WO2024234344A1 - Communication method and apparatus, and storage medium - Google Patents

Abstract

The present disclosure relates to a communication method and apparatus, and a storage medium. The communication method comprises: sending broadcast information, wherein the broadcast information comprises a parameter for an artificial intelligence (AI) operation. In the present disclosure, broadcast information with a parameter for an AI operation is sent, so as to realize the control over the AI operation.

Description

A communication method, device and storage medium Technical Field

The present disclosure relates to the field of communication technology, and in particular to a communication method, device and storage medium.

Background Art

In recent years, artificial intelligence (AI) technology has made continuous breakthroughs in many fields. AI technology is gradually cross-penetrating into other disciplines, providing new directions and methods for the development of different disciplines.

In related technologies, the 3rd Generation Partnership Project (3GPP) has set up a research project on artificial intelligence technology in wireless air interfaces. The project aims to study the introduction of AI technology in wireless air interfaces and explore how AI technology can assist in improving the transmission technology of wireless air interfaces.

Summary of the invention

In order to overcome the problems existing in the related art, the present disclosure provides a communication method, device and storage medium.

According to a first aspect of an embodiment of the present disclosure, a communication method is provided, which is executed by a network device, and includes:

Send broadcast information, wherein the broadcast information includes parameters for artificial intelligence (AI) operations.

According to a second aspect of an embodiment of the present disclosure, a communication method is provided, which is executed by a terminal and includes: receiving broadcast information, wherein the broadcast information includes parameters for artificial intelligence (AI) operations.

According to a third aspect of an embodiment of the present disclosure, a communication device is provided, including: a sending unit, configured to send broadcast information, wherein the broadcast information includes parameters for artificial intelligence (AI) operations.

According to a fourth aspect of an embodiment of the present disclosure, a communication device is provided, including: a receiving unit, configured to receive broadcast information, wherein the broadcast information includes parameters for artificial intelligence (AI) operations.

According to a fifth aspect of an embodiment of the present disclosure, a communication device is provided, comprising: a processor; a memory for storing processor executable instructions; wherein the processor is configured to execute the communication method as described in the first aspect of the embodiment of the present disclosure.

According to the sixth aspect of an embodiment of the present disclosure, a communication device is provided, comprising: a processor; a memory for storing processor executable instructions; wherein the processor is configured to execute the communication method as described in the second aspect of the embodiment of the present disclosure.

According to a seventh aspect of an embodiment of the present disclosure, a storage medium is provided, in which instructions are stored. When the instructions in the storage medium are executed by a processor of a network device, the network device is enabled to execute the communication method described in the first aspect of the embodiment of the present disclosure.

In an eighth aspect of the embodiments of the present disclosure, a storage medium is provided, wherein instructions are stored in the storage medium. When the instructions in the storage medium are executed by a processor of a terminal, the terminal is enabled to execute the second aspect of the embodiments of the present disclosure. The method described.

According to a ninth aspect of an embodiment of the present disclosure, an artificial intelligence communication system is provided, the system comprising: a network device, used to execute the method described in the first aspect; and a terminal, used to execute the method described in the second aspect.

The technical solution provided by the embodiments of the present disclosure may include the following beneficial effects: controlling the AI operation is achieved by sending broadcast information including parameters for the AI operation.

It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

Fig. 1 is a schematic diagram showing a wireless communication system according to an exemplary embodiment.

Fig. 2 is a flow chart showing a communication method according to an exemplary embodiment.

Fig. 3 is a flow chart showing another communication method according to an exemplary embodiment.

Fig. 4 is a flow chart showing a communication method according to an exemplary embodiment.

Fig. 5 is a flow chart showing another communication method according to an exemplary embodiment.

Fig. 6 is a block diagram showing a communication device according to an exemplary embodiment.

Fig. 7 is a schematic diagram showing interaction of a communication system according to an exemplary embodiment.

Fig. 8 is a block diagram showing a communication device according to an exemplary embodiment.

Fig. 9 is a block diagram of a device for AI communication according to an exemplary embodiment.

Fig. 10 is a block diagram of a device for AI communication according to an exemplary embodiment.

DETAILED DESCRIPTION

Here, exemplary embodiments will be described in detail, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present disclosure.

The communication method of the embodiment of the present disclosure can be applied to the wireless communication system shown in Figure 1. Referring to Figure 1, the wireless communication system includes a network device and a terminal. The terminal is connected to the network device through wireless resources and performs data transmission.

It is understandable that the wireless communication system shown in FIG1 is only for schematic illustration, and the wireless communication system may also include other network devices, such as core network devices, wireless relay devices, and wireless backhaul devices, which are not shown in FIG1. The embodiments of the present disclosure do not limit the number of network devices and terminals included in the wireless communication system. Certainly.

