Communication method and related apparatus

Abstract

A communication method and a related apparatus. In the method, first information sent by a first communication apparatus is used for determining a first processing parameter, third information received by the first communication apparatus comprises first radio information, and an input of a radio map model is obtained on the basis of the first processing parameter. In other words, the first communication apparatus serves as a requester for radio information, and the first communication apparatus can specify processing parameters for an input of the radio map model by means of the first information, so as to obtain radio information corresponding to the processing parameters. Compared with an implementation mode in which a radio map model can only perform processing on the basis of a single-processing parameter input, the present application enables the described process in which radio information obtained by the first communication apparatus by means of a radio map model can be obtained on the basis of an input corresponding to processing parameters expected (or indicated or specified) by the first communication apparatus, thus improving the use flexibility of radio map models.

Description

A communication method and related device

[0001] This application claims priority to the Chinese patent application filed with the State Intellectual Property Office on March 14, 2024, with application number 202410294736.8 and application name “A communication method and related device”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of communications, and in particular to a communication method and related devices. Background Art

[0003] In wireless communication systems, radio map models are widely used in various radio network tasks, including but not limited to network planning, interference control, path loss prediction, signal strength prediction, power control, resource allocation, handover management, multi-hop routing, dynamic spectrum access and cognition.

[0004] For example, in the case of path loss prediction, the input of a radio map model may include information about a specific location, and the radio information output by the radio map model may include the path loss at that location. Another example is the case of signal strength prediction, in which the input of a radio map model may include information about a specific communication environment, and the radio signal strength of the user in that communication environment is determined.

[0005] However, how to improve the flexibility of using radio map models is a technical problem that needs to be solved urgently. Summary of the Invention

[0006] The present application provides a communication method and related apparatus for improving the flexibility of using a radio map model.

[0007] In a first aspect, the present application provides a communication method, which is performed by a first communication device, which may be a communication device (such as a terminal device or a network device), or a component of a communication device (such as a processor, a chip, or a chip system), or a logic module or software that can implement all or part of the functions of the communication device. In this method, the first communication device sends first information, which is used to determine a first processing parameter; the first communication device sends second information, which is determined based on communication status information; and the first communication device receives third information, which includes first radio information, which is obtained by processing the second information based on a radio map model; wherein the input of the radio map model is obtained based on the first processing parameter.

[0008] Based on the above scheme, the first information sent by the first communication device is used to determine the first processing parameter, the third information received by the first communication device includes the first radio information, and the input of the radio map model is obtained based on the first processing parameter. In other words, the first communication device acts as the requester of the radio information, and the first communication device can specify the processing parameter of the input of the radio map model through the first information to obtain the radio information corresponding to the processing parameter. Compared with the implementation method in which the radio map model can only be processed based on the input of a single processing parameter, in the above process, the radio information obtained by the first communication device through the radio map model can be obtained based on the input corresponding to the processing parameter expected (or indicated, or specified) by the first communication device, so as to enhance the flexibility of the use of the radio map model.

[0009] In this application, the radio map model can be a mathematical model, an artificial intelligence (AI) model, a neural network, a neural network model, an AI neural network model, a machine learning model, an AI processing model, etc.

[0010] It should be noted that the processing parameters involved in this application may include at least one of a scaling parameter and a precision conversion parameter. In addition, the processing parameters include processing parameters of the input of the radio map model (such as the first processing parameter described below) and / or processing parameters of the output of the radio map model (such as the second processing parameter described below).

[0011] In a possible implementation of the first aspect, the second information includes the communication status information, wherein the input of the radio map model includes a processing result obtained by processing the communication status information based on the first processing parameter; or, the second information includes a processing result obtained by processing the communication status information based on the first processing parameter.

[0012] Based on the above solution, the second information sent by the first communication device may include communication status information, so that the recipient of the second information can process the communication status information based on the first processing parameter to obtain the input of the radio map model, which can reduce the implementation complexity of the first communication device.

[0013] Alternatively, the second information sent by the first communication device may include a processing result obtained by processing the communication status information based on the first processing parameter, so that the recipient of the second information can directly use the processing result as part or all of the input of the radio map model, thereby reducing the implementation complexity of the recipient of the second information.

[0014] In a possible implementation manner of the first aspect, the first information includes at least one of the first processing parameter, an index of the first processing parameter, and an index of the radio map model.

[0015] It should be understood that the first information may include the index of the radio map model corresponding to the first processing parameter, wherein, since the input of the radio map model is obtained based on the first processing parameter, the first information may also include the index of the radio map model, so that the recipient of the first information can determine the first processing parameter indirectly.

[0016] Based on the above solution, the first information sent by the first communication device for determining the first processing parameter may include at least one of the above items to improve the flexibility of implementing the solution.

[0017] In a possible implementation manner of the first aspect, the method further includes: the first communication device processing the first radio information based on the second processing parameter to obtain second radio information.

[0018] Based on the above solution, after receiving the first radio information, the first communication device can also process the first radio information based on the second processing parameters to obtain the second radio information. In this way, the first communication device can process the radio information output by the radio map model to obtain an output corresponding to the specific processing parameters, so that the first communication device can perform the corresponding communication task based on the output corresponding to the specific processing parameters.

[0019] In a possible implementation manner of the first aspect, the method further includes: the first communication device receiving indication information for determining the second processing parameter.

[0020] Based on the above solution, the first communication device can also receive instruction information from other communication devices to determine the second processing parameter, that is, the first communication device can obtain output corresponding to a specific processing parameter based on the processing parameter specified by the other communication device.

[0021] In a possible implementation manner of the first aspect, the method further includes: the first communication device sending indication information for determining a second processing parameter; wherein the first radio information is obtained based on the second processing parameter.

[0022] It can be understood that the output of the radio map model may conform to the data characteristics corresponding to the second processing parameter (for example, the scaling characteristics of the output of the radio map model may conform to the scaling characteristics corresponding to the second processing parameter; for example, the accuracy characteristics of the output of the radio map model may conform to the accuracy characteristics corresponding to the second processing parameter). In this case, the second processing parameter can be regarded as a model parameter of the radio map model or a parameter of an internal module, etc.

[0023] Alternatively, the output of the radio map model may not conform to the data characteristics corresponding to the second processing parameter. In this case, the second communication device can process the output of the radio map model based on the second processing parameter to obtain first radio information that conforms to the data characteristics corresponding to the second processing parameter; accordingly, the second processing parameter can be regarded as a parameter of a processing module independent of the radio map model.

[0024] Based on the above scheme, the first communication device can also send indication information so that the recipient of the indication information can determine the second processing parameter, and the first radio information sent by the recipient to the first communication device is based on the second processing parameter, that is, the first communication device can specify the processing parameters to other communication devices to obtain the radio output corresponding to the specific processing parameters.

[0025] In a possible implementation manner of the first aspect, the indication information includes at least one of the second processing parameter, an index of the second processing parameter, and an index of the radio map model.

[0026] It should be understood that the indication information may include the index of the radio map model corresponding to the second processing parameter, wherein, since the first communication device expects to obtain the output as radio information that conforms to the data characteristics corresponding to the second processing parameter, for this reason, when the data characteristics of the outputs of different radio map models are different, the indication information may also include the index of the radio map model (that is, the data characteristics of the output of the radio map model conform to the data characteristics corresponding to the second processing parameter), so that the recipient of the indication information can determine the second processing parameter indirectly.

[0027] Based on the above solution, the indication information sent (or received) by the first communication device for determining the second processing parameter may include at least one of the above items to enhance the flexibility of the solution implementation.

[0028] In a possible implementation of the first aspect, before the first communication device sends the first information, the method also includes: the first communication device receives model information of N radio map models, the N radio map models including the radio map model, N is a positive integer; wherein the first information is determined based on the model information.

[0029] Optionally, the indication information for determining the second processing parameter is determined based on the model information.

[0030] Optionally, the model information may be pre-configured.

[0031] Based on the above solution, the first communication device may also receive model information of N radio map models, so that the first communication device can determine and send first information for determining the first processing parameter based on the model information.

[0032] Optionally, in the model information of the N radio map models, the model information of each radio map model includes at least one of an input processing parameter of each radio map model and an output processing parameter of each radio map model.

[0033] The second aspect of the present application provides a communication method, which is performed by a second communication device, which can be a communication device (such as a terminal device or a network device), or a component of a communication device (such as a processor, a chip, or a chip system), or a logic module or software that can implement all or part of the functions of the communication device. In this method, the second communication device receives first information, which is used to determine a first processing parameter; the second communication device receives second information, which is determined based on communication status information; and the second communication device sends third information, which includes first radio information, which is obtained by processing the second information based on a radio map model; wherein the input of the radio map model is obtained based on the first processing parameter.

[0034] Based on the above scheme, the first information received by the second communication device is used to determine the first processing parameter, the third information sent by the first communication device includes the first radio information, and the input of the radio map model is obtained based on the first processing parameter. In other words, the second communication device acts as a provider of radio information, and the second communication device can specify the processing parameter of the input of the radio map model through the first information to send the radio information corresponding to the processing parameter. Compared to the implementation method in which the radio map model can only perform processing based on the input of a single processing parameter, in the above process, the radio information obtained and sent by the second communication device through the radio map model can be obtained based on the input corresponding to the processing parameter expected (or indicated, or specified) by the first information, so as to enhance the flexibility of the use of the radio map model.

[0035] In a possible implementation of the second aspect, the second information includes the communication status information, wherein the input of the radio map model includes a processing result obtained by processing the communication status information based on the first processing parameter; or, the second information includes a processing result obtained by processing the communication status information based on the first processing parameter.

[0036] Based on the above solution, the second information received by the second communication device may include communication status information, so that the second communication device can process the communication status information based on the first processing parameter to obtain input of the radio map model, which can reduce the implementation complexity of the first communication device.

[0037] Alternatively, the second information received by the second communication device may include a processing result obtained by processing the communication status information based on the first processing parameter, so that the second communication device can directly use the processing result as part or all of the input of the radio map model, thereby reducing the implementation complexity of the second communication device.

[0038] In a possible implementation manner of the second aspect, the first information includes at least one of the first processing parameter, an index of the first processing parameter, and an index of the radio map model.

[0039] Based on the above solution, the first information received by the second communication device for determining the first processing parameter may include at least one of the above items, so as to improve the flexibility of implementing the solution.

[0040] In a possible implementation manner of the second aspect, the first radio information is used to determine second radio information; wherein the second radio information is obtained based on the second processing parameter.

