WO2025261007A1 - 一种通信方法及相关装置 - Google Patents

一种通信方法及相关装置

Info

Publication number
WO2025261007A1
WO2025261007A1 PCT/CN2025/094170 CN2025094170W WO2025261007A1 WO 2025261007 A1 WO2025261007 A1 WO 2025261007A1 CN 2025094170 W CN2025094170 W CN 2025094170W WO 2025261007 A1 WO2025261007 A1 WO 2025261007A1
Authority
WO
WIPO (PCT)
Prior art keywords
information
terminal device
function
message
model
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/CN2025/094170
Other languages
English (en)
French (fr)
Inventor
乔云飞
徐晨
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Huawei Technologies Co Ltd
Original Assignee
Huawei Technologies Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Huawei Technologies Co Ltd filed Critical Huawei Technologies Co Ltd
Publication of WO2025261007A1 publication Critical patent/WO2025261007A1/zh
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. Transmission Power Control [TPC] or power classes
    • H04W52/02—Power saving arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W8/00—Network data management
    • H04W8/22—Processing or transfer of terminal data, e.g. status or physical capabilities
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W8/00—Network data management
    • H04W8/22—Processing or transfer of terminal data, e.g. status or physical capabilities
    • H04W8/24—Transfer of terminal data

Definitions

  • This application relates to the field of communications, and more particularly to a communication method and related apparatus.
  • AI artificial intelligence
  • a communication system capable of handling AI services can also be called an AI system.
  • communication devices can serve as participating nodes in AI systems, applying their computing power to a specific stage of the AI system.
  • AI functions introduced into communication networks rely on models for implementation.
  • this process there is currently no solution to address how to manage these models.
  • This application provides a communication method and related apparatus for implementing model management.
  • the first communication device can be a communication equipment (such as a terminal device or network device), or it can be a component of the communication equipment (e.g., a circuit or chip responsible for communication functions, such as a modem chip, also known as a baseband chip, or a system-on-chip (SoC) chip containing a modem core, or a system-in-package (SIP) chip, etc.), or it can be a logic module or software capable of implementing all or part of the functions of the communication equipment.
  • a communication equipment such as a terminal device or network device
  • a component of the communication equipment e.g., a circuit or chip responsible for communication functions, such as a modem chip, also known as a baseband chip, or a system-on-chip (SoC) chip containing a modem core, or a system-in-package (SIP) chip, etc.
  • SoC system-on-chip
  • SIP system-in-package
  • the first communication device acquires first information indicating first state information of the terminal device; the first communication device determines whether to enable the AI function of the terminal device based on the first state information; the first communication device receives or sends second information indicating first processing of an AI model when the AI function of the terminal device is enabled, the AI model being associated with the AI function of the terminal device; or, the first communication device receives or sends third information indicating second processing of the AI model when the AI function of the terminal device is not enabled.
  • the first communication device can obtain the first state information of the terminal device through the first information, and determine whether to enable the AI function of the terminal device based on the first state information. Subsequently, if it is determined that the AI function of the terminal device is enabled, the first communication device can receive or send second information instructing the AI model to undergo first processing in that situation. Alternatively, if it is determined that the AI function of the terminal device is not enabled, the first communication device can receive or send third information instructing the AI model to undergo second processing in that situation. In this way, the recipient of the second information can perform model management of the AI model when the AI model is enabled (or, the recipient of the third information can perform model management of the AI model when the AI model is not enabled), thereby achieving model management of the AI model.
  • the first communication device determines whether to enable the AI function of the terminal device based on the first state information.
  • the basis for determining whether to enable the AI function of the terminal device includes the first state information of the terminal device. This allows the AI function of the terminal device to be matched with its state information. For example, enabling the AI function can provide benefits; conversely, disabling the AI function can save energy consumption and/or computing power. Therefore, when the first communication device determines to enable the AI function based on the first state information, the benefits of the AI function can be utilized to improve task processing efficiency; when the first communication device determines to disabling the AI function based on the first state information, the terminal device's costs can be saved.
  • the AI model (such as an AI model associated with AI functions) may include a mathematical model, a model, a neural network model, an AI neural network model, a machine learning model, or an AI processing model, etc.
  • AI function may be replaced with other terms, such as AI-enabled function, AI capability, or AI-enabled characteristic.
  • “enabled” can be replaced with other terms, such as startup, opening, not shutting down, not disabling, or enabling.
  • “disabled” can be replaced with other terms, such as not startup, not opening, shutting down, disabling, or not enabling.
  • the first process may instruct model management of the AI model when the AI function of the terminal device is enabled.
  • the first process may include one or more of model updates, model switching, model fine-tuning, or model fine-tuning.
  • the second process may instruct model management of the AI model without enabling the AI function of the terminal device.
  • the second process may include one or more of the following: determining the trigger conditions for model activation, data collection (e.g., the collected data can be used for subsequent model processing after the AI model is enabled).
  • the first state information indicates at least one of the following: the data characteristics of the data collected by the terminal device, the communication parameters of the terminal device, the model performance of the AI model associated with the AI function of the terminal device, or the computing resources of the terminal device.
  • the first communication device determining whether to enable the AI function of the terminal device based on the first state information includes: if the first state information satisfies a first condition, the first communication device determines to enable the AI function of the terminal device.
  • the first communication device can determine whether the first state information meets the first condition, and if the first condition is met, the first communication device determines to enable the AI function of the terminal device.
  • the method further includes: the first communication device receiving fourth information indicating the first condition.
  • the first communication device can determine the first condition by receiving the fourth information, so that the first communication device can realize the judgment process of whether to enable the AI function of the terminal device based on the first condition specified by other communication devices.
  • this first condition is pre-configured.
  • the first communication device determining whether to enable the AI function of the terminal device based on the first state information includes: if the first state information satisfies a second condition, the first communication device determines not to enable the AI function of the terminal device.
  • the first communication device can determine whether the first state information meets the second condition, and if the second condition is met, the first communication device determines not to enable the AI function of the terminal device.
  • the method further includes: the first communication device receiving fifth information, the fifth information indicating the second condition.
  • the first communication device can determine the first condition by receiving the fifth information, so that the first communication device can realize the judgment process of whether to enable the AI function of the terminal device based on the second condition specified by other communication devices.
  • this second condition is pre-configured.
  • the third information includes third time information; the method further includes: after the time unit indicated by the third time information or the time unit indicated by the third time information, the first communication device acquires fifth information, the fifth information indicating second status information of the terminal device; the first communication device determines whether to enable the AI function of the terminal device based on the second status information.
  • the third information received or sent by the first communication device may include third time information, so that the recipient of the third information can obtain the second state information of the terminal device based on the third time information, and further determine whether to enable the AI function of the terminal device based on the second state information, and can try to start the AI function again, so as to obtain the benefit brought by the AI function when it is determined to start the AI function, and improve the task processing efficiency.
  • the method further includes: the first communication device sending a sixth message indicating whether the AI function of the terminal device is enabled, the sixth message being determined based on the second state information.
  • the first communication device can send a sixth message, so that the recipient of the sixth message can determine whether to enable the AI function of the terminal device based on the sixth message, and communicate with the terminal device based on the sixth message (e.g., transmit data/signals/information/signaling for AI function, or transmit data/signals/information/signaling for other functions).
  • a sixth message e.g., transmit data/signals/information/signaling for AI function, or transmit data/signals/information/signaling for other functions.
  • the first communication device acquiring the first information includes: the first communication device receiving the first information.
  • the first communication device may not be a terminal device or a module in a terminal device. Therefore, the first communication device can receive first information to determine the first status information of the terminal device through the first information.
  • the process of the first communication device acquiring the fifth information includes: the first communication device receiving the fifth information.
  • the first communication device can send a seventh message, so that the recipient of the seventh message can determine whether to enable the AI function of the terminal device based on the seventh message, and communicate with the terminal device based on the seventh message (e.g., transmit data/signals/information/signaling for AI function, or transmit data/signals/information/signaling for other functions).
  • a seventh message so that the recipient of the seventh message can determine whether to enable the AI function of the terminal device based on the seventh message, and communicate with the terminal device based on the seventh message (e.g., transmit data/signals/information/signaling for AI function, or transmit data/signals/information/signaling for other functions).
  • a second aspect of this application provides a communication method performed by a second communication device.
  • the second communication device can be a communication device (e.g., a terminal device or a network device), or it can be a component of the communication device (e.g., a circuit or chip responsible for communication functions, such as a modem chip, also known as a baseband chip, or a SoC chip or SIP chip containing a modem core, etc.), or it can be a logic module or software capable of implementing all or part of the communication device's functions.
  • the second communication device receives seventh information indicating whether to enable the AI function of the terminal device; wherein the seventh information is determined based on first state information of the terminal device; the second communication device sends second information or third information, the second information indicating first processing of the AI model when the AI function of the terminal device is enabled, and the third information indicating second processing of the AI model when the AI function of the terminal device is not enabled, wherein the AI model is associated with the AI function of the terminal device.
  • the second communication device can receive seventh information indicating whether to enable the AI function of the terminal device. Subsequently, if it is determined that the AI function of the terminal device is enabled, the second communication device can receive or send second information indicating that a first process should be performed on the AI model in that situation. Alternatively, if it is determined that the AI function of the terminal device is not enabled, the second communication device can receive or send third information indicating that a second process should be performed on the AI model in that situation.
  • the recipient of the second information can perform model management of the AI model based on the second information when the AI model is enabled (or, the recipient of the third information can perform model management of the AI model based on the third information when the AI model is not enabled), thereby achieving model management of the AI model.
  • the basis for determining whether to enable the AI function of the terminal device includes the terminal device's first state information.
  • enabling the AI function can yield benefits; conversely, disabling the AI function can save on the terminal device's energy consumption and/or computing power. Therefore, if the first communication device determines to enable the terminal device's AI function based on the first state information, the benefits of the AI function can be utilized to improve task processing efficiency; if the first communication device determines to disabling the terminal device's AI function based on the first state information, the terminal device's costs can be saved.
  • the method further includes: the second communication device sending fourth information indicating a first condition; wherein, if the first state information satisfies the first condition, the AI function of the terminal device is enabled.
  • the second communication device can send fourth information, so that the first communication device can determine the first condition through the received fourth information, and the first communication device can perform the judgment process of whether to enable the AI function of the terminal device based on the first condition specified by the second communication device.
  • the method further includes: the second communication device sending fifth information indicating the second condition; wherein, if the first state information satisfies the second condition, the AI function of the terminal device is not enabled.
  • the second communication device can send a fifth message, so that the first communication device can determine the first condition by receiving the fifth message, and the first communication device can perform the judgment process of whether to enable the AI function of the terminal device based on the second condition specified by the second communication device.
  • the third information includes third time information; wherein, at or after the time unit indicated by the third time information, the second status information of the terminal device acquired by the first communication device is used to determine whether to enable the AI function of the terminal device.
  • the third information received or sent by the second communication device may include third time information, so that the recipient of the third information can obtain the second state information of the terminal device based on the third time information, and further determine whether to enable the AI function of the terminal device based on the second state information, and can try to start the AI function again, so as to obtain the benefits brought by the AI function when it is determined to start the AI function, and improve the task processing efficiency.
  • the method further includes: the second communication device receiving sixth information indicating whether to enable the AI function of the terminal device, the sixth information being determined based on the second state information.
  • the second communication device can receive the sixth information from the first communication device, so that the second communication device can determine whether to enable the AI function of the terminal device based on the sixth information, and communicate with the terminal device based on the sixth information (e.g., transmit data/signals/information/signaling for AI function, or transmit data/signals/information/signaling for other functions).
  • the sixth information e.g., transmit data/signals/information/signaling for AI function, or transmit data/signals/information/signaling for other functions.
  • a third aspect of this application provides a communication method executed by a third communication device.
  • This third communication device can be a communication device (such as a terminal device), or it can be a component of the communication device (e.g., a circuit or chip responsible for communication functions, such as a modem chip, also known as a baseband chip, or a SoC chip containing a modem core, or a system-in-package (SIP) chip), or it can be a logic module or software capable of implementing all or part of the functions of the communication device.
  • a communication device such as a terminal device
  • a component of the communication device e.g., a circuit or chip responsible for communication functions, such as a modem chip, also known as a baseband chip, or a SoC chip containing a modem core, or a system-in-package (SIP) chip
  • SIP system-in-package
  • the third communication device sends first information indicating first status information of the terminal device; the first status information is used to determine whether to enable the AI function of the terminal device; the third communication device receives second information or third information, the second information indicating first processing of an AI model when the AI function of the terminal device is enabled, and the third information indicating second processing of the AI model when the AI function of the terminal device is not enabled, wherein the AI model is associated with the AI function of the terminal device.
  • the first information sent by the third communication device can indicate the first status information of the terminal device, enabling the recipient of the first information to determine whether to enable the AI function of the terminal device based on the first status information. Subsequently, if it is determined that the AI function of the terminal device is enabled, the third communication device can receive or send second information instructing the AI model to undergo first processing in that situation. Alternatively, if it is determined that the AI function of the terminal device is not enabled, the third communication device can receive or send third information instructing the AI model to undergo second processing in that situation.
  • the recipient of the second information can perform model management of the AI model based on the second information when the AI model is enabled (or, the recipient of the third information can perform model management of the AI model based on the third information when the AI model is not enabled), thereby achieving model management of the AI model.
  • the basis for determining whether to enable the AI function of the terminal device includes the terminal device's first state information.
  • enabling the AI function can yield benefits; conversely, disabling the AI function can save on the terminal device's energy consumption and/or computing power. Therefore, if the first communication device determines to enable the terminal device's AI function based on the first state information, the benefits of the AI function can be utilized to improve task processing efficiency; if the first communication device determines to disabling the terminal device's AI function based on the first state information, the terminal device's costs can be saved.
  • the method further includes: the third communication device receiving seventh information indicating whether to enable the AI function of the terminal device; wherein the seventh information is determined based on the first state information of the terminal device.
  • the third communication device can receive the seventh information, so that the third communication device can determine whether to enable the AI function of the terminal device based on the seventh information, and communicate with the terminal device based on the sixth information (e.g., transmit data/signals/information/signaling for AI function, or transmit data/signals/information/signaling for other functions).
  • the sixth information e.g., transmit data/signals/information/signaling for AI function, or transmit data/signals/information/signaling for other functions.
  • the third information includes third time information; the method further includes: the third communication device sending fifth information after the time unit indicated by the third time information or after the time unit indicated by the third time information; wherein the fifth information indicates second status information of the terminal device, the second status information determining whether the AI function of the terminal device is enabled.
  • the third information received or sent by the third communication device may include third time information, so that the recipient of the third information can obtain the second state information of the terminal device based on the third time information, and further determine whether to enable the AI function of the terminal device based on the second state information, and can try to start the AI function again, so as to obtain the benefits brought by the AI function when it is determined to start the AI function, and improve the task processing efficiency.
  • the method further includes: the third communication device receiving sixth information indicating whether to enable the AI function of the terminal device, the sixth information being determined based on the second state information.
  • the third communication device can receive the sixth information, enabling the third communication device to determine whether to enable the AI function of the terminal device based on the sixth information, and to communicate with the terminal device based on the sixth information (e.g., transmitting data/signals/information/signaling for AI functions, or transmitting data/signals/information/signaling for other functions).
  • the second information includes any of the following:
  • First instruction information indicating first time information for the first processing
  • the first and third indication information indicate that the first time interval indicated by the first time information is updated to a second time interval; wherein the starting time unit of the second time interval is the receiving time unit or the sending time unit of the third indication information, and the receiving time unit or the sending time unit of the third indication information is located within the first time interval.
  • the second information can be implemented in multiple ways to improve the flexibility of the scheme implementation, and enable the recipient of the second information to perform first processing on the AI model based on at least one of the above methods.
  • the first process is a periodic process
  • the second information further includes at least one of the following:
  • the fourth instruction indicates whether to enable the first time information, or whether to enable the first time information in the period closest to the current time;
  • the fifth indication information indicates the first threshold; wherein, if the number of cycles in which the fourth indication information is not received or not sent is greater than or equal to the first threshold, the first time interval indicated by the first time information is triggered to be updated to the third time interval, which is greater than the first time interval;
  • the sixth indication information indicates the second threshold; wherein, within the duration indicated by the first timer, if the number of cycles of the fourth indication information received or sent is greater than or equal to the second threshold, and the fourth indication information received or sent indicates that the function is enabled, the first time interval indicated by the first time information is triggered to be updated to the fourth time interval, and the fourth time interval is less than the first time interval.
  • the seventh indication information indicates the third threshold; wherein, within the duration indicated by the second timer, if the number of cycles of the fourth indication information received or sent is greater than or equal to the third threshold, and the third indication information received or sent indicates that the third indication information is not enabled, the first process is triggered.
  • the second information includes at least one of the following:
  • the eighth instruction message indicates that the AI function of this terminal device should be turned off
  • the ninth instruction indicates that some or all of the data associated with the AI model should be cached
  • the tenth instruction message indicates the cached data required to re-enable the AI function of the terminal device after it has been turned off.
  • the second information can be implemented in multiple ways to improve the flexibility of the scheme implementation. Furthermore, the recipient of the second information can manage the AI model based on at least one of the above methods.
  • a fourth aspect of this application provides a communication device, which is a first communication device, comprising a transceiver unit and a processing unit; the processing unit is configured to acquire first information, the first information indicating first status information of a terminal device; the processing unit is further configured to determine whether to enable the AI function of the terminal device based on the first status information; the transceiver unit is configured to receive or send second information, the second information indicating first processing of an AI model when the AI function of the terminal device is enabled, the AI model being associated with the AI function of the terminal device; or, the transceiver unit is configured to receive or send third information, the third information indicating second processing of the AI model when the AI function of the terminal device is not enabled.
  • the constituent modules of the communication device can also be used to perform the steps executed in various possible implementations of the first aspect and achieve the corresponding technical effects.
  • the constituent modules of the communication device can also be used to perform the steps executed in various possible implementations of the first aspect and achieve the corresponding technical effects.
  • a fifth aspect of this application provides a communication device, which is a first communication device, comprising a transceiver unit and a processing unit; the transceiver unit is configured to receive seventh information, the seventh information indicating whether to enable the AI function of a terminal device; wherein the seventh information is determined based on first state information of the terminal device; the processing unit is configured to determine second information or third information; the transceiver unit is further configured to send the second information or third information, the second information indicating first processing of an AI model when the AI function of the terminal device is enabled, and the third information indicating second processing of the AI model when the AI function of the terminal device is not enabled, wherein the AI model is associated with the AI function of the terminal device.
  • the constituent modules of the communication device can also be used to perform the steps executed in various possible implementations of the second aspect and achieve the corresponding technical effects.
  • the second aspect please refer to the second aspect, which will not be repeated here.
  • a sixth aspect of this application provides a communication device, which is a third communication device.
  • the communication device includes a transceiver unit and a processing unit.
  • the processing unit is used to determine first information.
  • the transceiver unit is used to send the first information, which indicates first status information of a terminal device.
  • the first status information is used to determine whether to enable the AI function of the terminal device.
  • the transceiver unit is also used to receive second information or third information, where the second information indicates first processing of an AI model when the AI function of the terminal device is enabled, and the third information indicates second processing of the AI model when the AI function of the terminal device is not enabled.
  • the AI model is associated with the AI function of the terminal device.
  • the constituent modules of the communication device can also be used to perform the steps executed in various possible implementations of the third aspect and achieve the corresponding technical effects.
  • the constituent modules of the communication device can also be used to perform the steps executed in various possible implementations of the third aspect and achieve the corresponding technical effects.
  • a seventh aspect of this application provides a communication device including at least one processor coupled to a memory; the memory is used to store a program or instructions; the at least one processor is used to execute the program or instructions to enable the communication device to implement the method described in any possible implementation of any of the first to third aspects.
  • the communication device may include the memory.
  • the eighth aspect of this application provides a communication device including at least one logic circuit and an input/output interface; the logic circuit is used to perform the method as described in any one of the possible implementations of the first to third aspects described above.
  • the ninth aspect of this application provides a communication system, which includes the first communication device and the second communication device described above, or the communication system includes the first communication device and the third communication device described above.