It can be further understood that the wireless communication system of the embodiment of the present disclosure is a network that provides wireless communication functions. The wireless communication system can adopt different communication technologies, such as code division multiple access (code division multiple access, CDMA), wideband code division multiple access (wideband code division multiple access, WCDMA), time division multiple access (time division multiple access, TDMA), frequency division multiple access (frequency division multiple access, FDMA), orthogonal frequency division multiple access (orthogonal frequency-division multiple access, OFDMA), single carrier frequency division multiple access (single carrier FDMA, SC-FDMA), carrier sense multiple access/collision avoidance (Carrier Sense Multiple Access with Collision Avoidance). According to the capacity, rate, delay and other factors of different networks, the network can be divided into 2G (English: generation) network, 3G network, 4G network or future evolution network, such as 5G network, 5G network can also be called new wireless network (New Radio, NR). For the convenience of description, the present disclosure sometimes simply refers to a wireless communication network as a network.

Further, the network equipment involved in the present disclosure may also be referred to as a wireless access network equipment. The wireless access network equipment may be: a base station, an evolved node B (base station), a home base station, an access point (AP) in a wireless fidelity (WIFI) system, a wireless relay node, a wireless backhaul node, a transmission point (TP) or a transmission and reception point (TRP), etc. It may also be a gNB in an NR system, or it may also be a component or a part of a base station. It should be understood that in the embodiments of the present disclosure, the specific technology and specific device form adopted by the network equipment are not limited. In the present disclosure, the network equipment may provide communication coverage for a specific geographical area, and may communicate with a terminal located in the coverage area (cell). In addition, when it is a vehicle-to-everything (V2X) communication system, the network equipment may also be a vehicle-mounted device.

Furthermore, the terminal involved in the present disclosure may also be referred to as a terminal device, a user equipment (User Equipment, UE), a mobile station (Mobile Station, MS), a mobile terminal (Mobile Terminal, MT), etc., which is a device that provides voice and/or data connectivity to users. For example, the terminal may be a handheld device with a wireless connection function, a vehicle-mounted device, etc. At present, some examples of terminals are: a smart phone (Mobile Phone), a customer premises equipment (Customer Premise Equipment, CPE), a pocket computer (Pocket Personal Computer, PPC), a handheld computer, a personal digital assistant (Personal Digital Assistant, PDA), a laptop computer, a tablet computer, a wearable device, or a vehicle-mounted device, etc. In addition, when it is a vehicle-to-everything (V2X) communication system, the terminal device may also be a vehicle-mounted device. It should be understood that the embodiments of the present disclosure do not limit the specific technology and specific device form adopted by the terminal.

In recent years, artificial intelligence (AI) technology has made continuous breakthroughs in many fields. AI technology is gradually cross-penetrating into other disciplines, providing new directions and methods for the development of different disciplines.

In the related technologies, the 3rd Generation Partnership Project (3GPP) has set up a research project on artificial intelligence technology in wireless air interfaces. The project aims to study the introduction of AI technology in wireless air interfaces. At the same time, we will explore how AI technology can assist in improving the transmission technology of wireless air interfaces.

In the research on AI communications, AI use cases may include: AI-based channel state information (CSI) enhancement, AI-based beam management, and AI-based positioning.

It is understandable that AI use cases can also be called AI features. In AI-based communications, communication operations are performed based on AI use cases to achieve a certain communication scenario. For example, AI is used to predict channel information in the time domain. For example, AI-based channel state information (CSI) compression. Another example is AI-based beam management in the airspace. Usually an AI feature is defined in the protocol.

It is understandable that in the above use cases, each AI use case is used in the communication process, and will correspond to different AI operations, and different AI operations correspond to different parameter configurations. And due to the different application cases, in the current communication network, the configuration for AI operations in the network can be common to all terminals, such as which AI use cases this cell supports, and which data sets are used in the cell to test AI models.

In some scenarios, multiple AI functions are defined for a certain AI use case. For example, for beam enhancement, AI function 1 supports the prediction of the representation (identity, ID) of the best beam, and AI function 2 supports the prediction of the best beam and the measurement results of the corresponding beam. The implementation of AI functions relies on AI models. Different AI functions may be implemented by different AI models. In addition, the number of AI models corresponding to a certain AI function is also different. This makes the parameters for the operation of AI functions or AI models different, such as the parameters for activating or switching AI functions or AI models.

In the related art, in the current communication network, it is not clear how to configure the parameters of AI operations during communication.

Based on this, the present disclosure proposes a communication method to clearly configure the AI operation parameters so as to facilitate subsequent communication based on the AI operation parameters.

A communication method proposed in one embodiment of the present disclosure broadcasts parameters for AI operation through broadcast information, so as to configure relevant communication operation parameters of AI based on the broadcast information.

It should be noted that the parameters for AI operation mentioned in the following embodiments of the present disclosure may include parameters for operating AI functions or parameters for operating AI models. For ease of description, the following embodiments refer to the parameters for operating AI functions as parameters for AI operation.

It should be noted that the parameters used for AI operations mentioned in the following embodiments of the present disclosure can be divided into general parameters and special parameters according to the scope of application.

It can be understood that the parameters for AI operations mentioned in the following embodiments, specifically general parameters or dedicated parameters, can be adjusted according to actual application scenarios.