[0041] Based on the above solution, after the second communication device sends the first radio information to the first communication device, the first communication device can also process the first radio information based on the second processing parameters to obtain the second radio information. In this way, the first communication device can process the radio information output by the radio map model to obtain an output corresponding to the specific processing parameters, so that the first communication device can perform the corresponding communication task based on the output corresponding to the specific processing parameters.

[0042] In a possible implementation manner of the second aspect, the method further includes: the second communication device sending indication information for determining the second processing parameter;

[0043] Based on the above scheme, the second communication device can also send indication information to other communication devices, so that the recipient of the indication information can determine the second processing parameter, that is, the recipient of the indication information can obtain the output corresponding to the specific processing parameter based on the processing parameter specified by the other communication device.

[0044] In a possible implementation of the second aspect, the method further includes: the second communication device receives indication information for determining a second processing parameter; wherein the first radio information is obtained by processing the second information based on the radio map model to obtain third radio information, and then processing the third radio information, and the first radio information is obtained based on the second processing parameter.

[0045] Based on the above scheme, the second communication device can also receive indication information, so that the second communication device can determine the second processing parameter, and the first radio information sent by the second communication device to the first communication device is based on the second processing parameter, that is, the first communication device can specify the processing parameter to other communication devices to obtain the radio output corresponding to the specific processing parameter.

[0046] In a possible implementation manner of the second aspect, the indication information includes at least one of the second processing parameter, an index of the second processing parameter, and an index of the radio map model.

[0047] Based on the above solution, the indication information sent (or received) by the second communication device for determining the second processing parameter may include at least one of the above items to enhance the flexibility of the solution implementation.

[0048] In a possible implementation of the second aspect, before the second communication device sends the first information, the method also includes: the second communication device sends model information of N radio map models, the N radio map models including the radio map model, N is a positive integer; wherein the first information is determined based on the model information.

[0049] Optionally, the indication information for determining the second processing parameter is determined based on the model information.

[0050] Optionally, the model information may be pre-configured.

[0051] Based on the above solution, the second communication device may further send model information of N radio map models to the first communication device, so that the first communication device determines and sends first information for determining the first processing parameter based on the model information.

[0052] Optionally, in the model information of the N radio map models, the model information of each radio map model includes at least one of an input processing parameter of each radio map model and an output processing parameter of each radio map model.

[0053] The third aspect of the present application provides a communication device, which is a first communication device, and includes a transceiver unit and a processing unit; the processing unit is used to determine first information and second information; the transceiver unit is used to send the first information, and the first information is used to determine a first processing parameter; the transceiver unit is also used to send the second information, and the second information is determined based on the communication status information; the transceiver unit is also used to receive third information, and the third information includes first radio information, and the first radio information is obtained by processing the second information based on a radio map model; wherein the input of the radio map model is obtained based on the first processing parameter.

[0054] In the third aspect of the present application, the constituent modules of the communication device can also be used to execute the steps performed in each possible implementation method of the first aspect and achieve corresponding technical effects. For details, please refer to the first aspect and will not be repeated here.

[0055] The fourth aspect of the present application provides a communication device, which is a second communication device, and includes a transceiver unit and a processing unit. The transceiver unit is used to receive first information, and the first information is used to determine a first processing parameter; the transceiver unit is also used to receive second information, and the second information is determined based on communication status information; the processing unit is used to determine third information; the transceiver unit is also used to send third information, and the third information includes first radio information, and the first radio information is obtained by processing the second information based on a radio map model; wherein the input of the radio map model is obtained based on the first processing parameter.

[0056] In the fourth aspect of the present application, the constituent modules of the communication device can also be used to execute the steps performed in each possible implementation method of the second aspect and achieve corresponding technical effects. For details, please refer to the second aspect and will not be repeated here.

[0057] In a fifth aspect, the present application provides a communication device, comprising at least one processor coupled to a memory; the memory is configured to store programs or instructions; the at least one processor is configured to execute the programs or instructions, so that the device implements the method described in any possible implementation of any one of the first to second aspects. Optionally, the communication device may include the memory.

[0058] In a sixth aspect, the present application provides a communication device comprising at least one logic circuit and an input / output interface; the logic circuit is used to execute the method described in any possible implementation of any one of the first to second aspects.

[0059] In a seventh aspect, the present application provides a communication system, which includes the above-mentioned first communication device and second communication device.

[0060] In an eighth aspect, the present application provides a computer-readable storage medium for storing one or more computer-executable instructions. When the computer-executable instructions are executed by a processor, the processor executes the method described in any possible implementation of any one of the first to second aspects above.

[0061] In a ninth aspect, the present application provides a computer program product (or computer program). When the computer program in the computer program product is executed by the processor, the processor executes the method described in any possible implementation of any one of the first to second aspects above.

[0062] In a tenth aspect, the present application provides a chip or chip system, the chip or chip system including at least one processor, configured to support a communication device in implementing the method described in any possible implementation of any one of the first to second aspects. For example, the chip may be a baseband chip, a modem chip, a system-on-chip (SoC) chip including a modem core, a system-in-package (SIP) chip, or a communication module.

[0063] In one possible design, the chip or chip system may further include a memory for storing program instructions and data necessary for the communication device. The chip system may be composed of a chip or may include a chip and other discrete components. Optionally, the chip system also includes an interface circuit that provides program instructions and / or data to the at least one processor.

[0064] Among them, the technical effects brought about by any design method in the third to tenth aspects can refer to the technical effects brought about by the different design methods in the above-mentioned first to second aspects, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figures 1a to 1c are schematic diagrams of a communication system provided by this application;

[0066] Figures 1d, 1e, and 2a to 2e are schematic diagrams of the AI ​​processing process involved in this application;

[0067] FIG2 f is a schematic diagram of a radio map model involved in this application;

[0068] FIG3 is an interactive schematic diagram of the communication method provided by this application;

[0069] Figures 4a to 4d are some schematic diagrams of the radio map model provided by this application;

[0070] Figures 5a to 5d are some schematic diagrams of the radio map model provided by this application;

[0071] 6 to 10 are schematic diagrams of the communication device provided in this application. DETAILED DESCRIPTION

[0072] First, some of the terms used in the embodiments of the present application are explained to facilitate understanding by those skilled in the art.

[0073] (1) Terminal device: It can be a wireless terminal device that can receive network device scheduling and instruction information. The wireless terminal device can be a device that provides voice and / or data connectivity to the user, or a handheld device with wireless connection function, or other processing device connected to a wireless modem.

[0074] Terminal devices can communicate with one or more core networks or the Internet via a radio access network (RAN). Terminal devices can be mobile terminal devices, such as mobile phones (also known as "cellular" phones, mobile phones), computers, and data cards. For example, they can be portable, pocket-sized, handheld, computer-built-in, or vehicle-mounted mobile devices that exchange voice and / or data with the radio access network. Examples include personal communication service (PCS) phones, cordless phones, Session Initiation Protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), tablet computers, and computers with wireless transceiver capabilities. Wireless terminal equipment can also be called system, subscriber unit, subscriber station, mobile station, mobile station (MS), remote station, access point (AP), remote terminal equipment (remote terminal), access terminal equipment (access terminal), user terminal equipment (user terminal), user agent, subscriber station (SS), customer premises equipment (CPE), terminal, user equipment (UE), mobile terminal (MT), etc.

[0075] As an example and not a limitation, in the embodiments of the present application, the terminal device may also be a wearable device. Wearable devices may also be referred to as wearable smart devices or smart wearable devices, etc., which are a general term for wearable devices that are intelligently designed and developed using wearable technology for daily wear, such as glasses, gloves, watches, clothing, and shoes. A wearable device is a portable device that is worn directly on the body or integrated into the user's clothes or accessories. Wearable devices are not only hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are fully functional, large in size, and can achieve complete or partial functions without relying on smartphones, such as smart watches or smart glasses, etc., as well as those that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various smart bracelets, smart helmets, and smart jewelry for vital sign monitoring.

[0076] The terminal may also be a drone, a robot, a terminal in device-to-device (D2D) communication, a terminal in vehicle-to-everything (V2X), a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal in industrial control, a wireless terminal in self-driving, a wireless terminal in remote medical, a wireless terminal in smart grid, a wireless terminal in transportation safety, a wireless terminal in smart city, a wireless terminal in smart home, etc.

[0077] In addition, the terminal device may also be a terminal device in a communication system that has evolved after the fifth generation (5G) communication system (e.g., a sixth generation (6G) communication system) or a terminal device in a future public land mobile network (PLMN). For example, the 6G network can further expand the form and function of 5G communication terminals. 6G terminals include but are not limited to vehicles, cellular network terminals (with integrated satellite terminal functions), drones, and Internet of Things (IoT) devices.

[0078] In an embodiment of the present application, the terminal device may also obtain AI services provided by the network device. Optionally, the terminal device may also have AI processing capabilities.

[0079] (2) Network equipment: It can be a device in a wireless network. For example, the network equipment can be a RAN node (or device) that connects a terminal device to a wireless network, which can also be called a base station. Currently, some examples of RAN equipment include: base station, evolved NodeB (eNodeB), gNB (gNodeB) in a 5G communication system, transmission reception point (TRP), evolved Node B (eNB), radio network controller (RNC), Node B (NB), home base station (e.g., home evolved Node B, or home Node B, HNB), base band unit (BBU), or wireless fidelity (Wi-Fi) access point AP, etc. In addition, in a network structure, the network equipment can include a centralized unit (CU) node, a distributed unit (DU) node, or a RAN device including a CU node and a DU node.

[0080] Alternatively, a RAN node can be a macro base station, micro base station, indoor base station, relay node, donor node, or a wireless controller in a cloud radio access network (CRAN) scenario. A RAN node can also be a server, wearable device, vehicle, or vehicle-mounted device. For example, the access network device in vehicle-to-everything (V2X) technology can be a roadside unit (RSU).

[0081] In another possible scenario, multiple RAN nodes collaborate to assist the terminal in achieving wireless access, and different RAN nodes respectively implement part of the functions of the base station. For example, the RAN node can be a centralized unit (CU), a distributed unit (DU), a CU-control plane (CP), a CU-user plane (UP), or a radio unit (RU). The CU and DU can be set separately, or they can be included in the same network element, such as a baseband unit (BBU). The RU can be included in a radio frequency device or radio frequency unit, such as a remote radio unit (RRU), an active antenna unit (AAU), or a remote radio head (RRH).

