Communication method and related device

Abstract

The present application provides a communication method and a related device, used to, by means of an artificial intelligence (AI) task identifier, determine access information of an AI task in first information, such that a terminal device can, on the basis of the access information of the AI task, subsequently access the AI task; thus, a computing capability of the terminal device can be used for the AI task, so as to implement execution of the AI task in a communication network. In the present method, the terminal device receives first information, the first information indicating access information of the AI task, and the first information being obtained by performing processing of the access information of the AI task by means of an AI task identifier; and the terminal device, on the basis of the AI task identifier and the first information, determines access information of the AI task.

Description

A communication method and related equipment Technical Field

[0001] The present application relates to the field of communications, and in particular to a communication method and related equipment. Background Art

[0002] Wireless communication refers to the transmission of information between multiple communication nodes without the use of conductors or cables. Generally, network devices and terminal devices can act as different communication nodes and communicate based on wireless communication.

[0003] Currently, in wireless communication systems, communication nodes generally possess both signal transceiver and computing capabilities. For example, network devices with computing capabilities primarily provide computing power to support signal transceiver capabilities (for example, calculating the time and frequency domain resources required to carry the signal), enabling communication between the network device and other communication nodes.

[0004] However, in communication networks, communication nodes may have excess computing power beyond just supporting the aforementioned communication tasks. Therefore, how to utilize this computing power is a pressing technical issue.

[0005] Summary of the Invention

[0006] The present application provides a communication method and related equipment for obtaining access information of an artificial intelligence (AI) task in the first information through the identifier of the AI ​​task, so that the terminal device can subsequently access the AI ​​task based on the access information of the AI ​​task, thereby enabling the computing power of the terminal device to be used for the AI ​​task, in order to realize the execution of the AI ​​task in the communication network.

[0007] The first aspect of the present application provides a communication method, which is executed by a terminal device, or the method is executed by some components in the terminal device (such as a processor, chip or chip system, etc.), or the method can also be implemented by a logic module or software that can realize all or part of the terminal device functions. In the first aspect and its possible implementation, the method is described as being executed by a terminal device. In this method, the terminal device receives first information, which indicates access information of an AI task, and the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task; the terminal device determines the access information of the AI ​​task based on the identifier of the AI ​​task and the first information.

[0008] Based on the above technical solution, after a terminal device receives first information indicating access information for an AI task, the terminal device can determine the access information for the AI ​​task based on the identifier of the AI ​​task, wherein the first information is obtained by processing the access information for the AI ​​task using the identifier of the AI ​​task. In other words, when a network device indicates access information for an AI task via the first information, the terminal device can obtain the access information for the AI ​​task from the first information using the identifier of the AI ​​task, allowing the terminal device to subsequently access the AI ​​task based on the access information for the AI ​​task, thereby enabling the terminal device's computing power to be used for the AI ​​task, thereby enabling the execution of the AI ​​task within the communication network.

[0009] Furthermore, the first information sent by the network device is processed using the AI ​​task identifier. After receiving the first information, the terminal device can obtain the access information for the AI ​​task using the AI ​​task identifier. Thus, when the number of terminal devices is greater than one, different terminal devices can all obtain the access information for the AI ​​task using the AI ​​task identifier, reducing implementation complexity and improving efficiency.

[0010] Optionally, the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task, including: the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task and not through the identifier of the terminal device, or, the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task and the identifier of the terminal device; in comparison, since the former scheme does not require the identifier of the terminal device to participate in the processing of the access information, the processing of the access information can be achieved through the identifier of the AI ​​task, so that different terminal devices (or users) can obtain the access information of the AI ​​task through the identifier of the AI ​​task, and the privacy of the terminal device (or user) can be protected.

[0011] It should be understood that the first information can be the identifier of the AI ​​task obtained by processing the access information of the AI ​​task in various ways. For example, the processing can include at least one of scrambling, encryption, and encapsulation (or data packaging). In other words, the terminal device can determine the access information of the AI ​​task based on the identifier of the AI ​​task and the first information in various ways, such as at least one of descrambling, decryption, and decapsulation (or data unpacking).

[0012] In an implementation example, the processing may be scrambling processing. Accordingly, after receiving the first information, the terminal device may descramble the first information according to the identifier of the AI ​​task to obtain the access information of the AI ​​task. In other words, the network device may scramble different information (the different information may include the first information) using different identifiers. After receiving the different information, the terminal device descrambles the different information based on the different identifiers. In the process of descrambling the different information based on the different identifiers, the terminal device descrambles the first information based on the identifier of the AI ​​task to obtain the access information of the AI ​​task.

[0013] In another implementation example, the processing may be an encryption processing. Accordingly, after receiving the first information, the terminal device may decrypt the first information based on the identifier of the AI ​​task to obtain the access information of the AI ​​task. In other words, the network device may encrypt different information (the different information may include the first information) using different identifiers. After receiving the different information, the terminal device decrypts the different information based on the different identifiers. In the process of decrypting the different information based on the different identifiers, the terminal device decrypts the first information based on the identifier of the AI ​​task to obtain the access information of the AI ​​task.

[0014] In another implementation example, the processing may be an encapsulation process (or data packaging process). Accordingly, after receiving the first information, the terminal device may perform decapsulation processing (or data unpacking processing) on ​​the first information to obtain the data carried by the first information. The terminal device then determines the access information of the AI ​​task based on the identifier of the AI ​​task in the decapsulated data. In other words, the network device may encapsulate different information (the different information may include the first information) through different identifiers. After receiving the different information, the terminal device decapsulates the different information to obtain the decapsulated data. The terminal device then determines the access information of the AI ​​task based on the identifier of the AI ​​task in the decapsulated data.

[0015] It should be understood that the access information of the AI ​​task can be understood as information used to access the AI ​​task, that is, after the terminal device determines the access information of the AI ​​task, the terminal device can access the AI ​​task based on the access information of the AI ​​task.

[0016] It should be understood that the AI ​​task involved in this application may be a task that requires the participation of two or more communication nodes in processing, and the communication nodes include terminal devices and / or network devices. For example, the AI ​​task may include a federated learning (FL) task, a distributed training task, a distributed learning task, etc. Among them, the terminal device accessing the AI ​​task can be understood as the terminal device participating in the calculation process of the AI ​​task. In other words, a calculation result of the AI ​​task (including intermediate calculation results and / or final calculation results) is obtained by processing the calculation results of the terminal device and the calculation results of other communication nodes that may exist (for example, arithmetic average processing, weighted average processing, etc.). And / or, the terminal device accessing the AI ​​task can also be understood as the terminal device participating in the transmission process of the calculation result of the AI ​​task. In other words, a calculation result of the AI ​​task (including intermediate calculation results and / or final calculation results) is transmitted through the terminal device.

[0017] Optionally, the identifier of the AI ​​task is a radio network temporary identity (RNTI) associated with the AI ​​task, so that the terminal device can clearly identify the AI ​​task corresponding to the first information (or the access information indicated by the first information) based on the RNTI. For example, the first information mentioned above can be physical downlink control channel (PDCCH) data that has been scrambled by the radio network temporary identity (RNTI).

[0018] Optionally, the identifier of the AI ​​task is the RNTI associated with the AI ​​task, which can be understood as: the identifier of the AI ​​task is the RNTI of the AI ​​task, or the identifier of the AI ​​task is the RNTI used to transmit the business data of the AI ​​task, or the identifier of the AI ​​task is an RNTI dedicated to the AI ​​task, or the identifier of the AI ​​task is a specific RNTI of the AI ​​task, or the identifier of the AI ​​task is generated based on the task identifier (identity, ID) of the AI ​​task.

[0019] Optionally, the identifier of the AI ​​task is not bound to a specific terminal device and / or a specific transmission channel, so that different terminal devices and / or different transmission channels can use the same AI task identifier to receive and / or send business data of the same AI task. Compared with the implementation method of configuring different identifiers for different terminal devices and / or different transmission channels, it can simplify the configuration and save signaling overhead. Moreover, since the identifier does not need to be associated with a specific terminal device (and / or since the identifier does not need to be associated with a specific transmission channel), privacy leakage can be avoided to protect the privacy of the terminal device (or user).

[0020] In a possible implementation of the first aspect, the access information of the AI ​​task includes at least one of the following:

[0021] Information indicating the access conditions of the AI ​​task; information indicating the information update period of the AI ​​task; information indicating the training period of the AI ​​task; information indicating the uplink resource configuration of the service data of the AI ​​task; information indicating the downlink resource configuration of the service data of the AI ​​task; information indicating the codebook of the service data of the AI ​​task; information indicating the transmission mode of the service data of the AI ​​task; information indicating the uplink transmission parameters of the service data of the AI ​​task; information indicating the downlink transmission parameters of the service data of the AI ​​task.

[0022] Based on the above technical solution, in the access information of the AI ​​task indicated by the first information, the access information of the AI ​​task includes at least one of the above items, so that the recipient of the first information obtains various types of access information related to the AI ​​task through at least one item, thereby improving the flexibility of the implementation of the solution.

[0023] In a possible implementation of the first aspect, the information indicating the access condition of the AI ​​task includes at least one of the following:

[0024] The identification range of terminal devices that access the AI ​​task; the random number threshold for accessing the AI ​​task; the performance indicator threshold for accessing the AI ​​task; the start time for accessing the AI ​​task; and the end time for accessing the AI ​​task.

[0025] Based on the above technical solution, in the access information of the AI ​​task indicated by the first information, the information used to indicate the access conditions of the AI ​​task may include at least one of the above items, so that the network device can flexibly configure the access conditions of the AI ​​task and improve the flexibility of the implementation of the solution.

[0026] In a possible implementation of the first aspect, a transmission mode of the business data of the AI ​​task includes any one of the following:

[0027] A first transmission mode, wherein the first transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing using an identifier of the AI ​​task on service data of the AI ​​task; wherein transmission resources of at least two terminal devices in the first transmission mode are orthogonal;

[0028] A second transmission mode, where the second transmission mode indicates performing at least one of a third-order quantization modulation process, a pre-equalization superposition transmission process, and a coding modulation process based on a public codebook on the service data of the AI ​​task;

[0029] A third transmission mode, wherein the third transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing on the business data of the AI ​​task through the identifier of the AI ​​task; wherein the transmission resources of at least two terminal devices in the third transmission mode are the same.

[0030] Based on the above technical solution, in the access information of the AI ​​task indicated by the first information, the transmission mode of the business data of the indicated AI task includes at least one of the above items, so that the network device can flexibly configure the transmission mode of the business data of the AI ​​task and improve the flexibility of the implementation of the solution.

[0031] In a possible implementation of the first aspect, the uplink transmission configuration parameter and / or the downlink transmission configuration parameter include at least one of the following: a modulation and coding scheme (MCS), a hybrid automatic repeat request (HARQ) version, a power control and quantization modulation order, and a transmission power threshold.

[0032] Based on the above technical solution, in the access information of the AI ​​task indicated by the first information, the indicated transmission configuration parameters include at least one of the above items, so that the network device can flexibly configure the transmission configuration parameters of the AI ​​task and improve the flexibility of the solution implementation.

[0033] In a possible implementation of the first aspect, after the terminal device determines the access information of the AI ​​task based on the identifier of the AI ​​task and the first information, the method further includes: the terminal device sending local business data corresponding to the AI ​​task based on the access information of the AI ​​task; and the terminal device receiving fused business data corresponding to the AI ​​task.

[0034] Based on the above technical solution, after the terminal device determines the access information of the AI ​​task according to the identifier of the AI ​​task, the terminal device can receive and send business data related to the AI ​​task based on the access information of the AI ​​task, so that the terminal device can access (or participate in) the AI ​​task.

[0035] In a possible implementation manner of the first aspect, the method further includes: the terminal device sending indication information indicating confirmation of receiving the converged service data.

[0036] Based on the above technical solution, after the terminal device receives the integrated business data corresponding to the AI ​​task, the terminal device can also send indication information to confirm the reception of the integrated business data, so that the network device can determine whether the terminal device has successfully received it based on the indication information, which is conducive to the subsequent scheduling of one or more terminal devices participating in the AI ​​task based on the indication information.

[0037] In a possible implementation of the first aspect, before the terminal device sends the local business data corresponding to the AI ​​task based on the access information, the method also includes: the terminal device sends indication information indicating that the local training of the AI ​​task has been completed; and the terminal device receives indication information indicating that the local business data is sent.

[0038] Based on the above technical solution, through the interaction of indication information indicating that the local training of the AI ​​task has been completed and indication information indicating that local business data has been sent, the network device can clearly understand the execution status of the local training of the terminal device and implement scheduling of the terminal device based on the execution status.

[0039] In addition, through the above-mentioned interaction process, when the network device clearly knows that the number of terminal devices that have completed local training is greater than or equal to a threshold, the network device can schedule the terminal devices to send local business data to ensure that the number of terminal devices accessing the AI ​​task meets the requirements of the threshold.

[0040] In a possible implementation of the first aspect, before the terminal device receives the first information, the method further includes: the terminal device receives indication information instructing to report capability information for participating in the AI ​​task; the terminal device sends second information, where the second information indicates communication capability information and / or AI capability information; wherein the communication capability information includes at least one of channel information and communication frequency information; and the AI ​​capability information includes at least one of AI model performance, AI parameters, AI gradient variance, and AI data set size.

[0041] Based on the above technical solution, after the terminal device receives the indication information instructing it to report the capability information for participating in the AI ​​task, the terminal device may also send second information indicating communication capability information and / or AI capability information, so that the network device can clarify the capability information of the terminal device for participating in the AI ​​task based on the second information, and determine the access information of the AI ​​task based on the capability information of one or more terminal devices, so as to schedule it through the first information indicating the access information of the AI ​​task.

[0042] In a possible implementation of the first aspect, before the terminal device receives the first information, the method further includes: the terminal device receives third information, the third information indicating the release information of the AI ​​task, and the third information is obtained by processing the release information through the identifier of the AI ​​task; the terminal device sends fourth information, the fourth information is used to indicate registration to the AI ​​task, and the fourth information includes at least one of the following: AI capability information of the terminal device, and the identifier of the terminal device.

[0043] Based on the above technical solution, the terminal device can also receive third information indicating the release information of the AI ​​task, and the third information is obtained by processing the release information through the identifier of the AI ​​task, so that the terminal device can obtain the release information based on the identifier of the AI ​​task, and then send fourth information to the network device to indicate registration to the AI ​​task. The release process and registration process of the AI ​​task are realized through the interaction of the above third information and fourth information.

[0044] In a possible implementation manner of the first aspect, the published information includes at least one of the following: an identifier of the AI ​​task, a public codebook reported by the user information, and indication information of transmission resources.