It should be noted that the AI feature use cases mentioned in the following embodiments of the present disclosure may also be referred to as AI use cases.

Exemplarily, in the communication method provided by the embodiment of the present disclosure, the AI operation parameters carried in the broadcast information can be understood as parameters used for AI operation.

Exemplarily, the communication method provided by the embodiment of the present disclosure, for parameters used for AI operations, includes at least one of the following: parameters for AI-based CSI enhancement operations, parameters for AI-based beam management operations, and parameters for AI-based positioning operations.

It should be further explained that the parameters for AI operations involved in the following embodiments of the present disclosure include one or more parameters for AI-based CSI enhancement operations, parameters for AI-based beam management operations, and parameters for AI-based positioning operations.

Fig. 2 is a flow chart of a communication method according to an exemplary embodiment. As shown in Fig. 2, the communication method, executed by a network device, includes the following steps:

In step S11, broadcast information is sent, and the broadcast information includes parameters for AI operation.

In the embodiment of the present disclosure, the broadcast information includes parameters for AI operations, and the network device can configure the parameters for the AI to perform related communication operations through the broadcast information.

In the communication method provided by the embodiment of the present disclosure, multiple AI use cases can be sent based on one broadcast message or through multiple broadcast messages.

In one implementation of the embodiment of the present disclosure, the parameters used for AI operation include at least one of the following: a general parameter and a dedicated parameter.

In the embodiments of the present disclosure, the general parameters can be understood as AI operations applicable to all AI feature instances, while the dedicated parameters are dedicated to the AI operations of a single AI feature instance.

For example, parameter A is applicable to AI operations of all current AI use cases, so operation A is considered a universal parameter. Parameter B is a parameter specific to AI operations of AI use case b, so parameter B is considered a dedicated parameter.

In the embodiment of the present disclosure, the parameters used for AI operation include general parameters.

In the embodiment of the present disclosure, the parameters used for AI operation include dedicated parameters.

In the embodiment of the present disclosure, the parameters used for AI operation include general parameters and dedicated parameters.

In one implementation of the embodiments of the present disclosure, the parameters used for AI operation include cell parameters, and the cell is a cell that sends broadcast information.

In an embodiment of the present disclosure, the cell parameters include at least one of the following: whether the cell supports AI feature use cases; configuration information corresponding to the cell; data distribution information of the cell; and AI model download information of the cell.

Exemplarily, the cell parameters used for AI operation in the embodiments of the present disclosure include whether the cell supports AI feature use cases.

The cell parameters for AI operation may include at least one of the following: whether the cell supports AI-based CSI compression, whether the cell supports AI-based beam prediction, and whether the cell supports AI-based positioning.

In a communication method provided by an embodiment of the present disclosure, in response to a cell supporting an AI feature use case, a network device may indicate the type of a terminal.

Fig. 3 is a flow chart of another communication method according to an exemplary embodiment. In one implementation of the embodiment of the present disclosure, as shown in Fig. 3, the following steps are included.

In step S21, first information is sent. The first information is used to indicate the terminal type to which the cell supports the AI feature use case.

In the embodiment of the present disclosure, the terminal type includes a first type terminal or a second type terminal, and the first type communication terminal and the second type communication terminal have different communication capabilities. For example, the capabilities of the terminal may be transceiver bandwidth, the number of transceiver antennas, the maximum number of bits of a transmission block, and processing time delay. The different capabilities of the terminals may be one or more of the transceiver bandwidth, the number of transceiver antennas, the maximum number of bits of a transmission block, and the processing time delay.

Exemplarily, the terminal type may include: a normal terminal, a NR-lite terminal. In one example, the first type of terminal may be an NR-lite terminal, and the second type of terminal may be a normal terminal.

In one implementation of the embodiments of the present disclosure, the cell parameters used for AI operation include configuration information corresponding to the cell.

Exemplarily, the configuration information corresponding to the cell used for AI operation includes at least one of the following: antenna configuration information; cell type information; and cell scene information.

Exemplarily, the antenna configuration information may include at least one of the following: cell user density, communication frequency band, and supported communication standards, etc.

Exemplarily, the cell type information may include at least one of the following: an indoor cell, an outdoor cell, an indoor-outdoor integrated cell, a macro cell, a micro cell, and a millimeter wave cell, etc.

Exemplarily, the scene information of the cell includes: urban scene, rural scene, indoor scene, transportation scene, home scene and other scenes.

In one implementation of the embodiments of the present disclosure, the cell parameters used for AI operation include AI model download information of the cell.

Exemplarily, the AI model download information for AI operation includes at least one of the following (i) to (iii):

(1) Whether the community provides AI model downloads.

Exemplarily, whether the cell provides AI model downloading includes at least one of the following situations: the cell provides an AI model available for downloading or the cell does not provide an AI model available for downloading.

(2) The community can provide model information for AI model downloads.

Exemplarily, the model information that the cell can provide for AI model download includes: model identification or AI function, etc.

(3) AI model corresponds to the terminal’s demand information.