[0082] In different systems, CU (or CU-CP and CU-UP), DU or RU may also have different names, but those skilled in the art can understand their meanings. For example, in an open access network (open RAN, O-RAN or ORAN) system, CU may also be called O-CU (open CU), DU may also be called O-DU, CU-CP may also be called O-CU-CP, CU-UP may also be called O-CU-UP, and RU may also be called O-RU. For the convenience of description, this application takes CU, CU-CP, CU-UP, DU and RU as examples for description. Any unit of CU (or CU-CP, CU-UP), DU and RU in this application can be implemented by a software module, a hardware module, or a combination of a software module and a hardware module.

[0083] The communication between the access network device and the terminal device follows a certain protocol layer structure. The 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: a radio resource control (RRC) layer, a packet data convergence protocol (PDCP) layer, a radio link control (RLC) layer, a media access control (MAC) layer, or a physical (PHY) layer. The user plane protocol layer may include at least one of the following: a service data adaptation protocol (SDAP) layer, a PDCP layer, an RLC layer, a MAC layer, or a physical layer.

[0084] For the correspondence between network elements in the ORAN system and their achievable protocol layer functions, please refer to Table 1 below.

[0085] Table 1

[0086] The network device may be any other device that provides wireless communication functionality to the terminal device. The embodiments of this application do not limit the specific technology and device form used by the network device. For ease of description, the embodiments of this application do not limit this.

[0087] The network equipment may also include core network equipment, which may include, for example, a mobility management entity (MME), a home subscriber server (HSS), a serving gateway (S-GW), a policy and charging rules function (PCRF), and a public data network gateway (PDN gateway, P-GW) in a fourth generation (4G) network; and network elements such as an access and mobility management function (AMF), a user plane function (UPF), or a session management function (SMF) in a 5G network. In addition, the core network equipment may also include other core network equipment in a 5G network and a next generation network of a 5G network.

[0088] In an embodiment of the present application, the above-mentioned network device may also have a network node with AI capabilities, which can provide AI services for terminals or other network devices. For example, it can be an AI node on the network side (access network or core network), a computing power node, a RAN node with AI capabilities, a core network element with AI capabilities, etc.

[0089] In the embodiments of the present application, the apparatus for implementing the function of the network device may be the network device, or may be a device capable of supporting the network device in implementing the function, such as a chip system, which may be installed in the network device. In the technical solutions provided in the embodiments of the present application, the technical solutions provided in the embodiments of the present application are described by taking the network device as an example.

[0090] (3) Configuration and pre-configuration: In this application, configuration and pre-configuration are used at the same time. Configuration refers to the network device and / or server sending some parameter configuration information or parameter values ​​to the terminal through messages or signaling, so that the terminal can determine the communication parameters or resources during transmission based on these values ​​or information. Pre-configuration is similar to configuration, and can be parameter information or parameter values ​​that the network device and / or server have pre-negotiated with the terminal device, or parameter information or parameter values ​​used by the base station / network device or terminal device as specified in the standard protocol, or parameter information or parameter values ​​pre-stored in the base station and / or server or terminal device. This application does not limit this.

[0091] Furthermore, these values ​​and parameters can be changed or updated.

[0092] (4) The terms "system" and "network" in the embodiments of the present application can be used interchangeably. "Multiple" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, "at least one of A, B and C" includes A, B, C, AB, AC, BC or ABC. In addition, unless otherwise specified, the ordinal numbers such as "first" and "second" mentioned in the embodiments of the present application are used to distinguish multiple objects, and are not used to limit the order, timing, priority or importance of multiple objects.

[0093] (5) “Sending” and “receiving” in the embodiments of the present application indicate the direction of signal transmission. For example, “sending information to XX” can be understood as the destination of the information being XX, which can include direct sending through the air interface, as well as indirect sending through the air interface by other units or modules. “Receiving information from YY” can be understood as the source of the information being YY, which can include direct receiving from YY through the air interface, as well as indirect receiving from YY through the air interface from other units or modules. “Sending” can also be understood as the “output” of the chip interface, and “receiving” can also be understood as the “input” of the chip interface.

[0094] In other words, sending and receiving can be performed between devices, for example, between a network device and a terminal device, or can be performed within a device, for example, sending or receiving between components, modules, chips, software modules or hardware modules within the device through a bus, wiring or interface.

[0095] It is understandable that information may be processed between the source and destination of information transmission, such as coding, modulation, etc., but the destination can understand the valid information from the source. Similar expressions in this application can be understood similarly and will not be repeated.

[0096] (6) In the embodiments of the present application, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain information (such as the indication information described below) is called information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, directly indicating the information to be indicated, such as the information to be indicated itself or the index of the information to be indicated. The information to be indicated may also be indirectly indicated by indicating other information, wherein the other information is associated with the information to be indicated; or only a part of the information to be indicated may be indicated, while the other part of the information to be indicated is known or agreed in advance. For example, the indication of specific information may be achieved by means of the arrangement order of each information agreed in advance (such as predefined by the protocol), thereby reducing the indication overhead to a certain extent. The present application does not limit the specific method of indication. It is understandable that for the sender of the indication information, the indication information can be used to indicate the information to be indicated, and for the receiver of the indication information, the indication information can be used to determine the information to be indicated.

[0097] In this application, unless otherwise specified, the same or similar parts between the various embodiments can refer to each other. In the various embodiments of this application, and the various methods / designs / implementations in each embodiment, if there is no special explanation and logical conflict, the terms and / or descriptions between different embodiments and the various methods / designs / implementations in each embodiment are consistent and can be referenced to each other. The technical features in different embodiments and the various methods / designs / implementations in each embodiment can be combined to form new embodiments, methods, or implementations according to their inherent logical relationships. The following description of the implementation methods of this application does not constitute a limitation on the scope of protection of this application.

[0098] The present application can be applied to a long term evolution (LTE) system, a new radio (NR) system, or a communication system evolved after 5G (such as 6G, etc.). The communication system includes at least one network device and / or at least one terminal device.

[0099] Please refer to Figure 1a, which is a schematic diagram of a communication system in this application. Figure 1a exemplarily illustrates a network device and six terminal devices, namely terminal device 1, terminal device 2, terminal device 3, terminal device 4, terminal device 5, and terminal device 6. In the example shown in Figure 1a, terminal device 1 is a smart teacup, terminal device 2 is a smart air conditioner, terminal device 3 is a smart gas pump, terminal device 4 is a vehicle, terminal device 5 is a mobile phone, and terminal device 6 is a printer.

[0100] As shown in Figure 1a, the AI ​​configuration information sending entity can be a network device. The AI ​​configuration information receiving entity can be terminal devices 1-6. In this case, the network device and terminal devices 1-6 form a communication system. In this communication system, terminal devices 1-6 can send data to the network device, and the network device needs to receive data sent by terminal devices 1-6. At the same time, the network device can send configuration information to terminal devices 1-6.

[0101] For example, in Figure 1a, terminal devices 4 and 6 can also form a communication system. Terminal device 5 serves as a network device, i.e., the AI ​​configuration information sending entity; terminal devices 4 and 6 serve as terminal devices, i.e., the AI ​​configuration information receiving entities. For example, in a connected vehicle system, terminal device 5 sends AI configuration information to terminal devices 4 and 6, respectively, and receives data from them. Correspondingly, terminal devices 4 and 6 receive AI configuration information from terminal device 5 and send data to terminal device 5.

[0102] Taking the communication system shown in Figure 1a as an example, in addition to executing communication-related services, different devices (including between network devices, between network devices and terminal devices, and / or between terminal devices) may also execute AI-related services.

[0103] As shown in Figure 1b, taking the network device as a base station as an example, the base station can perform communication-related services and AI-related services with one or more terminal devices, and different terminal devices can also perform communication-related services and AI-related services.

[0104] As shown in Figure 1c, taking the terminal devices including a TV and a mobile phone as an example, communication-related services and AI-related services can also be performed between the TV and the mobile phone.

[0105] The technical solution provided in this application can be applied to a wireless communication system (e.g., the system shown in FIG. 1a , FIG. 1b , or FIG. 1c ). For example, an AI network element can be introduced into the communication system provided in this application to implement some or all AI-related operations. The AI ​​network element can also be referred to as an AI node, AI device, AI entity, AI module, AI model, or AI unit, etc. The AI ​​network element can be a network element built into the communication system. For example, the AI ​​network element can be an AI module built into: an access network device, a core network device, a cloud server, or a network management (OAM) to implement AI-related functions. The OAM can be a network management device for a core network device and / or a network management device for an access network device. Alternatively, the AI ​​network element can also be an independently set network element in the communication system. Optionally, the terminal or the chip built into the terminal can also include an AI entity to implement AI-related functions.

[0106] The following is a brief introduction to artificial intelligence (AI) that may be involved in this application.

[0107] Artificial intelligence (AI) can imbue machines with human intelligence. For example, it can enable machines to simulate certain intelligent human behaviors using computer hardware and software. Machine learning methods can be used to achieve AI. In machine learning, a machine uses training data to learn (or train) a model. This model represents the mapping from input to output. The learned model can be used for inference (or prediction), meaning that the model can be used to predict the output corresponding to a given input. This output can also be called an inference result (or prediction result).

[0108] Machine learning can include supervised learning, unsupervised learning, and reinforcement learning. Among them, unsupervised learning can also be called unsupervised learning.

[0109] Supervised learning uses machine learning algorithms to learn the mapping relationship between sample values ​​and sample labels based on collected sample values ​​and sample labels, and then expresses this learned mapping relationship using an AI model. The process of training a machine learning model is the process of learning this mapping relationship. During training, sample values ​​are input into the model to obtain the model's predicted values. The model parameters are optimized by calculating the error between the model's predicted values ​​and the sample labels (ideal values). Once the mapping relationship is learned, the learned mapping can be used to predict new sample labels. The mapping relationship learned by supervised learning can include linear mappings or nonlinear mappings. Based on the type of label, the learning task can be divided into classification tasks and regression tasks.

[0110] Unsupervised learning uses algorithms to discover inherent patterns in collected sample values. One type of unsupervised learning algorithm uses the samples themselves as supervisory signals, meaning the model learns the mapping from one sample to another. This is called self-supervised learning. During training, the model parameters are optimized by calculating the error between the model's predictions and the samples themselves. Self-supervised learning can be used in signal compression and decompression recovery applications. Common algorithms include autoencoders and generative adversarial networks.