[0045] Based on the above technical solution, the published information received by the terminal device may include at least one of the above items, so that the terminal device can obtain relevant information of the AI ​​task based on the at least one item, and send fourth information based on this information to implement the registration process of the AI ​​task.

[0046] In a possible implementation manner of the first aspect, the method further includes: the terminal device receiving indication information indicating confirmation of receiving the fourth information.

[0047] Based on the above technical solution, the terminal device can also receive indication information indicating confirmation of receiving the fourth information, so that the terminal device can determine whether the network device has successfully received the fourth information based on the indication information, and further determine whether the terminal device has successfully registered to the AI ​​task.

[0048] The second aspect of the present application provides a communication method, which is executed by a network device, or the method is executed by some components in the network device (such as a processor, chip or chip system, etc.), or the method can also be implemented by a logic module or software that can realize all or part of the network device functions. In the second aspect and its possible implementation, the method is described as being executed by a network device. In this method, the network device determines first information, which indicates access information of an artificial intelligence AI task, and the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task; the network device sends the first information.

[0049] Based on the above technical solution, after the network device sends the first information indicating the access information of the AI ​​task, the terminal device can determine the access information of the AI ​​task based on the identifier of the AI ​​task, wherein the first information is obtained by processing the access information of the AI ​​task using the identifier of the AI ​​task. In other words, when the network device indicates the access information of the AI ​​task through the first information, the terminal device can obtain the access information of the AI ​​task from the first information using the identifier of the AI ​​task, so that the terminal device can subsequently access the AI ​​task based on the access information of the AI ​​task, thereby enabling the computing power of the terminal device to be used for the AI ​​task, in order to realize the execution of the AI ​​task in the communication network.

[0050] Furthermore, the first information sent by the network device is processed using the AI ​​task identifier. After receiving the first information, the terminal device can obtain the access information for the AI ​​task using the AI ​​task identifier. Thus, when the number of terminal devices is greater than one, different terminal devices can all obtain the access information for the AI ​​task using the AI ​​task identifier, reducing implementation complexity and improving efficiency.

[0051] Optionally, the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task, including: the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task and not through the identifier of the terminal device, or, the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task and the identifier of the terminal device; in comparison, since the former scheme does not require the identifier of the terminal device to participate in the processing of the access information, the processing of the access information can be achieved through the identifier of the AI ​​task, so that different terminal devices (or users) can obtain the access information of the AI ​​task through the identifier of the AI ​​task, and the privacy of the terminal device (or user) can be protected.

[0052] It should be understood that the first information can be the identifier of the AI ​​task obtained by processing the access information of the AI ​​task in various ways. For example, the processing can include at least one of scrambling, encryption, and encapsulation (or data packaging). In other words, the terminal device can determine the access information of the AI ​​task based on the identifier of the AI ​​task and the first information in various ways, such as at least one of descrambling, decryption, and decapsulation (or data unpacking).

[0053] In an implementation example, the processing may be scrambling processing. Accordingly, after receiving the first information, the terminal device may descramble the first information according to the identifier of the AI ​​task to obtain the access information of the AI ​​task. In other words, the network device may scramble different information (the different information may include the first information) using different identifiers. After receiving the different information, the terminal device descrambles the different information based on the different identifiers. In the process of descrambling the different information based on the different identifiers, the terminal device descrambles the first information based on the identifier of the AI ​​task to obtain the access information of the AI ​​task.

[0054] In another implementation example, the processing may be an encryption processing. Accordingly, after receiving the first information, the terminal device may decrypt the first information based on the identifier of the AI ​​task to obtain the access information of the AI ​​task. In other words, the network device may encrypt different information (the different information may include the first information) using different identifiers. After receiving the different information, the terminal device decrypts the different information based on the different identifiers. In the process of decrypting the different information based on the different identifiers, the terminal device decrypts the first information based on the identifier of the AI ​​task to obtain the access information of the AI ​​task.

[0055] In another implementation example, the processing may be an encapsulation process (or data packaging process). Accordingly, after receiving the first information, the terminal device may perform decapsulation processing (or data unpacking processing) on ​​the first information to obtain the data carried by the first information. The terminal device then determines the access information of the AI ​​task based on the identifier of the AI ​​task in the decapsulated data. In other words, the network device may encapsulate different information (the different information may include the first information) through different identifiers. After receiving the different information, the terminal device decapsulates the different information to obtain the decapsulated data. The terminal device then determines the access information of the AI ​​task based on the identifier of the AI ​​task in the decapsulated data.

[0056] It should be understood that the access information of the AI ​​task can be understood as information used to access the AI ​​task, that is, after the terminal device determines the access information of the AI ​​task, the terminal device can access the AI ​​task based on the access information of the AI ​​task.

[0057] It should be understood that the AI ​​task involved in this application may be a task that requires the participation of two or more communication nodes in processing, and the communication nodes include terminal devices and / or network devices. For example, the AI ​​task may include a federated learning (FL) task, a distributed training task, a distributed learning task, etc. Among them, the terminal device accessing the AI ​​task can be understood as the terminal device participating in the calculation process of the AI ​​task. In other words, a calculation result of the AI ​​task (including intermediate calculation results and / or final calculation results) is obtained by processing the calculation results of the terminal device and the calculation results of other communication nodes that may exist (for example, arithmetic average processing, weighted average processing, etc.). And / or, the terminal device accessing the AI ​​task can also be understood as the terminal device participating in the transmission process of the calculation result of the AI ​​task. In other words, a calculation result of the AI ​​task (including intermediate calculation results and / or final calculation results) is transmitted through the terminal device.

[0058] Optionally, the identifier of the AI ​​task is a radio network temporary identity (RNTI) associated with the AI ​​task, so that the terminal device can clearly identify the AI ​​task corresponding to the first information (or the access information indicated by the first information) based on the RNTI.

[0059] Optionally, the identifier of the AI ​​task is the RNTI associated with the AI ​​task, which can be understood as: the identifier of the AI ​​task is the RNTI of the AI ​​task, or the identifier of the AI ​​task is the RNTI used to transmit the business data of the AI ​​task, or the identifier of the AI ​​task is an RNTI dedicated to the AI ​​task, or the identifier of the AI ​​task is a specific RNTI of the AI ​​task, or the identifier of the AI ​​task is generated based on the task identifier (identity, ID) of the AI ​​task.

[0060] Optionally, the identifier of the AI ​​task is not bound to a specific terminal device and / or a specific transmission channel, so that different terminal devices and / or different transmission channels can use the same AI task identifier to receive and / or send business data of the same AI task. Compared with the implementation method of configuring different identifiers for different terminal devices and / or different transmission channels, it can simplify the configuration and save signaling overhead. Moreover, since the identifier does not need to be associated with a specific terminal device (and / or since the identifier does not need to be associated with a specific transmission channel), privacy leakage can be avoided to protect the privacy of the terminal device (or user).

[0061] In a possible implementation of the second aspect, the access information of the AI ​​task includes at least one of the following:

[0062] Information indicating the access conditions of the AI ​​task; information indicating the information update period of the AI ​​task; information indicating the training period of the AI ​​task; information indicating the uplink resource configuration of the service data of the AI ​​task; information indicating the downlink resource configuration of the service data of the AI ​​task; information indicating the codebook of the service data of the AI ​​task; information indicating the transmission mode of the service data of the AI ​​task; information indicating the uplink transmission parameters of the service data of the AI ​​task; information indicating the downlink transmission parameters of the service data of the AI ​​task.

[0063] Based on the above technical solution, in the access information of the AI ​​task indicated by the first information, the access information of the AI ​​task includes at least one of the above items, so that the recipient of the first information obtains various types of access information related to the AI ​​task through at least one item, thereby improving the flexibility of the implementation of the solution.

[0064] In a possible implementation of the second aspect, the information indicating the access condition of the AI ​​task includes at least one of the following:

[0065] The identification range of terminal devices that access the AI ​​task; the random number threshold for accessing the AI ​​task; the performance indicator threshold for accessing the AI ​​task; the start time for accessing the AI ​​task; and the end time for accessing the AI ​​task.

[0066] Based on the above technical solution, in the access information of the AI ​​task indicated by the first information, the information used to indicate the access conditions of the AI ​​task may include at least one of the above items, so that the network device can flexibly configure the access conditions of the AI ​​task and improve the flexibility of the implementation of the solution.

[0067] In a possible implementation of the second aspect, a transmission mode of the business data of the AI ​​task includes any one of the following:

[0068] A first transmission mode, wherein the first transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing using an identifier of the AI ​​task on service data of the AI ​​task; wherein transmission resources of at least two terminal devices in the first transmission mode are orthogonal;

[0069] A second transmission mode, where the second transmission mode indicates performing at least one of a third-order quantization modulation process, a pre-equalization superposition transmission process, and a coding modulation process based on a public codebook on the service data of the AI ​​task;

[0070] A third transmission mode, wherein the third transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing on the business data of the AI ​​task through the identifier of the AI ​​task; wherein the transmission resources of at least two terminal devices in the third transmission mode are the same.

[0071] Based on the above technical solution, in the access information of the AI ​​task indicated by the first information, the transmission mode of the business data of the indicated AI task includes at least one of the above items, so that the network device can flexibly configure the transmission mode of the business data of the AI ​​task and improve the flexibility of the implementation of the solution.

[0072] In a possible implementation of the second aspect, the uplink transmission configuration parameter and / or the downlink transmission configuration parameter includes at least one of the following: coding modulation scheme MCS, hybrid automatic repeat request HARQ version, power control and quantization modulation order, and transmission power threshold.

[0073] Based on the above technical solution, in the access information of the AI ​​task indicated by the first information, the indicated transmission configuration parameters include at least one of the above items, so that the network device can flexibly configure the transmission configuration parameters of the AI ​​task and improve the flexibility of the solution implementation.

[0074] In a possible implementation of the second aspect, after the network device sends the first information, the method further includes: the network device receiving local business data corresponding to the AI ​​task; and the network device sending fused business data corresponding to the AI ​​task.

[0075] Based on the above technical solution, after the network device sends the first information, so that the terminal device determines the access information of the AI ​​task according to the identifier of the AI ​​task, the terminal device can receive and send business data related to the AI ​​task based on the access information of the AI ​​task, so that the terminal device can access (or participate in) the AI ​​task.

[0076] In a possible implementation manner of the second aspect, the method further includes: the network device receiving indication information indicating confirmation of receiving the converged service data.

[0077] Based on the above technical solution, after the terminal device receives the integrated business data corresponding to the AI ​​task, the terminal device can also send indication information to confirm the reception of the integrated business data, so that the network device can determine whether the terminal device has successfully received it based on the indication information, which is conducive to the subsequent scheduling of one or more terminal devices participating in the AI ​​task based on the indication information.

[0078] In a possible implementation of the second aspect, before the network device receives the local business data corresponding to the AI ​​task, the method also includes: the network device receives indication information indicating that the local training of the AI ​​task has been completed; and the network device sends indication information indicating that the local business data is sent.

[0079] Based on the above technical solution, through the interaction of indication information indicating that the local training of the AI ​​task has been completed and indication information indicating that local business data has been sent, the network device can clearly understand the execution status of the local training of the terminal device and implement scheduling of the terminal device based on the execution status.

[0080] In addition, through the above-mentioned interaction process, when the network device clearly knows that the number of terminal devices that have completed local training is greater than or equal to a threshold, the network device can schedule the terminal devices to send local business data to ensure that the number of terminal devices accessing the AI ​​task meets the requirements of the threshold.

[0081] In a possible implementation of the second aspect, before the network device sends the first information, the method also includes: the network device sends indication information indicating reporting of capability information for participating in the AI ​​task; the network device receives second information, where the second information indicates communication capability information and / or AI capability information; wherein the communication capability information includes at least one of channel information and communication frequency information; and the AI ​​capability information includes at least one of AI model performance, AI parameters, AI gradient variance, and AI data set size.

[0082] Based on the above technical solution, after the terminal device receives the indication information instructing it to report the capability information for participating in the AI ​​task, the terminal device may also send second information indicating communication capability information and / or AI capability information, so that the network device can clarify the capability information of the terminal device for participating in the AI ​​task based on the second information, and determine the access information of the AI ​​task based on the capability information of one or more terminal devices, so as to schedule it through the first information indicating the access information of the AI ​​task.

[0083] In a possible implementation of the second aspect, before the network device sends the first information, the method also includes: the network device sends third information, the third information indicating the release information of the AI ​​task, and the third information is obtained by processing the release information through the identifier of the AI ​​task; the network device receives fourth information, the fourth information is used to indicate registration to the AI ​​task, and the fourth information includes at least one of the following: AI capability information of the terminal device, and the identifier of the terminal device.

[0084] Based on the above technical solution, the terminal device can also receive third information indicating the release information of the AI ​​task, and the third information is obtained by processing the release information through the identifier of the AI ​​task, so that the terminal device can obtain the release information based on the identifier of the AI ​​task, and then send fourth information to the network device to indicate registration to the AI ​​task. The release process and registration process of the AI ​​task are realized through the interaction of the above third information and fourth information.

[0085] In a possible implementation manner of the second aspect, the method further includes: the network device sending indication information indicating confirmation of receiving the fourth information.

[0086] Based on the above technical solution, the terminal device can also receive indication information indicating confirmation of receiving the fourth information, so that the terminal device can determine whether the network device has successfully received the fourth information based on the indication information, and further determine whether the terminal device has successfully registered to the AI ​​task.

[0087] In a possible implementation manner of the second aspect, the published information includes at least one of the following: an identifier of the AI ​​task, a public codebook reported by the user information, and indication information of transmission resources.

[0088] Based on the above technical solution, the publishing information sent by the network device may include at least one of the above items, so that the terminal device can obtain relevant information of the AI ​​task based on the at least one item, and send fourth information based on this information to realize the registration process of the AI ​​task.

[0089] A third aspect of the present application provides a communication device, which is a terminal device, or a component of a terminal device (such as a processor, chip, or chip system), or a logic module or software capable of implementing all or part of the terminal device's functions. In the third aspect and its possible implementations, the communication device is described as an example of a terminal device.

[0090] The device includes a processing unit and a transceiver unit; the transceiver unit is used to receive first information, where the first information indicates access information of an AI task, and the first information is obtained by processing the access information of the AI ​​task through an identifier of the AI ​​task; the processing unit is used to determine the access information of the AI ​​task based on the identifier of the AI ​​task and the first information.

