of S540 and S550 above, and will not be repeated here in the embodiments of this application.

[0161] Example 3: The model is deployed on the terminal device, and data collection occurs on the terminal device.

[0162] Referring to Figure 7, as an example, Figure 7 is a schematic diagram of a communication method 700 provided in an embodiment of this application. In method 700, the terminal device can correspond to the first device in method 400, and the network device can correspond to device #A in method 400. The method 700 shown in Figure 7 may include the following steps.

[0163] S710, optionally, the terminal device sends a data collection request. Correspondingly, the network device receives the data collection request. As an example, the data collection request can be used to request data collection, or in other words, it can be used to request the network device to send a data collection instruction.

[0164] S720, the network device sends a data collection instruction. Correspondingly, the terminal device receives this data collection instruction.

[0165] In S730, the network device sends the first data. Correspondingly, the terminal device receives the first data.

[0166] It should be noted that the descriptions of S720 and S730 can be found in the relevant content of S510 and S520 above, and will not be repeated here in the embodiments of this application.

[0167] S740, the terminal device acquires a dataset. The dataset may include at least one of first data, second data, and a first communication indicator.

[0168] It is understandable that the first data can be data that the terminal device has already acquired before method 700, the second data can be data received by the terminal device after the first data has been affected by the nonlinearity of the link between the network device and the terminal device, and the first communication index can be calculated by the terminal device based on the received second data and the known first data.

[0169] Optionally, the terminal device can determine that the dataset is associated with the first identifier. For a detailed explanation, please refer to the relevant content in S430 above; this embodiment will not be repeated here.

[0170] S750, optionally, the terminal device sends the aforementioned dataset. Accordingly, device #B receives the dataset.

[0171] Optionally, device #B can be the network device in method 700.

[0172] Optionally, device #B can be a training node. For example, device #B can be a network device other than the network device in method 700, or a cloud server, or a distributed edge node, etc. This application embodiment does not limit the scope.

[0173] It is understood that in method 700, device #B can be used for model training based on the dataset. That is, device #B can be any device capable of model training. The embodiments of this application do not limit its specific form, as long as it can realize the function of model training.

[0174] Example 4: The model is deployed on the terminal device, and data collection occurs on the network device.

[0175] Referring to Figure 8, as an example, Figure 8 is a schematic diagram of a communication method 800 provided in an embodiment of this application. In method 800, the network device can correspond to the first device in method 400, and the terminal device can correspond to device #A in method 400. The method 800 shown in Figure 8 may include the following steps.

[0176] S810, optionally, the terminal device sends a data collection request. Accordingly, the network device receives the data collection request.

[0177] S820, the network device sends a data collection instruction. Correspondingly, the terminal device receives the data collection instruction.

[0178] S830, the network device sends the first data. Correspondingly, the terminal device receives the first data.

[0179] S840, the terminal device sends second data and / or the first communication indicator. Accordingly, the network device receives the second data and / or the first communication indicator.

[0180] S850, network devices acquire datasets.

[0181] S860, the network device determines that the dataset is associated with the first identifier.

[0182] It should be noted that S810 can refer to the relevant content in S710 above, and S820 to S860 can refer to the relevant content in S510 to S550 above. The embodiments of this application will not be described again here.

[0183] S870, optionally, the network sends the aforementioned dataset. Accordingly, device #C receives the dataset.

[0184] Optionally, device #C can be a network device other than the network device in method 800.

[0185] Optionally, device #C can be a training node, such as a cloud server or a distributed edge node, etc., which is not limited in the embodiments of this application.

[0186] It is understood that in method 800, device #C can be used for model training based on a dataset. That is, device #C can be any device capable of model training. The embodiments of this application do not limit its specific form, as long as it can achieve the function of model training.

[0187] The above examples 1 to 4 illustrate four possible flows corresponding to method 400 during downlink transmission. The following example 900 illustrates a possible flow corresponding to method 400 during uplink transmission.

[0188] Referring to Figure 9, as an example, Figure 9 is a schematic diagram of a communication method 900 provided in an embodiment of this application. The method 900 shown in Figure 9 may include the following steps.

[0189] It is understood that, for the uplink transmission case, the nonlinear data collection process can refer to any of the downlink transmission cases in Examples 1 to 4 above, and become the terminal device sending the first data based on the first communication configuration, and the network device receiving the first data based on the first communication configuration. Other steps can be adjusted accordingly. The embodiments of this application will not be repeated here.

[0190] As an example, for the case of uplink transmission, the following steps may also be included before the non-linear data collection process.

[0191] S910, optionally, the network device sends indication information #A. Correspondingly, the terminal device receives the indication information #A.