[0111] Reinforcement learning, unlike supervised learning, is a type of algorithm that learns problem-solving strategies through interaction with the environment. Unlike supervised and unsupervised learning, reinforcement learning problems lack explicit label data for "correct" actions. Instead, the algorithm must interact with the environment to obtain reward signals from the environment, and then adjust its decision-making actions to maximize the reward signal value. For example, in downlink power control, the reinforcement learning model adjusts the downlink transmit power of each user based on the overall system throughput fed back by the wireless network, hoping to achieve higher system throughput. The goal of reinforcement learning is also to learn the mapping between environmental states and optimal (e.g., optimal) decision-making actions. However, because the labels for "correct actions" cannot be obtained in advance, network optimization cannot be achieved by calculating the error between actions and "correct actions." Reinforcement learning training is achieved through iterative interaction with the environment.

[0112] A neural network (NN) is a specific model in machine learning technology. According to the universal approximation theorem, NNs can theoretically approximate any continuous function, enabling them to learn arbitrary mappings. Traditional communication systems require extensive expert knowledge to design communication modules. However, deep learning communication systems based on neural networks can automatically discover implicit patterns in massive data sets and establish mapping relationships between data, achieving performance superior to traditional modeling methods.

[0113] The idea of ​​a neural network is derived from the neuronal structure of the brain. For example, each neuron performs a weighted sum operation on its input values ​​and outputs the result through an activation function.

[0114] As shown in Figure 1d, it is a schematic diagram of the neuron structure. Assume that the input of the neuron is x=[x0,x1,…,x n ], and the weights corresponding to each input are w=[w0,w1,…,w n ], where n is a positive integer, w i and x i It can be a decimal, an integer (such as 0, a positive integer or a negative integer, etc.), or a complex number. i As x i The weight of x i Weighted. The bias of the weighted sum of the input values ​​according to the weight is, for example, b. The activation function can take many forms. Assuming that the activation function of a neuron is: y = f(z) = max(0,z), then the output of the neuron is: For another example, if the activation function of a neuron is: y = f(z) = z, then the output of the neuron is: b can be a decimal, an integer (eg, 0, a positive integer, or a negative integer), or a complex number, etc. The activation functions of different neurons in a neural network can be the same or different.

[0115] Furthermore, neural networks generally include multiple layers, each of which may include one or more neurons. Increasing the depth and / or width of a neural network can improve its expressive power, providing more powerful information extraction and abstract modeling capabilities for complex systems. The depth of a neural network can refer to the number of layers it comprises, and the number of neurons in each layer can be referred to as the width of that layer. In one implementation, a neural network includes an input layer and an output layer. The input layer processes the input information received by the neural network through neurons, passing the processing results to the output layer, which then obtains the output of the neural network. In another implementation, a neural network includes an input layer, a hidden layer, and an output layer. The input layer processes the input information received by the neural network through neurons, passing the processing results to an intermediate hidden layer. The hidden layer performs calculations on the received processing results to obtain a calculation result, which is then passed to the output layer or the next adjacent hidden layer, which ultimately obtains the output of the neural network. A neural network can include one hidden layer or multiple hidden layers connected in sequence, without limitation.

[0116] The neural network is, for example, a deep neural network (DNN). Depending on how the network is constructed, DNNs can include feedforward neural networks (FNNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs).

[0117] Figure 1e is a schematic diagram of a FNN network. A characteristic of FNN networks is that neurons in adjacent layers are fully connected. This characteristic typically requires a large amount of storage space and results in high computational complexity.

[0118] CNN is a neural network specifically designed to process data with a grid-like structure. For example, time series data (discrete sampling along the time axis) and image data (discrete sampling along two dimensions) can both be considered grid-like data. CNNs do not utilize all input information at once for computation. Instead, they use a fixed-size window to intercept a portion of the information for convolution operations, significantly reducing the computational complexity of model parameters. Furthermore, depending on the type of information intercepted by the window (e.g., people and objects in an image represent different types of information), each window can use a different convolution kernel, enabling CNNs to better extract features from the input data.

[0119] RNNs are a type of DNN that utilizes feedback time series information. Their input consists of a new input value at the current moment and their own output value at the previous moment. RNNs are suitable for capturing temporally correlated sequence features and are particularly well-suited for applications such as speech recognition and channel coding.

[0120] During the machine learning model training process, a loss function can be defined. This function describes the gap or discrepancy between the model's output and the ideal target value. Loss functions can be expressed in various forms, and there are no restrictions on their specific form. The model training process can be viewed as adjusting some or all of the model's parameters to keep the loss function below a threshold or meet the target.

[0121] A model may also be referred to as an AI model, rule, or other name. An AI model can be considered a specific method for implementing an AI function. An AI model represents a mapping relationship or function between the input and output of a model. AI functions may include one or more of the following: data collection, model training (or model learning), model information release, model inference (or model reasoning, inference, or prediction, etc.), model monitoring or model verification, or inference result release, etc. AI functions may also be referred to as AI (related) operations, or AI-related functions.

[0122] The following is an illustrative description of the implementation process of the neural network with reference to the accompanying drawings.

[0123] 1. Fully connected neural network, also known as multilayer perceptron (MLP).

[0124] As shown in Figure 2a, an MLP consists of an input layer (left), an output layer (right), and multiple hidden layers (center). Each layer of the MLP contains several nodes, called neurons. Neurons in adjacent layers are connected to each other.

[0125] Optionally, considering neurons in two adjacent layers, the output h of a neuron in the next layer is the weighted sum of all neurons x connected to it in the previous layer and passes through an activation function, which can be expressed as: h=f(wx+b).

[0126] Among them, w is the weight matrix, b is the bias vector, and f is the activation function.

[0127] Alternatively, the output of the neural network can be recursively expressed as: y = f n (w n f n-1 (…)+b n ).

[0128] Where n is the index of the neural network layer, 1<=n<=N, where N is the total number of neural network layers.

[0129] In other words, a neural network can be understood as a mapping from an input data set to an output data set. Neural networks are typically initialized randomly, and the process of obtaining this mapping from random w and b using existing data is called neural network training.

[0130] Optionally, a specific training method is to use a loss function to evaluate the output results of the neural network.

[0131] As shown in Figure 2b, the error can be backpropagated, and the neural network parameters (including w and b) can be iteratively optimized using gradient descent until the loss function reaches a minimum, which is the "better point (e.g., optimal point)" in Figure 2b. It is understood that the neural network parameters corresponding to the "better point (e.g., optimal point)" in Figure 2b can be used as the neural network parameters in the trained AI model information.

[0132] Alternatively, the gradient descent process can be expressed as:

[0133] Among them, θ is the parameter to be optimized (including w and b), L is the loss function, η is the learning rate, which controls the step size of gradient descent. represents the derivative operation, represents the derivative of θ with respect to L.

[0134] Optionally, the backpropagation process utilizes the chain rule for partial derivatives.

[0135] As shown in Figure 2c, the gradient of the previous layer parameters can be recursively calculated from the gradient of the next layer parameters, which can be expressed as:

[0136] Among them, w ij is the weight of node j connecting to node i, s i is the weighted sum of the inputs to node i.

[0137] 2. Federated Learning (FL)

[0138] The concept of federated learning effectively solves the current difficulties faced by the development of artificial intelligence. On the premise of fully protecting user data privacy and security, it efficiently completes the model learning task by promoting the collaboration between various edge devices and central servers.

[0139] As shown in Figure 2d, the FL architecture is the most widely used training architecture in the current FL field. The FedAvg algorithm is the basic algorithm of FL. Its algorithm flow is roughly as follows:

[0140] (1) The center initializes the model to be trained And broadcast it to all client devices.

[0141] (2) In the t∈[1,T]th round, client k∈[1,K] based on the local dataset For the received global model Perform E epochs of training to obtain local training results Report it to the central node.

[0142] (3) The central node aggregates and collects the local training results from all (or some) clients. Assume that the client set that uploads the local model in round t is The center will use the number of samples of the corresponding client as the weight to perform weighted averaging to obtain a new global model. The specific update rule is: The center then sends the latest version of the global model Broadcast to all client devices for a new round of training.

[0143] (4) Repeat steps (2) and (3) until the model finally converges or the number of training rounds reaches the upper limit.

[0144] In addition to reporting local models You can also use the local gradient of training After reporting, the central node averages the local gradients and updates the global model according to the direction of the average gradient.

[0145] As you can see, in the FL framework, datasets exist on distributed nodes. Distributed nodes collect local datasets, perform local training, and report the local training results (models or gradients) to the central node. The central node itself does not have a dataset; it is only responsible for fusing the training results of distributed nodes to obtain a global model and send it to the distributed nodes.

[0146] 3. Decentralized learning: Different from federated learning, decentralized learning is another distributed learning architecture.

[0147] As shown in Figure 2e, consider a fully distributed system without a central node. The design goal f(x) of a decentralized learning system is generally the goal f of each node. i The mean of (x), that is Where n is the number of distributed nodes, x is the parameter to be optimized. In machine learning, x is the parameter of the machine learning (such as neural network) model. Each node uses local data and local target f i (x) Calculate local gradient Then it is sent to the neighboring nodes that can be communicated with. After any node receives the gradient information sent by its neighbor, it can update the parameter x of the local model according to the following formula:

[0148] in, represents the parameters of the local model after the k+1th (k is a natural number) update in the i-th node, Represents the parameters of the local model after the kth update in the i-th node (if k is 0, it means is the parameter of the local model of the i-th node that does not participate in the update), α k Represents the tuning coefficient, N i is the set of neighbor nodes of node i, |N i | represents the number of elements in the neighbor node set of node i, that is, the number of neighbor nodes of node i. Through information interaction between nodes, the decentralized learning system will eventually learn a unified model.

[0149] The technical solutions provided in this application can be applied to wireless communication systems (e.g., the systems shown in Figures 1a and 1b). In wireless communication systems, communication nodes generally have both signal transceiver capabilities and computing capabilities. For example, network devices with computing capabilities primarily provide computing power to support signal transceiver capabilities (e.g., performing signal transmission and reception processing) to enable communication between the network device and other communication nodes.

[0150] In addition to processing communication signals within a communication network, communication devices may also handle other communication tasks. Radio map models can be widely applied to various communication tasks, including but not limited to network planning, interference control, path loss prediction, signal strength prediction, power control, resource allocation, handover management, multi-hop routing, or dynamic spectrum access. Generally, a radio map module can obtain radio information based on input information.