[0091] In a possible implementation of the third aspect, the access information of the AI ​​task includes at least one of the following:

[0092] Information indicating the access conditions of the AI ​​task; information indicating the information update period of the AI ​​task; information indicating the training period of the AI ​​task; information indicating the uplink resource configuration of the service data of the AI ​​task; information indicating the downlink resource configuration of the service data of the AI ​​task; information indicating the codebook of the service data of the AI ​​task; information indicating the transmission mode of the service data of the AI ​​task; information indicating the uplink transmission parameters of the service data of the AI ​​task; information indicating the downlink transmission parameters of the service data of the AI ​​task.

[0093] In a possible implementation of the third aspect, the information indicating the access condition of the AI ​​task includes at least one of the following:

[0094] The identification range of terminal devices that access the AI ​​task; the random number threshold for accessing the AI ​​task; the performance indicator threshold for accessing the AI ​​task; the start time for accessing the AI ​​task; and the end time for accessing the AI ​​task.

[0095] In a possible implementation of the third aspect, a transmission mode of the business data of the AI ​​task includes any one of the following:

[0096] A first transmission mode, wherein the first transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing using an identifier of the AI ​​task on service data of the AI ​​task; wherein transmission resources of at least two terminal devices in the first transmission mode are orthogonal;

[0097] A second transmission mode, where the second transmission mode indicates performing at least one of a third-order quantization modulation process, a pre-equalization superposition transmission process, and a coding modulation process based on a public codebook on the service data of the AI ​​task;

[0098] A third transmission mode, wherein the third transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing on the business data of the AI ​​task through the identifier of the AI ​​task; wherein the transmission resources of at least two terminal devices in the third transmission mode are the same.

[0099] In a possible implementation manner of the third aspect, the uplink transmission configuration parameter and / or the downlink transmission configuration parameter includes at least one of the following:

[0100] Coding modulation scheme MCS, hybrid automatic repeat request HARQ version, power control and quantization modulation order, transmission power threshold.

[0101] In a possible implementation of the third aspect, the transceiver unit is further used to send local service data corresponding to the AI ​​task based on the access information of the AI ​​task; the transceiver unit is further used to receive fused service data corresponding to the AI ​​task.

[0102] In a possible implementation manner of the third aspect, the transceiver unit is further configured to send indication information indicating confirmation of receiving the converged service data.

[0103] In a possible implementation of the third aspect, the transceiver unit is further used to send indication information indicating that the local training of the AI ​​task has been completed; the transceiver unit is further used to receive indication information instructing to send the local business data.

[0104] In a possible implementation manner of the third aspect, the identifier of the AI ​​task is a radio network temporary identifier RNTI associated with the AI ​​task.

[0105] In a possible implementation of the third aspect, the transceiver unit is further used to receive indication information indicating reporting capability information for participating in the AI ​​task; the transceiver unit is further used to send second information, where the second information indicates communication capability information and / or AI capability information; wherein the communication capability information includes at least one of channel information and communication frequency information; and the AI ​​capability information includes at least one of AI model performance, AI parameters, AI gradient variance, and AI data set size.

[0106] In a possible implementation of the third aspect, the transceiver unit is further used to receive third information, where the third information indicates the release information of the AI ​​task, and the third information is obtained by processing the release information using the identifier of the AI ​​task; the transceiver unit is further used to send fourth information, where the fourth information is used to indicate registration with the AI ​​task, and the fourth information includes at least one of the following: AI capability information of the terminal device and the identifier of the terminal device.

[0107] In a possible implementation manner of the third aspect, the transceiver unit is further configured to send indication information indicating confirmation of receiving the fourth information.

[0108] In a possible implementation manner of the third aspect, the published information includes at least one of the following: an identifier of the AI ​​task, a public codebook reported by the user information, and indication information of transmission resources.

[0109] In the third aspect of the present application, the constituent modules of the communication device can also be used to execute the steps performed in each possible implementation method of the first aspect and achieve corresponding technical effects. For details, please refer to the first aspect and will not be repeated here.

[0110] In a fourth aspect, the present application provides a communication device, which is a network device, or a component of a network device (such as a processor, chip, or chip system), or a logic module or software capable of implementing all or part of the network device's functions. In the fourth aspect and its possible implementations, the communication device is described as a network device.

[0111] The device includes a processing unit and a transceiver unit; the transceiver unit is used to determine first information, where the first information indicates access information of an artificial intelligence (AI) task, and the first information is obtained by processing the access information of the AI ​​task through an identifier of the AI ​​task; the transceiver unit is used to send the first information.

[0112] In a possible implementation of the fourth aspect, the access information of the AI ​​task includes at least one of the following:

[0113] Information indicating the access conditions of the AI ​​task; information indicating the information update period of the AI ​​task; information indicating the training period of the AI ​​task; information indicating the uplink resource configuration of the service data of the AI ​​task; information indicating the downlink resource configuration of the service data of the AI ​​task; information indicating the codebook of the service data of the AI ​​task; information indicating the transmission mode of the service data of the AI ​​task; information indicating the uplink transmission parameters of the service data of the AI ​​task; information indicating the downlink transmission parameters of the service data of the AI ​​task.

[0114] In a possible implementation of the fourth aspect, the information indicating the access condition of the AI ​​task includes at least one of the following:

[0115] The identification range of terminal devices that access the AI ​​task; the random number threshold for accessing the AI ​​task; the performance indicator threshold for accessing the AI ​​task; the start time for accessing the AI ​​task; and the end time for accessing the AI ​​task.

[0116] In a possible implementation of the fourth aspect, a transmission mode of the business data of the AI ​​task includes any one of the following:

[0117] A first transmission mode, wherein the first transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing using an identifier of the AI ​​task on service data of the AI ​​task; wherein transmission resources of at least two terminal devices in the first transmission mode are orthogonal;

[0118] A second transmission mode, where the second transmission mode indicates performing at least one of a third-order quantization modulation process, a pre-equalization superposition transmission process, and a coding modulation process based on a public codebook on the service data of the AI ​​task;

[0119] A third transmission mode, wherein the third transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing on the business data of the AI ​​task through the identifier of the AI ​​task; wherein the transmission resources of at least two terminal devices in the third transmission mode are the same.

[0120] In a possible implementation of the fourth aspect, the uplink transmission configuration parameter and / or the downlink transmission configuration parameter include at least one of the following: coding modulation scheme MCS, hybrid automatic repeat request HARQ version, power control and quantization modulation order, and transmission power threshold.

[0121] In a possible implementation of the fourth aspect, the transceiver unit is further used to receive local business data corresponding to the AI ​​task; the transceiver unit is further used to send fused business data corresponding to the AI ​​task.

[0122] In a possible implementation manner of the fourth aspect, the transceiver unit is further configured to receive indication information indicating confirmation of receiving the converged service data.

[0123] In a possible implementation of the fourth aspect, the transceiver unit is further used to receive indication information indicating that the local training of the AI ​​task has been completed; the transceiver unit is further used to send indication information instructing to send the local business data.

[0124] In a possible implementation manner of the fourth aspect, the identifier of the AI ​​task is a radio network temporary identifier RNTI associated with the AI ​​task.

[0125] In a possible implementation of the fourth aspect, the transceiver unit is further used to send indication information indicating reporting of capability information for participating in the AI ​​task; the transceiver unit is further used to receive second information, wherein the second information indicates communication capability information and / or AI capability information; wherein the communication capability information includes at least one of channel information and communication frequency information; and the AI ​​capability information includes at least one of AI model performance, AI parameters, AI gradient variance, and AI data set size.

[0126] In a possible implementation of the fourth aspect, the transceiver unit is further used to send third information, where the third information indicates the release information of the AI ​​task, and the third information is obtained by processing the release information using the identifier of the AI ​​task; the transceiver unit is further used to receive fourth information, where the fourth information is used to indicate registration with the AI ​​task, and the fourth information includes at least one of the following: AI capability information of the terminal device and the identifier of the terminal device.

[0127] In a possible implementation manner of the fourth aspect, the published information includes at least one of the following: an identifier of the AI ​​task, a public codebook reported by the user information, and indication information of transmission resources.

[0128] In the fourth aspect of the present application, the constituent modules of the communication device can also be used to execute the steps performed in each possible implementation method of the second aspect and achieve corresponding technical effects. For details, please refer to the second aspect and will not be repeated here.

[0129] A fifth aspect of an embodiment of the present application provides a communication device, comprising at least one processor, wherein the at least one processor is coupled to a memory; the memory is used to store programs or instructions; the at least one processor is used to execute the program or instructions so that the device implements the method described in the first aspect or any possible implementation method of the first aspect.

[0130] In a sixth aspect, an embodiment of the present application provides a communication device, comprising at least one processor, wherein the at least one processor is coupled to a memory; the memory is used to store programs or instructions; and the at least one processor is used to execute the program or instructions so that the device implements the method described in the second aspect or any possible implementation method of the second aspect.

[0131] In a seventh aspect, an embodiment of the present application provides a communication device, comprising at least one logic circuit and an input / output interface; the logic circuit is used to execute the method described in the first aspect or any possible implementation of the first aspect.

[0132] In an eighth aspect, an embodiment of the present application provides a communication device, comprising at least one logic circuit and an input / output interface; the logic circuit is used to execute the method described in the second aspect or any possible implementation of the second aspect.

[0133] A ninth aspect of an embodiment of the present application provides a computer-readable storage medium for storing one or more computer-executable instructions. When the computer-executable instructions are executed by a processor, the processor executes the method described in any possible implementation of any one of the first to second aspects above.

[0134] A tenth aspect of the embodiments of the present application provides a computer program product (or computer program). When the computer program product is executed by the processor, the processor executes the method described in any possible implementation of any one of the first to second aspects above.

[0135] In an eleventh aspect of an embodiment of the present application, a chip system is provided, which includes at least one processor for supporting a communication device to implement the functions involved in any possible implementation method of any aspect of the first to second aspects mentioned above.

[0136] In one possible design, the chip system may further include a memory for storing program instructions and data necessary for the first communication device. The chip system may be composed of a chip or may include a chip and other discrete components. Optionally, the chip system may further include an interface circuit that provides program instructions and / or data to the at least one processor.

[0137] A twelfth aspect of an embodiment of the present application provides a communication system, which includes the communication device of the third aspect and the communication device of the fourth aspect, and / or the communication system includes the communication device of the fifth aspect and the communication device of the sixth aspect, and / or the communication system includes the communication device of the seventh aspect and the communication device of the eighth aspect.

[0138] Among them, the technical effects brought about by any design method in the third aspect to the twelfth aspect can refer to the technical effects brought about by the different design methods in the above-mentioned first aspect to the second aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0139] FIG1a is a schematic diagram of a communication system provided by the present application;

[0140] FIG1b is another schematic diagram of the communication system provided by the present application;

[0141] FIG2a is a schematic diagram of the AI ​​processing process involved in this application;

[0142] FIG2b is a schematic diagram of AI data transmission involved in this application;

[0143] FIG3 is an interactive schematic diagram of the communication method provided by this application;

[0144] FIG4 is a schematic diagram of an application example of the communication method provided in this application;

[0145] FIG5 is another schematic diagram of an application example of the communication method provided by the present application;

[0146] FIG6a is another schematic diagram of an application example of the communication method provided in this application;

[0147] FIG6 b is another schematic diagram of an application example of the communication method provided in this application;

[0148] FIG7 is another schematic diagram of an application example of the communication method provided by the present application;

[0149] FIG8 is a schematic diagram of a communication device provided by the present application;

[0150] FIG9 is another schematic diagram of a communication device provided by the present application;

[0151] FIG10 is another schematic diagram of a communication device provided by the present application;

[0152] FIG11 is another schematic diagram of the communication device provided in this application. DETAILED DESCRIPTION

[0153] First, some of the terms used in the embodiments of the present application are explained to facilitate understanding by those skilled in the art.

[0154] (1) Terminal device: It can be a wireless terminal device that can receive network device scheduling and instruction information. The wireless terminal device can be a device that provides voice and / or data connectivity to the user, or a handheld device with wireless connection function, or other processing device connected to a wireless modem.

[0155] Terminal devices can communicate with one or more core networks or the Internet via the RAN. Terminal devices can be mobile terminal devices, such as mobile phones (also known as "cellular" phones, mobile phones), computers, and data cards. For example, they can be portable, pocket-sized, handheld, computer-built-in, or vehicle-mounted mobile devices that exchange voice and / or data with the radio access network. Examples include personal communication service (PCS) phones, cordless phones, Session Initiation Protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), tablet computers, and computers with wireless transceiver capabilities. Wireless terminal equipment can also be called system, subscriber unit, subscriber station, mobile station, mobile station (MS), remote station, access point (AP), remote terminal equipment (remote terminal), access terminal equipment (access terminal), user terminal equipment (user terminal), user agent, subscriber station (SS), customer premises equipment (CPE), terminal, user equipment (UE), mobile terminal (MT), etc.

[0156] As an example and not a limitation, in the embodiments of the present application, the terminal device may also be a wearable device. Wearable devices may also be referred to as wearable smart devices or smart wearable devices, etc., which are a general term for wearable devices that are intelligently designed and developed using wearable technology for daily wear, such as glasses, gloves, watches, clothing, and shoes. A wearable device is a portable device that is worn directly on the body or integrated into the user's clothes or accessories. Wearable devices are not only hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are fully functional, large in size, and can achieve complete or partial functions without relying on smartphones, such as smart watches or smart glasses, etc., as well as those that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various smart bracelets, smart helmets, and smart jewelry for vital sign monitoring.

[0157] The terminal may also be a drone, a robot, a terminal in device-to-device (D2D) communication, a terminal in vehicle-to-everything (V2X), a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal in industrial control, a wireless terminal in self-driving, a wireless terminal in remote medical, a wireless terminal in smart grid, a wireless terminal in transportation safety, a wireless terminal in smart city, a wireless terminal in smart home, etc.

[0158] In addition, the terminal device may also be a terminal device in a communication system that has evolved after the fifth generation (5G) communication system (e.g., a sixth generation (6G) communication system) or a terminal device in a future public land mobile network (PLMN). For example, the 6G network can further expand the form and function of 5G communication terminals. 6G terminals include but are not limited to vehicles, cellular network terminals (with integrated satellite terminal functions), drones, and Internet of Things (IoT) devices.

[0159] In an embodiment of the present application, the terminal device may also obtain AI services provided by the network device. Optionally, the terminal device may also have AI processing capabilities.

[0160] (2) Network equipment: It can be a device in a wireless network. For example, the network equipment can be a RAN node (or device) that connects a terminal device to a wireless network, which can also be called a base station. Currently, some examples of RAN equipment include: base stations gNB (gNodeB) in 5G communication systems, transmission reception points (TRP), evolved Node B (eNB), radio network controllers (RNC), Node B (NB), home base stations (e.g., home evolved Node B, or home Node B, HNB), base band units (BBU), or wireless fidelity (Wi-Fi) access points AP, etc. In addition, in a network structure, the network equipment can include centralized unit (CU) nodes, distributed unit (DU) nodes, or RAN equipment including CU nodes and DU nodes.

