Communication method and device and storage medium

Abstract

The invention relates to a communication method and device and a storage medium. The communication method comprises the following steps: sending broadcast information, wherein the broadcast information comprises parameters for artificial intelligence (AI) operation; according to the invention, the control of the AI operation is realized by sending the broadcast information with the parameters for the AI operation.

Description

Communication method, device and storage medium Technical Field

[0001] The present disclosure relates to the field of communication technologies, and in particular to a communication method, device, and storage medium. Background Art

[0002] 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.

[0003] In related technologies, the 3rd Generation Partnership Project (3GPP) has established a research project on artificial intelligence technology in wireless air interfaces. This project aims to study the introduction of AI technology in wireless air interfaces and explore how AI technology can assist in improving wireless air interface transmission technology.

[0004] Summary of the Invention

[0005] To overcome the problems existing in the related art, the present disclosure provides a communication method, device and storage medium.

[0006] According to a first aspect of an embodiment of the present disclosure, there is provided a communication method, which is performed by a network device and includes:

[0007] Send broadcast information, where the broadcast information includes parameters for artificial intelligence (AI) operations.

[0008] According to a second aspect of an embodiment of the present disclosure, a communication method is provided, which is executed by a terminal, including: receiving broadcast information, where the broadcast information includes parameters for artificial intelligence (AI) operations.

[0009] 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.

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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.

[0014] According to an eighth 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 terminal, the terminal is enabled to execute the method described in the second aspect of the embodiment of the present disclosure.

[0015] 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 for executing the method described in the first aspect; and a terminal for executing the method described in the second aspect.

[0016] The technical solution provided by the embodiments of the present disclosure may include the following beneficial effects: controlling AI operations is achieved by sending broadcast information including parameters for AI operations.

[0017] 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 disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] 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.

[0019] Fig. 1 is a schematic diagram showing a wireless communication system according to an exemplary embodiment.

[0020] Fig. 2 is a flow chart showing a communication method according to an exemplary embodiment.

[0021] Fig. 3 is a flow chart showing another communication method according to an exemplary embodiment.

[0022] Fig. 4 is a flow chart showing a communication method according to an exemplary embodiment.

[0023] Fig. 5 is a flowchart showing another communication method according to an exemplary embodiment.

[0024] Fig. 6 is a block diagram showing a communication device according to an exemplary embodiment.

[0025] Fig. 7 is a schematic diagram showing interaction of a communication system according to an exemplary embodiment.

[0026] Fig. 8 is a block diagram showing a communication device according to an exemplary embodiment.

[0027] Fig. 9 is a block diagram showing a device for AI communication according to an exemplary embodiment.

[0028] Fig. 10 is a block diagram of a device for AI communication according to an exemplary embodiment. DETAILED DESCRIPTION

[0029] Exemplary embodiments are described in detail herein, with examples illustrated in the accompanying drawings. When the following description refers to the drawings, identical numerals in different drawings represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present disclosure.

[0030] 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.

[0031] It should be understood that the wireless communication system shown in Figure 1 is for illustrative purposes only, 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 Figure 1. The embodiments of the present disclosure do not limit the number of network devices and terminals included in the wireless communication system.

[0032] 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 (CDMA), wideband code division multiple access (WCDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal frequency-division multiple access (OFDMA), single carrier frequency division multiple access (SC-FDMA), carrier sense multiple access / collision avoidance (Carrier Sense Multiple Access with CollisionAvoidance). According to factors such as the capacity, rate, and latency 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, which can also be called New Radio (NR). For the convenience of description, the present disclosure sometimes refers to the wireless communication network as simply a network.

[0033] Furthermore, the network devices involved in the present disclosure may also be referred to as wireless access network devices. The wireless access network device 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 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 device are not limited. In the present disclosure, the network device can provide communication coverage for a specific geographical area and can communicate with terminals located in the coverage area (cell). In addition, when it is a vehicle-to-everything (V2X) communication system, the network device may also be a vehicle-mounted device.