[0151] As an implementation example, as shown in Figure 2f, the current radio map model is generally a single-function radio map model (the radio map model is denoted as "RF map" in the figure), that is, the input is the state information of a specific user (such as location coordinates, environmental information, etc., the input is denoted as "(x, y)" in the figure), and the output is the radio-related information of the user in that state (such as location, state) (the output is denoted as "(z)" in the figure). For example, the input of the radio map model is the location information of user 1, and the output is the path loss of user 1 at that location. In this case, this radio map model can also be called a path loss map model, that is, the function of the radio map model is a path loss prediction model. For another example, the input of the radio map model is the location information of user 2, and the output is the radio signal strength of user 2 at that location. In this case, this radio map model can also be called a signal strength map model, that is, the function of the radio map model is a signal strength prediction model.

[0152] Furthermore, radio map models are typically pre-trained. Devices deploying radio map models (e.g., servers, wireless map servers, etc.) can provide radio information for different functions using different radio map models. Accordingly, for radio information for a specific function, the device typically deploys only one radio map model. For radio information for a specific function, the input processing parameters (e.g., scaling parameters, precision conversion parameters, etc.) of the radio map model providing that radio information are typically fixed. In other words, the provider of radio information relies on the input of specific processing parameters to provide that specific radio information.

[0153] However, the capabilities or requirements of different users may be different. The above method requires each user to input the same processing parameters to the provider of the radio information, resulting in poor flexibility in implementing the solution.

[0154] In order to solve the above problems, the present application provides a communication method and related devices, which will be described in detail below with reference to the accompanying drawings.

[0155] Please refer to FIG3 , which is a schematic diagram of an implementation of the communication method provided in this application. The method includes the following steps.

[0156] It should be noted that, in FIG3 , the method is illustrated by taking the first communication device and the second communication device as the execution entities of the interaction diagram as an example, but this application does not limit the execution entities of the interaction diagram. For example, in FIG3 , the execution entity of the method can be replaced by a chip, chip system, processor, logic module, or software in the communication device.

[0157] As an example, the first communication device may be a terminal device and the second communication device may be a network device or a third server. For example, the network device may be an access network device, a core network device, etc.

[0158] As another example, the first communication device may be an access network device, and the second communication device may be a core network device or a third-party server, etc.

[0159] As another example, the first communication device and the second communication device are both terminal devices, that is, the solution shown in Figure 3 can be applied to the sidelink communication scenario.

[0160] S301. A first communication device sends first information, and correspondingly, a second communication device receives the first information, wherein the first information is used to determine a first processing parameter.

[0161] S302: The first communication device sends second information, and correspondingly, the second communication device receives the second information, wherein the second information is determined based on the communication state information.

[0162] Optionally, the communication status information may include real-time information (or dynamic information) such as transmit power, modulation and coding scheme (MCS) level, number of retransmissions, or data cache status information; that is, the radio information may be determined by the real-time communication status of the communication device, so that the determination process of the radio information can take into account the influence of the real-time communication status, thereby improving the accuracy of the radio information. For another example, the communication status information may include non-real-time information (or static information) such as location coordinate information, environmental information, or antenna configuration information; that is, the radio information may be determined by the non-real-time communication status of the communication device, so that the determination process of the radio information can take into account the influence of the non-real-time communication status, thereby further improving the accuracy of the radio information.

[0163] S303. The second communication device sends third information, and the first communication device receives the third information accordingly. The third information includes first radio information, the first radio information being obtained by processing the second information based on a radio map model, the input of the radio map model being obtained based on the first processing parameter.

[0164] In this application, the radio map model can be a mathematical model, an artificial intelligence (AI) model, a neural network, a neural network model, an AI neural network model, a machine learning model, an AI processing model, etc.

[0165] Based on the scheme shown in Figure 3, the first information sent by the first communication device in step S301 is used to determine the first processing parameter, the third information received by the first communication device in step S303 includes the first radio information, and the input of the radio map model is obtained based on the first processing parameter. In other words, the first communication device, as the requestor of the radio information, can specify the processing parameter of the input of the radio map model through the first information to obtain the radio information corresponding to the processing parameter. Compared to the implementation method in which the radio map model can only input data obtained based on a single processing parameter for subsequent processing, in the above process, the radio information obtained by the first communication device through the radio map model can be obtained based on the input corresponding to the processing parameter expected (or indicated, or specified) by the first communication device, thereby improving the flexibility of the use of the radio map model.

[0166] Optionally, as shown in the method of Figure 3, the first communication device may be the requester of the radio information, and the second communication device may be the provider of the radio information; accordingly, the first communication device may be called a radio map user (or map user, or radio map model user, etc.), and the second communication device may be a radio map server (or map server, or radio map model server, etc.).

[0167] In one possible implementation of the solution shown in Figure 3, the first information sent by the first communications device in step S301 includes at least one of the first processing parameter, an index of the first processing parameter, and an index of the radio map model. In other words, the first information sent by the first communications device for determining the first processing parameter may include at least one of the aforementioned items, thereby increasing flexibility in implementing the solution.

[0168] It should be understood that the first information may include the index of the radio map model corresponding to the first processing parameter, wherein, since the input of the radio map model is obtained based on the first processing parameter, the first information may also include the index of the radio map model, so that the recipient of the first information can determine the first processing parameter indirectly.

[0169] In one possible implementation of the scheme shown in Figure 3, before the first communication device sends the first information in step S301, the method further includes: the first communication device receiving model information for N radio map models, the N radio map models including the radio map model, where N is a positive integer; wherein the first information is determined based on the model information. In other words, the first communication device may also receive model information for the N radio map models, so that the first communication device can determine and send first information for determining first processing parameters based on the model information. Furthermore, the second communication device may save (or store, or configure) a small number of N radio map models with fixed processing parameters, and process the input processing parameters of the map models according to user requirements (i.e., the requirements of the first communication device indicated by the first information).

[0170] Optionally, the model information of the N radio map models may be preconfigured.

[0171] Optionally, in the model information of the N radio map models, the model information of each radio map model includes at least one of an input processing parameter of each radio map model and an output processing parameter of each radio map model.

[0172] Exemplarily, taking the value of N as 3 as an example, the model information of N radio map models is shown in Table 2 below.

[0173] Table 2

[0174] It should be understood that, as described above, an "index" in Table 2 may be an index of a processing parameter or an index of a radio map model.

[0175] It should be noted that the processing parameters involved in this application may include at least one of a scaling parameter and a precision conversion parameter. In addition, the processing parameters include processing parameters of the input of the radio map model (e.g., a first processing parameter) and / or processing parameters of the output of the radio map model (e.g., a second processing parameter described below).

[0176] Furthermore, as described above, the input to the radio map model can include communication status information. As a possible implementation, this communication status information can be carried in the form of map information, indicating the device's communication status. In this case, if the processing parameters of the radio map model input include a scaling parameter, since different scaling parameters can represent map information at different scales, the scaling parameter of the radio map model input can also be understood as a scale or a scale-related parameter.

[0177] The following will take the case where the processing parameters include a scaling parameter and / or a precision conversion parameter (ie, the first processing parameter includes a first scaling parameter and / or a first precision conversion parameter) as an example, and describe it in combination with some implementation examples.

[0178] In the examples shown in Figures 4a through 4d below, the radio map model can be represented by the RF map. Referring to the example shown in Figure 2f, the radio map model can process input data to generate output data. In the solution shown in Figure 3, since the input of the radio map model is based on a first processing parameter, which is a first scaling parameter and / or a first precision conversion parameter, scaling and / or precision conversion processing must be performed on the input data (x, y) before using the RF map.

[0179] As an example, as shown in FIG4a , the first processing parameter includes a first scaling parameter. In this case, the input processing parameter of the RF map is the first scaling parameter. Accordingly, the input data (x, y) can be subjected to "scaling processing" to obtain a scaling processing result, and the scaling parameter used in the scaling processing is the first scaling parameter. The result of the scaling processing conforms to the data characteristics of the RF map input. That is, the scaling processing result can be processed as the input of the RF map to obtain the output data (z). For example, a radio map model requires a 100x100 environmental image for its input environmental information, and the environmental image size in the map user's status information (i.e., the communication status information obtained by the first communication device) is 200x200. The scaling process can indicate that its length and width are reduced by half so that it can be input into the radio map model.

[0180] Exemplarily, based on the example shown in FIG4 a , still taking the value of N as 3 as an example, the model information of the N radio map models in the aforementioned Table 2 can be implemented as shown in the following Table 3.

[0181] Table 3

[0182] In Table 3, the values ​​of A1 / B1 / C1 / D1 / E1 / F1 / G1 / H1 / I1 can be positive numbers.

[0183] As another example, as shown in FIG4b , the first processing parameter includes a first precision conversion parameter. In this case, the processing parameter of the RF map input is the first precision conversion parameter. Accordingly, the input data (x, y) can undergo "precision conversion processing" to obtain a precision conversion processing result, and the precision conversion processing result meets the precision conversion accuracy requirements of the RF map for its input. That is, the precision conversion processing result can be processed as the input of the RF map to obtain the output data (z). For example, if the input data type of a radio map model is integer, and the data type of the map user's status information is floating point, the precision conversion processing can refer to converting the floating point data into integer data for input into the radio map model; for another example, if the input data type of a radio map model is A-bit floating point number, and the data type of the map user's status information is B-bit floating point number, where A is not equal to B, the precision conversion processing can refer to converting the B-bit floating point number into an A-bit floating point number for input into the radio map model.

[0184] Exemplarily, based on the example shown in FIG4 b , still taking the value of N as 3 as an example, the model information of the N radio map models in the aforementioned Table 2 can be implemented as shown in the following Table 4.

[0185] Table 4

[0186] In Table 4, P1 / P2 / P3 are different from each other.

[0187] As another example, as shown in Figure 4c, the first processing parameter includes a first scaling parameter and a first precision conversion parameter. In this case, the input processing parameters of the RF map are the first scaling parameter and the first precision conversion parameter. Accordingly, the input data (x, y) can undergo "scaling processing" and "precision conversion processing" to obtain a scaling and precision conversion processing result. The scaling parameter of the scaling and precision conversion processing result is the first scaling parameter, and the scaling and precision conversion processing result conforms to the input data characteristics of the RF map. In other words, the scaling and precision conversion processing result can be processed as the input of the RF map to obtain the output data (z). For example, the environmental information in the input of a radio map model is a 100x100 environmental picture, and the input data type is an A-bit floating point number; while the environmental picture size in the map user's status information (i.e., the communication status information obtained by the first communication device) is 200x200, and the data type of the map user's status information is a B-bit floating point number (A is not equal to B), then the scaling processing can indicate that its length and width are reduced by half, and the precision conversion processing can indicate that the B-bit floating point number is converted into an A-bit floating point number for input into the radio map model.