[0192] As an example, the instruction message #A can be used to trigger the collection of nonlinear data, or in other words, the instruction message #A can be used to indicate the nonlinear data or model management process.

[0193] S920, the terminal device sends a first instruction message. Correspondingly, the network device receives the first instruction message.

[0194] As an example, the first indication information may indicate the power margin of the terminal device for transmitting data, which may include a power indication of the non-linear region.

[0195] Optionally, the first indication information may be power headroom (PHR), and the terminal device may carry a nonlinear data / model management request when reporting the PHR.

[0196] It is understood that, considering the nonlinear background of the embodiments in this application, the power margin includes a power indication of the nonlinear region. This can be understood as the power margin indicating the power of the RF device reaching the nonlinear region, thus causing the dataset to contain nonlinear distortion. Conversely, if the power margin can only indicate the power in the linear region, it may be difficult to obtain a dataset containing nonlinear data.

[0197] S930, the network device sends a second instruction message. Accordingly, the terminal device receives the second instruction message.

[0198] The second indication information can indicate the power at which the terminal device transmits the first data.

[0199] For example, the second indication information could be a transmit power control (TPC) command, that is, the network device can send a TPC command to indicate the power at which the terminal device actually transmits the first data.

[0200] In this embodiment of the application, during uplink transmission, the terminal device can report its own power margin by sending a first indication message, and the network device can send a second indication message to the terminal device, which can indicate the specific power of the terminal device in sending the first data uplink.

[0201] Referring to Figure 10, as an example, Figure 10 is a schematic diagram of a communication method 1000 provided in an embodiment of this application. For ease of description, a second device (e.g., a terminal device or a network device) will be used as an example for illustrative purposes. The second device can be replaced by components of the second device (e.g., a chip, a chip system, a circuit, a communication module, or a processor). Furthermore, the steps described below as being performed by a single execution entity can also be divided into steps performed by multiple execution entities, which can be logically and / or physically separated. The method 1000 shown in Figure 10 may include the following steps.

[0202] S1010, the second device obtains the dataset based on the first identifier.

[0203] Wherein, the first identifier is associated with the first communication configuration, the dataset includes at least one of first data, second data and first communication metric, the first data is sent or received based on the first communication configuration, the second data is the first data containing non-linearity, and the first communication metric indicates the transmission performance of the first data.

[0204] It should be noted that the descriptions of the first identifier, dataset, and first communication configuration can be found in the relevant content of method 400 above, and will not be repeated here in the embodiments of this application.

[0205] Optionally, the second device and the first device described above may be the same or different communication devices.

[0206] As one possible implementation, the second device and the first device are the same communication device. For example, in conjunction with any of the examples 1, 2 and 4 above, the first device is a network device that can determine the dataset associated with the first identifier based on the first identifier; or, in conjunction with example 3 above, the first device is a terminal device that can determine the dataset associated with the first identifier based on the first identifier.

[0207] For example, a network device or terminal device stores identifier #1 as "1", corresponding to dataset #1; the network device or terminal device also stores identifier #2 as "2", corresponding to dataset #2; where the first identifier is "1", then the network device or terminal device can determine dataset #1 from dataset #1 and dataset #2.

[0208] As another possible implementation, if the second device and the first device are different communication devices, then S1010 may include:

[0209] In step #A1, the second device sends a first identifier to the first device. Accordingly, the first device receives the first identifier.

[0210] In step #A2, the first device sends the dataset. Correspondingly, the second device receives the dataset.

[0211] For example, the first device stores identifier #1 as "1", corresponding to dataset #1; the first device also stores identifier #2 as "2", corresponding to dataset #2. Further, if the first device receives a first identifier of "1" from the second device, the first device can send dataset #1 to the second device, thereby allowing the second device to obtain the dataset corresponding to the first identifier.

[0212] It should be noted that S1010 is illustrated by the example of the first device storing one or more datasets corresponding to identifiers. In S1010, the first device can also be replaced by other devices. That is, the embodiments of this application do not limit the device for storing datasets to the first device mentioned above.

[0213] In this embodiment, the second device can obtain the nonlinear dataset associated with the first communication configuration based on the first identifier. It is understood that the nonlinear effect of the link is closely related to the communication configuration, and obtaining the nonlinear dataset requires associating it with a specific communication configuration. Considering that the communication configuration may contain multiple parameters, the above technical solution can reduce the indication overhead of the dataset.

[0214] S1020, the second device trains the first model based on the dataset to obtain the second model.

[0215] As an example, the first model is used to train the second model. The first model can be a model to be trained, or a model that has been pre-trained, or a model that has been trained with some nonlinear data, etc. The embodiments of this application are not limited to this.