[0161] The network device may be any other device that provides wireless communication functionality to the terminal device. The embodiments of this application do not limit the specific technology and device form used by the network device. For ease of description, the embodiments of this application do not limit this.

[0162] The network equipment may also include core network equipment, which may include, for example, a mobility management entity (MME), a home subscriber server (HSS), a serving gateway (S-GW), a policy and charging rules function (PCRF), and a public data network gateway (PDN gateway, P-GW) in a fourth generation (4G) network; and network elements such as an access and mobility management function (AMF), a user plane function (UPF), or a session management function (SMF) in a 5G network. In addition, the core network equipment may also include other core network equipment in a 5G network and a next generation network of a 5G network.

[0163] In an embodiment of the present application, the above-mentioned network device may also have a network node with AI capabilities, which can provide AI services for terminals or other network devices. For example, it can be an AI node on the network side (access network or core network), a computing power node, a RAN node with AI capabilities, a core network element with AI capabilities, etc.

[0164] In the embodiments of the present application, the apparatus for implementing the function of the network device may be the network device, or may be a device capable of supporting the network device in implementing the function, such as a chip system, which may be installed in the network device. In the technical solutions provided in the embodiments of the present application, the technical solutions provided in the embodiments of the present application are described by taking the network device as an example.

[0165] (3) Configuration and pre-configuration: In this application, configuration and pre-configuration are used simultaneously. Configuration refers to the network device / server sending some parameter configuration information or parameter values ​​to the terminal through messages or signaling, so that the terminal can determine the communication parameters or resources during transmission based on these values ​​or information. Pre-configuration is similar to configuration, and can be parameter information or parameter values ​​pre-negotiated between the network device / server and the terminal device, or parameter information or parameter values ​​used by the base station / network device or terminal device as specified in the standard protocol, or parameter information or parameter values ​​pre-stored in the base station / server or terminal device. This application does not limit this.

[0166] Furthermore, these values ​​and parameters can be changed or updated.

[0167] (4) The terms "system" and "network" in the embodiments of the present application can be used interchangeably. "Multiple" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, "at least one of A, B and C" includes A, B, C, AB, AC, BC or ABC. In addition, unless otherwise specified, the ordinal numbers such as "first" and "second" mentioned in the embodiments of the present application are used to distinguish multiple objects, and are not used to limit the order, timing, priority or importance of multiple objects.

[0168] (5) “Sending” and “receiving” in the embodiments of the present application indicate the direction of signal transmission. For example, “sending information to XX” can be understood as the destination of the information being XX, which can include direct sending through the air interface, as well as indirect sending through the air interface by other units or modules. “Receiving information from YY” can be understood as the source of the information being YY, which can include direct receiving from YY through the air interface, as well as indirect receiving from YY through the air interface from other units or modules. “Sending” can also be understood as the “output” of the chip interface, and “receiving” can also be understood as the “input” of the chip interface.

[0169] In other words, sending and receiving can be performed between devices, for example, between a network device and a terminal device, or can be performed within a device, for example, sending or receiving between components, modules, chips, software modules or hardware modules within the device through a bus, wiring or interface.

[0170] It is understandable that information may be processed between the source and destination of information transmission, such as coding, modulation, etc., but the destination can understand the valid information from the source. Similar expressions in this application can be understood similarly and will not be repeated.

[0171] (6) In the embodiments of the present application, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain information (such as the indication information described below) is called information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, directly indicating the information to be indicated, such as the information to be indicated itself or the index of the information to be indicated. The information to be indicated may also be indirectly indicated by indicating other information, wherein the other information is associated with the information to be indicated; or only a part of the information to be indicated may be indicated, while the other part of the information to be indicated is known or agreed in advance. For example, the indication of specific information may be achieved by means of the arrangement order of each information agreed in advance (such as predefined by the protocol), thereby reducing the indication overhead to a certain extent. The present application does not limit the specific method of indication. It is understandable that for the sender of the indication information, the indication information can be used to indicate the information to be indicated, and for the receiver of the indication information, the indication information can be used to determine the information to be indicated.

[0172] In this application, unless otherwise specified, the same or similar parts between the various embodiments can refer to each other. In the various embodiments of this application, and the various methods / designs / implementations in each embodiment, if there is no special explanation and logical conflict, the terms and / or descriptions between different embodiments and the various methods / designs / implementations in each embodiment are consistent and can be referenced to each other. The technical features in different embodiments and the various methods / designs / implementations in each embodiment can be combined to form new embodiments, methods, or implementations according to their inherent logical relationships. The following description of the implementation methods of this application does not constitute a limitation on the scope of protection of this application.

[0173] The present application can be applied to a long term evolution (LTE) system, a new radio (NR) system, or a communication system evolved after 5G (such as 6G, etc.). The communication system includes at least one network device and / or at least one terminal device.

[0174] Please refer to Figure 1a, which is a schematic diagram of a communication system in this application. Figure 1a exemplarily illustrates a network device 101 and six terminal devices, namely terminal device 1, terminal device 2, terminal device 3, terminal device 4, terminal device 5, and terminal device 6. In the example shown in Figure 1a, terminal device 1 is a smart teacup, terminal device 2 is a smart air conditioner, terminal device 3 is a smart gas pump, terminal device 4 is a vehicle, terminal device 5 is a mobile phone, and terminal device 6 is a printer.

[0175] As shown in Figure 1a, the AI ​​information sending entity can be a network device. The AI ​​information receiving entity can be terminal devices 1-6. In this case, the network device and terminal devices 1-6 form a communication system. In this communication system, terminal devices 1-6 can send data to the network device, and the network device needs to receive data sent by terminal devices 1-6. At the same time, the network device can send configuration information to terminal devices 1-6.

[0176] Optionally, the AI ​​information may include access information of the AI ​​task mentioned later, integrated business data, etc.; the data may include local business data mentioned later, etc.

[0177] For example, in Figure 1a, terminal devices 4 and 6 can also form a communication system. Terminal device 5 serves as a network device, i.e., the AI ​​information sending entity; terminal devices 4 and 6 serve as terminal devices, i.e., AI information receiving entities. For example, in a connected vehicle system, terminal device 5 sends AI information to terminal devices 4 and 6, respectively, and receives data from them. Correspondingly, terminal devices 4 and 6 receive AI information from terminal device 5 and send data to terminal device 5.

[0178] Taking the communication system shown in Figure 1a as an example, in addition to executing communication-related services, different devices (including between network devices, between network devices and terminal devices, and / or between terminal devices) may also execute AI-related services. For example, as shown in Figure 1b, taking the network device as a base station as an example, the base station can execute communication-related services and AI-related services with one or more terminal devices, and different terminal devices can also execute communication-related services and AI-related services.

[0179] The technical solutions provided in this application can be applied to wireless communication systems (e.g., the systems shown in Figures 1a and 1b). In wireless communication systems, communication nodes generally have both signal transceiver capabilities and computing capabilities. For example, network devices with computing capabilities primarily provide computing power to support signal transceiver capabilities (e.g., calculating the time and frequency domain resources that carry the signal), thereby enabling communication between the network device and other communication nodes.

[0180] However, in communication networks, communication nodes may have excess computing power beyond just supporting the aforementioned communication tasks. Therefore, how to utilize this computing power is a pressing technical issue.

[0181] In one possible implementation, the computing power of communication nodes can be used for distributed learning, an AI task. Distributed learning involves multiple devices training local models using local data, then fusing these models to form a global model. By transmitting these models rather than the user's original data, federated learning is achieved while protecting user data privacy. Distributed learning requires the transmission of locally derived model weight parameters or gradients between multiple devices, which are then fused to update the global model.

[0182] Exemplarily, taking federated learning as an example, the system includes a model parameter server and a client. If the system is applied to a communication network, the network device can be the server and the terminal device can be the client. In each round of training, the client updates the local model based on the global model weight parameters or gradients sent by the server; then obtains new local model weight parameters or gradients based on local data training, and uploads them to the server; the server averages the model weight parameters or gradients received from multiple clients to obtain the weight parameters or gradients of the global model for this round, and sends them to the client; each client updates to obtain a new round of global models. Averaging model weight parameters or gradients is a common way to achieve model fusion in distributed learning. As shown in Figure 2a, taking the example of the terminal devices participating in federated learning including K (K is greater than 1) terminal devices, the process of one round of federated learning is as follows:

[0183] Step 1. Local training: The kth terminal device among the K terminal devices (i.e., terminal device k) is trained based on local data and the global model of the tth round Perform gradient descent-based training to obtain weight parameters or update value (also called gradient)

[0184] Step 2. Model upload: terminal device uploads gradient (or weight parameter );

[0185] Step 3. Model fusion: The server averages the gradients or weights to obtain the global gradient (or weight );

[0186] Step 4. Model delivery: The server sends the global gradient (or weight w t+1 ) is sent to the terminal device;

[0187] Step 5. Model update: The terminal device updates the local model to the global model based on the global model or weights (or );

[0188] In addition, step 3 in Figure 2a above can be implemented through over-the-air computing, which is a method of performing specific calculations by adding wireless signals over the air. For model averaging in distributed learning, over-the-air computing can support the simultaneous transmission of model parameters or gradients for multiple clients through wireless signal superposition. The signal at the receiving end achieves the average of the model parameters or gradients, thereby reducing the use of communication resources. For signals sent simultaneously to multiple terminal devices, the received signal y at the receiving end is expressed as follows:

[0189] Where Δw k represents the model parameters or gradients of the kth terminal device, mod(·) represents the modulation of the model parameters or gradients into symbols, and h k represents the complex channel from the kth terminal device to the network device, and n represents the noise.

[0190] In addition, the process of uplink and downlink data transmission between the terminal device and the network device in steps 2 and 4 in Figure 2a above can be implemented through the process shown in Figure 2b, including the following steps.

[0191] Step 1. The terminal device accesses the network device through the random access channel (RACH) process.

[0192] Step 2. The terminal device sends a scheduling request (SR).

[0193] Step 3. The network device sends downlink control information (DCI).

[0194] Step 4. The network device and the terminal device transmit uplink data and downlink data on the physical uplink shared channel (PUSCH) and physical downlink shared channel (PDSCH) respectively.

[0195] Step 5. The network device and the terminal device can use hybrid automatic repeat request acknowledgement (HARQ ACK, ACK for short) and hybrid automatic repeat request negative acknowledgement (HARQ NACK, NACK for short) to feedback whether the PUSCH / PUSCH data is successfully received.

[0196] As shown in Figure 2b, when the terminal device has uplink data to send, it first obtains the authorized uplink transmission resources through the RACH process, sends an uplink transmission resource request through the SR, and the network device indicates the uplink or downlink transmission through the DCI encrypted with a specific RNTI, and the transmitted data is encrypted with the corresponding RNTI.

[0197] Generally, DCI formats include format 0_x for PUSCH transmissions on specific terminal devices; format 1_x for PDSCH transmissions on specific terminal devices; format 2_x for group terminal device control indications, including time slot format indication, power control, wake-up signals, etc.; format 3_x for sidelink transmissions; and format 4_x for multicast / broadcast. RNTIs include a global RNTI for system information, such as paging, broadcast, and random access procedures; a terminal-specific RNTI for unicast transmissions, including dynamic or semi-static transmissions; a group RNTI for multicast / broadcast transmissions; and a global RNTI for control indications.

[0198] However, in the aforementioned federated learning process where multiple terminal devices participate in training, in step 2 shown in Figure 2a, the terminal device needs to upload the model to the network device for integration. However, the network device may not need to decode the data of a single terminal device (such as the aforementioned implementation process of over-the-air computing), and thus may not need to distinguish between different terminal devices. In the access method shown in Figure 2b, the network device needs to perform dedicated access configuration for each terminal device with data transmission (such as the interactive process of steps 2 and 3 shown in Figure 2b), which cannot efficiently support the scenario in which multiple terminal devices in federated learning upload model parameters at the same time. The dedicated configuration may also lead to the leakage of terminal device privacy.

[0199] To solve the above problems, the present application provides a communication method and related devices, which will be described in detail below with reference to the accompanying drawings. Please refer to Figure 3, which is a schematic diagram of an implementation of the communication method provided by the present application. The method includes the following steps.

[0200] It should be noted that, in FIG3 , the method is illustrated by taking the network device and the terminal device as the execution subjects of the interaction diagram as an example, but the present application does not limit the execution subjects of the interaction diagram. For example, the execution subject of S301 in FIG3 and the corresponding implementation is the network device, and the execution subject may also be a chip, chip system, or processor that supports the network device to implement the method, or a logic module or software that can implement all or part of the network device functions. The terminal device in S301-S302 in FIG3 and the corresponding implementation may also be replaced by a chip, chip system, or processor that supports the terminal device to implement the method, or a logic module or software that can implement all or part of the terminal device functions.

[0201] S301. A network device sends first information, and a terminal device receives the first information accordingly. The first information is obtained by processing access information of the AI ​​task using the identifier of the AI ​​task.

[0202] S302. The terminal device determines access information of the AI ​​task based on the identifier of the AI ​​task and the first information.

[0203] It should be understood that the first information sent by the network device in step S301 can be the identifier of the AI ​​task obtained by processing the access information of the AI ​​task in various ways. For example, the processing can include at least one of scrambling, encryption, and encapsulation (or data packaging). In other words, after the terminal device receives the first information in step S301, in step S302, the terminal device can determine the access information of the AI ​​task based on the identifier of the AI ​​task and the first information in various ways, such as at least one of descrambling, decryption, and decapsulation (or data unpacking).

[0204] In an implementation example, the processing may be scrambling processing. Accordingly, after receiving the first information, the terminal device may descramble the first information according to the identifier of the AI ​​task to obtain the access information of the AI ​​task. In other words, the network device may scramble different information (the different information may include the first information) using different identifiers. After receiving the different information, the terminal device descrambles the different information based on the different identifiers. In the process of descrambling the different information based on the different identifiers, the terminal device descrambles the first information based on the identifier of the AI ​​task to obtain the access information of the AI ​​task.

[0205] In another implementation example, the processing may be an encryption processing. Accordingly, after receiving the first information, the terminal device may decrypt the first information based on the identifier of the AI ​​task to obtain the access information of the AI ​​task. In other words, the network device may encrypt different information (the different information may include the first information) using different identifiers. After receiving the different information, the terminal device decrypts the different information based on the different identifiers. In the process of decrypting the different information based on the different identifiers, the terminal device decrypts the first information based on the identifier of the AI ​​task to obtain the access information of the AI ​​task.