  • the tenth aspect of this application provides a computer-readable storage medium for storing one or more computer-executable instructions, which, when executed by a processor, perform the method as described in any possible implementation of any of the first to third aspects described above.
  • the eleventh aspect of this application provides a computer program product (or computer program) that, when executed by a processor, performs the method described in any possible implementation of any of the first to third aspects described above.
  • the twelfth aspect of this application provides a chip system including at least one processor for supporting a communication device in implementing the method described in any possible implementation of any of the first to third aspects.
  • the 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 chips or may include chips and other discrete devices.
  • the chip system may also include interface circuitry that provides program instructions and/or data to the at least one processor.
  • FIGS 1a to 1c are schematic diagrams of the communication system provided in this application.
  • FIGS. 2a to 2e are schematic diagrams of the AI processing involved in this application.
  • FIGS 3 to 5 are some schematic diagrams of the communication method provided in this application.
  • FIGS 6 to 10 are schematic diagrams of the communication device provided in this application.
  • Terminal device 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.
  • 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 (or "cellular" phones), computers, and data cards.
  • mobile phones or "cellular" phones
  • computers and data cards.
  • they can be portable, pocket-sized, handheld, computer-embedded, or vehicle-mounted mobile devices that exchange voice and/or data with the RAN.
  • Examples include personal communication service (PCS) phones, cordless phones, Session Initiation Protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), tablets, and computers with wireless transceiver capabilities.
  • PCS personal communication service
  • SIP Session Initiation Protocol
  • WLL wireless local loop
  • PDAs personal digital assistants
  • tablets and computers with wireless transceiver capabilities.
  • Wireless terminal equipment can also be referred to as a system, subscriber unit, subscriber station, mobile station, mobile station (MS), remote station, access point (AP), remote terminal, access terminal, user terminal, user agent, subscriber station (SS), customer premises equipment (CPE), terminal, user equipment (UE), mobile terminal (MT), etc.
  • the terminal device can also be a wearable device.
  • Wearable devices also known as wearable smart devices or smart wearable devices, are a general term for devices that utilize wearable technology to intelligently design and develop everyday wearables, such as glasses, gloves, watches, clothing, and shoes.
  • Wearable devices are portable devices that are worn directly on the body or integrated into the user's clothing or accessories.
  • Wearable devices are not merely hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction.
  • wearable smart devices include those that are feature-rich, large in size, and can achieve complete or partial functions without relying on a smartphone, such as smartwatches or smart glasses, as well as those that focus on a specific type of application function and require the use of other devices such as smartphones, such as various smart bracelets, smart helmets, and smart jewelry for vital sign monitoring.
  • Terminals can also be drones, robots, devices in device-to-device (D2D) communication, vehicles to everything (V2X) communication, virtual reality (VR) terminal devices, augmented reality (AR) terminal devices, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical care, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, and wireless terminals in smart homes, etc.
  • D2D device-to-device
  • V2X vehicles to everything
  • VR virtual reality
  • AR augmented reality
  • wireless terminals in industrial control wireless terminals in self-driving
  • wireless terminals in remote medical care wireless terminals in smart grids
  • wireless terminals in transportation safety wireless terminals in smart cities, and wireless terminals in smart homes, etc.
  • terminal devices can also be terminal devices in future communication systems evolving after the 5th generation (5G) communication system, or terminal devices in future evolved public land mobile networks (PLMNs).
  • future communication networks can further expand the form and function of 5G communication terminals, and the terminals of future communication networks include, but are not limited to, vehicles, cellular network terminals (integrating satellite terminal functions), drones, and Internet of Things (IoT) devices.
  • IoT Internet of Things
  • the terminal device can also obtain AI services provided by the network device.
  • the terminal device can also have AI processing capabilities.
  • Network equipment This can be equipment in a wireless network.
  • network equipment can be a RAN node (or device) that connects terminal devices to the wireless network, and can also be called a base station.
  • RAN equipment include: base station, evolved NodeB (eNodeB), gNB (gNodeB) in 5G communication systems, 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.
  • network equipment can include centralized unit (CU) nodes, distributed unit (DU) nodes, or RAN equipment including CU nodes and DU nodes.
  • CU centralized unit
  • DU distributed unit
  • RAN equipment including CU nodes and DU nodes.
  • RAN nodes can also be macro base stations, micro base stations or indoor stations, relay nodes or donor nodes, or radio controllers in cloud radio access network (CRAN) scenarios.
  • RAN nodes can also be servers, wearable devices, vehicles, or in-vehicle equipment.
  • the access network equipment in vehicle-to-everything (V2X) technology can be a roadside unit (RSU).
  • V2X vehicle-to-everything
  • RSU roadside unit
  • RAN nodes collaborate to assist the terminal in achieving wireless access, with each RAN node performing a portion of the base station's functions.
  • RAN nodes can be central units (CUs), distributed units (DUs), CU-control plane (CPs), CU-user plane (UPs), or radio units (RUs).
  • CUs and DUs can be separate entities or included in the same network element, such as a baseband unit (BBU).
  • RUs can be included in radio frequency equipment or radio frequency units, such as remote radio units (RRUs), active antenna units (AAUs), or remote radio heads (RRHs).
  • RRUs remote radio units
  • AAUs active antenna units
  • RRHs remote radio heads
  • CU or CU-CP and CU-UP
  • DU or RU
  • RU may have different names, but those skilled in the art will understand their meaning.
  • O-CU open CU
  • DU can also be called O-DU
  • CU-CP can also be called O-CU-CP
  • CU-UP can also be called O-CU-UP
  • RU can also be called O-RU.
  • this application uses CU, CU-CP, CU-UP, DU, and RU as examples.
  • Any of the units among CU (or CU-CP, CU-UP), DU, and RU in this application can be implemented through software modules, hardware modules, or a combination of software modules and hardware modules.
  • This protocol layer may include a control plane protocol layer and a user plane protocol layer.
  • the control plane protocol layer may include at least one of the following: radio resource control (RRC) layer, packet data convergence protocol (PDCP) layer, radio link control (RLC) layer, media access control (MAC) layer, or physical (PHY) layer, etc.
  • the user plane protocol layer may include at least one of the following: service data adaptation protocol (SDAP) layer, PDCP layer, RLC layer, MAC layer, or physical layer, etc.
  • SDAP service data adaptation protocol
  • Network devices can be other devices that provide wireless communication functions for terminal devices.
  • the embodiments of this application do not limit the specific technology or form of the network device. For ease of description, the embodiments of this application are not limited.
  • Network equipment may also include core network equipment, such as the Mobility Management Entity (MME), Home Subscriber Server (HSS), Serving Gateway (S-GW), Policy and Charging Rules Function (PCRF), and Public Data Network Gateway (PDN Gateway) in 4G networks; and access and mobility management function (AMF), user plane function (UPF), or session management function (SMF) in 5G networks.
  • MME Mobility Management Entity
  • HSS Home Subscriber Server
  • S-GW Serving Gateway
  • PCRF Policy and Charging Rules Function
  • PDN Gateway Public Data Network Gateway
  • AMF access and mobility management function
  • UPF user plane function
  • SMF Public Data Network Gateway
  • the network device may also have network nodes with AI capabilities, which can provide AI services to terminals or other network devices.
  • network nodes with AI capabilities can provide AI services to terminals or other network devices.
  • it may be an AI node, computing node, RAN node with AI capabilities, or core network element with AI capabilities on the network side (access network or core network).
  • the device for implementing the function of the network device can be the network device itself, or it can be a device capable of supporting the network device in implementing that function, such as a chip system, which can be installed in the network device.
  • a network device being used to implement the function of the network device is used to describe the technical solutions provided in this application embodiment.
  • Configuration and Pre-configuration In this application, both configuration and pre-configuration are used. Configuration refers to the network device and/or server sending configuration information or parameter values to the terminal via messages or signaling, so that the terminal can determine communication parameters or resources for transmission based on these values or information. Pre-configuration is similar to configuration; it can be parameter information or parameter values pre-negotiated between the network device and/or server and the terminal device, or parameter information or parameter values specified by standard protocols for use by the base station/network device or terminal device, or parameter information or parameter values pre-stored in the base station and/or server or terminal device. This application does not limit this.
  • “send” and “receive” indicate the direction of signal transmission.
  • “send information to XX” can be understood as the destination of the information being XX, which may include sending directly through the air interface or sending indirectly through the air interface by other units or modules.
  • “Receive information from YY” can be understood as the source of the information being YY, which may include receiving directly from YY through the air interface or receiving indirectly from YY through the air interface by other units or modules.
  • “Send” can also be understood as the "output” of the chip interface, and “receive” can also be understood as the "input” of the chip interface.
  • sending and receiving can occur between devices, such as between network devices and terminal devices, or within a device, such as between components, modules, chips, software modules, or hardware modules within the device via buses, wiring, or interfaces.
  • "instruction” may include direct instruction and indirect instruction, as well as explicit instruction and implicit instruction.
  • the information indicated by a certain piece of information (as described below, the instruction information) is called the information to be instructed.
  • the information to be instructed there are many ways to indicate the information to be instructed, such as, but not limited to, directly indicating the information to be instructed, such as the information to be instructed itself or its index. It can also indirectly indicate the information to be instructed by indicating other information, where there is an association between the other information and the information to be instructed; or it can only indicate a part of the information to be instructed, while the other parts of the information to be instructed are known or pre-agreed upon.
  • the instruction can be implemented by using a pre-agreed (e.g., protocol predefined) arrangement order of various information, thereby reducing the instruction overhead to a certain extent.
  • a pre-agreed e.g., protocol predefined
  • This application does not limit the specific method of instruction. It is understood that for the sender of the instruction information, the instruction information can be used to indicate the information to be instructed, and for the receiver of the instruction information, the instruction information can be used to determine the information to be instructed.
  • This application can be applied to long-term evolution (LTE) systems, new radio (NR) systems, or future communication systems evolving beyond 5G.
  • LTE long-term evolution
  • NR new radio
  • These communication systems include at least one network device and/or at least one terminal device.
  • Figure 1a is a schematic diagram of a communication system according to this application.
  • Figure 1a exemplarily shows one 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.
  • 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
  • terminal device 6 is a printer.
  • the entity sending AI configuration information can be a network device.
  • the entity receiving AI configuration information can be terminal devices 1-6.
  • the network device and terminal devices 1-6 form a communication system.
  • terminal devices 1-6 can send data to the network device, and the network device needs to receive the data sent by terminal devices 1-6.
  • the network device can send configuration information to terminal devices 1-6.
  • terminal devices 4 to 6 can also form a communication system.
  • Terminal device 5 acts as a network device, i.e., the entity sending AI configuration information
  • terminal devices 4 and 6 act as terminal devices, i.e., the entities receiving AI configuration information.
  • V2X vehicle-to-everything
  • terminal device 5 sends AI configuration information to terminal devices 4 and 6 respectively, and receives data sent by terminal devices 4 and 6; correspondingly, terminal devices 4 and 6 receive the AI configuration information sent by terminal device 5 and send data back to terminal device 5.
  • V2X vehicle-to-everything
  • different devices may also perform AI-related services.
  • 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.
  • communication-related services and AI-related services can also be performed between televisions and mobile phones.
  • AI network elements can be introduced into the communication system provided in this application to realize some or all AI-related operations.
  • AI network elements can also be called AI nodes, AI devices, AI entities, AI modules, AI models, or AI units, etc.
  • the AI network element can be built into a network element within the communication system.
  • the AI network element can be an AI module built into: access network equipment, core network equipment, cloud server, or operation, administration, and maintenance (OAM) management system, to implement AI-related functions.
  • OAM can be the management system of the core network equipment and/or the management system of the access network equipment.
  • the AI network element can also be an independently set network element in the communication system.
  • the terminal or its built-in chip can also include an AI entity to implement AI-related functions.
  • AI application cases may include, but are not limited to: channel status information (CSI) feedback enhancement, beam management enhancement, positioning accuracy enhancement, network energy saving, load balancing, and mobility optimization. These will be explained in detail below.
  • CSI channel status information
  • Channel quality information is the channel attribute of a communication link, reported by the terminal device to the network device.
  • MCS modulation and coding scheme
  • the terminal device can select an appropriate modulation and coding scheme (MCS) to adapt to changing wireless channels. For example, the terminal device performs channel estimation based on the received channel state information-reference signal (CSI-RS) and then feeds back the CSI-RS to the network device.
  • CSI-RS channel state information-reference signal
  • This information serves as input to the network device's model, enabling AI model training.
  • AI By applying AI to CSI feedback enhancement, overhead can be reduced, accuracy improved, and prediction capabilities enhanced.
  • CSI-RS feedback enhancement can include at least one sub-function, such as: CSI compression, CSI prediction, and CSI-RS configuration signaling reduction.
  • CSI compression can be further divided into CSI compression in at least one domain: spatial, time, and frequency.
  • AI-based sparse beam prediction can improve accuracy. Based on AI training and inference, it can be divided into network-side AI sparse beam prediction and terminal device-side AI sparse beam prediction. Taking terminal device-side AI sparse beam prediction as an example, the pre-trained AI model on the terminal device can be provided by the network or pre-stored on the terminal device. During the training phase, the network device scans all possible beams and then reports the transmit beam pattern to the terminal device. When the model training is complete, the network only needs to scan a small portion of the beams, and then the terminal device feeds back the inference results to the network. AI-based beam management can achieve beam prediction in, for example, the temporal and/or spatial domains, to reduce overhead and latency and improve beam selection accuracy.
  • Beam management enhancements may include at least one sub-function, such as: beam scan matrix prediction and optimal beam prediction.
  • Positioning enhancement can include at least one sub-function, such as: positioning enhancement based on access network devices, positioning enhancement based on positioning management function network elements, and positioning enhancement based on terminal devices.
  • Network energy conservation can be achieved through cell activation/deactivation, load reduction, coverage improvement, or other RAN setting adjustments.
  • AI technology can be used to optimize energy-saving decisions by leveraging data collected within the RAN network.
  • AI algorithms can predict energy efficiency and load status for the next cycle, which can be used to assist in cell activation/deactivation decisions to save energy. Based on the predicted load, the system can dynamically configure energy-saving strategies to maintain a balance between system performance and energy efficiency, and reduce energy consumption.
  • Load balancing can distribute the load evenly between cells and across different areas within a cell, or transfer some traffic from congested cells, or offload users across a single cell, carrier, or access standard, thereby improving network performance.
  • Mobility management is a solution that ensures service continuity for mobile devices by minimizing dropped calls, radio link failures (RLFs), unnecessary handovers, and ping-pong effects.
  • AI can enhance mobility management by, for example, reducing the probability of unexpected events, predicting device location/mobility/performance, and routing traffic.
  • an AI function may include multiple AI sub-functions.
  • AI application cases are also called AI application scenarios or AI functions.
  • AI can be widely used to improve network performance in areas such as CSI feedback enhancement, beam management, positioning accuracy enhancement, energy saving, mobility enhancement, and load balancing.
  • AI models can typically be deployed on the network side and/or the terminal device side.
  • the training of AI models relies on the collection of training data, which can come from measurements and feedback from the terminal devices.
  • AI artificial intelligence
  • AI Artificial intelligence
  • machines can be employed.
  • machine learning machines learn (or train) a model using training data. This model represents the mapping between inputs and outputs.
  • the learned model can be used for reasoning (or prediction), that is, it can be used to predict the output corresponding to a given input. This output can also be called the reasoning result (or prediction result).
  • Machine learning can include supervised learning, unsupervised learning, and reinforcement learning. Unsupervised learning can also be called learning without supervision.
  • Supervised learning based on collected sample values and labels, uses machine learning algorithms to learn the mapping relationship between sample values and labels, and then expresses this learned mapping relationship using an AI model.
  • the process of training the machine learning model is the process of learning this mapping relationship.
  • sample values are input into the model to obtain the model's predicted values, and the model parameters are optimized by calculating the error between the model's predicted values and the sample labels (ideal values).
  • the mapping relationship learned in supervised learning can include linear or non-linear mappings.
  • the learning task can be divided into classification tasks and regression tasks.
  • Unsupervised learning relies on collected sample values to discover inherent patterns within the samples themselves.
  • One type of unsupervised learning algorithm uses the samples themselves as supervisory signals, meaning the model learns the mapping relationship from sample to sample; this is called self-supervised learning.
  • model parameters are optimized by calculating the error between the model's predictions and the samples themselves.
  • Self-supervised learning can be used for signal compression and decompression recovery applications; common algorithms include autoencoders and generative adversarial networks.
  • 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 do not have explicit "correct" action labels.
  • the algorithm needs to interact with the environment to obtain reward signals from the environment, and then adjust its decision actions to obtain a larger reward signal value. For example, in downlink power control, the reinforcement learning model adjusts the downlink transmission power of each user based on the total system throughput feedback from the wireless network, aiming to achieve a higher system throughput.
  • the goal of reinforcement learning is also to learn the mapping relationship between the environment state and a better (e.g., optimal) decision action.
  • the network cannot be optimized by calculating the error between the action and the "correct action.” Reinforcement learning training is achieved through iterative interaction with the environment.
  • Neural networks are a specific model in machine learning techniques. According to the general approximation theorem, neural networks can theoretically approximate any continuous function, thus enabling them to learn arbitrary mappings.
  • Traditional communication systems rely on extensive expert knowledge to design communication modules, while deep learning communication systems based on neural networks can automatically discover hidden pattern structures from large datasets, establish mapping relationships between data, and achieve performance superior to traditional modeling methods.
  • each neuron performs a weighted summation of its input values and outputs the result through an activation function.
  • Figure 2a shows a schematic diagram of a neuron structure.
  • w ⁇ sub>i ⁇ /sub> is used as the weight for xi , and is used to weight xi .
  • the bias for the weighted summation of the input values based on the weights is, for example, b.
  • b can be any possible type, such as a decimal, an integer (e.g., 0, a positive integer, or a negative integer), or a complex number.
  • the activation functions of different neurons in a neural network can be the same or different.
  • neural networks generally consist of 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 includes, and the number of neurons in each layer can be called the width of that layer.
  • a neural network includes an input layer and an output layer. The input layer processes the received input information through neurons and passes the processing result to the output layer, which then obtains the output of the neural network.
  • a neural network includes an input layer, hidden layers, and an output layer. The input layer processes the received input information through neurons and passes the processing result to the hidden layer. The hidden layer calculates the received processing result and passes the calculation result to the output layer or the next adjacent hidden layer, ultimately obtaining the output of the neural network.
  • a neural network may include one hidden layer or multiple sequentially connected hidden layers, without limitation.
  • DNNs deep neural networks
  • DNNs can include feedforward neural networks (FNNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs).
  • FNNs feedforward neural networks
  • CNNs convolutional neural networks
  • RNNs recurrent neural networks
  • Figure 2b is a schematic diagram of an FNN network.
  • a characteristic of FNN networks is that neurons in adjacent layers are completely connected pairwise. This characteristic makes FNNs typically require a large amount of storage space, leading to high computational complexity.
  • CNNs are neural networks specifically designed to process data with a grid-like structure. For example, time-series data (discrete sampling along the time axis) and image data (two-dimensional discrete sampling) can both be considered grid-like data.
  • CNNs do not use all the input information at once for computation; instead, they use a fixed-size window to extract a portion of the information for convolution operations, which significantly reduces the computational cost of model parameters.
  • each window can use different convolution kernels, allowing CNNs to better extract features from the input data.
  • RNNs are a type of distributed neural network (DNN) that utilizes feedback time-series information. Their input includes the current input value and their own output value from the previous time step. RNNs are well-suited for acquiring temporally correlated sequence features, and are particularly applicable to applications such as speech recognition and channel coding/decoding.
  • a loss function can be defined.
  • the loss function describes the difference or discrepancy between the model's output value and the ideal target value.
  • the loss function can be expressed in various forms, and there are no restrictions on its specific form.
  • the model training process can be viewed as follows: by adjusting some or all of the model's parameters, the value of the loss function is made to be less than a threshold value or to meet the target requirement.
  • a model can also be called an AI model, a rule, or other names.
  • An AI model can be considered a specific method for implementing AI functions.