In one implementation of the embodiments of the present disclosure, the cell parameters used for AI operation include data distribution information of the cell.

Exemplarily, the data distribution information of the cell may be mathematical distribution characteristics corresponding to the data of the cell, including overall distribution and geometric distribution.

In one implementation of the embodiment of the present disclosure, the data distribution information of the cell includes: data set information for indicating the data distribution of the cell.

It can be understood that the data distribution of the cell can be represented by data set information.

In one implementation of the embodiment of the present disclosure, the data set information is used to indicate the correspondence between the data set and the terminal type.

Exemplarily, the cell data distribution may be represented based on a data set, for example, the data in data set #1 is distributed as a whole, and the data in data set #2 is distributed geometrically.

Exemplarily, the data set information may include a correspondence between terminals and data sets, for example: using data set #1 for type A terminals and using data set #2 for type B terminals.

Exemplarily, the parameters used for AI operation in the embodiments of the present disclosure include data distribution information for indicating a cell, for example, data set information reflecting the data distribution of the cell, such as the ID of the data set.

The data distribution information of the cell may be sent based on the system message. In response to the system message including the data distribution information of the cell, the data distribution information of the cell may further include data set information used for different terminals. For example, for a normal terminal, data set #1 is used, and for a terminal with reduced capabilities, data set #2 is used.

In the communication method provided by the embodiment of the present disclosure, the broadcast information including the AI operation parameters may be broadcast information dedicated to the AI operation, or may be broadcast information applicable to both the AI operation and the non-AI operation.

In one implementation of the embodiment of the present disclosure, the broadcast information is broadcast information dedicated to AI operations.

Exemplarily, the broadcast information contents are all related to AI operations.

In one implementation of the embodiment of the present disclosure, the broadcast information includes broadcast information of AI operation and broadcast information of non-AI operation.

Exemplarily, the broadcast information may include both content related to the AI operation and content unrelated to the AI operation.

In one implementation of the embodiments of the present disclosure, the AI operation corresponds to multiple AI feature use cases, and the broadcast information corresponding to the multiple AI feature use cases can be sent through one message, that is, the broadcast information corresponding to the multiple AI feature use cases is a single broadcast information.

In one implementation of the present disclosure, an AI operation corresponds to multiple AI feature use cases, and the broadcast information corresponding to the multiple AI feature use cases can be sent through different messages, that is, the broadcast information corresponding to the multiple AI feature use cases is multiple broadcast The number of the plurality of broadcast information is the same as or different from the number of the plurality of AI feature use cases.

Exemplarily, common parameters for CSI-related and beam management-related AI operations may be set and included in broadcast information with multiple-input multiple-output (MIMO) parameters.

Exemplarily, public parameters for CSI-related and beam management-related AI operations may be set in the broadcast information of MIMO parameters, and public parameters for positioning-related AI operations may be set and included in the broadcast information with positioning parameters.

In the communication method provided by the embodiment of the present disclosure, the broadcast information including the AI operation parameters may be sent periodically or based on demand.

Demand-based sending can be understood as when a terminal needs to read the information, it sends a request message to the network device, and the network broadcasts only after receiving the request message.

In one implementation of the embodiment of the present disclosure, the implementation of sending broadcast information includes at least one of the following (a) and (b):

(a) Sent based on a preset period.

Exemplarily, the preset period may be in one of the following representation forms, including: absolute time, communication time unit, and AI processing time unit.

Furthermore, absolute time includes seconds, milliseconds, microseconds, etc.

The communication time units include: Orthogonal Frequency Division Multiplexing (OFDM) symbols, time slots, subslots, and sampling intervals of OFDM symbols.

The AI time unit is used to describe the time unit of AI communication. It can be understood that the AI time unit is defined as the basic time unit used to measure AI processing tasks.

(b) Sending in response to receiving a sending request.

Exemplarily, the network device sends broadcast information in response to receiving a sending request sent by a terminal (which can also be understood as receiving a request information for requesting to send AI operation parameters).

It should be noted that those skilled in the art can understand that the various implementation methods/embodiments involved in the embodiments of the present disclosure can be used in conjunction with the aforementioned embodiments or can be used independently. Whether used alone or in conjunction with the aforementioned embodiments, the implementation principle is similar. In the implementation of the present disclosure, some embodiments are described in terms of implementation methods used together. Of course, those skilled in the art can understand that such examples are not limitations of the embodiments of the present disclosure.

Based on the same concept, the embodiment of the present disclosure also provides a communication method executed by a terminal. In the communication method, AI operation parameters are configured based on broadcast information.

FIG4 is a flow chart of a communication method according to an exemplary embodiment. In the embodiment, as shown in FIG4 , the communication method is executed by a terminal and includes the following steps.

In step S31, broadcast information is received.

In the embodiment of the present disclosure, the broadcast information includes parameters for AI operations.

In the embodiment of the present disclosure, the broadcast information includes parameters for AI operation, and the terminal can receive the broadcast information to enable the network device to configure the relevant communication operation parameters for AI.