[0188] Optionally, in FIG4c , the processing order of the scaling process and the precision conversion process can be swapped, as shown in FIG4d , the precision conversion process can be performed first and then the scaling process. The specific implementation process can refer to the process shown in FIG4c above.

[0189] Exemplarily, based on the examples shown in FIG. 4 c and FIG. 4 d , still taking the value of N as 3 as an example, the model information of the N radio map models in the aforementioned Table 2 can be implemented as shown in the following Table 5.

[0190] Table 5

[0191] In Table 5, the numerical values ​​can refer to the examples shown in Table 3 and Table 4.

[0192] As can be seen from the processes shown in Figures 4a through 4d, after step S302, the second communication device can obtain input processed based on the first processing parameters and then process the input based on the radio map model to obtain first radio information. The scaling and / or precision conversion processes shown in Figures 4a through 4d can be implemented in a variety of ways, which will be described below using Implementation Methods 1 and 2.

[0193] Implementation method 1: The second information sent by the first communication device in step S302 includes the communication status information.

[0194] In implementation method 1, after the second communication device transmits the second information including the communication status information in step S302, the second communication device may process the communication status information based on the first processing parameters to obtain input for the radio map model. For example, the scaling and / or precision conversion processing described above may be performed by the second communication device. This allows the second communication device to process the communication status information based on the first processing parameters indicated by the first information to obtain input for the radio map model, thereby reducing the implementation complexity of the first communication device.

[0195] Optionally, in implementation mode 1, the processing module that performs processing based on the first processing parameter may be independent of the radio map model (for example, the scaling processing module and / or the precision conversion processing module in Figures 4a to 4d may be independent of the RF map). Alternatively, the processing module that performs processing based on the first processing parameter may be an internal module of the radio map model (for example, the scaling processing module and / or the precision conversion processing module in Figures 4a to 4d may be an internal module of the RF map). In this case, the first processing parameter may be considered a model parameter of the radio map model or a parameter of the internal module, etc.

[0196] In a second implementation mode, the second information sent by the first communication device in step S302 includes a processing result obtained by processing the communication status information based on the first processing parameter.

[0197] In the second implementation, after the second communication device sends the second information including the processing result in step S302, the second communication device can directly use the processing result as part or all of the input of the radio map model, which can reduce the implementation complexity of the receiver of the second information.

[0198] In the above implementation process, the first communication device can act as a map user and the second communication device can act as a map server. The process shown in Figure 3 can enable the second communication device to process the model input based on the processing parameters specified by the first communication device. In order to further enhance the flexibility of the solution implementation, it is considered that the output of the radio map model can also be further processed based on the processing parameters. For example, the processing parameters used for further processing of the output may also be specified by the first communication device, and the second communication device may be triggered to process its output based on the specified second processing parameters (i.e., the second communication device may provide radio information obtained based on the second processing parameters in step S303); or, the first communication device may locally process the radio information received in step S303 based on the second processing parameters. Similarly, the following will take the second processing parameters including scaling parameters and / or precision conversion parameters (i.e., the second processing parameters include second scaling parameters and / or second precision conversion parameters) as an example, combined with some implementation examples for explanation.

[0199] In the examples shown in Figures 5a through 5d below, the radio map model can be represented as the RF map. Referring to the example shown in Figure 2f, the radio map model can be used to process input data to generate output data. In the scenario shown in Figure 3, the first communications device expects a target output that conforms to the data characteristics corresponding to the second processing parameter. Therefore, after obtaining an initial RF map output, the RF map can be scaled and / or precision-converted to obtain the target output. In the examples below, this target output is denoted as "(z)."

[0200] Optionally, in the following example, the second scaling parameter used in the "scaling process" of the output of the RF map in Figure 5a / Figure 5c / Figure 5d may be associated with the first scaling parameter used in the "scaling process" of the input of the RF map in Figure 4a / Figure 4c / Figure 4d above. In this way, the radio information (z) (i.e., the final output) can be matched with the input data (x, y) (i.e., the initial input), so that the requester of the radio information (e.g., the first communication device) can obtain radio information that matches its own communication state. For example, the first scaling parameter and the second scaling parameter are reciprocals of each other. For another example, the first scaling parameter and the second scaling parameter are the same.

[0201] For example, using the example shown in FIG. 4a above, a radio map model for path loss prediction (hereinafter referred to as a path loss map model) requires a 100x100 image of the environment as its input. However, the map user's status information (i.e., the communication status information obtained by the first communication device) contains an image of the environment with a size of 200x200. The "scaling" of the input in FIG. 4a can indicate that both its length and width are reduced by half. Therefore, the first scaling parameter p used in the "scaling" of the input can be 1 / 2 (i.e., reducing it by half). Accordingly, after the radio map model obtains an initial output through processing, the initial output can be processed based on the "scaling" in FIG. 5a to obtain a target output (z). The second scaling parameter q used in the "scaling" of the output can be 1 / p = 2, assuming that the actual distance between the transmitter and receiver in the original environment image is twice the distance after scaling. For the path loss map, based on the second scaling parameter q described in the above example, the initial output is processed by adding 20log2, i.e., z = z' + 20log2, where z' is the initial output of the radio map.

[0202] As an example, as shown in FIG5a , the second processing parameter includes a second scaling parameter. In this case, the target output (z) of the RF map is obtained based on the second scaling parameter. Accordingly, the initial output of the RF map can be "scaled" to obtain the target output (z).

[0203] Exemplarily, based on the example shown in FIG5a , still taking the value of N as 3 as an example, the model information of the N radio map models in the aforementioned Table 2 can be implemented as shown in the following Table 6.

[0204] Table 6

[0205] In Table 6, the values ​​of A2 / B2 / C2 / D2 / E2 / F2 / G2 / H2 / I2 can be positive numbers.

[0206] As another example, as shown in Figure 5b, take the example where the second processing parameter includes a second precision conversion parameter. In this case, the target output (z) of the RF map is obtained based on the second precision conversion parameter, and accordingly, the initial output of the RF map can undergo "precision conversion processing" to obtain the target output (z). For example, if the output data type of a certain radio map model is integer, and the second precision conversion parameter indicates floating point, then the precision conversion processing may refer to converting the integer data initially output by the model into floating point data to conform to the data characteristics corresponding to the second precision conversion parameter; for another example, if the output data type of a certain radio map model is A-bit floating point number, and the second precision conversion parameter indicates B-bit floating point number, where A is not equal to B, then the precision conversion processing may refer to converting the A-bit floating point number initially output by the model into a B-bit floating point number to conform to the data characteristics corresponding to the second precision conversion parameter.

[0207] Exemplarily, based on the example shown in FIG5 b , still taking the value of N as 3 as an example, the model information of the N radio map models in the aforementioned Table 2 can be implemented as shown in the following Table 7.

[0208] Table 7

[0209] In Table 7, Q1 / Q2 / Q3 are not equal to each other.

[0210] As another example, as shown in Figure 5c, the second processing parameters include a second scaling parameter and a second precision conversion parameter. In this case, the target output (z) of the RF map is obtained based on the second scaling parameter and the second precision conversion parameter. Accordingly, the initial output of the RF map can undergo "scaling processing" and "precision conversion processing" to obtain the target output (z). For example, the implementation process of the scaling process and the precision conversion process can refer to the examples shown in Figures 5a and 5b above, respectively.

[0211] Optionally, in FIG5c , the processing order of the scaling process and the precision conversion process can be swapped, as shown in FIG5d , where the precision conversion process can be performed first and then the scaling process. The specific implementation process can refer to the process shown in FIG5c above.

[0212] Exemplarily, based on the examples shown in FIG. 5 c and FIG. 5 d , still taking the value of N as 3 as an example, the model information of the N radio map models in the aforementioned Table 2 can be implemented as shown in the following Table 8.

[0213] Table 8

[0214] In Table 8, the numerical values ​​can refer to the examples shown in Table 6 and Table 7.

[0215] Optionally, the model information of the N radio map models may also include both input processing parameters and output processing parameters, i.e., any table in Tables 3 to 5 may be combined with any table in Tables 6 to 8. Taking the combination of Tables 5 and 8 as an example, this can be achieved as shown in Table 9 below.

[0216] Table 9

[0217] As shown in the processes illustrated in Figures 5a through 5d, during processing by the second communication device based on the radio map model, the second communication device can obtain an initial RF map output. Furthermore, this initial RF map output can be processed to obtain radio information with data characteristics that conform to second processing parameters. The scaling and / or precision conversion processes illustrated in Figures 5a through 5d can be implemented in a variety of ways, which will be described below using Implementation A and Implementation B.

[0218] Implementation A: After step S303, the method further includes: the first communication device processes the first radio information based on the second processing parameter to obtain second radio information.

[0219] In implementation A, the first communication device can process radio information output by the radio map model to obtain output corresponding to specific processing parameters, so that the first communication device performs a corresponding communication task based on the output corresponding to the specific processing parameters.

[0220] Optionally, in implementation A, the method further includes: the first communication device receiving instruction information for determining the second processing parameter (wherein the instruction information may be included in the third information in step S303, or may be included in other information / message / signaling). In other words, the first communication device may further receive the instruction information to determine the second processing parameter, i.e., the first communication device may obtain an output corresponding to a specific processing parameter based on the processing parameter specified by another communication device (e.g., the second communication device).

[0221] In implementation B, the first radio information included in the third information received by the first communication device in step S303 is obtained based on the second processing parameter.

[0222] In implementation B, before step S303, the method further includes: the first communication device sending instruction information for determining the second processing parameter. In other words, the first communication device may also send the instruction information so that a recipient of the instruction information (e.g., the second communication device) can determine the second processing parameter, and the first radio information sent by the recipient to the first communication device is based on the second processing parameter. In other words, the first communication device can specify the processing parameter to other communication devices to obtain a radio output corresponding to the specific processing parameter.