  • An AI model represents the mapping relationship or function between the model's input and output.
  • AI functions can include one or more of the following: data collection, model training (or model learning), model information dissemination, model inference (or model reasoning, inference, or prediction, etc.), model monitoring or model validation, or inference result publication, etc.
  • AI functions can also be called AI (related) operations or AI-related functions.
  • a fully connected neural network is also called a multilayer perceptron (MLP).
  • MLP multilayer perceptron
  • an MLP consists of an input layer (left side), an output layer (right side), and multiple hidden layers (middle).
  • Each layer of an MLP contains several nodes, called neurons. Neurons in adjacent layers are connected pairwise.
  • w is the weight matrix
  • b is the bias vector
  • f is the activation function
  • n is the index of the neural network layer
  • N is the total number of layers in the neural network.
  • 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; the process of obtaining this mapping from random values w and b using existing data is called training the neural network.
  • the training process can involve using a loss function to evaluate the output of the neural network.
  • 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 its minimum, which is the "better point (e.g., the optimal point)" in Figure 2d.
  • the neural network parameters corresponding to the "better point (e.g., the optimal point)" in Figure 2d can be used as the neural network parameters in the trained AI model information.
  • the gradient descent process can be represented as:
  • ⁇ represents the parameters to be optimized (including w and b)
  • L is the loss function
  • ⁇ is the learning rate, controlling the step size of gradient descent. This represents the differentiation operation. This indicates taking the derivative of ⁇ with respect to L.
  • the backpropagation process can utilize the chain rule for partial derivatives.
  • the gradient of the parameters in the previous layer can be recursively calculated from the gradient of the parameters in the next layer, and can be expressed as:
  • w ⁇ sub> ij ⁇ /sub> is the weight connecting node j to node i
  • s ⁇ sub>i ⁇ /sub> is the weighted sum of the inputs at node i.
  • wireless communication systems such as the systems shown in Figure 1a, 1b, or 1c.
  • communication nodes In wireless communication systems, communication nodes generally possess signal transmission and reception capabilities as well as computing capabilities.
  • communication devices can serve as participating nodes in AI systems, applying their computing power to a specific stage of the AI system.
  • AI functions introduced into communication networks rely on models for implementation.
  • Figure 3 is a schematic diagram of an implementation of the communication method provided in this application. The method includes the following steps.
  • the communication device can be a communication equipment, or a chip, baseband chip, modem chip, system-on-chip (SoC) chip containing a modem core, system-in-package (SIP) chip, communication module, chip system, processor, logic module, or software in the communication equipment.
  • the communication equipment can be a terminal device or network device (such as an access network device, access network element, core network element, or core network device).
  • the first communication device acquires first information.
  • the first information indicates the first status information of the terminal device.
  • the first communication device can be terminal device A or an internal module of terminal device A, or the first communication device can be another device different from terminal device A (such as a network device, or another terminal device B).
  • the first communication device determines whether to enable the AI function of the terminal device based on the first status information.
  • the first communication device may execute step S303 or S304.
  • the first communication device receives or sends second information, the second information indicating first processing of an AI model when the AI function of the terminal device is enabled, the AI model being associated with the AI function of the terminal device.
  • the first communication device receives or sends third information, which indicates a second processing of the AI model without enabling the AI function of the terminal device.
  • AI function may be replaced with other terms, such as AI-enabled function, AI capability, or AI-enabled characteristic.
  • “enabled” can be replaced with other terms, such as startup, opening, not shutting down, not disabling, or enabling.
  • “disabled” can be replaced with other terms, such as not startup, not opening, shutting down, disabling, or not enabling.
  • the first process may instruct model management of the AI model when the AI function of the terminal device is enabled.
  • the first process may include one or more of the following: model update, model switching, model fine-tuning, or model fine-tuning.
  • the second process may instruct model management of the AI model without enabling the AI function of the terminal device.
  • the second process may include one or more of the following: determining the trigger conditions for model activation, data collection (e.g., the collected data can be used for subsequent model processing after the AI model is enabled).
  • the first state information indicates at least one of the following: the data characteristics of the data collected by the terminal device, the communication parameters of the terminal device, the model performance of the AI model associated with the AI function of the terminal device, or the computing resources of the terminal device.
  • the first communication device determining whether to enable the AI function of the terminal device based on the first state information includes: if the first state information meets a first condition, the first communication device determines to enable the AI function of the terminal device. Specifically, the first communication device can determine whether the first state information meets the first condition, and if the first condition is met, the first communication device determines to enable the AI function of the terminal device.
  • the method shown in Figure 3 further includes: the first communication device receiving fourth information, the fourth information indicating the first condition.
  • the first communication device can determine the first condition through the received fourth information, enabling the first communication device to perform a judgment process on whether to enable the AI function of the terminal device based on the first condition specified by other communication devices.
  • this first condition is pre-configured.
  • the first communication device determining whether to enable the AI function of the terminal device based on the first state information includes: if the first state information meets a second condition, the first communication device determines not to enable the AI function of the terminal device. Specifically, the first communication device can determine whether the first state information meets the second condition, and if the second condition is met, the first communication device determines not to enable the AI function of the terminal device.
  • the method shown in Figure 3 further includes: the first communication device receiving fifth information, the fifth information indicating the second condition.
  • the first communication device can determine the first condition through the received fifth information, enabling the first communication device to determine whether to enable the AI function of the terminal device based on the second condition specified by other communication devices.
  • this second condition is pre-configured.
  • the first communication device can obtain the first state information of the terminal device through the first information, and determine whether to enable the AI function of the terminal device based on the first state information. Subsequently, if it is determined that the AI function of the terminal device is enabled, the first communication device can receive or send second information instructing the AI model to undergo first processing in that situation. Alternatively, if it is determined that the AI function of the terminal device is not enabled, the first communication device can receive or send third information instructing the AI model to undergo second processing in that situation.
  • the recipient of the second information can manage the AI model based on the second information when the AI model is enabled (or, the recipient of the third information can manage the AI model based on the third information when the AI model is not enabled), thereby achieving model management of the AI model.
  • the first communication device determines whether to enable the AI function of the terminal device based on the first state information.
  • the basis for determining whether to enable the AI function of the terminal device includes the first state information of the terminal device. This allows the AI function of the terminal device to be matched with its state information. For example, enabling the AI function can provide benefits; conversely, disabling the AI function can save energy consumption and/or computing power. Therefore, when the first communication device determines to enable the AI function based on the first state information, the benefits of the AI function can be utilized to improve task processing efficiency; when the first communication device determines to disabling the AI function based on the first state information, the terminal device's costs can be saved.
  • the first communication device may receive the second information in step S303 (or the first communication device may receive the third information in step S304), or it may send the second information in step S303 (or the first communication device may send the third information in step S304).
  • the first communication device may receive the second information in step S303 (or the first communication device may receive the third information in step S304), or it may send the second information in step S303 (or the first communication device may send the third information in step S304).
  • the first communication device is the receiver of the second or third information.
  • Example 1 after the first communication device determines whether to enable (or disable) the AI function of the terminal device in step S302, the first communication device can send a determination result, so that the recipient of the determination result sends a second message to the first communication device in step S303 (or sends a third message to the first communication device in step S304).
  • the second communication device will use the second communication device as an example to illustrate this, in conjunction with the example shown in Figure 4.
  • this method further includes:
  • Step A The first communication device sends a seventh message, and the second communication device receives the seventh message accordingly.
  • This seventh message indicates whether the AI function of the terminal device is enabled, and it is determined based on the first status information.
  • the first communication device can send the seventh information, so that the recipient of the seventh information can determine whether to enable the AI function of the terminal device based on the seventh information, and communicate with the terminal device based on the seventh information (e.g., transmit data/signals/information/signaling for AI function, or transmit data/signals/information/signaling for other functions).
  • the seventh information e.g., transmit data/signals/information/signaling for AI function, or transmit data/signals/information/signaling for other functions.
  • the first communication device can be terminal device A or an internal module of terminal device A, so that the first communication device can obtain the state information of its corresponding terminal device in step S301, and after determining whether to enable the AI function of the terminal device based on the state information in step S302, it indicates the determination result to the second communication device through the seventh information, so that the second communication device can provide the first communication device with the second information or the third information, so that the first communication device can perform the corresponding first process based on the second information (or so that the first communication device can perform the corresponding second process based on the third information).
  • the first communication device is the sender (or provider) of the second or third information.
  • Example 1 after the first communication device determines whether to enable (or disable) the AI function of the terminal device in step S302, the first communication device can send second information to the third communication device in step S303 (or send third information to the third communication device in step S304) based on the determination result.
  • the following description will take the second communication device as the recipient of the second or third information as an example, in conjunction with the example shown in Figure 5.
  • the process of the first communication device acquiring the first information includes: the first communication device receiving the first information.
  • the first information may indicate the first status information of the terminal device.
  • the terminal device may be the third communication device in Figure 5.
  • the first communication device may be other terminal devices or network devices different from the third communication device. Therefore, the first communication device may receive the first information to determine the first status information of the terminal device through the first information.
  • the first communication device can be another device different from terminal device A (e.g., terminal device B or network device), so that the first communication device can obtain the state information of the terminal device in step S301, and after determining whether to enable the AI function of the terminal device based on the state information in step S302, provide the second information or third information to the third communication device, so that the third communication device can perform the corresponding first processing based on the second information (or so that the third communication device can perform the corresponding second processing based on the third information).
  • terminal device B or network device e.g., terminal device B or network device
  • the second and third information transmitted in steps S303 and S304 can be implemented in various ways, which will be described below through some possible implementation methods.
  • Method 1 The second information includes the time information associated with the first processing.
  • the second information received or transmitted by the first communication device in step S303 includes any one of the following:
  • First instruction information indicating first time information for the first process
  • the first and third indication information indicate that the first time interval indicated by the first time information is updated to a second time interval; wherein the starting time unit of the second time interval is the receiving time unit or the sending time unit of the third indication information, and the receiving time unit or the sending time unit of the third indication information is located within the first time interval.
  • the second information can be implemented in the above-mentioned multiple ways to improve the flexibility of the solution implementation, and enable the recipient of the second information to perform the first processing on the AI model based on at least one of the above methods.
  • the second instruction information can extend the first time information indicated by the first instruction information, thereby providing sufficient processing time for the first process and improving the success rate of the first process.
  • the time corresponding to the first processing can be made not limited to the first time information indicated by the first instruction information, thereby improving the continuity of AI model task execution and reducing task latency.
  • the first process is a periodic process
  • the second information further includes at least one of the following fourth to seventh indication information.
  • the fourth indication information indicates whether to enable the first time information, or whether to enable the first time information in the period closest to the current time. This fourth indication information allows the sender of the second information to flexibly configure whether to enable the first time information. Optionally, for the receiver of the second information, the first processing may not be performed by default within the time interval indicated by the first time information. If the receiver receives the fourth indication information and the fourth indication information indicates that the first time information is enabled (or indicates that the first time information is enabled in the period closest to the current time), the receiver performs the first processing based on the time interval indicated by the first time information.
  • the fifth indication information indicates a first threshold. If the number of cycles in which the fourth indication information is not received or sent is greater than or equal to the first threshold, the first time interval indicated by the first time information is updated to a third time interval, which is greater than the first time interval.
  • the receiving end of the second information (optionally also including the sending end of the second information) can extend the cycle corresponding to the first time information to achieve model management through a lower frequency of first processing. This is beneficial for improving the continuity of AI model task execution and reducing task latency.
  • the sixth indication information indicates a second threshold; wherein, within the duration indicated by the first timer, if the number of cycles of the fourth indication information received or sent is greater than or equal to the second threshold, and the received or sent fourth indication information indicates activation, then the first time interval indicated by the first time information is updated to a fourth time interval, the fourth time interval being less than the first time interval.
  • the receiving end of the second information (optionally, also including the sending end of the second information) can shorten the cycle corresponding to the first time information to achieve model management through more frequent second processing. This facilitates continuous monitoring of model performance to identify events such as model failure or low performance, thereby meeting the needs of model management and ensuring the performance of the AI function.
  • the seventh indication information indicates the third threshold; wherein, within the duration indicated by the second timer, if the number of cycles of receiving or sending the fourth indication information is greater than or equal to the third threshold, and the received or sent third indication information indicates that the function is disabled, the first processing is triggered.
  • the seventh indication information if a large number of disabled indications corresponding to the fourth indication information are continuously received over multiple cycles, it indicates that the model currently associated with the AI function of the terminal device may have a problem. Therefore, the receiving end of the second information (optionally also including the sending end of the second information) can trigger the first processing (e.g., AI function rollback, model switching, model failure event recording, etc.) to meet the needs of model management and ensure the performance of the AI function.
  • the first processing e.g., AI function rollback, model switching, model failure event recording, etc.
  • Method 2 The second information includes other information related to the first processing.
  • the second information received or transmitted by the first communication device in step S303 includes at least one of the following:
  • the eighth instruction message indicates that the AI function of this terminal device should be turned off
  • the ninth instruction indicates that some or all of the data associated with the AI model should be cached
  • the tenth instruction message indicates the cached data required to re-enable the AI function of the terminal device after it has been turned off.
  • the second information can be implemented in the above-mentioned ways to improve the flexibility of the solution implementation, and the recipient of the second information can manage the AI model based on at least one of the above methods.
  • Method 3 The third information includes other information related to the second processing.
  • the third information received or sent by the first communication device in step S304 includes third time information.
  • the method shown in Figure 3 further includes: after the time unit indicated by the third time information, the first communication device acquires fifth information, which indicates the second status information of the terminal device; the first communication device determines whether to enable the AI function of the terminal device based on the second status information.
  • the third information received or sent by the first communication device may include third time information, enabling the recipient of the third information to acquire the second status information of the terminal device based on the third time information, and further determine whether to enable the AI function of the terminal device based on the second status information. This allows the recipient to retry activating the AI function, aiming to obtain the benefits brought by the AI function and improve task processing efficiency when the AI function is determined to be activated.
  • the process of the first communication device acquiring the fifth information includes: the first communication device receiving the fifth information.
  • the method further includes: the first communication device sending a sixth message, the sixth message indicating whether to enable the AI function of the terminal device, the sixth message being determined based on the second state information.
  • the first communication device may send a sixth message, enabling the recipient of the sixth message to determine whether to enable the AI function of the terminal device based on the sixth message, and to communicate with the terminal device based on the sixth message (e.g., transmitting data/signals/information/signaling for AI functions, or transmitting data/signals/information/signaling for other functions).
  • this application embodiment provides a communication device 600.
  • This communication device 600 can implement the functions of the second or first communication device in the above method embodiments, and therefore can also achieve the beneficial effects of the above method embodiments.
  • the communication device 600 can be the first communication device (or the second or third communication device), or it can be an integrated circuit or component inside the first communication device (or the second or third communication device), such as a chip.
  • the transceiver unit 602 may include a transmitting unit and a receiving unit, which are used to perform transmitting and receiving respectively.
  • the device 600 when the device 600 is used to execute the method performed by the first communication device in the foregoing embodiments, the device 600 includes a processing unit 601 and a transceiver unit 602; the processing unit 601 is used to acquire first information, the first information indicating first status information of the terminal device; the processing unit 601 is also used to determine whether to enable the AI function of the terminal device based on the first status information; the transceiver unit 602 is used to receive or send second information, the second information indicating first processing of the AI model when the AI function of the terminal device is enabled, the AI model being associated with the AI function of the terminal device; or, the transceiver unit 602 is used to receive or send third information, the third information indicating second processing of the AI model when the AI function of the terminal device is not enabled.
  • the device 600 when the device 600 is used to execute the method performed by the second communication device in the aforementioned embodiments, the device 600 includes a processing unit 601 and a transceiver unit 602; the transceiver unit 602 is used to receive seventh information, which indicates whether the AI function of the terminal device is enabled; wherein, the seventh information is determined based on the first state information of the terminal device; the processing unit 601 is used to determine second information or third information; the transceiver unit 602 is also used to send the second information or the third information, the second information indicating first processing of the AI model when the AI function of the terminal device is enabled, and the third information indicating second processing of the AI model when the AI function of the terminal device is not enabled, wherein the AI model is associated with the AI function of the terminal device.
  • the device 600 when the device 600 is used to execute the method performed by the third communication device in the foregoing embodiments, the device 600 includes a processing unit 601 and a transceiver unit 602; the processing unit 601 is used to determine first information; the transceiver unit 602 is used to send the first information, the first information indicating first status information of the terminal device; the first status information is used to determine whether to enable the AI function of the terminal device; the transceiver unit 602 is also used to receive second information or third information, the second information indicating first processing of the AI model when the AI function of the terminal device is enabled, and the third information indicating second processing of the AI model when the AI function of the terminal device is not enabled, the AI model being associated with the AI function of the terminal device.
  • the communication device 700 includes a logic circuit 701 and an input/output interface 702.
  • the communication device 700 can be a chip or an integrated circuit.
  • the transceiver unit 602 can be a communication interface, which can be the input/output interface 702 in Figure 7, and the input/output interface 702 can include an input interface and an output interface.
  • the communication interface can also be a transceiver circuit, which can include an input interface circuit and an output interface circuit.
  • the logic circuit 701 is used to acquire first information, which indicates first state information of the terminal device; the logic circuit 701 is also used to determine whether to enable the AI function of the terminal device based on the first state information; the input/output interface 702 is used to receive or send second information, which indicates first processing of the AI model when the AI function of the terminal device is enabled, the AI model being associated with the AI function of the terminal device; or, the input/output interface 702 is used to receive or send third information, which indicates second processing of the AI model when the AI function of the terminal device is not enabled.
  • the input/output interface 702 is used to receive a seventh piece of information, which indicates whether the AI function of the terminal device is enabled; wherein, the seventh piece of information is determined based on the first state information of the terminal device; the logic circuit 701 is used to determine a second piece of information or a third piece of information; the input/output interface 702 is also used to send the second piece of information or the third piece of information, wherein the second piece of information indicates a first processing of the AI model when the AI function of the terminal device is enabled, and the third piece of information indicates a second processing of the AI model when the AI function of the terminal device is not enabled, and the AI model is associated with the AI function of the terminal device.
  • logic circuit 701 is used to determine first information; input/output interface 702 is used to send the first information, which indicates first status information of the terminal device; the first status information is used to determine whether the AI function of the terminal device is enabled; input/output interface 702 is also used to receive second information or third information, the second information indicating first processing of the AI model when the AI function of the terminal device is enabled, and the third information indicating second processing of the AI model when the AI function of the terminal device is not enabled, the AI model being associated with the AI function of the terminal device.
  • the logic circuit 701 and the input/output interface 702 can also perform other steps executed by the first, second, or third communication device in any embodiment and achieve corresponding beneficial effects, which will not be elaborated here.
  • the processing unit 601 shown in FIG6 can be the logic circuit 701 in FIG7.
  • the logic circuit 701 can be a processing device, the functions of which can be partially or entirely implemented in software.
  • the processing apparatus 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 the corresponding processing and/or steps in any of the method embodiments.
  • the processing device may consist of only a processor.
  • a memory for storing computer programs is located outside the processing device, and the processor is connected to the memory via circuitry/wires to read and execute the computer programs stored in the memory.
  • the memory and processor may be integrated together or physically independent of each other.
  • the processing device may be one or more chips, or one or more integrated circuits.
  • the processing device may be one or more field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), system-on-chips (SoCs), central processing 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.
  • FPGAs field-programmable gate arrays
  • ASICs application-specific integrated circuits
  • SoCs system-on-chips
  • CPUs central processing units
  • NPs network processors
  • DSPs digital signal processors
  • MCUs microcontroller units
  • PLDs programmable logic devices
  • Figure 8 shows the communication device 800 involved in the above embodiments provided in the embodiments of this application.
  • the communication device 800 can be the communication device as a terminal device in the above embodiments.
  • the communication device shown in Figure 8 is implemented through a terminal device (or a component in the terminal device).
  • the present invention is a possible logical structure diagram of the communication device 800, which may include, but is not limited to, at least one processor 801 and a communication port 802.
  • the transceiver unit 602 can be a communication interface, which can be the communication port 802 in Figure 8.