[0216] As an example, the second model can be used to compensate for nonlinear distortion in data transmission. This second model may also be called a nonlinear compensation model, or a nonlinear correction model, etc., and its name does not limit the scope of protection of the embodiments of this application.

[0217] As an example, training a first model based on a dataset to obtain a second model can be understood as the second device using the second data as the model input and the first data as the target of the model output to train the first model and obtain the second model.

[0218] Optionally, method 1000 may also include:

[0219] S1030, the second device associates the second model with the first identifier and / or the second identifier.

[0220] The second identifier may include the ID of the terminal device and / or the ID of the group to which the terminal device belongs, wherein the terminal device is the terminal device that sends or receives the first data.

[0221] For example, in Examples 1 to 4 above, terminal device #1 is the device that receives the first data. Assume that terminal device #1 receives the first data with a first communication configuration #1, and the first communication configuration #1 is associated with the dataset #1 through the first identifier "1". The second device trains the first model based on the dataset #1 to obtain the second model #1. Then the second device can associate the second model #1 with the first identifier "1" and / or the UEID or UE group ID of terminal device #1.

[0222] As one possible implementation, the second device and the first device in method 400 can be the same device.

[0223] For example, in Example 1 or Example 2, after the network device obtains the dataset, it can train a model based on the dataset to obtain a second model, and associate the trained second model with the first identifier and / or the second identifier.

[0224] For example, in Example 3, after the terminal device obtains the dataset, it can train a model based on the dataset to obtain a second model, or device #B can train a model based on the dataset to obtain a second model. The terminal device can then associate the trained second model with the first identifier.

[0225] For another example, in Example 4, after the network device acquires the dataset, it can train a model based on the dataset to obtain a second model, or device #C can train a model based on the dataset to obtain a second model. The network device can then associate the trained second model with the first identifier and / or the second identifier.

[0226] In this embodiment, the second device can associate a second model trained on a nonlinear dataset with a first identifier and / or a second identifier. It is understood that the nonlinear effect of the link is highly dependent on the communication configuration. Managing the model used to compensate for nonlinear distortion in data transmission requires associating it with a specific communication configuration. Considering that the communication configuration may contain multiple parameters, the above technical solution can reduce the model's indication overhead.

[0227] Furthermore, the second identifier may include UEID and / or UE group ID. It is understood that the nonlinear effect of the link is related to specific radio frequency devices. For example, the nonlinear effect of the link may be directly related to specific terminal devices. In the above technical solution, the second model is further associated with UEID and / or UE group ID, which can enable the second model to compensate for nonlinear distortion for specific UEs or UE groups and enhance the nonlinear compensation effect of the second model.

[0228] As one possible implementation, after the second device trains the first model based on the dataset to obtain the second model, the transmitting device between the second device and the counterpart device can update its maximum transmission power.

[0229] Referring to Figure 11, as an example, Figure 11 is a schematic diagram of a communication method 1100 provided in an embodiment of this application. Optionally, in the case of uplink transmission and the second device being a terminal device, the method 1100 shown in Figure 11 may include the following steps.

[0230] S1110, the terminal device sends a request message. Correspondingly, the network device receives the request message. This request message requests the terminal device's maximum transmission power.

[0231] It is understandable that after the terminal device obtains the corresponding second model through training, it can use the second model to compensate for the nonlinear distortion generated when it transmits data with higher power. Therefore, the terminal device can request to update its maximum transmission power by sending a request message, thereby improving the transmission performance of the terminal device.

[0232] S1120, the terminal device receives the third indication information. Accordingly, the network device sends the third indication information. The third indication information indicates the maximum transmission power.

[0233] Optionally, the request information in S1110 may include the nonlinear compensation status of the terminal device locally. For example, the request information may include the KPI of the first data transmission, and the maximum transmission power indicated by the third indication information is determined based on the KPI.

[0234] Alternatively, the network device can also determine the KPIs on the receiving side itself and indicate the maximum transmission power to the terminal device based on the KPIs on the receiving side.

[0235] In this embodiment of the application, the maximum transmission power of the terminal device can be determined based on the KPI of the first data transmission. That is, the network device can more accurately determine and indicate the updated maximum transmission power of the terminal device based on the quality of the first data transmission.

[0236] As one possible implementation, in the case of uplink transmission and the second device being a network device, or in the case of downlink transmission, the network device can determine the maximum transmission power based on the KPI of the first data transmission.

[0237] As an example, in the case of uplink transmission and the second device being a network device, the network device can directly determine the maximum transmission power based on the network-side KPIs, which is the maximum transmission power of the terminal device.