[0034] Furthermore, the terminal involved in the present disclosure may also be referred to as a terminal device, user equipment (UE), mobile station (MS), mobile terminal (MT), etc., which is a device that provides voice and / or data connectivity to users. For example, the terminal can be a handheld device with wireless connection function, a vehicle-mounted device, etc. At present, some examples of terminals are: smart phones (Mobile Phones), customer premises equipment (Customer Premise Equipment, CPE), pocket computers (Pocket Personal Computers, PPCs), handheld computers, personal digital assistants (Personal Digital Assistants, PDAs), laptops, tablet computers, wearable devices, or vehicle-mounted devices, etc. In addition, when it is a vehicle-to-everything (V2X) communication system, the terminal device can 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.

[0035] 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.

[0036] In related technologies, the 3rd Generation Partnership Project (3GPP) has established a research project on artificial intelligence technology in wireless air interfaces. This project aims to study the introduction of AI technology in wireless air interfaces and explore how AI technology can assist in improving wireless air interface transmission technology.

[0037] 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.

[0038] It's understandable that AI use cases can also be referred to as AI features. In AI-based communications, communication operations are performed based on AI use cases to achieve a specific communication scenario. For example, AI can be used to predict channel information in the time domain. Another example is AI-based channel state information (CSI) compression. Another example is AI-based beam management in the airspace. An AI feature is typically defined in the protocol.

[0039] It is understandable that in the above use cases, each AI use case corresponds to different AI operations during the communication process, and different AI operations correspond to different parameter configurations. Furthermore, due to the different application cases, in current communication networks, the network configuration for AI operations can be universal for all terminals, such as which AI use cases are supported in a cell and which data sets are used to test AI models in the cell.

[0040] 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 optimal beam representation (identity, ID), and AI function 2 supports the prediction of the optimal 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 results in different parameters for the operation of AI functions or AI models, such as different parameters for activating or switching AI functions or AI models.

[0041] In the related art, in the current communication network, there is no clear definition of how to configure the parameters of AI operations during communication.

[0042] Based on this, the present disclosure proposes a communication method to clearly configure the AI ​​operation parameters so that subsequent communication can be carried out based on the parameters of the AI ​​operation.

[0043] A communication method proposed in one embodiment of the present disclosure broadcasts parameters for AI operations through broadcast information, so as to configure relevant communication operation parameters of the AI ​​based on the broadcast information.

[0044] It should be noted that the parameters for AI operations mentioned in the following embodiments of this disclosure may include parameters for operating AI functions or parameters for operating AI models. For ease of description, the following embodiments refer to parameters for operating AI functions as parameters for AI operations.

[0045] It should be noted that the parameters used for AI operations mentioned in the following embodiments of this disclosure can be divided into general parameters and special parameters according to the scope of application.

[0046] It is understandable that the parameters for AI operations mentioned in the following embodiments, whether they are general parameters or dedicated parameters, can be adjusted according to actual application scenarios.

[0047] It should be noted that the AI ​​feature use cases mentioned in the following embodiments of this disclosure may also be referred to as AI use cases.

[0048] Illustratively, 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.

[0049] Exemplarily, the communication method provided by the embodiment of the present disclosure includes at least one of the following parameters for AI operations: parameters for AI-based CSI enhancement operations, parameters for AI-based beam management operations, and parameters for AI-based positioning operations.

[0050] 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.

[0051] FIG2 is a flow chart of a communication method according to an exemplary embodiment. As shown in FIG2 , the communication method, executed by a network device, includes the following steps:

[0052] In step S11, broadcast information is sent, including parameters for AI operation.

[0053] 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.

[0054] 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.

[0055] 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.

[0056] In the embodiments of the present disclosure, a general parameter can be understood as an AI operation applicable to all AI feature instances, while a dedicated parameter is dedicated to the AI ​​operation of a single AI feature instance.

[0057] For example, if parameter A is applicable to all AI operations in the current AI use case, then operation A is considered a universal parameter. If parameter B is a parameter specific to the AI ​​operation in AI use case B, then parameter B is considered a dedicated parameter.

[0058] In the embodiment of the present disclosure, the parameters used for AI operations include general parameters.

[0059] In the embodiment of the present disclosure, the parameters used for AI operations include dedicated parameters.

[0060] In the embodiment of the present disclosure, the parameters used for AI operations include general parameters and dedicated parameters.

[0061] 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.

[0062] 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.

[0063] Exemplarily, the cell parameters used for AI operation in the embodiments of the present disclosure include whether the cell supports AI feature use cases.