  • the communication port 802 can include an input interface and an output interface.
  • the communication port 802 can also be a transceiver circuit, which can include an input interface circuit and an output interface circuit.
  • the device may also include at least one of a memory 803 and a bus 804.
  • the at least one processor 801 is used to control the operation of the communication device 800.
  • the processor 801 can be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field-programmable gate array, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application.
  • the processor can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a digital signal processor and a microprocessor, etc.
  • the communication device 800 shown in Figure 8 can be used to implement the steps implemented by the terminal device in the aforementioned method embodiments and achieve the corresponding technical effects of the terminal device.
  • the specific implementation of the communication device shown in Figure 9 can be referred to the description in the aforementioned method embodiments, and will not be repeated here.
  • Figure 9 is a schematic diagram of the structure of the communication device 900 involved in the above embodiments provided in the embodiments of this application.
  • the communication device 900 can be a communication device as a network device in the above embodiments.
  • the communication device shown in Figure 9 is implemented through a network device (or a component in a network device).
  • the structure of the communication device can refer to the structure shown in Figure 9.
  • the communication device 900 includes at least one processor 911 and at least one network interface 914.
  • the communication device further includes at least one memory 912, at least one transceiver 913, and one or more antennas 915.
  • the processor 911, memory 912, transceiver 913, and network interface 914 are connected, for example, via a bus. In this embodiment, the connection may include various interfaces, transmission lines, or buses, etc., and this embodiment is not limited thereto.
  • the antenna 915 is connected to the transceiver 913.
  • the network interface 914 enables the communication device to communicate with other communication devices through a communication link.
  • the network interface 914 may include a network interface between the communication device and core network equipment, such as an S1 interface, or a network interface between the communication device and other communication devices (e.g., other network devices or core network equipment), such as an X2 or Xn interface.
  • core network equipment such as an S1 interface
  • other communication devices e.g., other network devices or core network equipment
  • the transceiver unit 602 can be a communication interface, which can be the network interface 914 in Figure 9.
  • the network interface 914 can include an input interface and an output interface.
  • the network interface 914 can also be a transceiver circuit, which can include an input interface circuit and an output interface circuit.
  • the processor 911 is primarily used to process communication protocols and communication data, control the entire communication device, execute software programs, and process data from these programs, for example, to support the actions described in the embodiments of the communication device.
  • the communication device may include a baseband processor and a central processing unit (CPU).
  • the baseband processor is primarily used to process communication protocols and communication data, while the CPU is primarily used to control the entire terminal device, execute software programs, and process data from these programs.
  • the processor 911 in Figure 9 can integrate the functions of both a baseband processor and a CPU. Those skilled in the art will understand that the baseband processor and CPU can also be independent processors interconnected via technologies such as buses.
  • a terminal device may include multiple baseband processors to adapt to different network standards, and multiple CPUs to enhance its processing capabilities.
  • the various components of the terminal device can be connected via various buses.
  • the baseband processor can also be described as a baseband processing circuit or a baseband processing chip.
  • the CPU can also be described as a central processing circuit or a central processing chip.
  • the function of processing communication protocols and communication data can be built into the processor or stored in memory as a software program, which is then executed by the processor to implement the baseband processing function.
  • the memory is primarily used to store software programs and data.
  • the memory 912 can exist independently or be connected to the processor 911.
  • the memory 912 can be integrated with the processor 911, for example, integrated into a single chip.
  • the memory 912 can store program code that executes the technical solutions of the embodiments of this application, and its execution is controlled by the processor 911.
  • the various types of computer program code being executed can also be considered as drivers for the processor 911.
  • Figure 9 shows only one memory and one processor. In actual terminal devices, there may be multiple processors and multiple memories. Memory can also be called storage medium or storage device, etc. Memory can be a storage element on the same chip as the processor, i.e., an on-chip storage element, or it can be a separate storage element; this application does not limit this.
  • Transceiver 913 can be used to support the reception or transmission of radio frequency (RF) signals between a communication device and a terminal.
  • Transceiver 913 can be connected to antenna 915.
  • Transceiver 913 includes a transmitter Tx and a receiver Rx. Specifically, one or more antennas 915 can receive RF signals.
  • the receiver Rx of transceiver 913 receives the RF signals from the antennas, converts the RF signals into digital baseband signals or digital intermediate frequency (IF) signals, and provides the digital baseband signals or IF signals to processor 911 so that processor 911 can perform further processing on the digital baseband signals or IF signals, such as demodulation and decoding.
  • IF intermediate frequency
  • the transmitter Tx in transceiver 913 is also used to receive modulated digital baseband signals or IF signals from processor 911, convert the modulated digital baseband signals or IF signals into RF signals, and transmit the RF signals through one or more antennas 915.
  • the receiver Rx can selectively perform one or more stages of downmixing and analog-to-digital conversion on the radio frequency signal to obtain a digital baseband signal or a digital intermediate frequency (IF) signal.
  • IF digital intermediate frequency
  • the order of these downmixing and IF conversion processes is adjustable.
  • the transmitter Tx can selectively perform one or more stages of upmixing and digital-to-analog conversion on the modulated digital baseband signal or digital IF signal to obtain a radio frequency signal.
  • the order of these upmixing and IF conversion processes is also adjustable.
  • the digital baseband signal and the digital IF signal can be collectively referred to as digital signals.
  • the transceiver 913 can also be called a transceiver unit, transceiver, transceiver device, etc.
  • the device in the transceiver unit that performs the receiving function can be regarded as the receiving unit
  • the device in the transceiver unit that performs the transmitting function can be regarded as the transmitting unit. That is, the transceiver unit includes a receiving unit and a transmitting unit.
  • the receiving unit can also be called a receiver, input port, receiving circuit, etc.
  • the transmitting unit can be called a transmitter, transmitter, or transmitting circuit, etc.
  • the communication device 900 shown in Figure 9 can be used to implement the steps implemented by the network device in the aforementioned method embodiments and achieve the corresponding technical effects of the network device.
  • the specific implementation of the communication device 900 shown in Figure 9 can be referred to the description in the aforementioned method embodiments, and will not be repeated here.
  • Figure 10 is a schematic diagram of the structure of the communication device involved in the above embodiments provided in the embodiments of this application.
  • the communication device 100 includes, for example, modules, units, elements, circuits, or interfaces, which are appropriately configured together to execute the technical solutions provided in this application.
  • the communication device 100 may be the terminal device or network device described above, or a component (e.g., a chip) within these devices, used to implement the methods described in the following method embodiments.
  • the communication device 100 includes one or more processors 101.
  • the processor 101 may be a general-purpose processor or a dedicated processor, for example, a baseband processor or a central processing unit.
  • the baseband processor can be used to process communication protocols and communication data
  • the central processing unit can be used to control the communication device (e.g., a RAN node, terminal, or chip), execute software programs, and process data from the software programs.
  • processor 101 may include program 103 (sometimes also referred to as code or instructions), which may be executed on processor 101 to cause communication device 100 to perform the methods described in the embodiments below.
  • communication device 100 includes circuitry (not shown in FIG10).
  • the communication device 100 may include one or more memories 102 storing a program 104 (sometimes referred to as code or instructions), which can be run on the processor 101 to cause the communication device 100 to perform the methods described in the above method embodiments.
  • a program 104 sometimes referred to as code or instructions
  • the processor 101 and/or memory 102 may include AI modules 107 and 108, which are used to implement AI-related functions.
  • the AI modules can be implemented through software, hardware, or a combination of both.
  • the AI module may include a radio intelligence control (RIC) module.
  • the AI module may be a near real-time RIC or a non-real-time RIC.
  • processor 101 and/or memory 102 may also store data.
  • the processor and memory may be configured separately or integrated together.