[0238] Furthermore, the network device can send third indication information to the terminal device. Accordingly, the terminal device receives this third indication information. The third indication information indicates the maximum transmission power of the terminal device.

[0239] As an example, in the case of downlink transmission, the network device can determine the communication configuration. For instance, if the second model is deployed on the network device, the network device can determine the maximum transmission power based on the network-side KPIs and / or the KPIs fed back by the terminal device. Alternatively, if the second model is deployed on the terminal device, the network device can determine the maximum transmission power based on the KPIs fed back by the terminal device.

[0240] Referring to Figure 12, as an example, Figure 12 is a schematic diagram of a communication method 1200 provided in an embodiment of this application. For ease of description, a third device (e.g., a terminal device or a network device) and device #E (e.g., a network device or a terminal device) are used as examples for illustrative purposes. The third device can be replaced by a component of the third device (e.g., a chip, a chip system, a circuit, a communication module, or a processor), and device #E can be replaced by a component of device #E (e.g., a chip, a chip system, a circuit, a communication module, or a processor). Furthermore, the steps described below as being performed by a single execution entity can also be divided into steps performed by multiple execution entities, which can be logically and / or physically separated. The method 1200 shown in Figure 12 may include the following steps.

[0241] S1210, the third device obtains the second model based on the first identifier and / or the second identifier.

[0242] As an example, the first identifier is associated with the first communication configuration, and the second identifier includes the ID of the terminal device and / or the ID of the group to which the terminal device belongs.

[0243] The terminal device is a terminal device that sends or receives first data, which is sent or received based on a first communication configuration.

[0244] As an example, the second model is used to compensate for nonlinear distortion in data transmission. The second model is obtained by training the first model based on a dataset, which may include at least one of first data, second data, and a first communication metric. The second data is the first data containing nonlinearity, and the first communication metric indicates the transmission performance of the first data.

[0245] It should be noted that the descriptions of the first identifier, the second identifier, and the second model can be found in the relevant content above, and will not be repeated here in the embodiments of this application.

[0246] As an example, in conjunction with the method 1000 above, assuming that device #D stores the second model #1, which is associated with the first identifier "1" and UEID "1", and device #D also stores the second model #2, which is associated with the first identifier "1" and UEID "2", then the third device can send the first identifier "1" and UEID "2" to device #D to obtain the corresponding second model #2.

[0247] S1220, the third device sends or receives the second data via the second model. Accordingly, device #E receives or sends the second data.

[0248] As an example, sending or receiving second data via the second model can also be replaced by using the second model to send or receive second data, or by using the second model to compensate for nonlinear distortion in sending or receiving second data, etc. The embodiments of this application are not limited.

[0249] For example, device #E sends second data, and correspondingly, a third device receives the second data. However, due to the nonlinear link between device #E and the third device, the third device actually receives second data #1 that includes nonlinearity. The third device, through a second model, can compensate for the nonlinearity in second data #1.

[0250] For another example, the third device sends second data, and correspondingly, device #E receives the second data. The third device's radio frequency devices transmit the second data in a nonlinear range, generating nonlinearity. The actual transmitted data is second data #2, which includes nonlinearity. Therefore, the third device, through the second model, can compensate for the nonlinearity in the second data #2.

[0251] In this embodiment, the third device can obtain the second model based on the first identifier and / or the second identifier. It is understood that the nonlinear effect of the link is closely related to the communication configuration. Obtaining a model to compensate for nonlinear distortion in data transmission requires associating it with the specific communication configuration. Considering that the communication configuration may contain multiple parameters, the above technical solution can reduce the indication overhead of obtaining the model.

[0252] Referring to Figure 13, as an example, Figure 13 is a schematic diagram of a communication method 1300 provided in an embodiment of this application. As an example, the third device is a network device, and device #E is a terminal device. Before the third device obtains the second model based on the first identifier and / or the second identifier in method 1200, method 1300 may include the following steps.

[0253] S1310, the network device sends a third identifier. Accordingly, device #F receives the third identifier.

[0254] The third identifier may include the ID of the terminal device currently maintained by the network device and / or the ID of the group to which the terminal device belongs.

[0255] As an example, as shown in Figure 13, the third identifier can be sent by the terminal device to the network device, for example, it is the UEID of the network device currently accessed by the terminal device.

[0256] S1320, Device #F determines the second identifier based on the third identifier.

[0257] As an example, device #F can be a device that maintains the mapping from UEID to terminal device; for example, device #F can be a core network device.