[0064] 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.

[0065] 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.

[0066] Fig. 3 is a flow chart showing 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.

[0067] In step S21, first information is sent. The first information is used to indicate the terminal types applicable to the AI ​​feature use case supported by the cell.

[0068] In the embodiments of the present disclosure, terminal types include first-type terminals and second-type terminals, and the first-type and second-type communication terminals have different communication capabilities. For example, terminal capabilities may include transceiver bandwidth, number of transceiver antennas, maximum number of bits in a transport block, and processing time delay. The different terminal capabilities may include one or more of the following: transceiver bandwidth, number of transceiver antennas, maximum number of bits in a transport block, and processing time delay.

[0069] Exemplarily, the terminal type may include: a normal terminal and a reduced capability terminal (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.

[0070] In one implementation of the embodiments of the present disclosure, the cell parameters used for AI operation include configuration information corresponding to the cell.

[0071] 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 scenario information.

[0072] Exemplarily, the antenna configuration information may include at least one of the following: cell user density, communication frequency band, and supported communication standards, etc.

[0073] Exemplarily, the cell type information may include at least one of the following: an indoor cell, an outdoor cell, an integrated indoor and outdoor cell, a macro cell, a micro cell, and a millimeter wave cell.

[0074] Exemplarily, the scene information of a cell includes: urban scene, rural scene, indoor scene, transportation scene, home scene and other scenes.

[0075] 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.

[0076] Exemplarily, the AI ​​model download information for AI operation includes at least one of the following (1) to (3):

[0077] (1) Whether the community provides AI model downloads.

[0078] 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.

[0079] (2) The community can provide model information for AI model downloads.

[0080] Exemplarily, the model information that the cell can provide for AI model download includes: model identification or AI function, etc.

[0081] (3) The AI ​​model corresponds to the terminal’s demand information.

[0082] In one implementation of the embodiments of the present disclosure, the cell parameters used for AI operation include data distribution information of the cell.

[0083] Illustratively, the data distribution information of a cell may be mathematical distribution characteristics corresponding to the data of the cell, including overall distribution and geometric distribution.

[0084] In one implementation of the embodiments of the present disclosure, the data distribution information of a cell includes: data set information for indicating the data distribution of the cell.

[0085] It is understandable that the data distribution of a cell can be represented by data set information.

[0086] In one implementation of the embodiments of the present disclosure, the dataset information is used to indicate the correspondence between the dataset and the terminal type.

[0087] Exemplarily, the cell data distribution can be represented based on the data set. For example, the data in data set #1 is distributed overall, and the data in data set #2 is distributed geometrically.

[0088] 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.

[0089] Exemplarily, the parameters used for AI operations in the embodiments of the present disclosure include data distribution information indicating a cell, for example, data set information reflecting the data distribution of the cell, such as the ID of the data set.

[0090] The cell data distribution information can be sent based on a system message. In response to the system message containing the cell data distribution information, the cell data distribution information can further include information about the datasets used for different terminals. For example, for normal terminals, dataset #1 is used, while for terminals with reduced capabilities, dataset #2 is used.

[0091] In the communication method provided by the embodiments 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.

[0092] In one implementation of the embodiment of the present disclosure, the broadcast information is broadcast information dedicated to AI operations.

[0093] Exemplarily, the broadcast information content is all related to AI operations.

[0094] In one implementation of the embodiments of the present disclosure, the broadcast information includes broadcast information of AI operations and broadcast information of non-AI operations.

[0095] For example, the broadcast information may include both content related to the AI ​​operation and content unrelated to the AI ​​operation.

[0096] 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.

[0097] 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 via different messages. That is, the broadcast information corresponding to the multiple AI feature use cases is multiple broadcast messages. The number of the multiple broadcast messages is the same as or different from the number of the multiple AI feature use cases.

[0098] For example, 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.

[0099] Exemplarily, public parameters for CSI-related and beam management-related AI operations can be set in the broadcast information of MIMO parameters, and public parameters for positioning-related AI operations can be set and included in the broadcast information with positioning parameters.

[0100] In the communication method provided by the embodiment of the present disclosure, the broadcast information including the AI ​​operation parameters can be sent periodically or based on demand.