  • the communication device 100 may further include a transceiver 105 and/or an antenna 106.
  • the processor 101 sometimes referred to as a processing unit, controls the communication device (e.g., a RAN node or terminal).
  • the transceiver 105 sometimes referred to as a transceiver unit, transceiver, transceiver circuit, or transceiver, is used to realize the transmission and reception functions of the communication device through the antenna 106.
  • the processing unit 601 shown in Figure 6 can be a processor 101.
  • the transceiver unit 602 shown in Figure 6 can be a communication interface, which can be the transceiver 105 in Figure 10.
  • the transceiver 105 can include an input interface and an output interface.
  • the transceiver 105 can also be a transceiver circuit, which can include an input interface circuit and an output interface circuit.
  • This application also provides a computer-readable storage medium for storing one or more computer-executable instructions.
  • the processor When the computer-executable instructions are executed by a processor, the processor performs the method described in the possible implementations of the first, second, or third communication device in the foregoing embodiments.
  • This application also provides a computer program product (or computer program) that, when executed by a processor, executes the method of the first, second, or third communication device as described above.
  • This application also provides a chip system including at least one processor for supporting a communication device in implementing the functions involved in the possible implementations of the communication device described above.
  • the chip system further includes an interface circuit that provides program instructions and/or data to the at least one processor.
  • the chip system may further include a memory for storing the program instructions and data necessary for the communication device.
  • the chip system may be composed of chips or may include chips and other discrete devices, wherein the communication device may specifically be the first, second, or third communication device in the aforementioned method embodiments.
  • This application also provides a communication system, which includes a first communication device and a second communication device in any of the above embodiments, or the system includes a first communication device and a third communication device in any of the above embodiments.
  • the disclosed systems, apparatuses, and methods can be implemented in other ways.
  • the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods.
  • multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.
  • the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.
  • the units described as separate components may or may not be physically separate.
  • the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
  • the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.
  • the integrated unit can be implemented in hardware or as a software functional unit. If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.
  • This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.
  • the aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

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Abstract

一种通信方法及相关装置，在该方法中，第一通信装置可以通过第一信息获取终端设备的第一状态信息，并基于该第一状态信息确定是否启用该终端设备的AI功能。此后，在确定启用该终端设备的AI功能的情况下，该第一通信装置可以接收或发送指示该情况下对AI模型进行第一处理的第二信息。或，在确定不启用该终端设备的AI功能的情况下，该第一通信装置可以接收或发送指示该情况下对AI模型进行第二处理的第三信息。通过这种方式，第二信息的接收方能够基于该第二信息在启用AI模型的情况下对AI模型进行模型管理(或，第三信息的接收方能够基于该第三信息在不启用AI模型的情况下对AI模型进行模型管理)，以实现对AI模型的模型管理。

Description

一种通信方法及相关装置
本申请要求于2024年06月21日提交国家知识产权局、申请号为202410814801.5、申请名称为“一种通信方法及相关装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及通信领域，尤其涉及一种通信方法及相关装置。
背景技术
随着通信技术的发展，在通信系统中，通信设备执行的业务除了传统的通信业务之外，还可以包括其它新型业务，例如人工智能(artificial intelligence，AI)业务。一般地，能够处理AI业务的通信系统也可以称为AI系统。
目前，通信设备可以作为AI系统的参与节点，将该通信设备的算力应用于AI系统的某一个环节。一般来说，在通信网络中引入的AI功能，需要依赖模型来实现。然而，在上述过程中，如何对模型进行模型管理，当前尚未有相关方案能够解决。
发明内容
本申请提供了一种通信方法及相关装置，用于实现模型管理。
本申请第一方面提供了一种通信方法，该方法由第一通信装置执行，该第一通信装置可以是通信设备(如终端设备或网络设备)，或者，该第一通信装置可以是通信设备中的部分组件(例如负责通信功能的电路或芯片(如调制解调(Modem)芯片，又称基带(baseband)芯片，或包含modem核的片上系统(system on chip,SoC)芯片或系统级封装(system in package，SIP)芯片)等)，或者该第一通信装置还可以是能实现全部或部分通信设备功能的逻辑模块或软件。在该方法中，第一通信装置获取第一信息，该第一信息指示终端设备的第一状态信息；该第一通信装置基于该第一状态信息确定是否启用该终端设备的AI功能；该第一通信装置接收或发送第二信息，该第二信息指示启用该终端设备的AI功能的情况下对AI模型的第一处理，该AI模型关联于该终端设备的AI功能；或，该第一通信装置接收或发送第三信息，该第三信息指示不启用该终端设备的AI功能的情况下对该AI模型的第二处理。
基于上述方案，第一通信装置可以通过第一信息获取终端设备的第一状态信息，并基于该第一状态信息确定是否启用该终端设备的AI功能。此后，在确定启用该终端设备的AI功能的情况下，该第一通信装置可以接收或发送指示该情况下对AI模型进行第一处理的第二信息。或，在确定不启用该终端设备的AI功能的情况下，该第一通信装置可以接收或发送指示该情况下对AI模型进行第二处理的第三信息。通过这种方式，第二信息的接收方能够基于该第二信息在启用AI模型的情况下对AI模型进行模型管理(或，第三信息的接收方能够基于该第三信息在不启用AI模型的情况下对AI模型进行模型管理)，以实现对AI模型的模型管理。
此外，在上述方案中，第一通信装置基于该第一状态信息确定是否启用该终端设备的AI功能，换言之，用于确定是否启用该终端设备的AI功能的确定依据包括终端设备的第一状态信息。通过这种方式，能够使得终端设备的AI功能与该终端设备的状态信息相匹配。例如，启用AI功能可以获得AI功能带来的增益；相应的，不启用AI功能可以节省终端设备的能耗和/或算力等开销；为此，在第一通信装置基于第一状态信息确定启用该终端设备的AI功能的情况下，可以利用AI功能带来的增益，提升任务处理效率；在第一通信装置基于第一状态信息确定不启用该终端设备的AI功能的情况下，可以节省终端设备的开销。
本申请中，AI模型(例如AI功能关联的AI模型等)可以包括数学模型、模型、神经网络模型、AI神经网络模型、机器学习模型、或AI处理模型等。
本申请中，AI功能可以替换为其它术语，例如AI使能的功能、AI能力、或AI使能的特性等。
本申请中，启用可以替换为其它术语，例如启动、开启、不关闭、不禁止、或使能等。相应的，不启用可以替换为其它术语，例如不启动、不开启、关闭、禁止或不使能等。
应理解，第一处理可以指示在启用该终端设备的AI功能的情况下，对AI模型的模型管理。例如，该第一处理可以包括模型更新、模型切换、模型微调、或模型精调中的一项或多项。
应理解，第二处理可以指示在不启用该终端设备的AI功能的情况下，对AI模型的模型管理。例如，该第二处理可以包括模型启用的触发条件的判断、数据收集(例如收集得到的数据可以用于后续启用AI模型之后的模型处理)中的一项或多项。
可选的，第一状态信息(或者后文的第二状态信息)指示以下至少一项：该终端设备采集的数据的数据特征、该终端设备的通信参数、该终端设备的AI功能关联的AI模型的模型性能、或、该终端设备的计算资源。
在第一方面的一种可能的实现方式中，该第一通信装置基于该第一状态信息确定是否启用该终端设备的AI功能包括：在该第一状态信息满足第一条件的情况下，该第一通信装置确定启用该终端设备的AI功能。
基于上述方案，第一通信装置可以判断第一状态信息是否满足第一条件，并在满足第一条件的情况下，该第一通信装置确定启用该终端设备的AI功能。
在第一方面的一种可能的实现方式中，该方法还包括：该第一通信装置接收第四信息，该第四信息指示该第一条件。
基于上述方案，第一通信装置可以通过接收的第四信息确定第一条件，使得该第一通信装置可以基于其它通信装置指定的第一条件实现是否启用终端设备的AI功能的判断过程。
可选的，该第一条件为预配置的。
在第一方面的一种可能的实现方式中，该第一通信装置基于该第一状态信息确定是否启用该终端设备的AI功能包括：在该第一状态信息满足第二条件的情况下，该第一通信装置确定不启用该终端设备的AI功能。
基于上述方案，第一通信装置可以判断第一状态信息是否满足第二条件，并在满足第二条件的情况下，该第一通信装置确定不启用该终端设备的AI功能。
在第一方面的一种可能的实现方式中，该方法还包括：该第一通信装置接收第五信息，该第五信息指示该第二条件。
基于上述方案，第一通信装置可以通过接收的第五信息确定第一条件，使得该第一通信装置可以基于其它通信装置指定的第二条件实现是否启用终端设备的AI功能的判断过程。
可选的，该第二条件为预配置的。
在第一方面的一种可能的实现方式中，该第三信息包括第三时间信息；该方法还包括：在该第三时间信息指示的时间单元或该第三时间信息指示的时间单元之后，该第一通信装置获取第五信息，该第五信息指示终端设备的第二状态信息；该第一通信装置基于该第二状态信息确定是否启用该终端设备的AI功能。
基于上述方案，在第一通信装置基于第一状态信息确定不启用该终端设备的AI功能的情况下，该第一通信装置接收或发送的第三信息可以包括第三时间信息，使得该第三信息的接收方能够基于该第三时间信息获取终端设备的第二状态信息，并基于该第二状态信息进一步判断是否启用该终端设备的AI功能，能够再次尝试启动AI功能，以期在确定启动AI功能的情况下获得AI功能带来的增益，提升任务处理效率。
在第一方面的一种可能的实现方式中，该方法还包括：该第一通信装置发送第六信息，该第六信息指示是否启用该终端设备的AI功能，该第六信息是基于该第二状态信息确定的。
基于上述方案，第一通信装置在基于第二状态信息确定是否启用终端设备的AI功能之后，该第一通信装置可以发送第六信息，使得该第六信息的接收方能够基于该第六信息确定是否启用终端设备的AI功能，并基于该第六信息与该终端设备进行通信(例如传输用于AI功能的数据/信号/信息/信令等，或传输用于其它功能的数据/信号/信息/信令等)。
在第一方面的一种可能的实现方式中，该第一通信装置获取第一信息，包括：该第一通信装置接收该第一信息。
基于上述方案，第一通信装置可以不是终端设备或终端设备中的模块，为此，该第一通信装置可以接收第一信息，以通过该第一信息确定终端设备的第一状态信息。
类似地，第一通信装置获取第五信息的过程，包括：该第一通信装置接收该第五信息。
在第一方面的一种可能的实现方式中，该方法还包括：该第一通信装置发送第七信息，该第七信息指示是否启用该终端设备的AI功能，该第七信息是基于该第一状态信息确定的。
基于上述方案，第一通信装置在基于第一状态信息确定是否启用终端设备的AI功能之后，该第一通信装置可以发送第七信息，使得该第七信息的接收方能够基于该第七信息确定是否启用终端设备的AI功能，并基于该第七信息与该终端设备进行通信(例如传输用于AI功能的数据/信号/信息/信令等，或传输用于其它功能的数据/信号/信息/信令等)。
本申请第二方面提供了一种通信方法，该方法由第二通信装置执行，该第二通信装置可以是通信设备(如，终端设备或网络设备)，或者，该第二通信装置可以是通信设备中的部分组件(例如负责通信功能的电路或芯片(如Modem芯片，又称baseband芯片，或包含modem核的SoC芯片或SIP芯片等)，或者该第二通信装置还可以是能实现全部或部分通信设备功能的逻辑模块或软件。在该方法中，第二通信装置接收第七信息，该第七信息指示是否启用终端设备的AI功能；其中，该第七信息是基于该终端设备的第一状态信息确定的；该第二通信装置发送第二信息或第三信息，该第二信息指示启用该终端设备的AI功能的情况下对AI模型的第一处理，该第三信息指示不启用该终端设备的AI功能的情况下对该AI模型的第二处理，该AI模型关联于该终端设备的AI功能。
基于上述方案，第二通信装置可以接收指示是否启用该终端设备的AI功能的第七信息。此后，在确定启用该终端设备的AI功能的情况下，该第二通信装置可以接收或发送指示该情况下对AI模型进行第一处理的第二信息。或，在确定不启用该终端设备的AI功能的情况下，该第二通信装置可以接收或发送指示该情况下对AI模型进行第二处理的第三信息。通过这种方式，第二信息的接收方能够基于该第二信息在启用AI模型的情况下对AI模型进行模型管理(或，第三信息的接收方能够基于该第三信息在不启用AI模型的情况下对AI模型进行模型管理)，以实现对AI模型的模型管理。
此外，在上述方案中，用于确定是否启用该终端设备的AI功能的确定依据包括终端设备的第一状态信息。通过这种方式，能够使得终端设备的AI功能与该终端设备的状态信息相匹配。例如，启用AI功能可以获得AI功能带来的增益；相应的，不启用AI功能可以节省终端设备的能耗和/或算力等开销；为此，在第一通信装置基于第一状态信息确定启用该终端设备的AI功能的情况下，可以利用AI功能带来的增益，提升任务处理效率；在第一通信装置基于第一状态信息确定不启用该终端设备的AI功能的情况下，可以节省终端设备的开销。
在第二方面的一种可能的实现方式中，该方法还包括：该第二通信装置发送第四信息，该第四信息指示第一条件；其中，在该第一状态信息满足该第一条件的情况下，启用该终端设备的AI功能。
基于上述方案，第二通信装置可以发送第四信息，使得第一通信装置可以通过接收的第四信息确定第一条件，并使得该第一通信装置可以基于第二通信装置指定的第一条件实现是否启用终端设备的AI功能的判断过程。
在第二方面的一种可能的实现方式中，该方法还包括：该第二通信装置发送第五信息，该第五信息指示该第二条件；其中，在该第一状态信息满足该第二条件的情况下，不启用该终端设备的AI功能。
基于上述方案，第二通信装置可以发送第五信息，使得第一通信装置可以通过接收的第五信息确定第一条件，并使得该第一通信装置可以基于第二通信装置指定的第二条件实现是否启用终端设备的AI功能的判断过程。
在第二方面的一种可能的实现方式中，该第三信息包括第三时间信息；其中，在该第三时间信息指示的时间单元或该第三时间信息指示的时间单元之后，第一通信装置获取的终端设备的第二状态信息用于确定是否启用该终端设备的AI功能。
基于上述方案，在基于第一状态信息确定不启用该终端设备的AI功能的情况下，该第二通信装置接收或发送的第三信息可以包括第三时间信息，使得该第三信息的接收方能够基于该第三时间信息获取终端设备的第二状态信息，并基于该第二状态信息进一步判断是否启用该终端设备的AI功能，能够再次尝试启动AI功能，以期在确定启动AI功能的情况下获得AI功能带来的增益，提升任务处理效率。
在第二方面的一种可能的实现方式中，该方法还包括：该第二通信装置接收第六信息，该第六信息指示是否启用该终端设备的AI功能，该第六信息是基于该第二状态信息确定的。
基于上述方案，第一通信装置在基于第二状态信息确定是否启用终端设备的AI功能之后，该第二通信装置可以接收来自该第一通信装置第六信息，使得该第二通信装置能够基于该第六信息确定是否启用终端设备的AI功能，并基于该第六信息与该终端设备进行通信(例如传输用于AI功能的数据/信号/信息/信令等，或传输用于其它功能的数据/信号/信息/信令等)。
本申请第三方面提供了一种通信方法，该方法由第三通信装置执行，该第三通信装置可以是通信设备(如终端设备)，或者，该第三通信装置可以是通信设备中的部分组件(例如负责通信功能的电路或芯片(如Modem芯片，又称baseband芯片，或包含modem核的SoC芯片或系统级封装SIP芯片)等)，或者该第三通信装置还可以是能实现全部或部分通信设备功能的逻辑模块或软件。在该方法中，第三通信装置发送第一信息，该第一信息指示终端设备的第一状态信息；该第一状态信息用于确定是否启用该终端设备的AI功能；该第三通信装置接收第二信息或第三信息，该第二信息指示启用该终端设备的AI功能的情况下对AI模型的第一处理，该第三信息指示不启用该终端设备的AI功能的情况下对该AI模型的第二处理，该AI模型关联于该终端设备的AI功能。
基于上述方案，第三通信装置发送的第一信息可以指示终端设备的第一状态信息，使得该第一信息的接收方可以基于该第一状态信息确定是否启用该终端设备的AI功能。此后，在确定启用该终端设备的AI功能的情况下，该第三通信装置可以接收或发送指示该情况下对AI模型进行第一处理的第二信息。或，在确定不启用该终端设备的AI功能的情况下，该第三通信装置可以接收或发送指示该情况下对AI模型进行第二处理的第三信息。通过这种方式，第二信息的接收方能够基于该第二信息在启用AI模型的情况下对AI模型进行模型管理(或，第三信息的接收方能够基于该第三信息在不启用AI模型的情况下对AI模型进行模型管理)，以实现对AI模型的模型管理。
此外，在上述方案中，用于确定是否启用该终端设备的AI功能的确定依据包括终端设备的第一状态信息。通过这种方式，能够使得终端设备的AI功能与该终端设备的状态信息相匹配。例如，启用AI功能可以获得AI功能带来的增益；相应的，不启用AI功能可以节省终端设备的能耗和/或算力等开销；为此，在第一通信装置基于第一状态信息确定启用该终端设备的AI功能的情况下，可以利用AI功能带来的增益，提升任务处理效率；在第一通信装置基于第一状态信息确定不启用该终端设备的AI功能的情况下，可以节省终端设备的开销。
在第三方面的一种可能的实现方式中，该方法还包括：该第三通信装置接收第七信息，该第七信息指示是否启用终端设备的AI功能；其中，该第七信息是基于该终端设备的第一状态信息确定的。
基于上述方案，在基于第一状态信息确定是否启用终端设备的AI功能之后，该第三通信装置可以接收第七信息，使得该第三通信装置能够基于该第七信息确定是否启用终端设备的AI功能，并基于该第六信息与该终端设备进行通信(例如传输用于AI功能的数据/信号/信息/信令等，或传输用于其它功能的数据/信号/信息/信令等)。
在第三方面的一种可能的实现方式中，该第三信息包括第三时间信息；该方法还包括：该第三通信装置在该第三时间信息指示的时间单元或该第三时间信息指示的时间单元之后，发送第五信息；其中，该第五信息指示终端设备的第二状态信息，该第二状态信息确定是否启用该终端设备的AI功能。
基于上述方案，在基于第一状态信息确定不启用该终端设备的AI功能的情况下，该第三通信装置接收或发送的第三信息可以包括第三时间信息，使得该第三信息的接收方能够基于该第三时间信息获取终端设备的第二状态信息，并基于该第二状态信息进一步判断是否启用该终端设备的AI功能，能够再次尝试启动AI功能，以期在确定启动AI功能的情况下获得AI功能带来的增益，提升任务处理效率。
在第三方面的一种可能的实现方式中，该方法还包括：该第三通信装置接收第六信息，该第六信息指示是否启用该终端设备的AI功能，该第六信息是基于该第二状态信息确定的。
基于上述方案，在基于第二状态信息确定是否启用终端设备的AI功能之后，该第三通信装置可以接收第六信息，使得该第三通信装置能够基于该第六信息确定是否启用终端设备的AI功能，并基于该第六信息与该终端设备进行通信(例如传输用于AI功能的数据/信号/信息/信令等，或传输用于其它功能的数据/信号/信息/信令等)。
在第一方面至第三方面的任一方面的一种可能的实现方式中，该第二信息包括以下任一项：
第一指示信息，指示用于该第一处理的第一时间信息；