[0223] It can be understood that in implementation method B, the output of the radio map model may conform to the data characteristics corresponding to the second processing parameter (for example, the scaling characteristics of the output of the radio map model may conform to the scaling characteristics corresponding to the second processing parameter; for example, the precision conversion characteristics of the output of the radio map model may conform to the precision conversion characteristics corresponding to the second processing parameter). In this case, the second processing parameter can be regarded as a model parameter of the radio map model or a parameter of an internal module, etc.

[0224] Alternatively, in implementation method B, the output of the radio map model may not conform to the data characteristics corresponding to the second processing parameter. In this case, the second communication device can process the output of the radio map model based on the second processing parameter to obtain first radio information that conforms to the data characteristics corresponding to the second processing parameter; accordingly, the second processing parameter can be regarded as a parameter of a processing module independent of the radio map model.

[0225] Optionally, in implementation manner A or implementation manner B, the indication information sent or received by the first communication device includes at least one of the second processing parameter, an index of the second processing parameter, and an index of the radio map model.

[0226] It should be understood that the indication information may include an index of a radio map model corresponding to the second processing parameter, wherein, since the output of the radio map model is obtained based on the second processing parameter, the indication information may also include an index of the radio map model, so that the recipient of the indication information can indirectly determine the second processing parameter. Specifically, the indication information sent (or received) by the first communication device for determining the second processing parameter may include at least one of the above items to enhance the flexibility of the solution implementation.

[0227] Optionally, the indication information for determining the second processing parameter is determined based on model information of N radio map models (eg, the examples shown in any one of Tables 6 to 9 above).

[0228] Referring to Figure 6 , an embodiment of the present application provides a communication device 600. This communication device 600 can implement the functions of the second communication device or the first communication device in the above-described method embodiment, thereby also achieving the beneficial effects of the above-described method embodiment. In this embodiment of the present application, the communication device 600 can be the first communication device (or second communication device), or it can be an integrated circuit or component, such as a chip, within the first communication device (or second communication device).

[0229] It should be noted that the transceiver unit 602 may include a sending unit and a receiving unit, which are respectively used to perform sending and receiving.

[0230] In one possible implementation, when the device 600 is used to execute the method executed by the first communication device in the aforementioned embodiment, the device 600 includes a processing unit 601 and a transceiver unit 602; the processing unit 601 is used to determine the first information and the second information; the transceiver unit 602 is used to send the first information, and the first information is used to determine the first processing parameter; the transceiver unit 602 is also used to send the second information, and the second information is determined based on the communication status information; the transceiver unit 602 is also used to receive third information, and the third information includes first radio information, and the first radio information is obtained by processing the second information based on a radio map model; wherein the input of the radio map model is obtained based on the first processing parameter.

[0231] In one possible implementation, when the device 600 is used to execute the method executed by the second communication device in the aforementioned embodiment, the device 600 includes a processing unit 601 and a transceiver unit 602; the transceiver unit 602 is used to receive first information, and the first information is used to determine a first processing parameter; the transceiver unit 602 is also used to receive second information, and the second information is determined based on the communication status information; the processing unit 601 is used to determine third information; the transceiver unit 602 is also used to send third information, and the third information includes first radio information, and the first radio information is obtained by processing the second information based on a radio map model; wherein the input of the radio map model is obtained based on the first processing parameter.

[0232] It should be noted that, for details of the information execution process and other contents of the units of the above-mentioned communication device 600, please refer to the description in the method embodiment shown above in this application, and will not be repeated here.

[0233] Please refer to Fig. 7, which is another schematic structural diagram of a communication device 700 provided in this application. The communication device 700 includes a logic circuit 701 and an input / output interface 702. The communication device 700 may be a chip or an integrated circuit.

[0234] The transceiver unit 602 shown in FIG6 may be a communication interface, which may be the input / output interface 702 in FIG7 , which may include an input interface and an output interface. Alternatively, the communication interface may be a transceiver circuit, which may include an input interface circuit and an output interface circuit.

[0235] Optionally, the logic circuit 701 is used to determine the first information and the second information; the input-output interface 702 is used to send the first information, and the first information is used to determine the first processing parameter; the input-output interface 702 is also used to send the second information, and the second information is determined based on the communication status information; the input-output interface 702 is also used to receive the third information, and the third information includes the first radio information, and the first radio information is obtained by processing the second information based on the radio map model; wherein the input of the radio map model is obtained based on the first processing parameter.

[0236] Optionally, the input-output interface 702 is used to receive first information, which is used to determine a first processing parameter; the input-output interface 702 is also used to receive second information, which is determined based on the communication status information; the logic circuit 701 is used to determine third information; the input-output interface 702 is also used to send third information, which includes first radio information, which is obtained by processing the second information based on a radio map model; wherein the input of the radio map model is obtained based on the first processing parameter.

[0237] The logic circuit 701 and the input / output interface 702 may also execute other steps executed by the first communication device or the second communication device in any embodiment and achieve corresponding beneficial effects, which will not be described in detail here.

[0238] In a possible implementation, the processing unit 601 shown in FIG. 6 may be the logic circuit 701 in FIG. 7 .

[0239] Optionally, the logic circuit 701 may be a processing device, and the functions of the processing device may be partially or entirely implemented by software. The functions of the processing device may be partially or entirely implemented by software.

[0240] Optionally, the processing device may include a memory and a processor, wherein the memory is used to store a computer program, and the processor reads and executes the computer program stored in the memory to perform corresponding processing and / or steps in any one of the method embodiments.

[0241] Alternatively, the processing device may include only a processor. A memory for storing the computer program is located outside the processing device, and the processor is connected to the memory via circuits / wires to read and execute the computer program stored in the memory. The memory and processor may be integrated or physically separate.

[0242] Optionally, the processing device may be one or more chips, or one or more integrated circuits. For example, the processing device may be one or more field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), system-on-chips (SoCs), central processor units (CPUs), network processors (NPs), digital signal processors (DSPs), microcontroller units (MCUs), programmable logic devices (PLDs), or other integrated chips, or any combination of the above chips or processors.

[0243] Please refer to Figure 8, which shows the communication device 800 involved in the above-mentioned embodiments provided in an embodiment of the present application. The communication device 800 can specifically be a communication device serving as a terminal device in the above-mentioned embodiments. The example shown in Figure 8 is that the terminal device is implemented through the terminal device (or a component in the terminal device).

[0244] Herein, a possible logical structure diagram of the communication device 800 is shown. The communication device 800 may include but is not limited to at least one processor 801 and a communication port 802 .

[0245] The transceiver unit 602 shown in FIG6 may be a communication interface, which may be the communication port 802 in FIG8 , which may include an input interface and an output interface. Alternatively, the communication port 802 may be a transceiver circuit, which may include an input interface circuit and an output interface circuit.

[0246] Further optionally, the device may also include at least one of a memory 803 and a bus 804. In an embodiment of the present application, the at least one processor 801 is used to control and process the actions of the communication device 800.

[0247] Furthermore, the processor 801 may be a central processing unit (CPU), a general-purpose processor (GPPC), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic device (PLD), a transistor logic device (TLD), a hardware component, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like. Those skilled in the art will clearly understand that, for ease and brevity of description, the specific operating processes of the systems, devices, and units described above may refer to the corresponding processes in the aforementioned method embodiments and will not be further described herein.

[0248] It should be noted that the communication device 800 shown in Figure 8 can be specifically used to implement the steps implemented by the terminal device in the aforementioned method embodiment and achieve the corresponding technical effects of the terminal device. The specific implementation methods of the communication device shown in Figure 8 can refer to the description in the aforementioned method embodiment and will not be repeated here.

[0249] Please refer to Figure 9, which is a structural diagram of the communication device 900 involved in the above-mentioned embodiments provided in an embodiment of the present application. The communication device 900 can specifically be a communication device as a network device in the above-mentioned embodiments. The example shown in Figure 9 is that the network device is implemented through the network device (or a component in the network device), wherein the structure of the communication device can refer to the structure shown in Figure 9.

[0250] The communication device 900 includes at least one processor 911 and at least one network interface 914. Further optionally, the communication device also includes at least one memory 912, at least one transceiver 913 and one or more antennas 915. The processor 911, the memory 912, the transceiver 913 and the network interface 914 are connected, for example, via a bus. In an embodiment of the present application, the connection may include various interfaces, transmission lines or buses, etc., which are not limited in this embodiment. The antenna 915 is connected to the transceiver 913. The network interface 914 is used to enable the communication device to communicate with other communication devices through a communication link. For example, the network interface 914 may include a network interface between the communication device and the core network device, such as an S1 interface, and the network interface may include a network interface between the communication device and other communication devices (such as other network devices or core network devices), such as an X2 or Xn interface.

[0251] The transceiver unit 602 shown in FIG6 may be a communication interface, which may be the network interface 914 in FIG9 , which may include an input interface and an output interface. Alternatively, the network interface 914 may be a transceiver circuit, which may include an input interface circuit and an output interface circuit.

[0252] Processor 911 is primarily used to process communication protocols and communication data, control the entire communication device, execute software programs, and process software program data, for example, to support the communication device in performing the actions described in the embodiments. The communication device may include a baseband processor and a central processing unit. The baseband processor is primarily used to process communication protocols and communication data, while the central processing unit is primarily used to control the entire terminal device, execute software programs, and process software program data. Processor 911 in Figure 9 may integrate the functions of both a baseband processor and a central processing unit. Those skilled in the art will appreciate that the baseband processor and the central processing unit may also be independent processors interconnected via a bus or other technology. Those skilled in the art will appreciate that a terminal device may include multiple baseband processors to accommodate different network standards, multiple central processing units to enhance its processing capabilities, and various components of the terminal device may be connected via various buses. The baseband processor may also be referred to as a baseband processing circuit or a baseband processing chip. The central processing unit may also be referred to as a central processing circuit or a central processing chip. The functionality for processing communication protocols and communication data may be built into the processor or stored in memory as a software program, which is executed by the processor to implement the baseband processing functionality.

[0253] The memory is primarily used to store software programs and data. Memory 912 can exist independently and be connected to processor 911. Alternatively, memory 912 and processor 911 can be integrated together, for example, within a single chip. Memory 912 can store program code for executing the technical solutions of the embodiments of the present application, and execution is controlled by processor 911. The various computer program codes executed can also be considered drivers for processor 911.

[0254] Figure 9 shows only one memory and one processor. In an actual terminal device, there may be multiple processors and multiple memories. The memory may also be referred to as a storage medium or a storage device. The memory may be a storage element on the same chip as the processor, i.e., an on-chip storage element, or an independent storage element, which is not limited in the present embodiment.