The broadcast information received by the terminal in the embodiment of the present disclosure is the same as the broadcast information sent by the network device, and the scenario for the terminal to receive the broadcast information is similar to the scenario for the network device to send the broadcast information. Therefore, for the same scenario in the communication method, please refer to the relevant description in the embodiment of the above-mentioned terminal device, which will not be repeated here one by one.

In one implementation of the disclosed embodiment, the parameters used for AI operations include: general parameters and/or special parameters; the general parameters are applicable to AI operations of all AI feature instances; and the special parameters are dedicated to AI operations of a single AI feature instance.

In one implementation of the embodiments of the present disclosure, the parameters used for AI operations include cell parameters of broadcast information; the cell parameters include at least one of the following: whether the cell supports AI feature use cases; configuration information corresponding to the cell; data distribution information of the cell; and AI model download information of the cell.

Fig. 5 is a flow chart of another communication method according to an exemplary embodiment. In one implementation of the embodiment of the present disclosure, as shown in Fig. 5, receiving a cell parameter including a cell supporting an AI use case is implemented by the following steps.

In step S41, first information is received. The first information is used to indicate the terminal type to which the cell supports the AI feature use case.

In the embodiment of the present disclosure, the terminal type includes a first type terminal or a second type terminal, and the first type communication terminal and the second type communication terminal have different communication capabilities.

In one implementation of the embodiment of the present disclosure, the configuration information corresponding to the cell includes at least one of the following: antenna configuration information; cell type information; and cell scene information.

In one implementation of the embodiment of the present disclosure, the AI model download information of the cell includes at least one of the following:

(1) Whether the community provides AI model downloads.

Exemplarily, whether the cell provides AI model downloading includes at least one of the following situations: the cell provides an AI model available for downloading or the cell does not provide an AI model available for downloading.

(2) The community can provide model information for AI model downloads.

Exemplarily, the model information that the cell can provide for AI model download includes: model identification or AI function, etc.

(3) AI model corresponds to the terminal’s demand information.

In one implementation of the embodiments of the present disclosure, the data distribution information of a cell includes: data set information for indicating data distribution of the cell.

In one implementation of the present disclosure, the data set information is used to indicate the correspondence between the data set and the terminal type. Should relationship.

In one implementation of the embodiment of the present disclosure, the broadcast information includes broadcast information of AI operation and broadcast information of non-AI operation.

In one implementation of the embodiments of the present disclosure, the AI operation corresponds to multiple AI feature use cases, and the broadcast information corresponding to the multiple AI feature use cases is a single broadcast information, or multiple broadcast information.

In one implementation of the embodiment of the present disclosure, the implementation method of sending the broadcast information includes at least one of the following:

(a) Sent based on a preset period.

Exemplarily, the preset period may include at least one of the following representation forms: absolute time, communication time unit, and AI processing time unit.

Furthermore, absolute time includes seconds, milliseconds, microseconds, etc.

The communication time units include: Orthogonal Frequency Division Multiplexing (OFDM) symbols, time slots, subslots, and sampling intervals of OFDM symbols.

The AI time unit is used to describe the time unit of AI communication. It can be understood that the AI time unit is defined as the basic time unit used to measure AI processing tasks.

(b) Sending in response to receiving a sending request.

It can be understood that the implementation process of the communication method executed by the terminal in the embodiment of the present disclosure is similar to that of the communication method executed by the network device. The similarities will not be repeated here, and reference may be made to the implementation process of the communication method executed by the above-mentioned network device.

The communication method provided by the embodiment of the present disclosure is applicable to the implementation process of interaction between a terminal and a network device in a communication system.

Based on the same concept, an embodiment of the present disclosure provides a communication system, which includes a terminal and a network device that execute the above communication method.

FIG6 is a schematic diagram of a method interaction of a communication system shown in an exemplary embodiment of the present disclosure. As shown in FIG6 , the present disclosure embodiment relates to a communication system, and the method includes:

Step S101: a network device sends broadcast information, and a terminal receives the broadcast information.

In one implementation, the broadcast information includes parameters for AI operations.

In one embodiment, the parameters used for AI operation include cell parameters for sending broadcast information; the cell parameters include at least one of the following: whether the cell supports AI feature use cases; configuration information corresponding to the cell; data distribution information of the cell; and AI model download information of the cell.

Step S102: the network device sends first information, and the terminal receives the first information.

In one implementation, the first information is used to indicate the terminal type to which the cell supports the AI feature use case.

In one embodiment, the terminal type includes a first type terminal or a second type terminal, wherein the first type communication terminal The communication capabilities of the terminal and the second type of communication terminal are different.

In one implementation, the first information is used to indicate the terminal type to which the cell supports the AI feature use case.

In one implementation, the terminal type includes a first type terminal or a second type terminal, and the first type communication terminal and the second type communication terminal have different communication capabilities.