[0101] 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 the message only after receiving the request message.

[0102] In one implementation of the embodiments of the present disclosure, the implementation of sending broadcast information includes at least one of the following (a) and (b):

[0103] (a) Sent based on a preset period.

[0104] Exemplarily, the preset period may be in one of the following forms of expression: absolute time, communication time unit, and AI processing time unit.

[0105] Furthermore, absolute time includes seconds, milliseconds, microseconds, etc.

[0106] Communication time units include: Orthogonal Frequency Division Multiplexing (OFDM) symbols, slots, subslots, and OFDM symbol sampling intervals.

[0107] The AI ​​time unit is used to describe the time unit of AI communication. It is understood that the AI ​​time unit is defined as the basic time unit used to measure AI processing tasks.

[0108] (b) Sending in response to receiving a sending request.

[0109] Exemplarily, the network device sends the broadcast information in response to receiving a sending request sent by the terminal (which can also be understood as receiving a request information requesting to send the AI ​​operation parameters).

[0110] It should be noted that those skilled in the art will appreciate 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 principles are 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 will appreciate that such examples are not limitations on the embodiments of the present disclosure.

[0111] Based on the same concept, the embodiments of the present disclosure further provide a communication method performed by a terminal, wherein AI operation parameters are configured based on broadcast information.

[0112] Figure 4 is a flow chart showing a communication method according to an exemplary embodiment. In one implementation of the embodiment of the present disclosure, as shown in Figure 4, the communication method is executed by a terminal and includes the following steps.

[0113] In step S31, broadcast information is received.

[0114] In the embodiment of the present disclosure, the broadcast information includes parameters for AI operations.

[0115] 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 relevant communication operation parameters for AI.

[0116] 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 scenarios in the communication method, please refer to the relevant description in the embodiment of the above-mentioned terminal device, and will not be repeated here one by one.

[0117] In one implementation of the embodiments of the present disclosure, parameters used for AI operations include: general parameters and / or dedicated parameters; general parameters are applicable to AI operations of all AI feature instances; dedicated parameters are dedicated to AI operations of a single AI feature instance.

[0118] In one implementation of an embodiment 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.

[0119] FIG5 is a flow chart of another communication method according to an exemplary embodiment. In one implementation of the disclosed embodiment, as shown in FIG5 , receiving cell parameters including cell support for AI use cases is implemented by the following steps.

[0120] In step S41, first information is received, where the first information indicates the terminal type to which the cell supports the AI ​​feature use case.

[0121] 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.

[0122] 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 scenario information.

[0123] In one implementation of the present disclosure, the AI ​​model download information of the cell includes at least one of the following:

[0124] (1) Whether the community provides AI model downloads.

[0125] 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.

[0126] (2) The community can provide model information for AI model downloads.

[0127] Exemplarily, the model information that the cell can provide for AI model download includes: model identification or AI function, etc.

[0128] (3) The AI ​​model corresponds to the terminal’s demand information.

[0129] In one implementation of the embodiments of the present disclosure, the data distribution information of a cell includes: data set information for indicating the data distribution of the cell.

[0130] In one implementation of the embodiments of the present disclosure, the dataset information is used to indicate the correspondence between the dataset and the terminal type.

[0131] In one implementation of the embodiments of the present disclosure, the broadcast information includes broadcast information of AI operations and broadcast information of non-AI operations.

[0132] 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.

[0133] In one implementation of the embodiments of the present disclosure, the implementation of sending broadcast information includes at least one of the following:

[0134] (a) Sent based on a preset period.

[0135] Exemplarily, the preset period may include at least one of the following representations: absolute time, communication time unit, and AI processing time unit.

[0136] Furthermore, absolute time includes seconds, milliseconds, microseconds, etc.

[0137] Communication time units include: Orthogonal Frequency Division Multiplexing (OFDM) symbols, slots, subslots, and OFDM symbol sampling intervals.

[0138] The AI ​​time unit is used to describe the time unit of AI communication. It is understood that the AI ​​time unit is defined as the basic time unit used to measure AI processing tasks.

[0139] (b) Sending in response to receiving a sending request.

[0140] 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 can be made to the implementation process of the communication method executed by the above-mentioned network device.

[0141] 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.