[0206] In another implementation example, the processing may be an encapsulation process (or data packaging process). Accordingly, after receiving the first information, the terminal device may perform decapsulation processing (or data unpacking processing) on ​​the first information to obtain the data carried by the first information. The terminal device then determines the access information of the AI ​​task based on the identifier of the AI ​​task in the decapsulated data. In other words, the network device may encapsulate different information (the different information may include the first information) through different identifiers. After receiving the different information, the terminal device decapsulates the different information to obtain the decapsulated data. The terminal device then determines the access information of the AI ​​task based on the identifier of the AI ​​task in the decapsulated data.

[0207] It should be understood that the access information of the AI ​​task indicated by the first information can be understood as information used to access the AI ​​task, that is, after the terminal device determines the access information of the AI ​​task in step S302, the terminal device can access the AI ​​task based on the access information of the AI ​​task.

[0208] It should be understood that the AI ​​task involved in this application may be a task that requires the participation of two or more communication nodes in processing, and the communication nodes include terminal devices and / or network devices. For example, the AI ​​task may include a federated learning (FL) task, a distributed training task, a distributed learning task, etc. Among them, the terminal device accessing the AI ​​task can be understood as the terminal device participating in the calculation process of the AI ​​task. In other words, a calculation result of the AI ​​task (including intermediate calculation results and / or final calculation results) is obtained by processing the calculation results of the terminal device and the calculation results of other communication nodes that may exist (for example, arithmetic average processing, weighted average processing, etc.). And / or, the terminal device accessing the AI ​​task can also be understood as the terminal device participating in the transmission process of the calculation result of the AI ​​task. In other words, a calculation result of the AI ​​task (including intermediate calculation results and / or final calculation results) is transmitted through the terminal device.

[0209] Optionally, the identifier of the AI ​​task is a radio network temporary identity (RNTI) associated with the AI ​​task, so that the terminal device can clearly identify the AI ​​task corresponding to the first information (or the access information indicated by the first information) based on the RNTI. In other words, after the network device scrambles the access information of the AI ​​task based on the RNTI of the AI ​​task to obtain the first information, the network device sends the first information in step S301; thereafter, in step S302, the terminal device can descramble the first information based on the RNTI of the AI ​​task to determine the access information of the AI ​​task.

[0210] It should be noted that, for a terminal device, the terminal device can obtain the identifier of the AI ​​task in a variety of ways. For example, one or more AI task identifiers are pre-configured in the terminal device through protocol / standard pre-configuration. For another example, the terminal device can determine the identifier of the AI ​​task in a message / information sent by a network device through configuration, where the message / information can be an RRC message, MAC CE, DCI, or the third information mentioned later.

[0211] Optionally, the identifier of the AI ​​task is an RNTI associated with the AI ​​task, which can be understood as: the identifier of the AI ​​task is the RNTI of the AI ​​task, or the identifier of the AI ​​task is the RNTI used to transmit the business data of the AI ​​task, or the identifier of the AI ​​task is an RNTI dedicated to the AI ​​task, or the identifier of the AI ​​task is a specific RNTI of the AI ​​task, or the identifier of the AI ​​task is generated based on the task identifier (identity, ID) of the AI ​​task.

[0212] Optionally, when the AI ​​task is a federated learning task, the RNTI of the AI ​​task may be a federated learning radio network temporary identity (FL-RNTI).

[0213] Optionally, the identifier of the AI ​​task is not bound to a specific terminal device and / or a specific transmission channel, so that different terminal devices and / or different transmission channels can use the same AI task identifier to receive and / or send business data of the same AI task. Compared with the implementation method of configuring different identifiers for different terminal devices and / or different transmission channels, it can simplify the configuration and save signaling overhead. Moreover, since the identifier does not need to be associated with a specific terminal device (and / or since the identifier does not need to be associated with a specific transmission channel), privacy leakage can be avoided to protect the privacy of the terminal device (or user).

[0214] Optionally, the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task, including: the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task and not through the identifier of the terminal device, or, the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task and the identifier of the terminal device; in comparison, since the former scheme does not require the identifier of the terminal device to participate in the processing of the access information, the processing of the access information can be achieved through the identifier of the AI ​​task, so that different terminal devices (or users) can obtain the access information of the AI ​​task through the identifier of the AI ​​task, and the privacy of the terminal device (or user) can be protected.

[0215] It should be noted that the identifier of the terminal device may include a cell radio network temporary identifier (C-RNTI), a universal terrestrial radio access network radio network temporary identity (U-RNTI), a random access radio network temporary identity (RA-RNTI), or an international mobile subscriber identifier (IMSI), etc., which is not limited here.

[0216] In one possible implementation, the access information of the AI ​​task indicated by the first information sent by the network device in step S301 includes at least one of the following:

[0217] Information A: Information indicating access conditions for the AI ​​task;

[0218] Information B. Information indicating the information update cycle of the AI ​​task;

[0219] Information C: information indicating the training cycle of the AI ​​task;

[0220] Information D. Information indicating the uplink resource configuration of the business data of the AI ​​task;

[0221] Information E. Information indicating the downlink resource configuration of the service data of the AI ​​task;

[0222] Information F: Information indicating the codebook of the business data of the AI ​​task;

[0223] Information G. Information indicating the transmission mode of the business data of the AI ​​task;

[0224] Information H. Information indicating uplink transmission parameters of the service data of the AI ​​task;

[0225] Information I: Information indicating downlink transmission parameters of the service data of the AI ​​task.

[0226] Specifically, in the access information of the AI ​​task indicated by the first information, the access information of the AI ​​task includes at least one of the above items, so that the recipient of the first information obtains various types of access information related to the AI ​​task through at least one item, thereby improving the flexibility of the solution implementation.

[0227] In one possible implementation, in the access information of the AI ​​task, the access condition indicated by the information A (i.e., the information indicating the access condition of the AI ​​task) includes at least one of the following:

[0228] Condition 1. The identification range of the terminal devices accessing the AI ​​task;

[0229] Condition 2. The random number threshold for accessing the AI ​​task;

[0230] Condition 3. Access the performance indicator threshold of the AI ​​task;

[0231] Condition 4. The start time of the AI ​​task;

[0232] Condition 5. Access the termination time of the AI ​​task.

[0233] Exemplarily, for the above-mentioned condition 1, it can be understood that condition 1 is satisfied when the identification range is satisfied, that is, the identification range is used to indicate that the terminal device within a specific identification (identify, ID) range satisfies condition 1. For example, the identification range may include a lower limit of the ID, so that when the user identification of the terminal device is greater than or equal to the lower limit, it can be determined that the terminal device meets the access conditions of the AI ​​task; for another example, the identification range may include an upper limit of the ID, so that when the user identification of the terminal device is less than or equal to the lower limit, it can be determined that the terminal device meets the access conditions of the AI ​​task; for another example, the identification range may include the value of the modulus Q, so that when the result of the value of the terminal device's user identification modulo Q is 0, it can be determined that the terminal device meets the access conditions of the AI ​​task.

[0234] For example, for the above condition 2, it can be understood that condition 2 is satisfied when the probability threshold is met, that is, the terminal device locally generates a random number, and condition 2 is satisfied when the random number generated by the terminal device is greater than or less than the random number threshold.

[0235] Exemplarily, the above-mentioned condition 3 can be understood as satisfying condition 3 when the performance indicator threshold is met, that is, when the local performance of the terminal device is greater than or equal to the performance indicator threshold, the terminal device can determine that condition 3 is satisfied. For example, the performance may include one or more indicators of AI training results (such as gradient variance, the distance between the local model and the global model, etc.), indicators of AI processing performance (such as model performance, AI computing power performance, AI split learning ability, etc.), etc.

[0236] For example, the above condition 4 can be understood as satisfying the condition 4 when sufficient computing power is available to execute the AI ​​task at the starting moment. That is, the terminal device may need computing power to execute local applications locally at the starting moment. If the terminal device still has sufficient computing power at the starting moment, it can be determined that the terminal device meets condition 4.

[0237] For example, the above condition 5 can be understood as satisfying the condition 5 when there is sufficient computing power to execute the AI ​​task before the termination time. That is, the terminal device may need computing power to execute local applications locally before the termination time. If the terminal device still has sufficient computing power before the termination time, it can be determined that the terminal device meets condition 5.

[0238] Therefore, in the access information of the AI ​​task indicated by the first information, the information used to indicate the access conditions of the AI ​​task may include at least one of the above items, so that the network device can flexibly configure the access conditions of the AI ​​task and improve the flexibility of the solution implementation.

[0239] In one possible implementation, in the access information of the AI ​​task, the information update period indicated by the above information can be understood as the period for updating the uplink and downlink transmission parameters of the service data of the AI ​​task.

[0240] In one possible implementation, in the access information of the AI ​​task, the training cycle indicated by the above information C can be understood as the training cycle of the AI ​​task when the AI ​​task is multi-node joint training (such as federated training / federated learning, etc.).

[0241] In one possible implementation, in the access information of the AI ​​task, the uplink resource configuration indicated by the above information D and / or the downlink resource configuration indicated by the information E can be understood as resources used to configure the uplink data and / or downlink data related to the AI ​​task, such as one or more time domain resources, frequency domain resources, code domain resources, etc.

[0242] In one possible implementation, in the access information of the AI ​​task, the codebook indicated by the above information F is used to transmit the uplink data and / or downlink data related to the AI ​​task. Taking the codebook used to transmit the uplink data related to the AI ​​task as an example, the codebook indicated by the information F can be the codebook used to transmit the uplink data, wherein the codebook includes a set of codewords, and after processing the local business data (such as quantization), it is mapped to the corresponding codeword according to the preset mapping rules. For example, if the quantization range of a data is 0 to 255, corresponding to 256 codewords, and the specific quantization is 17, codeword 17 is selected for transmission.

[0243] In one possible implementation, in the access information of the AI ​​task, the transmission mode of the service data of the AI ​​task indicated by the information G includes any one of the following:

[0244] A first transmission mode (which may be referred to as a traditional transmission mode) indicates that at least one of quantization processing, coding and modulation processing, and processing based on an identifier of the AI ​​task is performed on the service data of the AI ​​task; wherein transmission resources of at least two terminal devices in the first transmission mode are orthogonal;

[0245] A second transmission mode (which may be referred to as an analog transmission mode) indicates that at least one of third-order quantization modulation processing, pre-equalization superposition transmission processing, and public codebook-based coding and modulation processing is performed on the service data of the AI ​​task;

[0246] A third transmission mode (which may be called a non-orthogonal transmission mode) indicates that at least one of quantization processing, coding modulation processing, and processing is performed on the business data of the AI ​​task through the identification of the AI ​​task; wherein, the transmission resources of at least two terminal devices in the third transmission mode are the same.

[0247] Specifically, in the access information of the AI ​​task indicated by the first information, the transmission mode of the service data of the indicated AI task includes at least one of the above items, so that the network device can flexibly configure the transmission mode of the service data of the AI ​​task and improve the flexibility of the solution implementation. In addition, the transmission configuration parameters of different transmission modes are different. For example, the traditional transmission mode and the non-orthogonal transmission mode require the configuration of the coding modulation order MCS and HARQ version, etc.; the analog transmission mode requires the configuration of power control and quantization modulation order, transmission power threshold, etc. Different transmission modes can be indicated using different downlink control information formats. In addition, the uplink and downlink transmission resources can be publicly or jointly indicated.

[0248] Exemplarily, when the number of terminal devices accessing the AI ​​task is greater than or equal to a certain threshold (or when the channel quality between the network device and the terminal device is lower than or equal to a certain threshold), the second transmission mode can be adopted; when the number of terminal devices accessing the task is less than or equal to a certain threshold (when the channel quality between the network device and the terminal device is higher than or equal to the first threshold), the first transmission mode can be adopted; when the number of terminal devices accessing the task is less than or equal to a certain threshold (when the channel quality between the network device and the terminal device is higher than or equal to the second threshold, where the first threshold is greater than the second threshold), the third transmission mode is adopted.

[0249] In one possible implementation, in the access information of the AI ​​task, the uplink transmission configuration parameters indicated by the information H and / or the downlink transmission configuration parameters indicated by the information I include at least one of the following: modulation and coding scheme (MCS), hybrid automatic repeat request (HARQ) version, power control and quantization modulation order, and transmission power threshold. This enables network devices to flexibly configure the transmission configuration parameters of the AI ​​task and improves the flexibility of solution implementation.

[0250] Optionally, one or more of the above information A to information I can be carried by a DCI encrypted with the identifier of the AI ​​task, that is, the first information received by the terminal device can be DCI, and one or more of the above information A to information I can be determined through the DCI.

[0251] Optionally, one or more of the above-mentioned information A to information I may be jointly indicated by other information and the DCI encrypted with the identifier of the AI ​​task. The other information may include a radio resource control (RRC) message or a media access control control element (MAC CE), etc. For example, when the first information sent by the network device indicates one of the information A to information I, a set of values ​​for the one of the items may be configured through an RRC message or a MAC CE, and one of the values ​​in the set may be activated / indicated through the DCI encrypted with the identifier of the AI ​​task, so that the terminal device can clearly identify one of the values ​​corresponding to the one of the items based on the DCI.

[0252] In one possible implementation, after the terminal device determines the access information of the AI ​​task based on the identifier of the AI ​​task and the first information in step S302, the method may further include: the terminal device sending local service data corresponding to the AI ​​task based on the access information of the AI ​​task; and the terminal device receiving integrated service data corresponding to the AI ​​task. Specifically, after the terminal device determines the access information of the AI ​​task based on the identifier of the AI ​​task, the terminal device may receive and send service data related to the AI ​​task based on the access information of the AI ​​task, so that the terminal device can access (or participate in) the AI ​​task.

[0253] For example, if the AI ​​task is a federated learning task, the terminal device determines whether to participate in the current round of federated learning training based on the access information obtained in step S302, for example, by detecting the access conditions indicated by the access information and determining whether they are met. If so, the terminal device may send local service data corresponding to the AI ​​task and receive converged service data corresponding to the AI ​​task based on the access information of the AI ​​task; if not, the terminal device may not perform the local training process corresponding to the AI ​​task.

[0254] As an implementation example, the first information can be carried on a control channel, while the local business data corresponding to the AI ​​task and the fused business data corresponding to the AI ​​task can be carried on a business channel. Taking the AI ​​task as federated learning as an example, as shown in Figure 4, a federated learning control channel (FLCCH) and a business channel (FLTCH) for federated learning transmission can be defined, where the control channel can be mapped to the uplink unsourced random access channel (URACH) and the downlink PDCCH encrypted by FL-RNTI, that is, the relevant control information of the AI ​​task is transmitted through URACH and PDCCH; the business channel can be mapped to the uplink PUSCH and the downlink PDSCH, that is, the relevant business information of the AI ​​task is transmitted through PUSCH and PDSCH.