The positioning measurement method involved in the embodiments of the present disclosure may include at least one of steps S101 to S102. For example, step S101 can be implemented as an independent embodiment, step S102 can be implemented as an independent embodiment, and step S101+step S102 can be implemented as an independent embodiment. Among them, at least one of the partial embodiments in step S101 and the partial embodiments of step S102. The network device sending broadcast information in step S102+the network device sending the first information in step S102 can be implemented as an independent embodiment, but is not limited to this. In some embodiments, the network device sending broadcast information and the terminal receiving broadcast information in step S101 can be exchanged in order or executed simultaneously. The network device sending the first information and the terminal receiving the first information in step S102 can be exchanged in order or executed simultaneously. In some embodiments, step S102 is optional, and one or more of these steps can be omitted or replaced in different embodiments.

Based on the same concept, the embodiment of the present disclosure also provides an AI communication device.

Fig. 7 is a structural block diagram of a communication device according to an exemplary embodiment. As shown in Fig. 7 , an embodiment of the present disclosure provides a communication device. The communication device includes a sending unit 101 .

Sending unit 101: used to send broadcast information, where the broadcast information includes parameters for artificial intelligence AI operations.

In one implementation, the parameters used for AI operations include: general parameters and/or special parameters; general parameters are applicable to AI operations of all AI feature instances; special parameters are specific to AI operations of a single AI feature instance.

In one embodiment, the parameters used for AI operation include cell parameters for sending broadcast information; the cell parameters include at least one of the following: whether the cell supports AI feature use cases; configuration information corresponding to the cell; data distribution information of the cell; and AI model download information of the cell.

In one implementation, the sending unit 101 is further used to send first information, where the first information is used to indicate the terminal type applicable to the cell supporting the AI feature use case; the terminal type includes a first type terminal or a second type terminal, and the first type communication terminal and the second type communication terminal have different communication capabilities.

In one implementation, the configuration information corresponding to the cell includes at least one of the following: antenna configuration information; cell type information; and cell scenario information.

In one implementation, the data distribution information of a cell includes: data set information for indicating data distribution of the cell.

In one implementation, the broadcast information includes: data set information for indicating cell data distribution, where the data set information is used to indicate a correspondence between a data set and a terminal type.

In one implementation, the AI model download information of the cell includes at least one of the following: whether the cell provides an AI model Download; the community can provide model information for AI model download; and the demand information of the terminal corresponding to the AI model.

In one implementation, the broadcast information is broadcast information dedicated to AI operations.

In one implementation, the broadcast information includes broadcast information of AI operations and broadcast information of non-AI operations.

In one implementation, the AI operation corresponds to multiple AI feature use cases, and the broadcast information corresponding to the multiple AI feature use cases is a single broadcast information, or is multiple broadcast information.

In one implementation, sending the broadcast information includes: sending based on a preset period; or sending in response to receiving a sending request.

Based on the same concept, the embodiment of the present disclosure also provides an AI communication device.

Fig. 8 is a structural block diagram showing a communication device according to an exemplary embodiment.

As shown in FIG. 8 , an embodiment of the present disclosure provides a communication device, including a receiving unit 201 .

Receiving unit 201: used to receive broadcast information, which includes parameters for artificial intelligence AI operations.

In one implementation, the parameters used for AI operations include: general parameters and/or special parameters; general parameters are applicable to AI operations of all AI feature instances; special parameters are specific to AI operations of a single AI feature instance.

In one embodiment, the parameters used for AI operation include cell parameters of broadcast information; the cell parameters include at least one of the following: whether the cell supports AI feature use cases; configuration information corresponding to the cell; data distribution information of the cell; and AI model download information of the cell.

In one implementation, the receiving unit 701 is further used to receive first information, where the first information is used to indicate the terminal type applicable to the cell supporting the AI feature use case; the terminal type includes a first type terminal or a second type terminal, and the first type communication terminal and the second type communication terminal have different communication capabilities.

In one implementation, the configuration information corresponding to the cell includes at least one of the following: antenna configuration information; cell type information; and cell scenario information.

In one implementation, the data distribution information of a cell includes: data set information for indicating data distribution of the cell.

In one implementation, the broadcast information includes: data set information for indicating cell data distribution, where the data set information is used to indicate a correspondence between a data set and a terminal type.

In one implementation, the AI model download information of the cell includes at least one of the following: whether the cell provides the AI model download; model information that the cell can provide for AI model download; and demand information of the terminal corresponding to the AI model.

In one implementation, the broadcast information is broadcast information dedicated to AI operations.

In one implementation, the broadcast information includes broadcast information of AI operations and broadcast information of non-AI operations.

In one implementation, the AI operation corresponds to multiple AI feature use cases, and the broadcast information corresponding to the multiple AI feature use cases is a single broadcast information, or is multiple broadcast information.

In one embodiment, receiving broadcast information includes: receiving based on a preset period; or responding to a network device sending broadcast information reception.

Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

Fig. 9 is a schematic diagram of a communication device according to an exemplary embodiment. For example, the device 300 may be any terminal such as a mobile phone, a computer, a digital broadcast terminal, a message transceiver device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

9 , device 300 may include one or more of the following components: a processing component 302 , a memory 304 , a power component 306 , a multimedia component 308 , an audio component 310 , an input/output (I/O) interface 312 , a sensor component 314 , and a communication component 316 .

The processing component 302 generally controls the overall operation of the device 300, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 302 may include one or more processors 320 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 302 may include one or more modules to facilitate the interaction between the processing component 302 and other components. For example, the processing component 302 may include a multimedia module to facilitate the interaction between the multimedia component 308 and the processing component 302.

The memory 304 is configured to store various types of data to support operations on the device 300. Examples of such data include instructions for any application or method operating on the device 300, contact data, phone book data, messages, pictures, videos, etc. The memory 304 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

The power component 306 provides power to the various components of the device 300. The power component 306 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 300.

The multimedia component 308 includes a screen that provides an output interface between the device 300 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 308 includes a front camera and/or a rear camera. When the device 300 is in an operating mode, such as a shooting mode or a video mode, the front camera and/or the rear camera may receive external multimedia data. Each front camera and the rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

The audio component 310 is configured to output and/or input audio signals. For example, the audio component 310 includes a microphone (MIC), when the device 300 is in an operation mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 304 or sent via the communication component 316. In some embodiments, the audio component 310 also includes a speaker for outputting an audio signal.

I/O interface 312 provides an interface between processing component 302 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

The sensor assembly 314 includes one or more sensors for providing various aspects of status assessment for the device 300. For example, the sensor assembly 314 can detect the open/closed state of the device 300, the relative positioning of components, such as the display and keypad of the device 300, and the sensor assembly 314 can also detect the position change of the device 300 or a component of the device 300, the presence or absence of user contact with the device 300, the orientation or acceleration/deceleration of the device 300, and the temperature change of the device 300. The sensor assembly 314 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 314 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 314 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 316 is configured to facilitate wired or wireless communication between the device 300 and other devices. The device 300 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 316 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 316 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

In an exemplary embodiment, the device 300 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 304 including instructions, which can be executed by a processor 320 of the device 300 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

FIG10 is a schematic diagram of another communication device according to an exemplary embodiment. For example, device 400 may be provided as a base station or a server. Referring to FIG10 , device 400 includes a processing component 422, which further includes one or more processors, and a memory resource represented by a memory 432 for storing instructions executable by processing component 422, such as an application. The application stored in memory 432 may include one or more of each A module corresponding to a set of instructions. In addition, the processing component 422 is configured to execute instructions to perform the above method.

The device 400 may also include a power supply component 426 configured to perform power management of the device 400, a wired or wireless network interface 450 configured to connect the device 400 to a network, and an input/output (I/O) interface 458. The device 400 may operate based on an operating system stored in the memory 432, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, or the like.

In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 432 including instructions, which can be executed by the processing component 422 of the device 400 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

In some embodiments, the terms communication method, information processing method, communication method, etc. can be replaced with each other, the terms communication device, information processing device, etc. can be replaced with each other, and the terms information processing system, communication system, etc. can be replaced with each other.

The embodiments of the present disclosure are not exhaustive, but are only illustrative of some embodiments, and are not intended to be a specific limitation on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a certain embodiment can also be implemented as an independent embodiment, and the order of the steps in a certain embodiment can be arbitrarily exchanged. In addition, the optional implementation methods in a certain embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined, for example, some or all of the steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

In each embodiment of the present disclosure, if there is no special explanation and logical conflict, the terms and/or descriptions between the embodiments are consistent and can be referenced to each other, and the technical features in different embodiments can be combined to form a new embodiment according to their inherent logical relationship. The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments, and are not intended to limit the present disclosure.

It is further understood that in the present disclosure, "plurality" refers to two or more than two, and other quantifiers are similar thereto. "And/or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and/or B may represent: A exists alone, A and B exist at the same time, and B exists alone. The character "/" generally indicates that the associated objects before and after are in an "or" relationship. The singular forms "a", "the" and "the" are also intended to include plural forms, unless the context clearly indicates other meanings.

It is further understood that the meanings of the words "in response to" and "if" involved in the present disclosure depend on the context and the actual usage scenario. For example, the word "in response to" used herein can be interpreted as "at..." or "when..." or "if".

It is further understood that the terms "first", "second", etc. are used to describe various information, but these information should not be These terms are limited to these terms. These terms are only used to distinguish the same type of information from each other and do not indicate a specific order or importance. In fact, expressions such as "first" and "second" can be used interchangeably. For example, without departing from the scope of this disclosure, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information.

It is further understood that, although the operations are described in a specific order in the drawings in the embodiments of the present disclosure, it should not be understood as requiring the operations to be performed in the specific order shown or in a serial order, or requiring the execution of all the operations shown to obtain the desired results. In certain environments, multitasking and parallel processing may be advantageous.

Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any modifications, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure.

It should be understood that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the scope of the appended claims.