[0142] Based on the same concept, an embodiment of the present disclosure provides a communication system, which includes a terminal and a network device that executes the above communication method.

[0143] Figure 6 is a schematic diagram of a method interaction of a communication system shown in an exemplary embodiment of the present disclosure. As shown in Figure 6, the embodiment of the present disclosure relates to a communication system, and the above method includes:

[0144] Step S101: a network device sends broadcast information, and a terminal receives the broadcast information.

[0145] In one embodiment, the broadcast information includes parameters for AI operations.

[0146] 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.

[0147] Step S102: The network device sends first information, and the terminal receives the first information.

[0148] In one implementation, the first information is used to indicate the terminal type to which the cell supports the AI ​​feature use case.

[0149] In one embodiment, 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.

[0150] In one implementation, the first information is used to indicate the terminal type to which the cell supports the AI ​​feature use case.

[0151] In one embodiment, 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.

[0152] 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 of step S101 and the partial embodiments of step S102. The network device sending broadcast information in step S102 + the network device sending 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.

[0153] Based on the same concept, an embodiment of the present disclosure also provides an AI communication device.

[0154] FIG7 is a block diagram of a communication device according to an exemplary embodiment. As shown in FIG7 , an embodiment of the present disclosure provides a communication device. The communication device includes a sending unit 101.

[0155] Sending unit 101: used to send broadcast information, which includes parameters for artificial intelligence (AI) operations.

[0156] In one embodiment, the parameters used for AI operations include: general parameters and / or specific parameters; general parameters are applicable to AI operations of all AI feature instances; specific parameters are specific to AI operations of a single AI feature instance.

[0157] 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.

[0158] In one embodiment, the sending unit 101 is further used to send first information, where the first information is used to indicate the terminal type to which the cell supports 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.

[0159] 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.

[0160] In one implementation, the data distribution information of a cell includes: data set information for indicating the data distribution of the cell.

[0161] 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.

[0162] In one embodiment, the AI ​​model download information of the cell includes at least one of the following: whether the cell provides AI model download; model information of the AI ​​model download that the cell can provide; and demand information of the terminal corresponding to the AI ​​model.

[0163] In one implementation, the broadcast information is broadcast information dedicated to AI operations.

[0164] In one implementation, the broadcast information includes broadcast information of AI operations and broadcast information of non-AI operations.

[0165] 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 multiple broadcast information.

[0166] In one embodiment, sending the broadcast information includes: sending based on a preset period; or sending in response to receiving a sending request.

[0167] Based on the same concept, an embodiment of the present disclosure also provides an AI communication device.

[0168] Fig. 8 is a structural block diagram showing a communication device according to an exemplary embodiment.

[0169] As shown in FIG8 , an embodiment of the present disclosure provides a communication device, including a receiving unit 201 .

[0170] Receiving unit 201: used to receive broadcast information, which includes parameters for artificial intelligence (AI) operations.

[0171] In one embodiment, the parameters used for AI operations include: general parameters and / or specific parameters; general parameters are applicable to AI operations of all AI feature instances; specific parameters are specific to AI operations of a single AI feature instance.

[0172] 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.

[0173] In one embodiment, the receiving unit 701 is further used to receive first information, where the first information is used to indicate the terminal type to which the cell supports 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.

[0174] 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.

[0175] In one implementation, the data distribution information of a cell includes: data set information for indicating the data distribution of the cell.

[0176] 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.

[0177] In one embodiment, 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 of the AI ​​model download that the cell can provide; and demand information of the terminal corresponding to the AI ​​model.

[0178] In one implementation, the broadcast information is broadcast information dedicated to AI operations.

[0179] In one implementation, the broadcast information includes broadcast information of AI operations and broadcast information of non-AI operations.

[0180] 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 multiple broadcast information.

[0181] In one embodiment, receiving the broadcast information includes: receiving based on a preset period; or receiving in response to broadcast information sent by a network device.

[0182] Regarding the apparatus 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.

[0183] Figure 9 is a schematic diagram of a communication device according to an exemplary embodiment. For example, device 300 can be any terminal such as a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0184] 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 .