该第一指示信息和第二指示信息，该第二指示信息指示第二时间信息；其中，在该第一时间信息指示的时长不足以完成该第一处理的情况下，该第二时间信息用于该第一处理；
该第一指示信息和第三指示信息，指示将该第一时间信息指示的第一时间间隔更新为第二时间间隔；其中，该第二时间间隔的起始时间单元为该第三指示信息的接收时间单元或发送时间单元，该第三指示信息的接收时间单元或发送时间单元位于该第一时间间隔内。
基于上述方案，第二信息可以通过上述多种方式实现，以提升方案实现的灵活性，并且，使得第二信息的接收方可以基于上述至少一项对AI模型进行第一处理。
可选的，该第一处理为周期性的处理，该第二信息还包括以下至少一项：
第四指示信息，指示是否启用该第一时间信息，或，指示是否在与当前时刻最近的周期启用该第一时间信息；
第五指示信息，指示第一阈值；其中，在未接收到或未发送该第四指示信息的周期次数大于或等于该第一阈值的情况下，触发将该第一时间信息指示的第一时间间隔更新为第三时间间隔，该第三时间间隔大于该第一时间间隔；
第六指示信息，指示第二阈值；其中，在第一定时器指示的时长内，接收到的或发送的该第四指示信息的周期次数大于或等于该第二阈值，且该接收到的或发送的该第四指示信息指示启用的情况下，触发将该第一时间信息指示的第一时间间隔更新为第四时间间隔，该第四时间间隔小于该第一时间间隔；
第七指示信息，指示第三阈值；其中，在第二定时器指示的时长内，接收到的或发送的该第四指示信息的周期次数大于或等于该第三阈值，且该接收到的或发送的该第三指示信息指示不启用的情况下，触发该第一处理。
在第一方面至第三方面的任一方面的一种可能的实现方式中，该第二信息包括以下至少一项：
第八指示信息，指示关闭该终端设备的AI功能；
第九指示信息，指示对该AI模型关联的部分或全部数据进行缓存；
第十指示信息，指示在关闭该终端设备的AI功能之后，重新启用该终端设备的AI功能所需的缓存数据。
基于上述方案，第二信息可以通过上述多种方式实现，以提升方案实现的灵活性，并且，第二信息的接收方可以基于上述至少一项对AI模型进行模型管理。
本申请第四方面提供了一种通信装置，该通信装置为第一通信装置，该通信装置包括收发单元和处理单元；该处理单元用于获取第一信息，该第一信息指示终端设备的第一状态信息；该处理单元还用于基于该第一状态信息确定是否启用该终端设备的AI功能；该收发单元用于接收或发送第二信息，该第二信息指示启用该终端设备的AI功能的情况下对AI模型的第一处理，该AI模型关联于该终端设备的AI功能；或，该收发单元用于接收或发送第三信息，该第三信息指示不启用该终端设备的AI功能的情况下对该AI模型的第二处理。
本申请第四方面中，通信装置的组成模块还可以用于执行第一方面的各个可能实现方式中所执行的步骤，并实现相应的技术效果，具体均可以参阅第一方面，此处不再赘述。
本申请第五方面提供了一种通信装置，该通信装置为第一通信装置，该通信装置包括收发单元和处理单元；该收发单元用于接收第七信息，该第七信息指示是否启用终端设备的AI功能；其中，该第七信息是基于该终端设备的第一状态信息确定的；该处理单元用于确定第二信息或第三信息；该收发单元还用于发送第二信息或第三信息，该第二信息指示启用该终端设备的AI功能的情况下对AI模型的第一处理，该第三信息指示不启用该终端设备的AI功能的情况下对该AI模型的第二处理，该AI模型关联于该终端设备的AI功能。
本申请第五方面中，通信装置的组成模块还可以用于执行第二方面的各个可能实现方式中所执行的步骤，并实现相应的技术效果，具体均可以参阅第二方面，此处不再赘述。
本申请第六方面提供了一种通信装置，该通信装置为第三通信装置，该通信装置包括收发单元和处理单元，该处理单元用于确定第一信息；该收发单元用于发送第一信息，该第一信息指示终端设备的第一状态信息；该第一状态信息用于确定是否启用该终端设备的AI功能；该收发单元还用于接收第二信息或第三信息，该第二信息指示启用该终端设备的AI功能的情况下对AI模型的第一处理，该第三信息指示不启用该终端设备的AI功能的情况下对该AI模型的第二处理，该AI模型关联于该终端设备的AI功能。
本申请第六方面中，通信装置的组成模块还可以用于执行第三方面的各个可能实现方式中所执行的步骤，并实现相应的技术效果，具体均可以参阅第三方面，此处不再赘述。
本申请第七方面提供了一种通信装置，包括至少一个处理器，所述至少一个处理器与存储器耦合；该存储器用于存储程序或指令；该至少一个处理器用于执行该程序或指令，以使该通信装置实现前述第一方面至第三方面任一方面中的任意一种可能的实现方式所述的方法。可选的，所述通信装置可以包括所述存储器。
本申请第八方面提供了一种通信装置，包括至少一个逻辑电路和输入输出接口；该逻辑电路用于执行如前述第一方面至第三方面任一方面中的任意一种可能的实现方式所述的方法。
本申请第九方面提供了一种通信系统，该通信系统包括上述第一通信装置以及第二通信装置，或，该通信系统包括上述第一通信装置以及第三通信装置。
本申请第十方面提供一种计算机可读存储介质，该存储介质用于存储一个或多个计算机执行指令，当计算机执行指令被处理器执行时，该处理器执行如上述第一方面至第三方面中任一方面的任意一种可能的实现方式所述的方法。
本申请第十一方面提供一种计算机程序产品(或称计算机程序)，当计算机程序产品中的计算机程序被该处理器执行时，该处理器执行上述第一方面至第三方面中任一方面的任意一种可能的实现方式所述的方法。
本申请第十二方面提供了一种芯片系统，该芯片系统包括至少一个处理器，用于支持通信装置实现上述第一方面至第三方面中任一方面的任意一种可能的实现方式所述的方法。
在一种可能的设计中，该芯片系统还可以包括存储器，存储器，用于保存该通信装置必要的程序指令和数据。该芯片系统，可以由芯片构成，也可以包含芯片和其他分立器件。可选的，所述芯片系统还包括接口电路，所述接口电路为所述至少一个处理器提供程序指令和/或数据。
其中，第四方面至第十二方面中任一种设计方式所带来的技术效果可参见上述第一方面至第三方面中不同设计方式所带来的技术效果，在此不再赘述。
附图说明
图1a至图1c为本申请提供的通信系统的示意图；
图2a至图2e为本申请涉及的AI处理过程的示意图；
图3至图5为本申请提供的通信方法的一些示意图；
图6至图10为本申请提供的通信装置的示意图。
具体实施方式
首先，对本申请实施例中的部分用语进行解释说明，以便于本领域技术人员理解。
(1)终端设备：可以是能够接收网络设备调度和指示信息的无线终端设备，无线终端设备可以是指向用户提供语音和/或数据连通性的设备，或具有无线连接功能的手持式设备，或连接到无线调制解调器的其他处理设备。
终端设备可以经无线接入网(radio access network，RAN)与一个或多个核心网或者互联网进行通信，终端设备可以是移动终端设备，如移动电话(或称为“蜂窝”电话，手机(mobile phone))、计算机和数据卡，例如，可以是便携式、袖珍式、手持式、计算机内置的或者车载的移动装置，它们与无线接入网交换语音和/或数据。例如，个人通信业务(personal communication service，PCS)电话、无绳电话、会话发起协议(SIP)话机、无线本地环路(wireless local loop，WLL)站、个人数字助理(personal digital assistant，PDA)、平板电脑(Pad)、带无线收发功能的电脑等设备。无线终端设备也可以称为系统、订户单元(subscriber unit)、订户站(subscriber station)，移动站(mobile station)、移动台(mobile station，MS)、远程站(remote station)、接入点(access point，AP)、远程终端设备(remote terminal)、接入终端设备(access terminal)、用户终端设备(user terminal)、用户代理(user agent)、用户站(subscriber station，SS)、用户端设备(customer premises equipment，CPE)、终端(terminal)、用户设备(user equipment，UE)、移动终端(mobile terminal，MT)等。
作为示例而非限定，在本申请实施例中，该终端设备还可以是可穿戴设备。可穿戴设备也可以称为穿戴式智能设备或智能穿戴式设备等，是应用穿戴式技术对日常穿戴进行智能化设计、开发出可以穿戴的设备的总称，如眼镜、手套、手表、服饰及鞋等。可穿戴设备即直接穿在身上，或是整合到用户的衣服或配件的一种便携式设备。可穿戴设备不仅仅是一种硬件设备，更是通过软件支持以及数据交互、云端交互来实现强大的功能。广义穿戴式智能设备包括功能全、尺寸大、可不依赖智能手机实现完整或者部分的功能，例如：智能手表或智能眼镜等，以及只专注于某一类应用功能，需要和其它设备如智能手机配合使用，如各类进行体征监测的智能手环、智能头盔、智能首饰等。
终端还可以是无人机、机器人、设备到设备通信(device-to-device，D2D)中的终端、车到一切(vehicle to everything，V2X)中的终端、虚拟现实(virtual reality，VR)终端设备、增强现实(augmented reality，AR)终端设备、工业控制(industrial control)中的无线终端、无人驾驶(self driving)中的无线终端、远程医疗(remote medical)中的无线终端、智能电网(smart grid)中的无线终端、运输安全(transportation safety)中的无线终端、智慧城市(smart city)中的无线终端、智慧家庭(smart home)中的无线终端等。
此外，终端设备也可以是第五代(5th generation，5G)通信系统之后演进的未来通信系统中的终端设备或者未来演进的公共陆地移动网络(public land mobile network，PLMN)中的终端设备等。示例性的，未来通信网络可以进一步扩展5G通信终端的形态和功能，未来通信网络的终端包括但不限于车、蜂窝网络终端(融合卫星终端功能)、无人机、物联网(internet of things，IoT)设备。
在本申请实施例中，上述终端设备还可以获得网络设备提供的AI服务。可选地，终端设备还可以具有AI处理能力。
(2)网络设备：可以是无线网络中的设备，例如网络设备可以为将终端设备接入到无线网络的RAN节点(或设备)，又可以称为基站。目前，一些RAN设备的举例为：基站(base station)、演进型基站(evolved NodeB，eNodeB)、5G通信系统中的基站gNB(gNodeB)、传输接收点(transmission reception point，TRP)、演进型节点B(evolved Node B，eNB)、无线网络控制器(radio network controller，RNC)、节点B(Node B，NB)、家庭基站(例如，home evolved Node B，或home Node B，HNB)、基带单元(base band unit，BBU)，或无线保真(wireless fidelity，Wi-Fi)接入点AP等。另外，在一种网络结构中，网络设备可以包括集中单元(centralized unit，CU)节点、或分布单元(distributed unit，DU)节点、或包括CU节点和DU节点的RAN设备。
可选的，RAN节点还可以是宏基站、微基站或室内站、中继节点或施主节点、或者是云无线接入网络(cloud radio access network，CRAN)场景下的无线控制器。RAN节点还可以是服务器，可穿戴设备，车辆或车载设备等。例如，车辆外联(vehicle to everything，V2X)技术中的接入网设备可以为路侧单元(road side unit，RSU)。
在另一种可能的场景中，由多个RAN节点协作协助终端实现无线接入，不同RAN节点分别实现基站的部分功能。例如，RAN节点可以是集中式单元(central unit，CU)，分布式单元(distributed unit，DU)，CU-控制面(control plane，CP)，CU-用户面(user plane，UP)，或者无线单元(radio unit，RU)等。CU和DU可以是单独设置，或者也可以包括在同一个网元中，例如基带单元(baseband unit，BBU)中。RU可以包括在射频设备或者射频单元中，例如包括在射频拉远单元(remote radio unit，RRU)、有源天线处理单元(active antenna unit，AAU)或远程射频头(remote radio head，RRH)中。
在不同系统中，CU(或CU-CP和CU-UP)、DU或RU也可以有不同的名称，但是本领域的技术人员可以理解其含义。例如，在开放式接入网(open RAN，O-RAN或ORAN)系统中，CU也可以称为O-CU(开放式CU)，DU也可以称为O-DU，CU-CP也可以称为O-CU-CP，CU-UP也可以称为O-CU-UP，RU也可以称为O-RU。为描述方便，本申请中以CU，CU-CP，CU-UP、DU和RU为例进行描述。本申请中的CU(或CU-CP、CU-UP)、DU和RU中的任一单元，可以是通过软件模块、硬件模块、或者软件模块与硬件模块结合来实现。
接入网设备和终端设备之间的通信遵循一定的协议层结构。该协议层可以包括控制面协议层和用户面协议层。控制面协议层可以包括以下至少一项：无线资源控制(radio resource control，RRC)层、分组数据汇聚层协议(packet data convergence protocol，PDCP)层、无线链路控制(radio link control，RLC)层、媒体接入控制(media access control，MAC)层、或物理(physical，PHY)层等。用户面协议层可以包括以下至少一项：业务数据适配协议(service data adaptation protocol，SDAP)层、PDCP层、RLC层、MAC层、或物理层等。
对于ORAN系统中的网元及其可实现的协议层功能对应关系，可参照下表1。
表1
网络设备可以是其它为终端设备提供无线通信功能的装置。本申请的实施例对网络设备所采用的具体技术和具体设备形态不做限定。为方便描述，本申请实施例并不限定。
网络设备还可以包括核心网设备，核心网设备例如包括第四代(4th generation，4G)网络中的移动性管理实体(mobility management entity，MME)，归属用户服务器(home subscriber server，HSS)，服务网关(serving gateway，S-GW)，策略和计费规则功能(policy and charging rules function，PCRF)，公共数据网网关(public data network gateway，PDN gateway，P-GW)；5G网络中的访问和移动管理功能(access and mobility management function，AMF)、用户面功能(user plane function，UPF)或会话管理功能(session management function，SMF)等网元。此外，该核心网设备还可以包括5G网络以及5G网络的下一代网络中的其他核心网设备。
本申请实施例中，上述网络设备还可以具有AI能力的网络节点，可以为终端或其他网络设备提供AI服务，例如，可以为网络侧(接入网或核心网)的AI节点、算力节点、具有AI能力的RAN节点、具有AI能力的核心网网元等。
本申请实施例中，用于实现网络设备的功能的装置可以是网络设备，也可以是能够支持网络设备实现该功能的装置，例如芯片系统，该装置可以被安装在网络设备中。在本申请实施例提供的技术方案中，以用于实现网络设备的功能的装置是网络设备为例，描述本申请实施例提供的技术方案。
(3)配置与预配置：在本申请中，会同时用到配置与预配置。其中，配置是指网络设备和/或服务器通过消息或信令将一些参数的配置信息或参数的取值发送给终端，以便终端根据这些取值或信息来确定通信的参数或传输时的资源。预配置与配置类似，可以是网络设备和/或服务器预先与终端设备协商好的参数信息或参数值，也可以是标准协议规定的基站/网络设备或终端设备采用的参数信息或参数值，还可以是预先存储在基站和/或服务器或终端设备的参数信息或参数值。本申请对此不做限定。
进一步地，这些取值和参数，是可以变化或更新的。
(4)本申请实施例中的术语“系统”和“网络”可被互换使用。“多个”是指两个或两个以上。“和/或”，描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A、同时存在A和B、单独存在B的情况，其中A，B可以是单数或者复数。字符“/”一般表示前后关联对象是一种“或”的关系。“以下至少一项(个)”或其类似表达，是指的这些项中的任意组合，包括单项(个)或复数项(个)的任意组合。例如“A，B和C中的至少一项”包括A，B，C，AB，AC，BC或ABC。以及，除非有特别说明，本申请实施例提及“第一”、“第二”等序数词是用于对多个对象进行区分，不用于限定多个对象的顺序、时序、优先级或者重要程度。
(5)本申请实施例中的“发送”和“接收”，表示信号传递的走向。例如，“向XX发送信息”可以理解为该信息的目的端是XX，可以包括通过空口直接发送，也包括其他单元或模块通过空口间接发送。“接收来自YY的信息”可以理解为该信息的源端是YY，可以包括通过空口直接从YY接收，也可以包括通过空口从其他单元或模块间接地从YY接收。“发送”也可以理解为芯片接口的“输出”，“接收”也可以理解为芯片接口的“输入”。
换言之，发送和接收可以是在设备之间进行的，例如，网络设备和终端设备之间进行的，也可以是在设备内进行的，例如，通过总线、走线或接口在设备内的部件之间、模组之间、芯片之间、软件模块或者硬件模块之间发送或接收。
可以理解的是，信息在信息发送的源端和目的端之间可能会被进行必要的处理，比如编码、调制等，但目的端可以理解来自源端的有效信息。本申请中类似的表述可以做相似的理解，不再赘述。
(6)在本申请实施例中，“指示”可以包括直接指示和间接指示，也可以包括显式指示和隐式指示。将某一信息(如下文所述的指示信息)所指示的信息称为待指示信息，则具体实现过程中，对待指示信息进行指示的方式有很多种，例如但不限于，可以直接指示待指示信息，如待指示信息本身或者该待指示信息的索引等。也可以通过指示其他信息来间接指示待指示信息，其中该其他信息与待指示信息之间存在关联关系；还可以仅仅指示待指示信息的一部分，而待指示信息的其他部分则是已知的或者提前约定的，例如可以借助预先约定(例如协议预定义)的各个信息的排列顺序来实现对特定信息的指示，从而在一定程度上降低指示开销。本申请对于指示的具体方式不作限定。可以理解的是，对于该指示信息的发送方来说，该指示信息可用于指示待指示信息，对于指示信息的接收方来说，该指示信息可用于确定待指示信息。
本申请中，除特殊说明外，各个实施例之间相同或相似的部分可以互相参考。在本申请中各个实施例、以及各实施例中的各个方法/设计/实现方式中，如果没有特殊说明以及逻辑冲突，不同的实施例之间、以及各实施例中的各个方法/设计/实现方式之间的术语和/或描述具有一致性、且可以相互引用，不同的实施例、以及各实施例中的各个方法/设计/实现方式中的技术特征根据其内在的逻辑关系可以组合形成新的实施例、方法、或实现方式。以下所述的本申请实施方式并不构成对本申请保护范围的限定。
本申请可以应用于长期演进(long term evolution，LTE)系统、新无线(new radio，NR)系统，或者是5G之后演进的未来通信系统。其中，该通信系统中包括至少一个网络设备和/或至少一个终端设备。
请参阅图1a，为本申请中通信系统的一种示意图。图1a中，示例性的示出了一个网络设备和6个终端设备，6个终端设备分别为终端设备1、终端设备2、终端设备3、终端设备4、终端设备5以及终端设备6等。在图1a所示的示例中，是以终端设备1为智能茶杯，终端设备2为智能空调，终端设备3为智能加油机，终端设备4为交通工具，终端设备5为手机，终端设备6为打印机进行举例说明的。
如图1a所示，AI配置信息发送实体可以为网络设备。AI配置信息接收实体可以为终端设备1-终端设备6，此时，网络设备和终端设备1-终端设备6组成一个通信系统，在该通信系统中，终端设备1-终端设备6可以发送数据给网络设备，网络设备需要接收终端设备1-终端设备6发送的数据。同时，网络设备可以向终端设备1-终端设备6发送配置信息。
示例性的，在图1a中，终端设备4-终端设备6也可以组成一个通信系统。其中，终端设备5作为网络设备，即AI配置信息发送实体；终端设备4和终端设备6作为终端设备，即AI配置信息接收实体。例如车联网系统中，终端设备5分别向终端设备4和终端设备6发送AI配置信息，并且接收终端设备4和终端设备6发送的数据；相应的，终端设备4和终端设备6接收终端设备5发送的AI配置信息，并向终端设备5发送数据。
以图1a所示通信系统为例，不同的设备之间(包括网络设备与网络设备之间，网络设备与终端设备之间，和/或，终端设备和终端设备之间)除了执行通信相关业务之外，还有可能执行AI相关业务。
如图1b所示，以网络设备为基站为例，基站可以与一个或多个终端设备之间可以执行通信相关业务和AI相关业务，不同终端设备之间也可以执行通信相关业务和AI相关业务。
如图1c所示，以终端设备包括电视和手机为例，电视和手机之间也可以执行通信相关业务和AI相关业务。
本申请提供的技术方案可以应用于无线通信系统(例如图1a、图1b或图1c所示系统)，例如本申请提供的通信系统中可以引入AI网元来实现部分或全部AI相关的操作。AI网元也可以称为AI节点、AI设备、AI实体、AI模块、AI模型、或AI单元等。所述AI网元可以是内置在通信系统的网元中。例如，AI网元可以是内置在：接入网设备、核心网设备、云服务器、或网管(operation,administration and maintenance，OAM)中的AI模块，用以实现AI相关的功能。所述OAM可以是作为核心网设备网管和/或作为接入网设备的网管。或者，所述AI网元也可以是通信系统中独立设置的网元。可选的，终端或终端内置的芯片中也可以包括AI实体，用于实现AI相关的功能。
可选的，在通信系统中，可能涉及AI应用案例(use case)包括但不限于：信道状态信息(channel status information，CSI)反馈增强(CSI feedback enhancement)、波束管理增强(beam management enhancement)、定位增强(positioning accuracy enhancement)、网络节能(network energy saving)、负载均衡(load balancing)、移动性优化(mobility optimization)。下面分别说明。
1、CSI反馈增强
CSI是通信链路的信道属性，是终端设备上报给网络设备的信道质量信息，终端设备通过将信道质量信息上报给网络设备，以便为终端设备选择合适的调制与编码策略(modulation and coding scheme，MCS)，从而可以适应变换的无线信道。例如终端设备根据接收的信道状态信息参考信号(channel state information-reference signal，CSI-RS)做信道估计，然后反馈信道质量信息给网络设备，该信息作为网络设备的模型的输入，以使网络设备实现AI模型训练。通过将AI应用到CSI反馈增强，可以减少开销、提高精度以及实现预测等。
CSI-RS反馈增强可以包括至少一个子功能，比如分别为：CSI压缩，CSI预测，CSI-RS配置信令减少。其中，CSI压缩又可以分为在空域、时域和频域至少一种域上的CSI压缩。
2、波束管理增强
BM主要是要发现最强的发射/接收波束对(beam pair)。基于AI的稀疏波束预测，可以提升准确度。根据AI训练和推理，可以分为网络侧的AI稀疏波束预测和终端设备侧的AI稀疏波束预测。以终端设备侧的AI稀疏波束预测为例，终端设备侧的预先训练好的AI模型可以是网络侧下发的，也可以是终端设备侧预先存储的。在训练阶段，网络设备扫描所有可能的波束，然后网络上报需要将发射波束图样告诉终端设备。当模型训练完成时，网络只需要扫描一小部分波束，随后终端设备反馈推理结果给网络。基于AI的波束管理，可以实现例如时间和/或空间域中的波束预测，以减少开销和延迟，提高波束选择精度。
波束管理增强可以包括至少一个子功能，比如分别为：波束扫描矩阵预测、最优波束预测。
3、定位增强
在视线传输(line of sight，LOS)或非视线传输(not line of sight，NLOS)的场景中，基于AI的定位，可以在较少数量的TRP天线下改进定位准确度。定位增强可以包括至少一个子功能，比如分别为：基于接入网设备的定位增强、基于定位管理功能网元的定位增强、基于终端设备的定位增强。
4、网络节能