[0258] For example, after receiving the third identifier, the core network device can map / associate it with a specific terminal device to determine the second identifier. This second identifier, determined based on the third identifier, can be the global ID of the terminal device; for instance, it could be the UEID associated with the second model during training.

[0259] S1330, the network device receives the second identifier. Accordingly, device #F sends the second identifier.

[0260] It is understandable that after receiving the second identifier, the network device can further execute the steps in method 1200.

[0261] In this embodiment, the network device can request a second identifier associated with the second model by sending the currently maintained UEID and / or UE group ID. It is understood that the UEID or UE group ID may not be a fixed value for the cell; for example, the network device may not be able to obtain the second identifier associated with the second model due to security or privacy issues. Based on the above technical solution, the mapping from the network device's currently maintained UEID and / or UE group ID to the second identifier can be completed on other communication devices (e.g., the core network). For example, the second identifier can be the UEID and / or UE group ID used during model training, and the other communication device can indicate the second identifier to the network device.

[0262] As one possible implementation, the third device in method 1200 is a terminal device whose communication configuration for sending or receiving second data has not been trained, and the terminal device can obtain the second model through method 1400.

[0263] Referring to Figure 14, as an example, Figure 14 is a schematic diagram of a communication method 1400 provided in an embodiment of this application. The method 1400 shown in Figure 14 may include the following steps.

[0264] S1410, the terminal device sends a fourth identifier. Accordingly, the network device receives the fourth identifier.

[0265] The fourth identifier is associated with the second communication configuration, which is not used to train a model associated with the terminal device for compensating for nonlinear distortion in data transmission.

[0266] For example, in the cell where the terminal device is located, the models associated with that terminal device for compensating for nonlinear distortion in data transmission include model #1 and model #2. Model #1 is trained based on dataset #1, which is obtained under the transmission conditions of communication configuration #1; model #2 is trained based on dataset #2, which is obtained under the transmission conditions of communication configuration #2. If the second communication configuration is different from both communication configuration #1 and communication configuration #2, then the second communication configuration is not used to train the models associated with that terminal device for compensating for nonlinear distortion in data transmission.

[0267] S1420, the network device determines the first identifier.

[0268] As an example, after a network device determines that a second communication configuration is not used to train a model associated with the terminal device for compensating for nonlinear distortion in data transmission, it can determine a first identifier associated with a second model for compensating for nonlinear distortion in data transmission.

[0269] As an example, the first identifier is associated with a first communication configuration, which is the communication configuration that is closest to the second communication configuration among a plurality of communication configurations associated with a model for compensating for nonlinear distortion in data transmission.

[0270] As another example, a network device can identify multiple identifiers associated with multiple models. The network device can determine the model with the best nonlinear compensation effect from multiple models based on the effect of nonlinear compensation fed back by the terminal device, for example, based on the KPI fed back by the terminal device, and the second model is associated with the first identifier.

[0271] Optionally, the network device can maintain a mapping table, which allows the network device to map untrained communication configurations to trained communication configurations.

[0272] For example, in the case of transmission of the second communication configuration, the nonlinear compensation effect of the model associated with the first communication configuration is the best. The network device can map the second communication configuration to the first communication configuration through a mapping table, so that in the next transmission of the second communication configuration, the first communication configuration and its associated first identifier, second model, etc. can be directly determined based on the second communication configuration.

[0273] S1430, the network device sends a first identifier. Accordingly, the terminal device receives the first identifier.

[0274] It is understandable that after receiving the first identifier, the terminal device can further execute the steps in method 1200, thus eliminating the need to retrain the model.

[0275] In this embodiment of the application, when a terminal device requests to obtain a model that is not used for training and is associated with the terminal device for compensating for nonlinear distortion in data transmission, the network device can indicate a first identifier to the terminal device. This first identifier can be associated with a trained model, thereby achieving nonlinear compensation without retraining the model and saving model training time.

[0276] The methods provided by the embodiments of this application have been described in detail above with reference to Figures 4 to 14. The apparatus provided by the embodiments of this application will be described in detail below with reference to Figures 15 to 17. It should be understood that the descriptions of the apparatus embodiments correspond to the descriptions of the method embodiments; therefore, any content not described in detail can be referred to the method embodiments above, and for the sake of brevity, will not be repeated here.

[0277] Referring to Figure 15, as an example, Figure 15 is a schematic diagram of a communication device 1500 provided in an embodiment of this application. The communication device 1500 includes a transceiver unit 1510 and a processing unit 1520. The transceiver unit 1510 can be used to implement corresponding communication functions. The transceiver unit 1510 can also be referred to as a communication interface or a communication unit. The processing unit 1520 can be used to perform processing, such as determining information bits.