[0255] In one possible implementation, after the terminal device receives the converged service data corresponding to the AI ​​task, the method may further include: the terminal device sending indication information confirming receipt of the converged service data. This allows the network device to determine whether the terminal device successfully receives the data based on the indication information, which facilitates the network device to subsequently schedule one or more terminal devices participating in the AI ​​task based on the indication information.

[0256] In one possible implementation, before the terminal device sends the local service data corresponding to the AI ​​task based on the access information, the method further includes: the terminal device sending an indication message indicating that local training of the AI ​​task has been completed; and the terminal device receiving the indication message instructing the sending of the local service data. Specifically, through the interaction of the indication message indicating that local training of the AI ​​task has been completed and the indication message instructing the sending of the local service data, the network device can determine the execution status of the local training of the terminal device and schedule the terminal device based on the execution status.

[0257] In addition, through the above-mentioned interaction process, when the network device clearly knows that the number of terminal devices that have completed local training is greater than or equal to a threshold, the network device can schedule the terminal devices to send local business data to ensure that the number of terminal devices accessing the AI ​​task meets the requirements of the threshold.

[0258] As an implementation example, the access information indicated by the network device through the first information can be used to implement timing-based access. For example, when the access information indicated by the network device through the first information contains information A indicating the access condition of the AI ​​task, and the information A contains the aforementioned information indicating the starting time of accessing the AI ​​task (i.e., condition 4), the terminal device performs local training to obtain local business data before the start time arrives, and starts transmitting the local business data when the start time arrives. Similarly, the implementation process can also be referred to for replacing the start time corresponding to condition 4 with the end time corresponding to condition 5. This implementation example can be implemented by Figure 6a, that is, for the terminal device, on the timeline, after the terminal device receives the first information, the terminal device can send local business data at the start time (such as t1) indicated by the access information, and / or, the terminal device can send local business data before the end time (such as t2) indicated by the access information, and / or, the terminal device can receive fused business data at the start time (such as t3) indicated by the access information, and / or, the terminal device can receive fused business data before the end time (such as t4) indicated by the access information.

[0259] As another implementation example, the access information indicated by the network device through the first information can be used to implement request-based access. For example, the access information indicated by the network device through the first information can include the information indicating conditions 1 to 3 above (the information indicating condition 4 above may not be included, that is, the network device may not pre-specify the start time); thus, for the terminal device that completes local training based on the first information to obtain local service data, it can send an indication information to the network device to confirm the reception of the integrated service data; the network device accumulates and detects the number of terminal devices that have completed local training, and when the accumulated number reaches or exceeds a threshold, the network device instructs the terminal device to report by instructing the transmission of the local service data. This implementation example can be implemented by Figure 6b, that is, for the terminal device, on the timeline, after the terminal device receives the first information, the terminal device can send an indication information indicating that the local training has been completed after performing local training, and after receiving the indication information from the network device instructing the transmission of the local service data, the terminal device can send local service data on the resources corresponding to the uplink resource configuration indicated by the access information, and / or the terminal device can receive integrated service data on the resources corresponding to the downlink resource configuration indicated by the access information.

[0260] In one possible implementation, before the terminal device receives the first information, the method further includes: the terminal device receives indication information indicating the reporting of capability information for participating in the AI ​​task; the terminal device sends second information, the second information indicating communication capability information and / or AI capability information; wherein the communication capability information includes at least one of channel information and communication frequency information; the AI ​​capability information includes at least one of AI model performance, AI parameters, AI gradient variance, and AI data set size. Specifically, after the terminal device receives the indication information indicating the reporting of capability information for participating in the AI ​​task, the terminal device may also send second information indicating communication capability information and / or AI capability information, so that the network device can clarify the capability information of the terminal device for participating in the AI ​​task based on the second information, and determine the access information of the AI ​​task based on the capability information of one or more terminal devices, so as to schedule the task through the first information indicating the access information of the AI ​​task.

[0261] In one possible implementation, before the terminal device receives the first information, the method further includes: the terminal device receives third information, the third information indicating the release information of the AI ​​task, the third information being obtained by processing the release information through the identifier of the AI ​​task; the terminal device sends fourth information, the fourth information being used to indicate registration to the AI ​​task, the fourth information including at least one of the following: the AI ​​capability information of the terminal device (for example, the AI ​​capability information includes at least one of AI model performance, AI parameters, AI gradient variance, and AI data set size), the identifier of the terminal device. Specifically, the terminal device can also receive third information indicating the release information of the AI ​​task, and the third information is obtained by processing the release information through the identifier of the AI ​​task, so that the terminal device can obtain the release information based on the identifier of the AI ​​task, and then send fourth information indicating registration to the AI ​​task to the network device, and realize the release process and registration process of the AI ​​task through the interaction of the above-mentioned third and fourth information.

[0262] Optionally, the method further includes: the terminal device receiving indication information indicating confirmation of receipt of the fourth information. Specifically, the terminal device may also receive indication information indicating confirmation of receipt of the fourth information, so that the terminal device determines whether the network device has successfully received the fourth information based on the indication information, thereby determining whether the terminal device has successfully registered with the AI ​​task.

[0263] Optionally, the published information indicated by the third information includes at least one of the following: an identifier of the AI ​​task, a public codebook reported by the user information, and information indicating transmission resources. Specifically, the published information received by the terminal device may include at least one of the above items, enabling the terminal device to obtain relevant information about the AI ​​task based on the at least one item and send fourth information based on the information to implement the AI ​​task registration process.

[0264] Optionally, the third information may not be obtained by processing the published information through the identifier of the AI ​​task, wherein the published information of the AI ​​task indicated by the third information can be used to determine the identifier of the AI ​​task.

[0265] For example, when the published information indicated by the third information includes the identifier of the AI ​​task, the terminal device can obtain the identifier of the AI ​​task based on the published information.

[0266] For another example, the terminal device and the network device can pre-configure a mapping relationship between one or more time-frequency resources (such as a certain frequency point, a certain frequency band, etc.) and the identifiers of one or more AI tasks. When the release information of the AI ​​task indicated by the third information includes indication information of the transmission resource, the terminal device can determine the transmission resource based on the indication information, and then the terminal device can determine the identifier of the AI ​​task based on the mapping relationship.

[0267] For example, the published information indicated by the third information may also include the task identifier (task ID) of the AI ​​task. The terminal device and the network device may pre-configure a mapping relationship between one or more task IDs and the identifiers of one or more AI tasks, so that after the terminal device determines the task ID based on the indication information, the terminal device may also determine the identifier of the AI ​​task based on the task ID.

[0268] It is understandable that in the above-mentioned publishing process and registration process, the network device publishes the federated learning task, and the terminal device reports capabilities, data, participation / departure and other information. During the publishing process, the network device sends the federated learning task through the third information of the broadcast channel or the paging channel. The publishing information may include the task / model ID, the access resources reported by the user information, etc. (wherein, the access resource or task ID can be used to determine the RNTI for subsequent control information and data transmission of the federated learning task, that is, the RNTI of the AI ​​task; alternatively, the RNTI of the AI ​​task can also be sent by the network device to the terminal device to identify the federated learning task).

[0269] Exemplarily, when the fourth information includes the AI ​​capability information of the terminal device, the resource carrying the AI ​​capability information of the terminal device can be determined by a public codebook, that is, the terminal device can select a codeword from the public codebook for transmission based on the AI ​​capability information of the terminal device, wherein the public codebook can be composed of multiple codewords constructed such as a Gaussian codebook, and the codeword index can be mapped to the AI ​​capability information of the terminal device, so that the network device can determine the AI ​​capability information of the terminal device based on the detected transmission codeword. For example, the transmission format of the information is shown in Figure 5. The first type can be "direct transmission" in Figure 5, that is, the terminal device selects a codeword from the public codebook to identify the terminal device, and the AI ​​capability information (referred to as information in Figure 5) is attached to the codeword and transmitted in a traditional manner (the traditional transmission method can be to send the information after channel coding and modulation). The second type can be "sequential transmission" in Figure 5, that is, the public codebook can be used to identify the terminal device and can also be used to indicate the AI ​​capability information of the terminal device, wherein the terminal device identification is indicated by the public codebook, that is, one codeword corresponds to one identification; the capability information is also indicated by the public codebook, that is, one codeword corresponds to one level of capability. Afterwards, the network device detects the sent codeword from the received fourth information and confirms each terminal device with the codeword ID. Optionally, the codebook and ID can be shared by multiple terminal devices, that is, different federated learning tasks can share the same codebook and ID.

[0270] As an implementation example, let's take federated learning as an AI task. As shown in Figure 7, the interaction process of the third and fourth information can be called "user registration", the interaction process of the first information used to indicate the access information of the AI ​​task can be called "user selection", the process of the terminal device determining and sending local service data can be called "training and uploading", and the process of the network device determining and sending integrated service data can be called "aggregation and distribution". In Figure 7, the terminal device can register to the AI ​​task through the user registration process, and then perform a round of "user selection, training and uploading, aggregation and distribution" to complete a round of federated learning. After completing this round of learning, the next round of federated learning may require changing the access information. To this end, the network device and the terminal device can re-execute the "user selection, training and uploading, aggregation and distribution" process of the next round of learning until the federated learning task is completed.

[0271] Based on the technical solution shown in Figure 3, after a terminal device receives first information indicating access information for an AI task, the terminal device can determine the access information for the AI ​​task based on the identifier of the AI ​​task, wherein the first information is obtained by processing the access information for the AI ​​task using the identifier of the AI ​​task. In other words, when a network device indicates access information for an AI task via the first information, the terminal device can obtain the access information for the AI ​​task from the first information using the identifier of the AI ​​task, allowing the terminal device to subsequently access the AI ​​task based on the access information for the AI ​​task, thereby enabling the terminal device's computing power to be used for the AI ​​task, thereby enabling the execution of the AI ​​task in the communication network.

[0272] Furthermore, the first information sent by the network device is processed using the AI ​​task identifier. After receiving the first information, the terminal device can obtain the access information for the AI ​​task using the AI ​​task identifier. Thus, when the number of terminal devices is greater than one, different terminal devices can all obtain the access information for the AI ​​task using the AI ​​task identifier, reducing implementation complexity and improving efficiency.

[0273] Referring to Figure 8 , an embodiment of the present application provides a communication device 800. This communication device 800 can implement the functions of a terminal device or network device in the above-described method embodiments, thereby also achieving the beneficial effects of the above-described method embodiments. In the embodiments of the present application, the communication device 800 can be a terminal device or network device, or it can be an integrated circuit or component within the terminal device or network device, such as a chip. The following embodiments are described using the communication device 800 as an example of a terminal device or network device.

[0274] In one possible implementation, when the device 800 is used to execute the method executed by the terminal device in any of the aforementioned embodiments, the device 800 includes a processing unit 801 and a transceiver unit 802; the transceiver unit 802 is used to receive first information, which indicates the access information of the AI ​​task, and the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task; the processing unit 801 is used to determine the access information of the AI ​​task based on the identifier of the AI ​​task and the first information.

[0275] In one possible implementation, the access information of the AI ​​task includes at least one of the following:

[0276] Information indicating the access conditions of the AI ​​task; information indicating the information update period of the AI ​​task; information indicating the training period of the AI ​​task; information indicating the uplink resource configuration of the service data of the AI ​​task; information indicating the downlink resource configuration of the service data of the AI ​​task; information indicating the codebook of the service data of the AI ​​task; information indicating the transmission mode of the service data of the AI ​​task; information indicating the uplink transmission parameters of the service data of the AI ​​task; information indicating the downlink transmission parameters of the service data of the AI ​​task.

[0277] In one possible implementation, the information indicating the access condition of the AI ​​task includes at least one of the following:

[0278] The identification range of terminal devices that access the AI ​​task; the random number threshold for accessing the AI ​​task; the performance indicator threshold for accessing the AI ​​task; the start time for accessing the AI ​​task; and the end time for accessing the AI ​​task.

[0279] In one possible implementation, the transmission mode of the business data of the AI ​​task includes any of the following:

[0280] A first transmission mode, wherein the first transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing using an identifier of the AI ​​task on service data of the AI ​​task; wherein transmission resources of at least two terminal devices in the first transmission mode are orthogonal;

[0281] A second transmission mode, where the second transmission mode indicates performing at least one of a third-order quantization modulation process, a pre-equalization superposition transmission process, and a coding modulation process based on a public codebook on the service data of the AI ​​task;

[0282] A third transmission mode, wherein the third transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing on the business data of the AI ​​task through the identifier of the AI ​​task; wherein the transmission resources of at least two terminal devices in the third transmission mode are the same.

[0283] In a possible implementation, the uplink transmission configuration parameter and / or the downlink transmission configuration parameter includes at least one of the following:

[0284] Coding modulation scheme MCS, hybrid automatic repeat request HARQ version, power control and quantization modulation order, transmission power threshold.

[0285] In a possible implementation, the transceiver unit 802 is further configured to send local service data corresponding to the AI ​​task based on the access information of the AI ​​task; the transceiver unit 802 is further configured to receive integrated service data corresponding to the AI ​​task.

[0286] In a possible implementation, the transceiver unit 802 is further configured to send indication information indicating confirmation of receiving the converged service data.

[0287] In one possible implementation, the transceiver unit 802 is further used to send indication information indicating that the local training of the AI ​​task has been completed; the transceiver unit 802 is further used to receive indication information instructing to send the local business data.

[0288] In a possible implementation, the identifier of the AI ​​task is a radio network temporary identifier RNTI associated with the AI ​​task.

[0289] In one possible implementation, the transceiver unit 802 is further used to receive indication information indicating reporting capability information for participating in the AI ​​task; the transceiver unit 802 is further used to send second information, which indicates communication capability information and / or AI capability information; wherein the communication capability information includes at least one of channel information and communication frequency information; and the AI ​​capability information includes at least one of AI model performance, AI parameters, AI gradient variance, and AI data set size.

[0290] In one possible implementation, the transceiver unit 802 is further used to receive third information, which indicates the release information of the AI ​​task, and the third information is obtained by processing the release information through the identifier of the AI ​​task; the transceiver unit 802 is also used to send fourth information, which is used to indicate registration to the AI ​​task, and the fourth information includes at least one of the following: AI capability information of the terminal device, and the identifier of the terminal device.

[0291] In a possible implementation, the transceiver unit 802 is further configured to send indication information indicating confirmation of receiving the fourth information.

[0292] In a possible implementation, the published information includes at least one of the following: an identifier of the AI ​​task, a public codebook reported by the user information, and indication information of transmission resources.