网络节能可以通过小区激活/去激活(cell activation/deactivation)、减少负载、改进覆盖或者其它RAN设置调整。AI技术可用于通过利用在RAN网络中收集的数据来优化节能决策。AI算法可以预测下一个周期的能效和负载状态，这可以用于辅助决策小区激活/去激活，以节省能源。基于预测的负载，系统可以动态配置节能策略，以保持系统性能和能效之间的平衡，并降低能耗。
5、负载均衡
负载均衡可以使得负载在小区之间和小区内各区域之间均匀分布，或将部分流量从拥塞小区转移，或让用户在一个小区、载波或接入制式上进行分流，以提高网络性能。基于AI模型来提高负载均衡性能，如将终端设备和网络节点的各种测量和反馈、历史数据等输入AI模型来提高负载均衡性能，可以提供更高质量的用户体验，提高系统容量。
6、移动性管理
移动性管理是通过最大限度地减少掉话、无线链路失败(radio link failure，RLF)、不必要的切换和乒乓效应来保证终端设备移动期间业务连续性的方案。基于AI可以增强移动性管理，例如降低意外事件发生的概率、进行终端设备位置/移动性/性能预测以及流量引导等。
应理解，上述各个技术术语的定义仅为举例。例如随着技术的不断发展，上述定义的范围也有可能发生变化，本申请各实施例不作限制。
示例性的，一个AI功能可以包括多个AI子功能。
可选的，AI应用案例也称为AI应用场景或AI功能。
从上述对AI应用案例的描述可知，AI可以广泛用于CSI反馈增强、波束管理、定位精度增强、节能、移动性增强以及负载均衡等方面以提升网络性能。AI模型通常可以部署于网络侧和/或终端设备侧，AI模型的训练依赖于训练数据的收集，训练数据可以来源于终端设备的测量和反馈。
下面将本申请中可能涉及到的人工智能(artificial intelligence，AI)进行简要介绍。
人工智能(artificial intelligence，AI)，可以让机器具有人类的智能，例如可以让机器应用计算机的软硬件来模拟人类某些智能行为。为了实现人工智能，可以采用机器学习方法。机器学习方法中，机器利用训练数据学习(或训练)得到模型。该模型表征了从输入到输出之间的映射。学习得到的模型可以用于进行推理(或预测)，即可以利用该模型预测出给定输入所对应的输出。其中，该输出还可以称为推理结果(或预测结果)。
机器学习可以包括监督学习、无监督学习、和强化学习。其中，无监督学习还可以称为非监督学习。
监督学习依据已采集到的样本值和样本标签，利用机器学习算法学习样本值到样本标签的映射关系，并用AI模型来表达学到的映射关系。训练机器学习模型的过程就是学习这种映射关系的过程。在训练过程中，将样本值输入模型得到模型的预测值，通过计算模型的预测值与样本标签(理想值)之间的误差来优化模型参数。映射关系学习完成后，就可以利用学到的映射来预测新的样本标签。监督学习学到的映射关系可以包括线性映射或非线性映射。根据标签的类型可将学习的任务分为分类任务和回归任务。
无监督学习依据采集到的样本值，利用算法自行发掘样本的内在模式。无监督学习中有一类算法将样本自身作为监督信号，即模型学习从样本到样本的映射关系，称为自监督学习。训练时，通过计算模型的预测值与样本本身之间的误差来优化模型参数。自监督学习可用于信号压缩及解压恢复的应用，常见的算法包括自编码器和对抗生成型网络等。
强化学习不同于监督学习，是一类通过与环境进行交互来学习解决问题的策略的算法。与监督、无监督学习不同，强化学习问题并没有明确的“正确的”动作标签数据，算法需要与环境进行交互，获取环境反馈的奖励信号，进而调整决策动作以获得更大的奖励信号数值。如下行功率控制中，强化学习模型根据无线网络反馈的系统总吞吐率，调整各个用户的下行发送功率，进而期望获得更高的系统吞吐率。强化学习的目标也是学习环境状态与较优(例如最优)决策动作之间的映射关系。但因为无法事先获得“正确动作”的标签，所以不能通过计算动作与“正确动作”之间的误差来优化网络。强化学习的训练是通过与环境的迭代交互而实现的。
神经网络(neural network,NN)是机器学习技术中的一种具体的模型。根据通用近似定理，神经网络在理论上可以逼近任意连续函数，从而使得神经网络具备学习任意映射的能力。传统的通信系统需要借助丰富的专家知识来设计通信模块，而基于神经网络的深度学习通信系统可以从大量的数据集中自动发现隐含的模式结构，建立数据之间的映射关系，获得优于传统建模方法的性能。
神经网络的思想来源于大脑组织的神经元结构。例如，每个神经元都对其输入值进行加权求和运算，通过一个激活函数输出运算结果。
如图2a所示，为神经元结构的一种示意图。假设神经元的输入为x＝[x0,x1,…,xn]，与各个输入对应的权值分别为w＝[w0,w1,…,wn]，其中，n为正整数，wi和xi可以是小数、整数(例如0、正整数或负整数等)、或复数等各种可能的类型。wi作为xi的权值，用于对xi进行加权。根据权值对输入值进行加权求和的偏置例如为b。激活函数的形式可以有多种，假设一个神经元的激活函数为：y＝f(z)＝max(0,z)，则该神经元的输出为：再例如，一个神经元的激活函数为：y＝f(z)＝z，则该神经元的输出为： 其中，b可以是小数、整数(例如0、正整数或负整数)、或复数等各种可能的类型。神经网络中不同神经元的激活函数可以相同或不同。
此外，神经网络一般包括多个层，每层可包括一个或多个神经元。通过增加神经网络的深度和/或宽度，能够提高该神经网络的表达能力，为复杂系统提供更强大的信息提取和抽象建模能力。其中，神经网络的深度可以是指神经网络包括的层数，每层包括的神经元个数可以称为该层的宽度。在一种实现方式中，神经网络包括输入层和输出层。神经网络的输入层将接收到的输入信息经过神经元处理，将处理结果传递给输出层，由输出层得到神经网络的输出结果。在另一种实现方式中，神经网络包括输入层、隐藏层和输出层。神经网络的输入层将接收到的输入信息经过神经元处理，将处理结果传递给中间的隐藏层，隐藏层对接收的处理结果进行计算，得到计算结果，隐藏层将计算结果传递给输出层或者下一个相邻的隐藏层，最终由输出层得到神经网络的输出结果。其中，一个神经网络可以包括一个隐藏层，或者包括多个依次连接的隐藏层，不予限制。
神经网络例如为深度神经网络(deep neural network,DNN)。根据网络的构建方式，DNN可以包括前馈神经网络(feedforward neural network,FNN)、卷积神经网络(convolutional neural networks,CNN)和递归神经网络(recurrent neural network,RNN)。
图2b为一种FNN网络示意图。FNN网络的特点为相邻层的神经元之间两两完全相连。该特点使得FNN通常需要大量的存储空间、导致较高的计算复杂度。
CNN是一种专门来处理具有类似网格结构的数据的神经网络。例如，时间序列数据(时间轴离散采样)和图像数据(二维离散采样)都可以认为是类似网格结构的数据。CNN并不一次性利用全部的输入信息做运算，而是采用一个固定大小的窗截取部分信息做卷积运算，这就大大降低了模型参数的计算量。另外根据窗截取的信息类型的不同(如同一副图中的人和物为不同类型信息)，每个窗可以采用不同的卷积核运算，这使得CNN能更好的提取输入数据的特征。
RNN是一类利用反馈时间序列信息的DNN网络。它的输入包括当前时刻的新的输入值和自身在前一时刻的输出值。RNN适合获取在时间上具有相关性的序列特征，特别适用于语音识别、信道编译码等应用。
在上述机器学习的模型训练过程中，可以定义损失函数。损失函数描述了模型的输出值和理想目标值之间的差距或差异。损失函数可以通过多种形式体现，对于损失函数的具体形式不予限制。模型训练过程可以看作以下过程：通过调整模型的部分或全部参数，使得损失函数的值小于门限值或者满足目标需求。
模型还可以被称为AI模型、规则或者其他名称等。AI模型可以认为是实现AI功能的具体方法。AI模型表征了模型的输入和输出之间的映射关系或者函数。AI功能可以包括以下一项或多项：数据收集、模型训练(或模型学习)、模型信息发布、模型推断(或称为模型推理、推理、或预测等)、模型监控或模型校验、或推理结果发布等。AI功能还可以称为AI(相关的)操作、或AI相关的功能。
下面将结合附图，对全连接神经网络的实现过程进行示例性描述。其中，全连接神经网络,又叫多层感知机(multi layer perceptron，MLP)。
如图2c所示，一个MLP包含一个输入层(左侧)，一个输出层(右侧)，及多个隐藏层(中间)。其中，MLP的每层包含若干个节点，称为神经元。其中,相邻两层的神经元间两两相连。
可选的，考虑相邻两层的神经元，下一层的神经元的输出h为所有与之相连的上一层神经元x的加权和并经过激活函数，可以表示为：
h＝f(wx+b)。
其中，w为权重矩阵，b为偏置向量，f为激活函数。
进一步可选的，神经网络的输出可以递归表达为：
y＝fn(wnfn-1(…)+bn)。
其中,n是神经网络层的索引，1<＝n<＝N,其中N为神经网络的总层数。
换言之，可以将神经网络理解为一个从输入数据集合到输出数据集合的映射关系。而通常神经网络都是随机初始化的，用已有数据从随机的w和b得到这个映射关系的过程被称为神经网络的训练。
可选的，训练的具体方式为采用损失函数(loss function)对神经网络的输出结果进行评价。
如图2d所示，可以将误差反向传播，通过梯度下降的方法即能迭代优化神经网络参数(包括w和b)，直到损失函数达到最小值，即图2d中的“较优点(例如最优点)”。可以理解的是，图2d中的“较优点(例如最优点)”对应的神经网络参数可以作为训练好的AI模型信息中的神经网络参数。
进一步可选的，梯度下降的过程可以表示为：
其中，θ为待优化参数(包括w和b)，L为损失函数，η为学习率，控制梯度下降的步长，表示求导运算，表示对L求θ的导数。
进一步可选的，反向传播的过程利用到求偏导的链式法则。
如图2e所示，前一层参数的梯度可以由后一层参数的梯度递推计算得到，可以表达为：
其中，wij为节点j连接节点i的权重，si为节点i上的输入加权和。
本申请提供的技术方案可以应用于无线通信系统(例如图1a或图1b或图1c所示系统)，在无线通信系统中，通信节点一般具备信号收发能力和计算能力。目前，通信设备可以作为AI系统的参与节点，将该通信设备的算力应用于AI系统的某一个环节。一般来说，在通信网络中引入的AI功能，需要依赖模型来实现。然而，在上述过程中，如何对模型进行模型管理，当前尚未有相关方案能够解决。
为了解决上述问题，本申请提供了一种通信方法及相关装置，下面将结合附图进行详细描述。
请参阅图3，为本申请提供的通信方法的一个实现示意图，该方法包括如下步骤。
需要说明的是，在下文中，图3至图5中以第一通信装置和其它通信装置(例如第二通信装置、或第三通信装置等)作为该交互示意的执行主体为例来示意该方法，但本申请并不限制该交互示意的执行主体。例如，通信装置可以为通信设备，或者，通信设备中的芯片、基带(baseband)芯片、调制解调(modem)芯片、包含modem核的片上系统(system on chip,SoC)芯片、系统级封装(system in package，SIP)芯片、通信模组、芯片系统、处理器、逻辑模块或软件等。可选的，该通信设备可以为终端设备或网络设备(例如接入网设备、接入网网元、核心网网元、或核心网设备等)。
S301.第一通信装置获取第一信息。其中，该第一信息指示终端设备的第一状态信息。
需要说明的是，以第一信息指示终端设备A的第一状态信息为例。第一通信装置可以为该终端设备A或该终端设备A的内部模块，或者，该第一通信装置可以为不同于该终端设备A的其它设备(例如网络设备，或者另一个终端设备B)。
S302.第一通信装置基于该第一状态信息确定是否启用该终端设备的AI功能。
在步骤S302之后，第一通信装置可以执行步骤S303或S304。
S303.第一通信装置接收或发送第二信息，该第二信息指示启用该终端设备的AI功能的情况下对AI模型的第一处理，该AI模型关联于该终端设备的AI功能。
S304.第一通信装置接收或发送第三信息，该第三信息指示不启用该终端设备的AI功能的情况下对该AI模型的第二处理。
本申请中，AI功能可以替换为其它术语，例如AI使能的功能、AI能力、或AI使能的特性等。
本申请中，启用可以替换为其它术语，例如启动、开启、不关闭、不禁止、或使能等。相应的，不启用可以替换为其它术语，例如不启动、不开启、关闭、禁止或不使能等。
应理解，第一处理可以指示在启用该终端设备的AI功能的情况下，对AI模型的模型管理。例如，该第一处理可以包括模型更新、模型切换、模型微调、或模型精调中的一项或多项。
应理解，第二处理可以指示在不启用该终端设备的AI功能的情况下，对AI模型的模型管理。例如，该第二处理可以包括模型启用的触发条件的判断、数据收集(例如收集得到的数据可以用于后续启用AI模型之后的模型处理)中的一项或多项。
可选的，第一状态信息(或者后文的第二状态信息)指示以下至少一项：该终端设备采集的数据的数据特征、该终端设备的通信参数、该终端设备的AI功能关联的AI模型的模型性能、或、该终端设备的计算资源。
在一种可能的实现方式中，在步骤S302中，第一通信装置基于该第一状态信息确定是否启用该终端设备的AI功能包括：在该第一状态信息满足第一条件的情况下，该第一通信装置确定启用该终端设备的AI功能。具体地，第一通信装置可以判断第一状态信息是否满足第一条件，并在满足第一条件的情况下，该第一通信装置确定启用该终端设备的AI功能。
可选的，图3所示方法还包括：该第一通信装置接收第四信息，该第四信息指示该第一条件。从而，第一通信装置可以通过接收的第四信息确定第一条件，使得该第一通信装置可以基于其它通信装置指定的第一条件实现是否启用终端设备的AI功能的判断过程。
可选的，该第一条件为预配置的。
在一种可能的实现方式中，在步骤S302中，第一通信装置基于该第一状态信息确定是否启用该终端设备的AI功能包括：在该第一状态信息满足第二条件的情况下，该第一通信装置确定不启用该终端设备的AI功能。具体地，第一通信装置可以判断第一状态信息是否满足第二条件，并在满足第二条件的情况下，该第一通信装置确定不启用该终端设备的AI功能。
可选的，图3所示方法还包括：该第一通信装置接收第五信息，该第五信息指示该第二条件。从而，第一通信装置可以通过接收的第五信息确定第一条件，使得该第一通信装置可以基于其它通信装置指定的第二条件实现是否启用终端设备的AI功能的判断过程。
可选的，该第二条件为预配置的。
基于图3所示方案，第一通信装置可以通过第一信息获取终端设备的第一状态信息，并基于该第一状态信息确定是否启用该终端设备的AI功能。此后，在确定启用该终端设备的AI功能的情况下，该第一通信装置可以接收或发送指示该情况下对AI模型进行第一处理的第二信息。或，在确定不启用该终端设备的AI功能的情况下，该第一通信装置可以接收或发送指示该情况下对AI模型进行第二处理的第三信息。通过这种方式，第二信息的接收方能够基于该第二信息在启用AI模型的情况下对AI模型进行模型管理(或，第三信息的接收方能够基于该第三信息在不启用AI模型的情况下对AI模型进行模型管理)，以实现对AI模型的模型管理。
此外，在上述方案中，第一通信装置基于该第一状态信息确定是否启用该终端设备的AI功能，换言之，用于确定是否启用该终端设备的AI功能的确定依据包括终端设备的第一状态信息。通过这种方式，能够使得终端设备的AI功能与该终端设备的状态信息相匹配。例如，启用AI功能可以获得AI功能带来的增益；相应的，不启用AI功能可以节省终端设备的能耗和/或算力等开销；为此，在第一通信装置基于第一状态信息确定启用该终端设备的AI功能的情况下，可以利用AI功能带来的增益，提升任务处理效率；在第一通信装置基于第一状态信息确定不启用该终端设备的AI功能的情况下，可以节省终端设备的开销。
需要说明的是，在图3所示过程中，第一通信装置有可能在步骤S303中接收第二信息(或第一通信装置有可能在步骤S304中接收第三信息)，也有可能在步骤S303中发送第二信息(或第一通信装置有可能在步骤S304中发送第三信息)，下面将结合一些实现示例进行描述。
实现示例一，第一通信装置为第二信息或第三信息的接收方。
在实现示例一中，在步骤S302中，第一通信装置确定启用(或不启用)终端设备的AI功能之后，该第一通信装置可以发送确定结果，使得该确定结果的接收方在步骤S303中向第一通信装置发送第二信息(或在步骤S304中向第一通信装置发送第三信息)。下面将以该确定结果的接收方为第二通信装置为例，结合图4所示示例进行描述。
如图4所示，相比于图3所示方法，在步骤S302之后，该方法还包括：
步骤A.第一通信装置发送第七信息，相应的，第二通信装置接收该第七信息。其中，该第七信息指示是否启用该终端设备的AI功能，该第七信息是基于该第一状态信息确定的。
从而，第一通信装置在步骤S302中基于第一状态信息确定是否启用终端设备的AI功能之后，该第一通信装置可以发送第七信息，使得该第七信息的接收方能够基于该第七信息确定是否启用终端设备的AI功能，并基于该第七信息与该终端设备进行通信(例如传输用于AI功能的数据/信号/信息/信令等，或传输用于其它功能的数据/信号/信息/信令等)。
示例性的，以第一信息指示终端设备A的第一状态信息为例。在实现示例一中，第一通信装置可以为该终端设备A或该终端设备A的内部模块，使得第一通信装置能够在步骤S301中获得自身所对应的终端设备的状态信息，并在步骤S302中基于该状态信息确定是否启用终端设备的AI功能之后，通过第七信息向第二通信装置指示该确定结果，使得该第二通信装置能够向该第一通信装置提供第二信息或第三信息，以便于该第一通信装置能够基于该第二信息执行相应的第一处理(或以便于该第一通信装置能够基于该第三信息执行相应的第二处理)。
实现示例二，第一通信装置为第二信息或第三信息的发送方(或提供方)。
在实现示例一中，在步骤S302中，第一通信装置确定启用(或不启用)终端设备的AI功能之后，该第一通信装置可以基于该确定结果在步骤S303中向第三通信装置发送第二信息(或在步骤S304中向第三通信装置发送第三信息)。下面将以该第二信息或第三信息的接收方为第二通信装置为例，结合图5所示示例进行描述。
如图5所示，相比于图3所示方法，在步骤S301中，第一通信装置获取第一信息的过程，包括：该第一通信装置接收该第一信息。具体地，第一信息可以指示终端设备的第一状态信息，该终端设备可以为图5中的第三通信装置，第一通信装置可以是不同于第三通信装置的其它终端设备或网络设备，为此，该第一通信装置可以接收第一信息，以通过该第一信息确定终端设备的第一状态信息。
示例性的，以第一信息指示终端设备A的第一状态信息，且第三通信装置为终端设备A或终端设备A中的模块为例。在实现示例一中，第一通信装置可以为不同于终端设备A的其它设备(例如终端设备B或网络设备)，使得第一通信装置能够在步骤S301中获得终端设备的状态信息，并在步骤S302中基于该状态信息确定是否启用终端设备的AI功能之后，向第三通信装置提供第二信息或第三信息，以便于该第三通信装置能够基于该第二信息执行相应的第一处理(或以便于该第三通信装置能够基于该第三信息执行相应的第二处理)。
在一种可能的实现方式中，步骤S303和步骤S304中传输的第二信息和第三信息可以通过多种方式实现，下面将通过一些可能的实现方式进行描述。
方式一、第二信息包括第一处理相关联的时间信息。
在方式一中，第一通信装置在步骤S303中接收或发送的第二信息包括以下任一项：
第一指示信息，指示用于该第一处理的第一时间信息；
该第一指示信息和第二指示信息，该第二指示信息指示第二时间信息；其中，在该第一时间信息指示的时长不足以完成该第一处理的情况下，该第二时间信息用于该第一处理(该第二指示信息可以理解为延长或重配第一时间信息)；
该第一指示信息和第三指示信息，指示将该第一时间信息指示的第一时间间隔更新为第二时间间隔；其中，该第二时间间隔的起始时间单元为该第三指示信息的接收时间单元或发送时间单元，该第三指示信息的接收时间单元或发送时间单元位于该第一时间间隔内。
具体地，第二信息可以通过上述多种方式实现，以提升方案实现的灵活性，并且，使得第二信息的接收方可以基于上述至少一项对AI模型进行第一处理。
此外，通过第二指示信息的指示，可以延长第一指示信息所指示的第一时间信息，能够为第一处理提供充足的处理时间，以提升该第一处理的处理成功率。
此外，通过第二指示信息和/或第三指示信息的指示，能够使得第一处理对应的时间不局限于第一指示信息所指示的第一时间信息，以提高AI模型执行任务的连续性，可以降低任务时延。
可选的，在方式一中，该第一处理为周期性的处理，该第二信息还包括以下第四指示信息至第七指示信息中的至少一项。
第四指示信息，指示是否启用该第一时间信息，或，指示是否在与当前时刻最近的周期启用该第一时间信息。通过第四指示信息，能够使得该第二信息的发送方能够灵活地配置是否启用第一时间信息。可选的，对于第二信息的接收方而言，第一时间信息指示的时间间隔内可以是默认不执行第一处理的，在该接收方接收到第四指示信息且第四指示信息指示启用第一时间信息(或指示在与当前时刻最近的周期启用该第一时间信息)的情况下，该接收方基于该第一时间信息指示的时间间隔内执行第一处理。
第五指示信息，指示第一阈值；其中，在未接收到或未发送该第四指示信息的周期次数大于或等于该第一阈值的情况下，触发将该第一时间信息指示的第一时间间隔更新为第三时间间隔，该第三时间间隔大于该第一时间间隔。通过第五指示信息，如果经历多个周期仍未收到第四指示信息对应的启用指示的情况下，说明终端设备的AI功能关联的模型的性能可能比较高，为此，第二信息的接收端(可选的，还包括第二信息的发送端)可以将第一时间信息对应的周期延长，以通过较低频率的第一处理实现对模型进行模型管理，有利于提高AI模型执行任务的连续性，可以降低任务时延。
第六指示信息，指示第二阈值；其中，在第一定时器指示的时长内，接收到的或发送的该第四指示信息的周期次数大于或等于该第二阈值，且该接收到的或发送的该第四指示信息指示启用的情况下，触发将该第一时间信息指示的第一时间间隔更新为第四时间间隔，该第四时间间隔小于该第一时间间隔。通过第五指示信息，如果经历多个周期持续收到较多的第四指示信息对应的启用的指示的情况下，说明终端设备的AI功能关联的模型可用但是该模型的性能可能比较低，则第二信息的接收端(可选的，还包括第二信息的发送端)可以将第一时间信息对应的周期缩短，以通过更频繁的第二处理实现对模型进行模型管理，有利于对模型性能的持续监测以识别出模型失败或性能较低等事件，以满足模型管理的需求，保证AI功能的性能。
第七指示信息，指示第三阈值；其中，在第二定时器指示的时长内，接收到的或发送的该第四指示信息的周期次数大于或等于该第三阈值，且该接收到的或发送的该第三指示信息指示不启用的情况下，触发该第一处理。通过第七指示信息，如果经历多个周期持续收到较多的第四指示信息对应的不启用的指示的情况下，说明终端设备的AI功能当前关联的模型可能出现问题，为此，第二信息的接收端(可选的，还包括第二信息的发送端)可以触发该第一处理(例如AI功能回退、模型切换、模型失效事件记录等)，以满足模型管理的需求，保证AI功能的性能。
方式二、第二信息包括第一处理相关联的其它信息。
在方式二中，第一通信装置在步骤S303中接收或发送的第二信息包括以下至少一项：
第八指示信息，指示关闭该终端设备的AI功能；
第九指示信息，指示对该AI模型关联的部分或全部数据进行缓存；
第十指示信息，指示在关闭该终端设备的AI功能之后，重新启用该终端设备的AI功能所需的缓存数据。
具体地，第二信息可以通过上述多种方式实现，以提升方案实现的灵活性，并且，第二信息的接收方可以基于上述至少一项对AI模型进行模型管理。
方式三、第三信息包括第二处理相关联的其它信息。
在方式三中，第一通信装置在步骤S304中接收或发送的第三信息包括第三时间信息。相应的，图3所示方法还包括：在该第三时间信息指示的时间单元或该第三时间信息指示的时间单元之后，该第一通信装置获取第五信息，该第五信息指示终端设备的第二状态信息；该第一通信装置基于该第二状态信息确定是否启用该终端设备的AI功能。具体地，在第一通信装置基于第一状态信息确定不启用该终端设备的AI功能的情况下，该第一通信装置接收或发送的第三信息可以包括第三时间信息，使得该第三信息的接收方能够基于该第三时间信息获取终端设备的第二状态信息，并基于该第二状态信息进一步判断是否启用该终端设备的AI功能，能够再次尝试启动AI功能，以期在确定启动AI功能的情况下获得AI功能带来的增益，提升任务处理效率。
类似地，如图5所示实现过程，在上述方式三中，第一通信装置获取第五信息的过程，包括：该第一通信装置接收该第五信息。
可选的，第一通信装置基于第二状态信息确定是否启用该终端设备的AI功能之后，该方法还包括：该第一通信装置发送第六信息，该第六信息指示是否启用该终端设备的AI功能，该第六信息是基于该第二状态信息确定的。具体地，第一通信装置在基于第二状态信息确定是否启用终端设备的AI功能之后，该第一通信装置可以发送第六信息，使得该第六信息的接收方能够基于该第六信息确定是否启用终端设备的AI功能，并基于该第六信息与该终端设备进行通信(例如传输用于AI功能的数据/信号/信息/信令等，或传输用于其它功能的数据/信号/信息/信令等)。