[0278] Optionally, the device 1500 may further include a storage unit for storing instructions and / or data, and the processing unit 1520 may read the instructions and / or data from the storage unit to enable the device to implement the aforementioned method embodiments.

[0279] In a first possible design, the device 1500 can be the first device in the foregoing embodiments, which can implement the steps or processes corresponding to those performed by the first device in the above method embodiments. Specifically, the transceiver unit 1510 can be used to perform transceiver-related operations (such as sending and / or receiving data or messages) of the first device in the above method embodiments, and the processing unit 1520 can be used to perform processing-related operations of the first device in the above method embodiments, or operations other than transceiver (such as operations other than sending and / or receiving data or messages).

[0280] In one possible implementation, transceiver unit 1510 is configured to send or receive first data based on a first communication configuration associated with a first identifier; transceiver unit 1510 is further configured to acquire a dataset, the dataset including at least one of the first data, second data, and a first communication indicator, the second data being the first data containing nonlinearity, and the first communication indicator indicating the transmission performance of the first data; and processing unit 1520 is configured to determine that the dataset is associated with the first identifier.

[0281] In a second possible design, the device 1500 can be the second device in the foregoing embodiments, which can implement the steps or processes corresponding to those performed by the second device in the above method embodiments. Specifically, the transceiver unit 1510 can be used to perform transceiver-related operations (such as sending and / or receiving data or messages) of the second device in the above method embodiments, and the processing unit 1520 can be used to perform processing-related operations of the second device in the above method embodiments, or operations other than transceiver (such as operations other than sending and / or receiving data or messages).

[0282] One possible implementation is a transceiver unit 1510, configured to acquire a dataset based on a first identifier associated with a first communication configuration. The dataset includes at least one of first data, second data, and a first communication metric. The first data is sent or received based on the first communication configuration. The second data is the first data with nonlinearity. The first communication metric indicates the transmission performance of the first data. A processing unit 1520 is configured to train a first model based on the dataset to obtain a second model. The second model is used to compensate for nonlinear distortion in data transmission.

[0283] In a third possible design, the device 1500 can be the third device in the foregoing embodiments, which can implement the steps or processes corresponding to those performed by the third device in the above method embodiments. Specifically, the transceiver unit 1510 can be used to perform transceiver-related operations (such as sending and / or receiving data or messages) of the third device in the above method embodiments, and the processing unit 1520 can be used to perform processing-related operations of the third device in the above method embodiments, or operations other than transceiver (such as operations other than sending and / or receiving data or messages).

[0284] In one possible implementation, the transceiver unit 1510 is configured to obtain a second model based on a first identifier and / or a second identifier, wherein the first identifier is associated with a first communication configuration, and the second identifier includes the ID of a terminal device and / or the ID of the group to which the terminal device belongs, wherein the terminal device is a terminal device that sends or receives first data, the first data being sent or received based on the first communication configuration, the second model being used to compensate for nonlinear distortion in data transmission, the second model being obtained by training a first model based on a dataset, the dataset including at least one of the first data, second data, and a first communication metric, the second data being the first data containing nonlinearity, and the first communication metric indicating the transmission performance of the first data; the transceiver unit 1510 is further configured to send or receive the second data via the second model.

[0285] It should be understood that the specific process of each unit performing the above-mentioned corresponding steps has been described in detail in the above method embodiments, and will not be repeated here for the sake of brevity.

[0286] It should also be understood that the device 1500 here is embodied in the form of a functional unit. The term "unit" here can refer to an application-specific integrated circuit (ASIC), electronic circuitry, a processor (e.g., a shared processor, a proprietary processor, or a group processor, etc.) and memory for executing one or more software or firmware programs, integrated logic circuitry, and / or other suitable components supporting the described functions. In an alternative example, those skilled in the art will understand that the device 1500 can be specifically the communication device in the above embodiments, and can be used to execute the various processes and / or steps corresponding to the communication device in the above method embodiments; to avoid repetition, these will not be described again here.

[0287] The apparatus 1500 of each of the above-described schemes has the function of implementing the corresponding steps performed by the communication device (such as the first device, the second device, or the third device) in the above-described methods. The function can be implemented in 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, each performing the transceiver operations and related processing operations in the respective method embodiments.

[0288] In addition, the transceiver unit 1510 may also be a transceiver circuit (for example, it may include a receiving circuit and a transmitting circuit), and the processing unit may be a processing circuit.

[0289] It should be noted that the device in Figure 15 can be the communication device (such as the first device, the second device, or the third 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.