[0293] In one possible implementation, when the device 800 is used to execute the method executed by the network device in any of the foregoing embodiments, the device 800 includes a processing unit 801 and a transceiver unit 802; the transceiver unit 802 is used to determine the first information, which indicates the access information of the artificial intelligence AI task, and the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task; the transceiver unit 802 is used to send the first information.

[0294] In one possible implementation, the access information of the AI ​​task includes at least one of the following:

[0295] Information indicating the access conditions of the AI ​​task; information indicating the information update period of the AI ​​task; information indicating the training period of the AI ​​task; information indicating the uplink resource configuration of the service data of the AI ​​task; information indicating the downlink resource configuration of the service data of the AI ​​task; information indicating the codebook of the service data of the AI ​​task; information indicating the transmission mode of the service data of the AI ​​task; information indicating the uplink transmission parameters of the service data of the AI ​​task; information indicating the downlink transmission parameters of the service data of the AI ​​task.

[0296] In one possible implementation, the information indicating the access condition of the AI ​​task includes at least one of the following:

[0297] The identification range of terminal devices that access the AI ​​task; the random number threshold for accessing the AI ​​task; the performance indicator threshold for accessing the AI ​​task; the start time for accessing the AI ​​task; and the end time for accessing the AI ​​task.

[0298] In one possible implementation, the transmission mode of the business data of the AI ​​task includes any of the following:

[0299] A first transmission mode, wherein the first transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing using an identifier of the AI ​​task on service data of the AI ​​task; wherein transmission resources of at least two terminal devices in the first transmission mode are orthogonal;

[0300] A second transmission mode, where the second transmission mode indicates performing at least one of a third-order quantization modulation process, a pre-equalization superposition transmission process, and a coding modulation process based on a public codebook on the service data of the AI ​​task;

[0301] A third transmission mode, wherein the third transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing on the business data of the AI ​​task through the identifier of the AI ​​task; wherein the transmission resources of at least two terminal devices in the third transmission mode are the same.

[0302] In a possible implementation, the uplink transmission configuration parameter and / or the downlink transmission configuration parameter includes at least one of the following: a coding modulation scheme MCS, a hybrid automatic repeat request HARQ version, a power control and quantization modulation order, and a transmission power threshold.

[0303] In a possible implementation, the transceiver unit 802 is further configured to receive local service data corresponding to the AI ​​task; the transceiver unit 802 is further configured to send fused service data corresponding to the AI ​​task.

[0304] In a possible implementation, the transceiver unit 802 is further configured to receive indication information indicating confirmation of receiving the converged service data.

[0305] In one possible implementation, the transceiver unit 802 is further used to receive indication information indicating that the local training of the AI ​​task has been completed; the transceiver unit 802 is further used to send indication information indicating that the local business data is sent.

[0306] In a possible implementation, the identifier of the AI ​​task is a radio network temporary identifier RNTI associated with the AI ​​task.

[0307] In one possible implementation, the transceiver unit 802 is further used to send indication information indicating reporting capability information for participating in the AI ​​task; the transceiver unit 802 is further used to receive second information, which indicates communication capability information and / or AI capability information; wherein the communication capability information includes at least one of channel information and communication frequency information; and the AI ​​capability information includes at least one of AI model performance, AI parameters, AI gradient variance, and AI data set size.

[0308] In one possible implementation, the transceiver unit 802 is also used to send third information, which indicates the release information of the AI ​​task, and the third information is obtained by processing the release information through the identifier of the AI ​​task; the transceiver unit 802 is also used to receive fourth information, which is used to indicate registration to the AI ​​task, and the fourth information includes at least one of the following: AI capability information of the terminal device, and the identifier of the terminal device.

[0309] In a possible implementation, the published information includes at least one of the following: an identifier of the AI ​​task, a public codebook reported by the user information, and indication information of transmission resources.

[0310] It should be noted that, for details on the information execution process of the units of the above-mentioned communication device 800, please refer to the description in the method embodiment shown above in this application, and no further details will be given here.

[0311] Please refer to Fig. 9, which is another schematic structural diagram of a communication device 900 provided in this application. The communication device 900 at least includes an input and output interface 902. The communication device 900 may be a chip or an integrated circuit.

[0312] Optionally, the communication device further includes a logic circuit 901 .

[0313] The transceiver unit 802 shown in FIG8 may be a communication interface, which may be the input / output interface 902 in FIG9 , which may include an input interface and an output interface. Alternatively, the communication interface may be a transceiver circuit, which may include an input interface circuit and an output interface circuit.

[0314] Optionally, the input-output interface 902 is used to receive first information, which indicates access information of the AI ​​task, and the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task; the logic circuit 901 is used to determine the access information of the AI ​​task based on the identifier of the AI ​​task and the first information.

[0315] Optionally, the logic circuit 901 is used to determine first information, where the first information indicates access information of the AI ​​task, and the first information is obtained by processing the access information of the AI ​​task through the identifier of the AI ​​task; the input and output interface 902 is used to send the first information.

[0316] The logic circuit 901 and the input / output interface 902 may also execute other steps executed by the terminal device or the network device in any embodiment and achieve corresponding beneficial effects, which will not be described in detail here.

[0317] In a possible implementation, the processing unit 801 shown in FIG. 8 may be the logic circuit 901 in FIG. 9 .

[0318] Optionally, the logic circuit 901 may be a processing device, and the functions of the processing device may be partially or entirely implemented by software. The functions of the processing device may be partially or entirely implemented by software.

[0319] Optionally, the processing device may include a memory and a processor, wherein the memory is used to store a computer program, and the processor reads and executes the computer program stored in the memory to perform corresponding processing and / or steps in any one of the method embodiments.

[0320] Alternatively, the processing device may include only a processor. A memory for storing the computer program is located outside the processing device, and the processor is connected to the memory via circuits / wires to read and execute the computer program stored in the memory. The memory and processor may be integrated or physically separate.

[0321] Optionally, the processing device may be one or more chips, or one or more integrated circuits. For example, the processing device may be one or more field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), system-on-chips (SoCs), central processor units (CPUs), network processors (NPs), digital signal processors (DSPs), microcontroller units (MCUs), programmable logic devices (PLDs), or other integrated chips, or any combination of the above chips or processors.

[0322] Please refer to Figure 10, which shows the communication device 1000 involved in the above embodiments provided in an embodiment of the present application. The communication device 1000 can specifically be the communication device as a terminal device in the above embodiments. The communication device 1000 shown in Figure 10 can be a terminal device or a component in a terminal device.

[0323] Herein, a possible logical structure diagram of the communication device 1000 is shown. The communication device 1000 may include but is not limited to at least one processor 1001 and a communication port 1002 .

[0324] Further optionally, the device may also include at least one of a memory 1003 and a bus 1004. In an embodiment of the present application, the at least one processor 1001 is used to control and process the actions of the communication device 1000.

[0325] In addition, the processor 1001 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 device, a transistor logic device, a hardware component, 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, and so on. Those skilled in the art will clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0326] It should be noted that the communication device 1000 shown in Figure 10 can be specifically used to implement the steps implemented by the terminal device in the aforementioned method embodiment and achieve the corresponding technical effects of the terminal device. The specific implementation methods of the communication device shown in Figure 10 can refer to the description in the aforementioned method embodiment and will not be repeated here.

[0327] Please refer to Figure 11, which is a structural diagram of the communication device 1100 involved in the above-mentioned embodiments provided in an embodiment of the present application. The communication device 1100 can specifically be a communication device as a network device in the above-mentioned embodiments. The communication device 1100 shown in Figure 11 can be a network device or a component in a network device, wherein the structure of the communication device can refer to the structure shown in Figure 11.

[0328] The communication device 1100 includes at least one processor 1111 and at least one network interface 1114. Further optionally, the communication device also includes at least one memory 1112, at least one transceiver 1113 and one or more antennas 1115. The processor 1111, the memory 1112, the transceiver 1113 and the network interface 1114 are connected, for example, via a bus. In an embodiment of the present application, the connection may include various interfaces, transmission lines or buses, etc., which are not limited in this embodiment. The antenna 1115 is connected to the transceiver 1113. The network interface 1114 is used to enable the communication device to communicate with other communication devices through a communication link. For example, the network interface 1114 may include a network interface between the communication device and the core network device, such as an S1 interface, and the network interface may include a network interface between the communication device and other communication devices (such as other network devices or core network devices), such as an X2 or Xn interface.

[0329] Processor 1111 is primarily used to process communication protocols and communication data, control the entire communication device, execute software programs, and process software program data, for example, to support the communication device in performing the actions described in the embodiments. The communication device may include a baseband processor and a central processing unit. The baseband processor is primarily used to process communication protocols and communication data, while the central processing unit is primarily used to control the entire terminal device, execute software programs, and process software program data. Processor 1111 in Figure 11 may integrate the functions of both a baseband processor and a central processing unit. Those skilled in the art will appreciate that the baseband processor and the central processing unit may also be independent processors interconnected via a bus or other technology. Those skilled in the art will appreciate that a terminal device may include multiple baseband processors to accommodate different network standards, multiple central processing units to enhance its processing capabilities, and various components of the terminal device may be connected via various buses. The baseband processor may also be referred to as a baseband processing circuit or a baseband processing chip. The central processing unit may also be referred to as a central processing circuit or a central processing chip. The functionality for processing communication protocols and communication data may be built into the processor or stored in memory as a software program, which is executed by the processor to implement the baseband processing functionality.

[0330] The memory is primarily used to store software programs and data. Memory 1112 can exist independently and be connected to processor 1111. Alternatively, memory 1112 can be integrated with processor 1111, for example, within a single chip. Memory 1112 can store program code for executing the technical solutions of the embodiments of the present application, and execution is controlled by processor 1111. The various computer program codes executed can also be considered drivers for processor 1111.

[0331] Figure 11 shows only one memory and one processor. In an actual terminal device, there may be multiple processors and multiple memories. The memory may also be referred to as a storage medium or a storage device. The memory may be a storage element on the same chip as the processor, i.e., an on-chip storage element, or an independent storage element, which is not limited in the present embodiment.

[0332] The transceiver 1113 can be used to support the reception or transmission of radio frequency signals between the communication device and the terminal. The transceiver 1113 can be connected to the antenna 1115. The transceiver 1113 includes a transmitter Tx and a receiver Rx. Specifically, one or more antennas 1115 can receive radio frequency signals. The receiver Rx of the transceiver 1113 is used to receive the radio frequency signal from the antenna, convert the radio frequency signal into a digital baseband signal or a digital intermediate frequency signal, and provide the digital baseband signal or digital intermediate frequency signal to the processor 1111 so that the processor 1111 can further process the digital baseband signal or digital intermediate frequency signal, such as demodulation and decoding. In addition, the transmitter Tx in the transceiver 1113 is also used to receive a modulated digital baseband signal or digital intermediate frequency signal from the processor 1111, convert the modulated digital baseband signal or digital intermediate frequency signal into a radio frequency signal, and transmit the radio frequency signal through one or more antennas 1115. Specifically, the receiver Rx can selectively perform one or more stages of down-mixing and analog-to-digital conversion on the RF signal to obtain a digital baseband signal or a digital intermediate frequency signal. The order of the down-mixing and analog-to-digital conversion processes is adjustable. The transmitter Tx can selectively perform one or more stages of up-mixing and digital-to-analog conversion on the modulated digital baseband signal or digital intermediate frequency signal to obtain a RF signal. The order of the up-mixing and digital-to-analog conversion processes is adjustable. The digital baseband signal and the digital intermediate frequency signal may be collectively referred to as digital signals.

[0333] The transceiver 1113 may also be referred to as a transceiver unit, a transceiver, a transceiver device, etc. Optionally, a device in the transceiver unit that implements a receiving function may be referred to as a receiving unit, and a device in the transceiver unit that implements a transmitting function may be referred to as a transmitting unit. That is, the transceiver unit includes a receiving unit and a transmitting unit. The receiving unit may also be referred to as a receiver, an input port, a receiving circuit, etc., and the transmitting unit may be referred to as a transmitter, a transmitter, or a transmitting circuit, etc.

[0334] It should be noted that the communication device 1100 shown in Figure 11 can be specifically used to implement the steps implemented by the network device in the aforementioned method embodiment, and to achieve the corresponding technical effects of the network device. The specific implementation methods of the communication device 1100 shown in Figure 11 can refer to the description in the aforementioned method embodiment, and will not be repeated here one by one.

[0335] An embodiment of the present application also provides a computer-readable storage medium, which is used to store one or more computer-executable instructions. When the computer-executable instructions are executed by a processor, the processor executes the method described in the possible implementation methods of the terminal device or network device in the above embodiments.

[0336] An embodiment of the present application also provides a computer program product (or computer program). When the computer program product is executed by the processor, the processor executes the method of the possible implementation mode of the above-mentioned terminal device or network device.

[0337] An embodiment of the present application also provides a chip system, which includes at least one processor for supporting a communication device to implement the functions involved in the possible implementation methods of the above-mentioned communication device. Optionally, the chip system also includes an interface circuit, which provides program instructions and / or data to the at least one processor. In one possible design, the chip system may also include a memory, which is used to store the necessary program instructions and data for the communication device. The chip system can be composed of chips, or it can include chips and other discrete devices, wherein the communication device can specifically be a terminal device or network device in the aforementioned method embodiment.

[0338] An embodiment of the present application also provides a communication system, and the network system architecture includes the terminal device and network device in any of the above embodiments.

[0339] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0340] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0341] In addition, the functional units in the various embodiments of the present application can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the contributing part or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

Claims

1. A communication method, characterized in that: include: Receive first information, where the first information indicates access information of an artificial intelligence (AI) task, and the first information is obtained by processing the access information of the AI ​​task through an identifier of the AI ​​task; Access information of the AI ​​task is determined according to the identifier of the AI ​​task and the first information.

2. The method according to claim 1, characterized in that The access information of the AI ​​task includes at least one of the following: Information indicating access conditions for the AI ​​task; Information indicating an information update period of the AI ​​task; Information indicating a training period of the AI ​​task; Information indicating uplink resource configuration of the service data of the AI ​​task; Information indicating downlink resource configuration of service data of the AI ​​task; Information indicating a codebook of business data of the AI ​​task; Information indicating a transmission mode of business data of the AI ​​task; Information indicating uplink transmission parameters of service data of the AI ​​task; Information indicating downlink transmission parameters of the business data of the AI ​​task.

3. The method according to claim 2, characterized in that The information indicating the access condition of the AI ​​task includes at least one of the following: The identification range of terminal devices accessing the AI ​​task; A random number threshold for accessing the AI ​​task; Access to the performance indicator threshold of the AI ​​task; The start time of accessing the AI ​​task; The termination time of the accessed AI task.