[0255] The transceiver 913 can be used to support the reception or transmission of radio frequency signals between the communication device and the terminal, and the transceiver 913 can be connected to the antenna 915. The transceiver 913 includes a transmitter Tx and a receiver Rx. Specifically, one or more antennas 915 can receive radio frequency signals. The receiver Rx of the transceiver 913 is used to receive the radio frequency signal from the antenna, convert the radio frequency signal into a digital baseband signal or a digital intermediate frequency signal, and provide the digital baseband signal or digital intermediate frequency signal to the processor 911 so that the processor 911 can further process the digital baseband signal or digital intermediate frequency signal, such as demodulation and decoding. In addition, the transmitter Tx in the transceiver 913 is also used to receive a modulated digital baseband signal or digital intermediate frequency signal from the processor 911, convert the modulated digital baseband signal or digital intermediate frequency signal into a radio frequency signal, and send the radio frequency signal through one or more antennas 915. Specifically, the receiver Rx can selectively perform one or more stages of down-mixing and analog-to-digital conversion on the RF signal to obtain a digital baseband signal or a digital intermediate frequency signal. The order of the down-mixing and analog-to-digital conversion processes is adjustable. The transmitter Tx can selectively perform one or more stages of up-mixing and digital-to-analog conversion on the modulated digital baseband signal or digital intermediate frequency signal to obtain a RF signal. The order of the up-mixing and digital-to-analog conversion processes is adjustable. The digital baseband signal and the digital intermediate frequency signal may be collectively referred to as digital signals.

[0256] The transceiver 913 may also be referred to as a transceiver unit, a transceiver, a transceiver device, etc. Optionally, a device in the transceiver unit that implements a receiving function may be referred to as a receiving unit, and a device in the transceiver unit that implements a transmitting function may be referred to as a transmitting unit. That is, the transceiver unit includes a receiving unit and a transmitting unit. The receiving unit may also be referred to as a receiver, an input port, a receiving circuit, etc., and the transmitting unit may be referred to as a transmitter, a transmitter, or a transmitting circuit, etc.

[0257] It should be noted that the communication device 900 shown in Figure 9 can be specifically used to implement the steps implemented by the network device in the aforementioned method embodiment and achieve the corresponding technical effects of the network device. The specific implementation methods of the communication device 900 shown in Figure 9 can refer to the description in the aforementioned method embodiment and will not be repeated here.

[0258] Please refer to FIG10 , which is a schematic structural diagram of the communication device involved in the above-mentioned embodiment provided in an embodiment of the present application.

[0259] It can be understood that the communication device 100 includes, for example, modules, units, elements, circuits, or interfaces, which are appropriately configured together to implement the technical solutions provided in this application. The communication device 100 can be the terminal device or network device described above, or a component (such as a chip) in these devices, used to implement the method described in the following method embodiment. The communication device 100 includes one or more processors 101. The processor 101 can be a general-purpose processor or a dedicated processor. For example, it can be a baseband processor or a central processing unit. The baseband processor can be used to process communication protocols and communication data, and the central processing unit can be used to control the communication device (such as a RAN node, terminal, or chip, etc.), execute software programs, and process data of software programs.

[0260] Optionally, in one design, the processor 101 may include a program 103 (sometimes also referred to as code or instructions), which may be executed on the processor 101 to cause the communication device 100 to perform the methods described in the following embodiments. In yet another possible design, the communication device 100 includes circuitry (not shown in FIG10 ).

[0261] Optionally, the communication device 100 may include one or more memories 102 on which a program 104 (sometimes also referred to as code or instructions) is stored. The program 104 can be run on the processor 101, so that the communication device 100 executes the method described in the above method embodiment.

[0262] Optionally, the processor 101 and / or the memory 102 may include AI modules 107 and 108, which are used to implement AI-related functions. The AI ​​module may be implemented through software, hardware, or a combination of software and hardware. For example, the AI ​​module may include a wireless intelligent control (RIC) module. For example, the AI ​​module may be a near-real-time RIC or a non-real-time RIC.

[0263] Optionally, data may be stored in the processor 101 and / or the memory 102. The processor and the memory may be provided separately or integrated together.

[0264] Optionally, the communication device 100 may further include a transceiver 105 and / or an antenna 106. The processor 101 may also be sometimes referred to as a processing unit, and controls the communication device (e.g., a RAN node or terminal). The transceiver 105 may also be sometimes referred to as a transceiver unit, a transceiver, a transceiver circuit, or a transceiver, and is configured to implement the transceiver functions of the communication device through the antenna 106.

[0265] The processing unit 701 shown in FIG7 may be the processor 101. The transceiver unit 702 shown in FIG7 may be a communication interface, which may be the transceiver 105 shown in FIG10 . The transceiver 105 may include an input interface and an output interface. Alternatively, the transceiver 105 may be a transceiver circuit, which may include an input interface circuit and an output interface circuit.

[0266] An embodiment of the present application further provides a computer-readable storage medium, which is used to store one or more computer-executable instructions. When the computer-executable instructions are executed by a processor, the processor executes the method described in the possible implementation methods of the first communication device or the second communication device in the aforementioned embodiment.

[0267] An embodiment of the present application also provides a computer program product (or computer program). When the computer program product is executed by the processor, the processor executes the method that may be implemented by the above-mentioned first communication device or second communication device.

[0268] An embodiment of the present application also provides a chip system, which includes at least one processor for supporting a communication device to implement the functions involved in the possible implementation methods of the above-mentioned communication device. Optionally, the chip system also includes an interface circuit, which provides program instructions and / or data to the at least one processor. In one possible design, the chip system may also include a memory, which is used to store the necessary program instructions and data for the communication device. The chip system can be composed of chips, or it can include chips and other discrete devices, wherein the communication device can specifically be the first communication device or the second communication device in the aforementioned method embodiment.

[0269] An embodiment of the present application further provides a communication system, wherein the network system architecture includes the first communication device and the second communication device in any of the above embodiments.

[0270] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0271] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0272] In addition, the functional units in the various embodiments of the present application can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the contributing part or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

Claims

1. A communication method, characterized in that: include: Sending first information, where the first information is used to determine a first processing parameter; sending second information, where the second information is determined based on the communication state information; Third information is received, where the third information includes first radio information, where the first radio information is obtained by processing the second information based on a radio map model; wherein an input of the radio map model is obtained based on the first processing parameter.

2. The method according to claim 1, characterized in that The second information includes the communication status information, wherein the input of the radio map model includes a processing result obtained by processing the communication status information based on the first processing parameter; or The second information includes a processing result obtained by processing the communication status information based on the first processing parameter.

3. The method according to claim 1 or 2, characterized in that The first information includes at least one of the first processing parameter, an index of the first processing parameter, and an index of the radio map model.

4. The method according to any one of claims 1 to 3, characterized in that The method further comprises: The first radio information is processed based on a second processing parameter to obtain second radio information.

5. The method according to claim 4, characterized in that The method further comprises: Indication information indicating the second processing parameter is received.

6. The method according to any one of claims 1 to 3, characterized in that The method further comprises: Sending instruction information for determining a second processing parameter; wherein the first radio information is obtained based on the second processing parameter.

7. The method according to claim 5 or 6, characterized in that The indication information includes at least one of the second processing parameter, an index of the second processing parameter, and an index of the radio map model.

8. The method according to any one of claims 1 to 7, characterized in that Before sending the first information, the method further includes: Model information of N radio map models is received, where the N radio map models include the radio map model, and N is a positive integer; wherein the first information is determined based on the model information.

9. The method according to claim 8, characterized in that In the model information of the N radio map models, the model information of each radio map model includes at least one of an input processing parameter of each radio map model and an output processing parameter of each radio map model.

10. The method according to any one of claims 1 to 9, characterized in that The processing parameters include scaling parameters and / or precision conversion parameters.

11. A communication method, characterized in that: include: receiving first information, wherein the first information is used to determine a first processing parameter; receiving second information, where the second information is determined based on the communication state information; Third information is sent, where the third information includes first radio information, where the first radio information is obtained by processing the second information based on a radio map model; wherein an input of the radio map model is obtained based on the first processing parameter.

12. The method according to claim 11, characterized in that The second information includes the communication status information, wherein the input of the radio map model includes a processing result obtained by processing the communication status information based on the first processing parameter; or The second information includes a processing result obtained by processing the communication status information based on the first processing parameter.

13. The method according to claim 11 or 12, characterized in that The first information includes at least one of the first processing parameter, an index of the first processing parameter, and an index of the radio map model.

14. The method according to any one of claims 11 to 13, characterized in that The first radio information is used to determine second radio information; wherein the second radio information is obtained based on a second processing parameter.

15. The method according to claim 14, characterized in that The method further comprises: Send indication information for indicating the second processing parameter.

16. The method according to any one of claims 11 to 13, characterized in that The method further comprises: Receive instruction information for determining a second processing parameter; wherein the first radio information is obtained by processing the second information based on the radio map model to obtain third radio information, and then processing the third radio information based on the second processing parameter.

17. The method according to claim 15 or 16, characterized in that The indication information includes at least one of the second processing parameter, an index of the second processing parameter, and an index of the radio map model.

18. The method according to any one of claims 11 to 17, characterized in that Before sending the first information, the method further includes: Model information of N radio map models is sent, where the N radio map models include the radio map model, and N is a positive integer; wherein the first information is determined based on the model information.

19. The method according to claim 18, characterized in that In the model information of the N radio map models, the model information of each radio map model includes at least one of an input processing parameter of each radio map model and an output processing parameter of each radio map model.

20. The method according to any one of claims 11 to 19, characterized in that The processing parameters include scaling parameters and / or precision conversion parameters.

21. A communication device, characterized in that: The method comprises modules or units for executing the method according to any one of claims 1 to 20.

22. A communication device, characterized in that: The apparatus comprises a processor configured to run a computer program so as to cause the apparatus to perform the method according to any one of claims 1 to 20.

23. The device according to claim 22, characterized in that The apparatus further comprises a memory for storing the computer program.

24. A chip, characterized in that: comprising a processor configured to perform the method of any one of claims 1 to 20.

25. A readable storage medium, characterized in that The storage medium stores a computer program or instruction. When the computer program or instruction is executed by the communication device, the method according to any one of claims 1 to 20 is implemented.

26. A computer program product, characterized in that The method comprises instructions which, when executed on a computer, cause the computer to perform the method according to any one of claims 1 to 20.

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