[0290] Referring to Figure 16, as an example, Figure 16 is a schematic diagram of another communication device 1600 provided in an embodiment of this application. The device 1600 includes a processor 1610, which is coupled to a memory 1620. The memory 1620 is used to store computer programs or instructions and / or data. The processor 1610 is used to execute the computer programs or instructions stored in the memory 1620, or to read the data stored in the memory 1620, in order to perform the methods in the above method embodiments.

[0291] Optionally, there may be one or more processors 1610.

[0292] Optionally, the memory 1620 may be one or more.

[0293] Alternatively, the memory 1620 can be integrated with the processor 1610, or it can be set separately.

[0294] Optionally, as shown in FIG16, the device 1600 further includes a transceiver 1630 for receiving and / or transmitting signals. For example, a processor 1610 is used to control the transceiver 1630 to receive and / or transmit signals.

[0295] As an example, processor 1610 may have the functions of processing unit 1520 shown in FIG15, memory 1620 may have the functions of storage unit, and transceiver 1630 may have the functions of transceiver unit 1510 shown in FIG15.

[0296] As one option, the device 1600 is used to implement the operations performed by the communication device (such as the first device, the second device, or the third device) in the various method embodiments described above.

[0297] For example, processor 1610 is used to execute computer programs or instructions stored in memory 1620 to implement the relevant operations of the communication device in the various method embodiments described above.

[0298] It should be understood that the processor mentioned 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), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0299] It should also be understood that the memory mentioned in the embodiments of this application can be volatile memory and / or non-volatile memory. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM). For example, RAM can be used as an external cache. By way of example and not limitation, RAM includes the following forms: static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM).

[0300] It should be noted that when the processor is a general-purpose processor, DSP, ASIC, FPGA, or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, the memory (storage module) can be integrated into the processor.

[0301] It should also be noted that the memory described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0302] Referring to Figure 17, as an example, Figure 17 is a schematic diagram of a chip system 1700 provided in an embodiment of this application. The chip system 1700 (or may also be referred to as a processing system) includes logic circuitry 1710 and an input / output interface 1720.

[0303] The logic circuit 1710 can be a processing circuit in the chip system 1700. The logic circuit 1710 can be coupled to a memory unit, calling instructions from the memory unit, enabling the chip system 1700 to implement the methods and functions of the embodiments of this application. The input / output interface 1720 can be an input / output circuit in the chip system 1700, outputting processed information from the chip system 1700, or inputting data or signaling information to be processed into the chip system 1700 for processing.

[0304] As one approach, the chip system 1700 is used to implement operations performed by communication devices (such as terminal devices or network devices) in the various method embodiments described above.

[0305] For example, logic circuit 1710 is used to implement processing-related operations performed by a communication device (such as a terminal device or a network device) in the above method embodiments; input / output interface 1720 is used to implement sending and / or receiving-related operations performed by a communication device (such as a terminal device or a network device) in the above method embodiments.

[0306] This application also provides a computer-readable storage medium storing a computer program or instructions for implementing the methods executed by a communication device (such as a terminal device or a network device) in the above-described method embodiments. For example, when the computer program or instructions are run on the communication device, the communication device (such as a terminal device or a network device) executes the above-described methods (such as method 400, method 1000, or method 1200).

[0307] This application also provides a computer program product comprising instructions that, when executed by a computer, implement the methods described above as performed by a communication device (such as a terminal device or a network device). For example, when the computer program or instructions are run on the communication device, the communication device (such as a terminal device or a network device) performs the methods described above (such as method 400, method 1000, or method 1200).

[0308] This application also provides a communication system that includes the terminal device and / or network device described in the embodiments above. For example, the system includes the terminal device and network device described in the embodiments of FIG4, FIG10, or FIG12.

[0309] The explanations and beneficial effects of the relevant contents in any of the devices provided above can be found in the corresponding method embodiments provided above, and will not be repeated here.

[0310] In the several embodiments provided in this application, it should be understood that the disclosed apparatus 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 mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of apparatus or units may be electrical, mechanical, or other forms.

[0311] 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 instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. For example, the computer can be a personal computer, a server, or a network device, etc. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) 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 media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state disks, SSDs). For example, the aforementioned available media include, but are not limited to, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, and other media capable of storing program code.

[0312] 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 in that, include: Sending or receiving first data based on a first communication configuration, wherein the first communication configuration is associated with a first identifier; Obtain a dataset, the dataset including at least one of the first data, the second data, and the first communication metric, wherein the second data is the first data containing nonlinearity, and the first communication metric indicates the transmission performance of the first data; The dataset is determined to be associated with the first identifier.