4. The method according to claim 2 or 3, characterized in that: The transmission mode of the business data of the AI ​​task includes any of the following: A first transmission mode, wherein the first transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing by an identifier of the AI ​​task on the service data of the AI ​​task; wherein transmission resources of at least two terminal devices in the first transmission mode are orthogonal; A second transmission mode, wherein the second transmission mode indicates performing at least one of a third-order quantization modulation process, a pre-equalization superposition transmission process, and a coding modulation process based on a common codebook on the service data of the AI ​​task; A third transmission mode, wherein the third transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing through the identifier of the AI ​​task on the business data of the AI ​​task; wherein the transmission resources of at least two terminal devices in the third transmission mode are the same.

5. The method according to any one of claims 2 to 4, characterized in that: The uplink transmission configuration parameter and / or the downlink transmission configuration parameter includes at least one of the following: Coding modulation scheme MCS, hybrid automatic repeat request HARQ version, power control and quantization modulation order, transmission power threshold.

6. The method according to any one of claims 1 to 5, characterized in that: After determining the access information of the AI ​​task according to the identifier of the AI ​​task and the first information, the method further includes: Sending local service data corresponding to the AI ​​task based on the access information of the AI ​​task; Receive the fused business data corresponding to the AI ​​task.

7. The method according to claim 6, characterized in that Before sending the local service data corresponding to the AI ​​task based on the access information, the method further includes: Sending an indication that local training of the AI ​​task has been completed; Receive indication information indicating sending the local service data.

8. The method according to any one of claims 1 to 7, characterized in that: The identifier of the AI ​​task is a wireless network temporary identifier RNTI associated with the AI ​​task.

9. The method according to any one of claims 1 to 8, characterized in that: Before receiving the first information, the method further includes: Receiving instruction information for instructing to report capability information for participating in the AI ​​task; Send second information, wherein the second information indicates communication capability information and / or AI capability information; wherein the communication capability information includes at least one of channel information and communication frequency information; and the AI ​​capability information includes at least one of AI model performance, AI parameters, AI gradient variance, and AI data set size.

10. The method according to any one of claims 1 to 9, characterized in that: Before receiving the first information, the method further includes: receiving third information, where the third information indicates the release information of the AI ​​task, and the third information is obtained by processing the release information through the identifier of the AI ​​task; Send fourth information, where the fourth information is used to indicate registration to the AI ​​task, and the fourth information includes at least one of the following: AI capability information of the terminal device and an identifier of the terminal device.

11. The method according to claim 10, characterized in that The published information includes at least one of the following: The identifier of the AI ​​task, the public codebook reported by the user information, and the indication information of the transmission resources.

12. A communication method, characterized in that: include: Determine first information, where the first information indicates access information of an artificial intelligence (AI) task, and the first information is obtained by processing the access information of the AI ​​task through an identifier of the AI ​​task; The first information is sent.

13. The method according to claim 12, characterized in that The access information of the AI ​​task includes at least one of the following: Information indicating access conditions for the AI ​​task; Information indicating an information update period of the AI ​​task; Information indicating a training period of the AI ​​task; Information indicating uplink resource configuration of the service data of the AI ​​task; Information indicating downlink resource configuration of service data of the AI ​​task; Information indicating a codebook of business data of the AI ​​task; Information indicating a transmission mode of business data of the AI ​​task; Information indicating uplink transmission parameters of service data of the AI ​​task; Information indicating downlink transmission parameters of the business data of the AI ​​task.

14. The method according to claim 13, characterized in that The information indicating the access condition of the AI ​​task includes at least one of the following: The identification range of terminal devices accessing the AI ​​task; A random number threshold for accessing the AI ​​task; Access to the performance indicator threshold of the AI ​​task; The start time of accessing the AI ​​task; The termination time of the accessed AI task.

15. The method according to claim 13 or 14, characterized in that The transmission mode of the business data of the AI ​​task includes any of the following: A first transmission mode, wherein the first transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing by an identifier of the AI ​​task on the service data of the AI ​​task; wherein transmission resources of at least two terminal devices in the first transmission mode are orthogonal; A second transmission mode, wherein the second transmission mode indicates performing at least one of a third-order quantization modulation process, a pre-equalization superposition transmission process, and a coding modulation process based on a common codebook on the service data of the AI ​​task; A third transmission mode, wherein the third transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing through the identifier of the AI ​​task on the business data of the AI ​​task; wherein the transmission resources of at least two terminal devices in the third transmission mode are the same.

16. The method according to any one of claims 13 to 15, characterized in that The uplink transmission configuration parameter and / or the downlink transmission configuration parameter includes at least one of the following: Coding modulation scheme MCS, hybrid automatic repeat request HARQ version, power control and quantization modulation order, transmission power threshold.

17. The method according to any one of claims 12 to 16, characterized in that: After sending the first information, the method further includes: Receiving local business data corresponding to the AI ​​task; Send the fused business data corresponding to the AI ​​task.

18. The method according to claim 17, characterized in that Before receiving the local business data corresponding to the AI ​​task, the method further includes: Receiving an indication that local training of the AI ​​task has been completed; The sending instruction indicates the sending of the local service data.

19. The method according to any one of claims 12 to 18, characterized in that The identifier of the AI ​​task is a wireless network temporary identifier RNTI associated with the AI ​​task.

20. The method according to any one of claims 12 to 19, characterized in that Before sending the first information, the method further includes: Sending instruction information for instructing to report capability information for participating in the AI ​​task; Receive second information, wherein the second information indicates communication capability information and / or AI capability information; wherein the communication capability information includes at least one of channel information and communication frequency information; and the AI ​​capability information includes at least one of AI model performance, AI parameters, AI gradient variance, and AI data set size.

21. The method according to any one of claims 12 to 20, characterized in that Before sending the first information, the method further includes: Sending third information, where the third information indicates the release information of the AI ​​task, and the third information is obtained by processing the release information through the identifier of the AI ​​task; Receive fourth information, where the fourth information is used to indicate registration to the AI ​​task, and the fourth information includes at least one of the following: AI capability information of the terminal device, and an identifier of the terminal device.

22. The method according to claim 21, characterized in that The published information includes at least one of the following: The identifier of the AI ​​task, the public codebook reported by the user information, and the indication information of the transmission resources.

23. A communication device, characterized in that: including a processing unit and a transceiver unit; The transceiver unit is used to receive first information, where the first information indicates access information of an artificial intelligence AI task, and the first information is obtained by processing the access information of the AI ​​task through an identifier of the AI ​​task; The processing unit is used to determine the access information of the AI ​​task according to the identifier of the AI ​​task and the first information.

24. The device according to claim 23, characterized in that The access information of the AI ​​task includes at least one of the following: Information indicating access conditions for the AI ​​task; Information indicating an information update period of the AI ​​task; Information indicating a training period of the AI ​​task; Information indicating uplink resource configuration of the service data of the AI ​​task; Information indicating downlink resource configuration of service data of the AI ​​task; Information indicating a codebook of business data of the AI ​​task; Information indicating a transmission mode of business data of the AI ​​task; Information indicating uplink transmission parameters of service data of the AI ​​task; Information indicating downlink transmission parameters of the business data of the AI ​​task.

25. The device according to claim 24, characterized in that The information indicating the access condition of the AI ​​task includes at least one of the following: The identification range of terminal devices accessing the AI ​​task; A random number threshold for accessing the AI ​​task; Access to the performance indicator threshold of the AI ​​task; The start time of accessing the AI ​​task; The termination time of the accessed AI task.

26. The device according to claim 24 or 25, characterized in that The transmission mode of the business data of the AI ​​task includes any of the following: A first transmission mode, wherein the first transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing by an identifier of the AI ​​task on the service data of the AI ​​task; wherein transmission resources of at least two terminal devices in the first transmission mode are orthogonal; A second transmission mode, wherein the second transmission mode indicates performing at least one of a third-order quantization modulation process, a pre-equalization superposition transmission process, and a coding modulation process based on a common codebook on the service data of the AI ​​task; A third transmission mode, wherein the third transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing through the identifier of the AI ​​task on the business data of the AI ​​task; wherein the transmission resources of at least two terminal devices in the third transmission mode are the same.

27. The device according to any one of claims 24 to 26, characterized in that The uplink transmission configuration parameter and / or the downlink transmission configuration parameter includes at least one of the following: Coding modulation scheme MCS, hybrid automatic repeat request HARQ version, power control and quantization modulation order, transmission power threshold.

28. The device according to any one of claims 23 to 27, characterized in that The transceiver unit is further used to send local service data corresponding to the AI ​​task based on the access information of the AI ​​task; The transceiver unit is also used to receive fusion service data corresponding to the AI ​​task.

29. The device according to claim 28, characterized in that The transceiver unit is further used to send indication information indicating that the local training of the AI ​​task has been completed; The transceiver unit is further configured to receive instruction information for instructing to send the local service data.

30. The device according to any one of claims 23 to 29, characterized in that The identifier of the AI ​​task is a wireless network temporary identifier RNTI associated with the AI ​​task.

31. The device according to any one of claims 23 to 30, characterized in that The transceiver unit is further configured to receive instruction information for instructing to report capability information for participating in the AI ​​task; The transceiver unit is also used to send second information, which indicates communication capability information and / or AI capability information; wherein the communication capability information includes at least one of channel information and communication frequency information; the AI ​​capability information includes at least one of AI model performance, AI parameters, AI gradient variance, and AI data set size.

32. The device according to any one of claims 23 to 31, characterized in that The transceiver unit is further used to receive third information, where the third information indicates the release information of the AI ​​task, and the third information is obtained by processing the release information through the identifier of the AI ​​task; The transceiver unit is further used to send fourth information, where the fourth information is used to indicate registration to the AI ​​task, and the fourth information includes at least one of the following: AI capability information of the terminal device, and an identifier of the terminal device.

33. The device according to claim 32, characterized in that The published information includes at least one of the following: The identifier of the AI ​​task, the public codebook reported by the user information, and the indication information of the transmission resources.

34. A communication device, characterized in that: including a processing unit and a transceiver unit; The transceiver unit is used to determine first information, where the first information indicates access information of an artificial intelligence AI task, and the first information is obtained by processing the access information of the AI ​​task through an identifier of the AI ​​task; The transceiver unit is used to send the first information.

35. The device according to claim 34, characterized in that The access information of the AI ​​task includes at least one of the following: Information indicating access conditions for the AI ​​task; Information indicating an information update period of the AI ​​task; Information indicating a training period of the AI ​​task; Information indicating uplink resource configuration of the service data of the AI ​​task; Information indicating downlink resource configuration of service data of the AI ​​task; Information indicating a codebook of business data of the AI ​​task; Information indicating a transmission mode of business data of the AI ​​task; Information indicating uplink transmission parameters of service data of the AI ​​task; Information indicating downlink transmission parameters of the business data of the AI ​​task.

36. The device according to claim 35, characterized in that The information indicating the access condition of the AI ​​task includes at least one of the following: The identification range of terminal devices accessing the AI ​​task; A random number threshold for accessing the AI ​​task; Access to the performance indicator threshold of the AI ​​task; The start time of accessing the AI ​​task; The termination time of the accessed AI task.

37. The device according to claim 35 or 36, characterized in that The transmission mode of the business data of the AI ​​task includes any of the following: The first transmission mode indicates that the service data of the AI ​​task is quantized, coded and modulated. At least one of the processing is performed through the identification of the AI ​​task; wherein the transmission resources of at least two terminal devices in the first transmission mode are orthogonal; A second transmission mode, wherein the second transmission mode indicates performing at least one of a third-order quantization modulation process, a pre-equalization superposition transmission process, and a coding modulation process based on a common codebook on the service data of the AI ​​task; A third transmission mode, wherein the third transmission mode indicates performing at least one of quantization processing, coding modulation processing, and processing through the identifier of the AI ​​task on the business data of the AI ​​task; wherein the transmission resources of at least two terminal devices in the third transmission mode are the same.

38. The device according to any one of claims 35 to 37, characterized in that The uplink transmission configuration parameter and / or the downlink transmission configuration parameter includes at least one of the following: Coding modulation scheme MCS, hybrid automatic repeat request HARQ version, power control and quantization modulation order, transmission power threshold.

39. The device according to any one of claims 34 to 38, characterized in that The transceiver unit is also used to receive local business data corresponding to the AI ​​task; The transceiver unit is also used to send the fusion service data corresponding to the AI ​​task.

40. The device according to claim 39, characterized in that The transceiver unit is also used to receive indication information indicating that the local training of the AI ​​task has been completed; The transceiver unit is further configured to send indication information for instructing to send the local service data.

41. The device according to any one of claims 34 to 40, characterized in that The identifier of the AI ​​task is a wireless network temporary identifier RNTI associated with the AI ​​task.

42. The device according to any one of claims 34 to 41, characterized in that The transceiver unit is further used to send instruction information for instructing to report capability information for participating in the AI ​​task; The transceiver unit is also used to receive second information, which indicates communication capability information and / or AI capability information; wherein the communication capability information includes at least one of channel information and communication frequency information; and the AI ​​capability information includes at least one of AI model performance, AI parameters, AI gradient variance, and AI data set size.

43. The device according to any one of claims 34 to 42, characterized in that The transceiver unit is further used to send third information, where the third information indicates the release information of the AI ​​task, and the third information is obtained by processing the release information through the identifier of the AI ​​task; The transceiver unit is further used to receive fourth information, where the fourth information is used to indicate registration to the AI ​​task, and the fourth information includes at least one of the following: AI capability information of the terminal device, and an identifier of the terminal device.

44. The device according to claim 43, characterized in that The published information includes at least one of the following: The identifier of the AI ​​task, the public codebook reported by the user information, and the indication information of the transmission resources.

45. A communication device, characterized in that: comprising at least one processor coupled to a memory; The at least one processor is configured to execute the method of any one of claims 1 to 11.

46. ​​A communication device, characterized in that: comprising at least one processor coupled to a memory; The at least one processor is configured to execute the method of any one of claims 12 to 22.

47. A communication system, characterized in that: The system comprises a communication device according to any one of claims 23 to 33, and a method according to any one of claims 34 to 44. The communication device described in item 1; or, The system comprises the communication device as claimed in claim 45 and the communication device as claimed in claim 46.

48. A computer-readable storage medium, characterized in that The medium stores instructions, and when the instructions are executed by a computer, the method according to any one of claims 1 to 22 is implemented.

49. A computer program product, characterized in that The method comprises instructions which, when executed on a computer, cause the computer to perform the method according to any one of claims 1 to 22.

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