请参阅图6，本申请实施例提供了一种通信装置600，该通信装置600可以实现上述方法实施例中第二通信装置或第一通信装置的功能，因此也能实现上述方法实施例所具备的有益效果。在本申请实施例中，该通信装置600可以是第一通信装置(或第二通信装置或第三通信装置)，也可以是第一通信装置(或第二通信装置或第三通信装置)内部的集成电路或者元件等，例如芯片。
需要说明的是，收发单元602可以包括发送单元和接收单元，分别用于执行发送和接收。
一种可能的实现方式中，当该装置600为用于执行前述实施例中第一通信装置所执行的方法时，该装置600包括处理单元601和收发单元602；该处理单元601用于获取第一信息，该第一信息指示终端设备的第一状态信息；该处理单元601还用于基于该第一状态信息确定是否启用该终端设备的AI功能；该收发单元602用于接收或发送第二信息，该第二信息指示启用该终端设备的AI功能的情况下对AI模型的第一处理，该AI模型关联于该终端设备的AI功能；或，该收发单元602用于接收或发送第三信息，该第三信息指示不启用该终端设备的AI功能的情况下对该AI模型的第二处理。
一种可能的实现方式中，当该装置600为用于执行前述实施例中第二通信装置所执行的方法时，该装置600包括处理单元601和收发单元602；该收发单元602用于接收第七信息，该第七信息指示是否启用终端设备的AI功能；其中，该第七信息是基于该终端设备的第一状态信息确定的；该处理单元601用于确定第二信息或第三信息；该收发单元602还用于发送第二信息或第三信息，该第二信息指示启用该终端设备的AI功能的情况下对AI模型的第一处理，该第三信息指示不启用该终端设备的AI功能的情况下对该AI模型的第二处理，该AI模型关联于该终端设备的AI功能。
一种可能的实现方式中，当该装置600为用于执行前述实施例中第三通信装置所执行的方法时，该装置600包括处理单元601和收发单元602；该处理单元601用于确定第一信息；该收发单元602用于发送第一信息，该第一信息指示终端设备的第一状态信息；该第一状态信息用于确定是否启用该终端设备的AI功能；该收发单元602还用于接收第二信息或第三信息，该第二信息指示启用该终端设备的AI功能的情况下对AI模型的第一处理，该第三信息指示不启用该终端设备的AI功能的情况下对该AI模型的第二处理，该AI模型关联于该终端设备的AI功能。
需要说明的是，上述通信装置600的单元的信息执行过程等内容，具体可参见本申请前述所示的方法实施例中的叙述，此处不再赘述。
请参阅图7，为本申请提供的通信装置700的另一种示意性结构图，通信装置700包括逻辑电路701和输入输出接口702。其中，通信装置700可以为芯片或集成电路。
其中，图6所示收发单元602可以为通信接口，该通信接口可以是图7中的输入输出接口702，该输入输出接口702可以包括输入接口和输出接口。或者，该通信接口也可以是收发电路，该收发电路可以包括输入接口电路和输出接口电路。
可选的，逻辑电路701用于获取第一信息，该第一信息指示终端设备的第一状态信息；该逻辑电路701还用于基于该第一状态信息确定是否启用该终端设备的AI功能；该输入输出接口702用于接收或发送第二信息，该第二信息指示启用该终端设备的AI功能的情况下对AI模型的第一处理，该AI模型关联于该终端设备的AI功能；或，该输入输出接口702用于接收或发送第三信息，该第三信息指示不启用该终端设备的AI功能的情况下对该AI模型的第二处理。
可选地，输入输出接口702用于接收第七信息，该第七信息指示是否启用终端设备的AI功能；其中，该第七信息是基于该终端设备的第一状态信息确定的；该逻辑电路701用于确定第二信息或第三信息；该输入输出接口702还用于发送第二信息或第三信息，该第二信息指示启用该终端设备的AI功能的情况下对AI模型的第一处理，该第三信息指示不启用该终端设备的AI功能的情况下对该AI模型的第二处理，该AI模型关联于该终端设备的AI功能。
可选的，逻辑电路701用于确定第一信息；该输入输出接口702用于发送第一信息，该第一信息指示终端设备的第一状态信息；该第一状态信息用于确定是否启用该终端设备的AI功能；该输入输出接口702还用于接收第二信息或第三信息，该第二信息指示启用该终端设备的AI功能的情况下对AI模型的第一处理，该第三信息指示不启用该终端设备的AI功能的情况下对该AI模型的第二处理，该AI模型关联于该终端设备的AI功能。
其中，逻辑电路701和输入输出接口702还可以执行任一实施例中第一通信装置或第二通信装置或第三通信装置执行的其他步骤并实现对应的有益效果，此处不再赘述。
在一种可能的实现方式中，图6所示处理单元601可以为图7中的逻辑电路701。
可选的，逻辑电路701可以是一个处理装置，处理装置的功能可以部分或全部通过软件实现。其中，处理装置的功能可以部分或全部通过软件实现。
可选的，处理装置可以包括存储器和处理器，其中，存储器用于存储计算机程序，处理器读取并执行存储器中存储的计算机程序，以执行任意一个方法实施例中的相应处理和/或步骤。
可选地，处理装置可以仅包括处理器。用于存储计算机程序的存储器位于处理装置之外，处理器通过电路/电线与存储器连接，以读取并执行存储器中存储的计算机程序。其中，存储器和处理器可以集成在一起，或者也可以是物理上互相独立的。
可选地，该处理装置可以是一个或多个芯片，或一个或多个集成电路。例如，处理装置可以是一个或多个现场可编程门阵列(field-programmable gate array，FPGA)、专用集成芯片(application specific integrated circuit，ASIC)、系统芯片(system on chip，SoC)、中央处理器(central processor unit，CPU)、网络处理器(network processor，NP)、数字信号处理电路(digital signal processor，DSP)、微控制器(micro controller unit，MCU)，可编程控制器(programmable logic device，PLD)或其它集成芯片，或者上述芯片或者处理器的任意组合等。
请参阅图8，为本申请的实施例提供的上述实施例中所涉及的通信装置800，该通信装置800具体可以为上述实施例中的作为终端设备的通信装置，图8所示示例的通信装置通过终端设备(或者终端设备中的部件)实现。
其中，该通信装置800的一种可能的逻辑结构示意图，该通信装置800可以包括但不限于至少一个处理器801以及通信端口802。
其中，图6所示收发单元602可以为通信接口，该通信接口可以是图8中的通信端口802，该通信端口802可以包括输入接口和输出接口。或者，该通信端口802也可以是收发电路，该收发电路可以包括输入接口电路和输出接口电路。
进一步可选的，该装置还可以包括存储器803、总线804中的至少一个，在本申请的实施例中，该至少一个处理器801用于对通信装置800的动作进行控制处理。
此外，处理器801可以是中央处理器单元，通用处理器，数字信号处理器，专用集成电路，现场可编程门阵列或者其他可编程逻辑器件、晶体管逻辑器件、硬件部件或者其任意组合。其可以实现或执行结合本申请公开内容所描述的各种示例性的逻辑方框，模块和电路。该处理器也可以是实现计算功能的组合，例如包含一个或多个微处理器组合，数字信号处理器和微处理器的组合等等。所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统，装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
需要说明的是，图8所示通信装置800具体可以用于实现前述方法实施例中终端设备所实现的步骤，并实现终端设备对应的技术效果，图9所示通信装置的具体实现方式，均可以参考前述方法实施例中的叙述，此处不再一一赘述。
请参阅图9，为本申请的实施例提供的上述实施例中所涉及的通信装置900的结构示意图，该通信装置900具体可以为上述实施例中的作为网络设备的通信装置，图9所示示例的通信装置通过网络设备(或者网络设备中的部件)实现，其中，该通信装置的结构可以参考图9所示的结构。
通信装置900包括至少一个处理器911以及至少一个网络接口914。进一步可选的，该通信装置还包括至少一个存储器912、至少一个收发器913和一个或多个天线915。处理器911、存储器912、收发器913和网络接口914相连，例如通过总线相连，在本申请实施例中，该连接可包括各类接口、传输线或总线等，本实施例对此不做限定。天线915与收发器913相连。网络接口914用于使得通信装置通过通信链路，与其它通信设备通信。例如网络接口914可以包括通信装置与核心网设备之间的网络接口，例如S1接口，网络接口可以包括通信装置和其他通信装置(例如其他网络设备或者核心网设备)之间的网络接口，例如X2或者Xn接口。
其中，图6所示收发单元602可以为通信接口，该通信接口可以是图9中的网络接口914，该网络接口914可以包括输入接口和输出接口。或者，该网络接口914也可以是收发电路，该收发电路可以包括输入接口电路和输出接口电路。
处理器911主要用于对通信协议以及通信数据进行处理，以及对整个通信装置进行控制，执行软件程序，处理软件程序的数据，例如用于支持通信装置执行实施例中所描述的动作。通信装置可以包括基带处理器和中央处理器，基带处理器主要用于对通信协议以及通信数据进行处理，中央处理器主要用于对整个终端设备进行控制，执行软件程序，处理软件程序的数据。图9中的处理器911可以集成基带处理器和中央处理器的功能，本领域技术人员可以理解，基带处理器和中央处理器也可以是各自独立的处理器，通过总线等技术互联。本领域技术人员可以理解，终端设备可以包括多个基带处理器以适应不同的网络制式，终端设备可以包括多个中央处理器以增强其处理能力，终端设备的各个部件可以通过各种总线连接。该基带处理器也可以表述为基带处理电路或者基带处理芯片。该中央处理器也可以表述为中央处理电路或者中央处理芯片。对通信协议以及通信数据进行处理的功能可以内置在处理器中，也可以以软件程序的形式存储在存储器中，由处理器执行软件程序以实现基带处理功能。
存储器主要用于存储软件程序和数据。存储器912可以是独立存在，与处理器911相连。可选的，存储器912可以和处理器911集成在一起，例如集成在一个芯片之内。其中，存储器912能够存储执行本申请实施例的技术方案的程序代码，并由处理器911来控制执行，被执行的各类计算机程序代码也可被视为是处理器911的驱动程序。
图9仅示出了一个存储器和一个处理器。在实际的终端设备中，可以存在多个处理器和多个存储器。存储器也可以称为存储介质或者存储设备等。存储器可以为与处理器处于同一芯片上的存储元件，即片内存储元件，或者为独立的存储元件，本申请实施例对此不做限定。
收发器913可以用于支持通信装置与终端之间射频信号的接收或者发送，收发器913可以与天线915相连。收发器913包括发射机Tx和接收机Rx。具体地，一个或多个天线915可以接收射频信号，该收发器913的接收机Rx用于从天线接收该射频信号，并将射频信号转换为数字基带信号或数字中频信号，并将该数字基带信号或数字中频信号提供给该处理器911，以便处理器911对该数字基带信号或数字中频信号做进一步的处理，例如解调处理和译码处理。此外，收发器913中的发射机Tx还用于从处理器911接收经过调制的数字基带信号或数字中频信号，并将该经过调制的数字基带信号或数字中频信号转换为射频信号，并通过一个或多个天线915发送该射频信号。具体地，接收机Rx可以选择性地对射频信号进行一级或多级下混频处理和模数转换处理以得到数字基带信号或数字中频信号，该下混频处理和模数转换处理的先后顺序是可调整的。发射机Tx可以选择性地对经过调制的数字基带信号或数字中频信号时进行一级或多级上混频处理和数模转换处理以得到射频信号，该上混频处理和数模转换处理的先后顺序是可调整的。数字基带信号和数字中频信号可以统称为数字信号。
收发器913也可以称为收发单元、收发机、收发装置等。可选的，可以将收发单元中用于实现接收功能的器件视为接收单元，将收发单元中用于实现发送功能的器件视为发送单元，即收发单元包括接收单元和发送单元，接收单元也可以称为接收机、输入口、接收电路等，发送单元可以称为发射机、发射器或者发射电路等。
需要说明的是，图9所示通信装置900具体可以用于实现前述方法实施例中网络设备所实现的步骤，并实现网络设备对应的技术效果，图9所示通信装置900的具体实现方式，均可以参考前述方法实施例中的叙述，此处不再一一赘述。
请参阅图10，为本申请的实施例提供的上述实施例中所涉及的通信装置的结构示意图。
可以理解的是，通信装置100包括例如模块、单元、元件、电路、或接口等，以适当地配置在一起以执行本申请提供的技术方案。所述通信装置100可以是前文描述的终端设备或网络设备，也可以是这些设备中的部件(例如芯片)，用以实现下述方法实施例中描述的方法。通信装置100包括一个或多个处理器101。所述处理器101可以是通用处理器或者专用处理器等。例如可以是基带处理器、或中央处理器。基带处理器可以用于对通信协议以及通信数据进行处理，中央处理器可以用于对通信装置(如，RAN节点、终端、或芯片等)进行控制，执行软件程序，处理软件程序的数据。
可选的，在一种设计中，处理器101可以包括程序103(有时也可以称为代码或指令)，所述程序103可以在所述处理器101上被运行，使得所述通信装置100执行下述实施例中描述的方法。在又一种可能的设计中，通信装置100包括电路(图10未示出)。
可选的，所述通信装置100中可以包括一个或多个存储器102，其上存有程序104(有时也可以称为代码或指令)，所述程序104可在所述处理器101上被运行，使得所述通信装置100执行上述方法实施例中描述的方法。
可选的，所述处理器101和/或存储器102中可以包括AI模块107,108，所述AI模块用于实现AI相关的功能。所述AI模块可以是通过软件，硬件，或软硬结合的方式实现。例如，AI模块可以包括无线智能控制(radio intelligence control，RIC)模块。例如AI模块可以是近实时RIC或者非实时RIC。
可选的，所述处理器101和/或存储器102中还可以存储有数据。所述处理器和存储器可以单独设置，也可以集成在一起。
可选的，所述通信装置100还可以包括收发器105和/或天线106。所述处理器101有时也可以称为处理单元，对通信装置(例如RAN节点或终端)进行控制。所述收发器105有时也可以称为收发单元、收发机、收发电路、或者收发器等，用于通过天线106实现通信装置的收发功能。
其中，图6所示处理单元601可以是处理器101。图6所示收发单元602可以为通信接口，该通信接口可以是图10中的收发器105，该收发器105可以包括输入接口和输出接口。或者，该收发器105也可以是收发电路，该收发电路可以包括输入接口电路和输出接口电路。
本申请实施例还提供一种计算机可读存储介质，该存储介质用于存储一个或多个计算机执行指令，当计算机执行指令被处理器执行时，该处理器执行如前述实施例中第一通信装置或第二通信装置或第三通信装置可能的实现方式所述的方法。
本申请实施例还提供一种计算机程序产品(或称计算机程序)，当计算机程序产品被该处理器执行时，该处理器执行上述第一通信装置或第二通信装置或第三通信装置可能实现方式的方法。
本申请实施例还提供了一种芯片系统，该芯片系统包括至少一个处理器，用于支持通信装置实现上述通信装置可能的实现方式中所涉及的功能。可选的，所述芯片系统还包括接口电路，所述接口电路为所述至少一个处理器提供程序指令和/或数据。在一种可能的设计中，该芯片系统还可以包括存储器，存储器，用于保存该通信装置必要的程序指令和数据。该芯片系统，可以由芯片构成，也可以包含芯片和其他分立器件，其中，该通信装置具体可以为前述方法实施例中第一通信装置或第二通信装置或第三通信装置。
本申请实施例还提供了一种通信系统，该系统包括上述任一实施例中的第一通信装置和第二通信装置，或，该系统包括上述任一实施例中的第一通信装置和第三通信装置。
在本申请所提供的几个实施例中，应该理解到，所揭露的系统，装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。

Claims (27)

  1. 一种通信方法，其特征在于，包括：
    获取第一信息，所述第一信息指示终端设备的第一状态信息；
    基于所述第一状态信息确定是否启用所述终端设备的人工智能AI功能；
    接收或发送第二信息，所述第二信息指示启用所述终端设备的AI功能的情况下对AI模型的第一处理，所述AI模型关联于所述终端设备的AI功能；或，
    接收或发送第三信息，所述第三信息指示不启用所述终端设备的AI功能的情况下对所述AI模型的第二处理。
  2. 根据权利要求1所述的方法，其特征在于，所述基于所述第一状态信息确定是否启用所述终端设备的AI功能包括：
    在所述第一状态信息满足第一条件的情况下，确定启用所述终端设备的AI功能。
  3. 根据权利要求2所述的方法，其特征在于，所述方法还包括：
    接收第四信息，所述第四信息指示所述第一条件。
  4. 根据权利要求1所述的方法，其特征在于，所述基于所述第一状态信息确定是否启用所述终端设备的AI功能包括：
    在所述第一状态信息满足第二条件的情况下，确定不启用所述终端设备的AI功能。
  5. 根据权利要求4所述的方法，其特征在于，所述方法还包括：
    接收第五信息，所述第五信息指示所述第二条件。
  6. 根据权利要求1至5任一项所述的方法，其特征在于，所述第三信息包括第三时间信息；所述方法还包括：
    在所述第三时间信息指示的时间单元或所述第三时间信息指示的时间单元之后，获取第五信息，所述第五信息指示终端设备的第二状态信息；
    基于所述第二状态信息确定是否启用所述终端设备的AI功能。
  7. 根据权利要求6所述的方法，其特征在于，所述方法还包括：
    发送第六信息，所述第六信息指示是否启用所述终端设备的AI功能，所述第六信息是基于所述第二状态信息确定的。
  8. 根据权利要求1至7任一项所述的方法，其特征在于，所述获取第一信息，包括：
    接收所述第一信息。
  9. 根据权利要求1至8任一项所述的方法，其特征在于，所述方法还包括：
    发送第七信息，所述第七信息指示是否启用所述终端设备的AI功能，所述第七信息是基于所述第一状态信息确定的。
  10. 一种通信方法，其特征在于，包括：
    接收第七信息，所述第七信息指示是否启用终端设备的AI功能；其中，所述第七信息是基于所述终端设备的第一状态信息确定的；
    发送第二信息或第三信息，所述第二信息指示启用所述终端设备的AI功能的情况下对AI模型的第一处理，所述第三信息指示不启用所述终端设备的AI功能的情况下对所述AI模型的第二处理，所述AI模型关联于所述终端设备的AI功能。
  11. 根据权利要求10所述的方法，其特征在于，所述方法还包括：
    发送第四信息，所述第四信息指示第一条件；其中，在所述第一状态信息满足所述第一条件的情况下，启用所述终端设备的AI功能。
  12. 根据权利要求10或11所述的方法，其特征在于，所述方法还包括：
    发送第五信息，所述第五信息指示所述第二条件；其中，在所述第一状态信息满足所述第二条件的情况下，不启用所述终端设备的AI功能。
  13. 根据权利要求10至12任一项所述的方法，其特征在于，所述第三信息包括第三时间信息；
    其中，在所述第三时间信息指示的时间单元或所述第三时间信息指示的时间单元之后，第一通信装置获取的终端设备的第二状态信息用于确定是否启用所述终端设备的AI功能。
  14. 根据权利要求13所述的方法，其特征在于，所述方法还包括：
    接收第六信息，所述第六信息指示是否启用所述终端设备的AI功能，所述第六信息是基于所述第二状态信息确定的。
  15. 一种通信方法，其特征在于，包括：
    发送第一信息，所述第一信息指示终端设备的第一状态信息；所述第一状态信息用于确定是否启用所述终端设备的AI功能；
    接收第二信息或第三信息，所述第二信息指示启用所述终端设备的AI功能的情况下对AI模型的第一处理，所述第三信息指示不启用所述终端设备的AI功能的情况下对所述AI模型的第二处理，所述AI模型关联于所述终端设备的AI功能。
  16. 根据权利要求15所述的方法，其特征在于，所述方法还包括：
    接收第七信息，所述第七信息指示是否启用终端设备的AI功能；其中，所述第七信息是基于所述终端设备的第一状态信息确定的。
  17. 根据权利要求15或16所述的方法，其特征在于，所述第三信息包括第三时间信息；所述方法还包括：
    在所述第三时间信息指示的时间单元或所述第三时间信息指示的时间单元之后，发送第五信息；其中，所述第五信息指示终端设备的第二状态信息，所述第二状态信息确定是否启用所述终端设备的AI功能。
  18. 根据权利要求17所述的方法，其特征在于，所述方法还包括：
    接收第六信息，所述第六信息指示是否启用所述终端设备的AI功能，所述第六信息是基于所述第二状态信息确定的。
  19. 根据权利要求1至18任一项所述的方法，其特征在于，所述第二信息包括以下任一项：
    第一指示信息，指示用于所述第一处理的第一时间信息；
    所述第一指示信息和第二指示信息，所述第二指示信息指示第二时间信息；其中，在所述第一时间信息指示的时长不足以完成所述第一处理的情况下，所述第二时间信息用于所述第一处理；
    所述第一指示信息和第三指示信息，指示将所述第一时间信息指示的第一时间间隔更新为第二时间间隔；其中，所述第二时间间隔的起始时间单元为所述第三指示信息的接收时间单元或发送时间单元，所述第三指示信息的接收时间单元或发送时间单元位于所述第一时间间隔内。
  20. 根据权利要求19所述的方法，其特征在于，所述第一处理为周期性的处理，所述第二信息还包括以下至少一项：
    第四指示信息，指示是否启用所述第一时间信息，或，指示是否在与当前时刻最近的周期启用所述第一时间信息；
    第五指示信息，指示第一阈值；其中，在未接收到或未发送所述第四指示信息的周期次数大于或等于所述第一阈值的情况下，触发将所述第一时间信息指示的第一时间间隔更新为第三时间间隔，所述第三时间间隔大于所述第一时间间隔；
    第六指示信息，指示第二阈值；其中，在第一定时器指示的时长内，接收到的或发送的所述第四指示信息的周期次数大于或等于所述第二阈值，且所述接收到的或发送的所述第四指示信息指示启用的情况下，触发将所述第一时间信息指示的第一时间间隔更新为第四时间间隔，所述第四时间间隔小于所述第一时间间隔；
    第七指示信息，指示第三阈值；其中，在第二定时器指示的时长内，接收到的或发送的所述第四指示信息的周期次数大于或等于所述第三阈值，且所述接收到的或发送的所述第三指示信息指示不启用的情况下，触发所述第一处理。
  21. 根据权利要求1至20任一项所述的方法，其特征在于，所述第二信息包括以下至少一项：
    第八指示信息，指示关闭所述终端设备的AI功能；
    第九指示信息，指示对所述AI模型关联的部分或全部数据进行缓存；
    第十指示信息，指示在关闭所述终端设备的AI功能之后，重新启用所述终端设备的AI功能所需的缓存数据。
  22. 根据权利要求1至21任一项所述的方法，其特征在于，所述第一状态信息指示以下至少一项：
    所述终端设备采集的数据的数据特征、所述终端设备的通信参数、所述终端设备的AI功能关联的AI模型的模型性能、或、所述终端设备的计算资源。
  23. 一种通信装置，其特征在于，包括用于执行如权利要求1至22任一项所述的方法的模块。
  24. 一种通信装置，其特征在于，包括至少一个处理器，所述至少一个处理器用于执行如权利要求1至22中任一项所述的方法。
  25. 根据权利要求24所述的通信装置，其特征在于，所述通信装置为芯片或芯片系统。
  26. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质中存储有计算机程序或指令，当所述计算机程序或指令被通信装置执行时，实现如权利要求1至22中任一项所述的方法。
  27. 一种计算机程序产品，其特征在于，包括计算机程序或指令，当所述计算机程序或指令被计算机执行时，实现如权利要求1至22中任一项所述的方法。
PCT/CN2025/094170 2024-06-21 2025-05-12 一种通信方法及相关装置 Pending WO2025261007A1 (zh)

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