2. The method according to claim 1, characterized in that, The first communication configuration includes at least one of the following: the transmission power of the first data, the transmission bandwidth of the first data, the modulation order of the first data, the transmission waveform of the first data, the precoding matrix for transmitting the first data, the reference signal configuration, or the spreading sequence of the first data.

3. The method according to claim 1 or 2, characterized in that, Applied to terminal devices, the sending or receiving of first data based on a first communication configuration includes: The method further includes sending the first data based on the first communication configuration; prior to sending the first data, the method also includes: Send a first indication message, the first indication message indicating the power margin of the terminal device for transmitting data, the power margin including a power indication of the non-linear region; Receive a second indication message, which indicates the power used to transmit the first data.

4. The method according to claim 1 or 2, characterized in that, Applied to network devices, the sending or receiving of first data based on a first communication configuration includes: The method further includes receiving the first data based on the first communication configuration; prior to receiving the first data, the method also includes: Receive first indication information, the first indication information indicating the power margin of the terminal device for transmitting data; Send a second indication message, which indicates the power at which the terminal device sends the first data.

5. The method according to any one of claims 1 to 4, characterized in that, The first identifier is a community-level identifier.

6. A communication method, characterized in that, include: A dataset is obtained based on a first identifier associated with a first communication configuration. The dataset includes at least one of first data, second data, and a first communication metric. The first data is sent or received based on the first communication configuration. The second data is the first data that includes non-linearity. The first communication metric indicates the transmission performance of the first data. The first model is trained based on the dataset to obtain the second model, which is used to compensate for nonlinear distortion in data transmission.

7. The method according to claim 6, characterized in that, The first communication configuration includes at least one of the following: the transmission power of the first data, the transmission bandwidth of the first data, the modulation order of the first data, the transmission waveform of the first data, the precoding matrix for transmitting the first data, the reference signal configuration, or the spreading sequence of the first data.

8. The method according to claim 6 or 7, characterized in that, Also includes: The second model is associated with the first identifier and / or the second identifier, the second identifier including the identity ID of the terminal device and / or the ID of the group to which the terminal device belongs, the terminal device being the terminal device that sends or receives the first data.

9. The method according to any one of claims 6 to 8, characterized in that, Applied to terminal devices, after training the first model based on the dataset to obtain the second model, the method further includes: Send a request message, the request message requesting the maximum transmission power of the terminal device; Receive a third indication message, which indicates the maximum transmission power.

10. The method according to claim 9, characterized in that, The request information includes key performance indicators (KPIs) for the first data transmission, and the maximum transmission power indicated by the third indication information is determined based on the KPIs.

11. The method according to any one of claims 6 to 8, characterized in that, Applied to network devices, after training the first model based on the dataset to obtain the second model, the method further includes: The maximum transmission power is determined based on the KPI of the first data transmission.

12. The method according to claim 11, characterized in that, The maximum transmission power is the maximum transmission power of the terminal device, and the method further includes: A third indication message is sent to the terminal device, the third indication message indicating the maximum transmission power of the terminal device.

13. A communication method, characterized in that, include: A second model is obtained based on a first identifier and / or a second identifier, wherein the first identifier is associated with a first communication configuration, and the second identifier includes the ID of a terminal device and / or the ID of the group to which the terminal device belongs. The terminal device is a terminal device that sends or receives first data, which is sent or received based on the first communication configuration. The second model is used to compensate for nonlinear distortion in data transmission. The second model is obtained by training a first model based on a dataset, wherein the dataset includes at least one of the first data, the second data, and a first communication metric, wherein the second data is the first data containing nonlinearity, and the first communication metric indicates the transmission performance of the first data. The second model sends or receives the second data.

14. The method according to claim 13, characterized in that, Applied to network devices, before obtaining the second model based on the first identifier and / or the second identifier, the method further includes: Send a third identifier, the third identifier including the ID of the terminal device currently maintained by the network device and / or the ID of the group to which the terminal device belongs; Receive the second identifier.

15. The method according to claim 13, characterized in that, Applied to terminal devices, the method further includes: Send a fourth identifier, which is associated with a second communication configuration that is not used to train a model associated with the terminal device for compensating for nonlinear distortion in data transmission; Receive the first identifier.

16. A communication device, characterized in that, Includes modules or units for performing the method according to any one of claims 1 to 15.

17. A communication device, characterized in that, Includes a processor, the processor being configured to cause the communication device to perform the method of any one of claims 1 to 15.

18. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program or instructions that, when executed on a communication device, cause the communication device to perform the method as described in any one of claims 1 to 15.

19. A computer program product, characterized in that, The computer program product includes a computer program or instructions that, when executed on a communication device, cause the communication device to perform the method as described in any one of claims 1 to 15.

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