Claims (28)

A communication method, characterized in that it is performed by a network device, and the method comprises: Send broadcast information, wherein the broadcast information includes parameters for artificial intelligence (AI) operations. The communication method according to claim 1, characterized in that the parameters used for AI operation include: general parameters and/or special parameters; The general parameters apply to AI operations of all AI feature instances; The dedicated parameters are specific to the AI operation of a single AI feature instance. The communication method according to claim 1, characterized in that the parameters used for AI operation include parameters of a cell for sending the broadcast information; The cell parameter includes at least one of the following: Whether the community supports AI feature use cases; Configuration information corresponding to the cell; Data distribution information of the cell; and AI model download information for the community. The communication method according to claim 3, characterized in that the cell parameters include the cell supporting AI feature use cases, and the method further comprises: Sending first information, where the first information is used to indicate a terminal type applicable to which the cell supports an AI feature use case; The terminal type includes a first type terminal or a second type terminal, and the first type communication terminal and the second type communication terminal have different communication capabilities. The communication method according to claim 3, characterized in that the configuration information corresponding to the cell includes at least one of the following: Antenna configuration information; Cell type information; and Scene information of the community. The communication method according to claim 3, wherein the data distribution information of the cell comprises: Data set information used to represent the distribution of cell data. The communication method according to claim 6 is characterized in that the data set information is used to indicate the correspondence between the data set and the terminal type. The communication method according to claim 3, characterized in that the AI model download information of the cell includes at least one of the following: Whether the community provides the AI model download; The cell can provide model information for downloading the AI model; and demand information of the terminal corresponding to the AI model. The communication method according to claim 1 is characterized in that the broadcast information is broadcast information dedicated to AI operations. The communication method according to claim 1 is characterized in that the broadcast information includes broadcast information of AI operation and broadcast information of non-AI operation. The communication method according to claim 1 is characterized in that the AI operation corresponds to multiple AI feature use cases, and the broadcast information corresponding to the multiple AI feature use cases is a single broadcast information, or multiple broadcast information. The communication method according to any one of claims 1 to 11, characterized in that the sending of broadcast information comprises: Sent based on a preset period; or Sending in response to receiving a sending demand. A communication method, characterized in that it is executed by a terminal, and the method comprises: Receive broadcast information, wherein the broadcast information includes parameters for artificial intelligence (AI) operations. The communication method according to claim 13, characterized in that the parameters used for AI operation include: general parameters and/or special parameters; The general parameters apply to AI operations of all AI feature instances; The dedicated parameters are specific to the AI operation of a single AI feature instance. The communication method according to claim 13, characterized in that the parameters used for AI operation include cell parameters of the broadcast information; The cell parameter includes at least one of the following: Whether the community supports AI feature use cases; Configuration information corresponding to the cell; Data distribution information of the cell; and AI model download information for the community. The communication method according to claim 15, characterized in that the cell parameters include the cell supporting AI feature use cases, and the method further comprises: receiving first information, where the first information is used to indicate a terminal type applicable to which the cell supports an AI feature use case; The terminal type includes a first type terminal or a second type terminal, and the first type communication terminal and the second type communication terminal have different communication capabilities. The communication method according to claim 15, characterized in that the configuration information corresponding to the cell includes at least one of the following: Antenna configuration information; Cell type information; and Scene information of the community. The communication method according to claim 15, characterized in that the data distribution information of the cell includes: Data set information used to represent the distribution of cell data. The communication method according to claim 18 is characterized in that the data set information is used to indicate the correspondence between the data set and the terminal type. The communication method according to claim 15, characterized in that the AI model download information of the cell includes at least one of the following: Whether the community provides the AI model download; The cell can provide model information for downloading the AI model; and demand information of the terminal corresponding to the AI model. The communication method according to claim 13, characterized in that the broadcast information is broadcast information dedicated to AI operations. The communication method according to claim 13, characterized in that the broadcast information includes broadcast information of AI operation and broadcast information of non-AI operation. The communication method according to claim 13 is characterized in that the AI operation corresponds to multiple AI feature use cases, and the broadcast information corresponding to the multiple AI feature use cases is a single broadcast information, or multiple broadcast information. The communication method according to any one of claims 13 to 23, characterized in that the receiving broadcast information comprises: Received based on a preset period; or Responds to broadcast information reception sent by a network device. A communication device, characterized in that it is executed by a network device, and the device comprises: A sending unit is used to send broadcast information, wherein the broadcast information includes parameters for artificial intelligence AI operations. A communication device, characterized in that it is executed by a terminal, and the device comprises: A receiving unit is used to receive broadcast information, wherein the broadcast information includes parameters for artificial intelligence (AI) operations. A communication device, comprising: processor; a memory for storing processor-executable instructions; The processor is configured to execute the method as described in any one of claims 1-12 or 13-24. A storage medium, characterized in that instructions are stored in the storage medium, and when the instructions in the storage medium are executed by a processor of a terminal, the terminal is enabled to execute the method described in any one of claims 1-12; or, when the instructions in the storage medium are executed by a processor of a network device, the network device is enabled to execute the method described in any one of claims 13-24.