[0185] The processing component 302 generally controls the overall operation of the device 300, such as operations associated with display, phone calls, data communications, camera operation, and recording operations. The processing component 302 may include one or more processors 320 to execute instructions to perform all or part of the steps of the above-described method. In addition, the processing component 302 may include one or more modules to facilitate interaction between the processing component 302 and other components. For example, the processing component 302 may include a multimedia module to facilitate interaction between the multimedia component 308 and the processing component 302.

[0186] 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.

[0187] 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 to the device 300.

[0188] 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 touches, slides, and gestures on the touch panel. The touch sensor can 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 can receive external multimedia data. Each front camera and rear camera can be a fixed optical lens system or have a focal length and optical zoom capability.

[0189] The audio component 310 is configured to output and / or input audio signals. For example, the audio component 310 includes a microphone (MIC) that is configured to receive external audio signals when the device 300 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal can be further stored in the memory 304 or transmitted via the communication component 316. In some embodiments, the audio component 310 also includes a speaker for outputting audio signals.

[0190] I / O interface 312 provides an interface between processing component 302 and peripheral interface modules, such as a keyboard, click wheel, buttons, etc. These buttons may include but are not limited to: a home button, volume buttons, a start button, and a lock button.

[0191] The sensor assembly 314 includes one or more sensors for providing various aspects of the status assessment of 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. The sensor assembly 314 can also detect changes in the position 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 temperature changes of the device 300. The sensor assembly 314 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 314 can 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 can also include an accelerometer, a gyroscope, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0192] 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.

[0193] 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-described methods.

[0194] 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 the 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.

[0195] Figure 10 is a schematic diagram of another communication device according to an exemplary embodiment. For example, device 400 can be provided as a base station or a server. Referring to Figure 10, device 400 includes a processing component 422, which further includes one or more processors, and memory resources represented by memory 432 for storing instructions executable by processing component 422, such as applications. The application stored in memory 432 can include one or more modules, each corresponding to a set of instructions. In addition, processing component 422 is configured to execute instructions to perform the above-described method.

[0196] 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.

[0197] 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 apparatus 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.

[0198] The present disclosure provides an artificial intelligence communication method, device, and storage medium. In some embodiments, the terms "communication method," "information processing method," and "communication method" are interchangeable; the terms "communication device," "information processing device," and "information processing system" are interchangeable; and the terms "information processing system," "communication system," and "communication system" are interchangeable.

[0199] The embodiments of the present disclosure are not exhaustive and are merely 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 steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0200] In the various embodiments of the present disclosure, unless otherwise specified or logically conflicting, the terms and / or descriptions between the various embodiments are consistent and can be referenced from each other. The technical features of different embodiments can be combined to form new embodiments based on their inherent logical relationships. 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.

[0201] It is further understood that in the present disclosure, "plurality" refers to two or more than two, and other quantifiers are similar. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the related objects before and after are in an "or" relationship. The singular forms "a", "the" and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0202] It is further understood that the meanings of words such as "in response to" and "if" involved in this 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".

[0203] It will be further understood that the terms "first," "second," and the like are used to describe various types of information, but such information should not be limited to these terms. These terms are used solely to distinguish information of the same type from one another and do not indicate a particular order or level of importance. In fact, the terms "first," "second," and the like are fully interchangeable. For example, first information could be referred to as second information, and similarly, second information could be referred to as first information without departing from the scope of this disclosure.

[0204] It is further understood that although operations are described in a particular order in the drawings in the embodiments of the present disclosure, this should not be construed as requiring that the operations be performed in the particular order shown or in a serial order, or that all of the operations shown be performed to obtain the desired results. In certain circumstances, multitasking and parallel processing may be advantageous.

[0205] 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 variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein.

[0206] It should be understood that the present disclosure is not limited to the exact structures 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

1. A communication method, characterized in that: Executed by a network device, the method includes: Send broadcast information, wherein the broadcast information includes parameters for artificial intelligence (AI) operations.

2. 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.

3. 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.

4. The communication method according to claim 3, characterized in that: The cell parameter includes a use case of an AI feature supported by the cell, and the method further includes: 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.

5. 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.

6. The communication method according to claim 3, characterized in that: The data distribution information of the cell includes: Data set information used to represent the distribution of cell data.

7. The communication method according to claim 6, characterized in that: The data set information is used to indicate the corresponding relationship between the data set and the terminal type.

8. The communication method according to claim 3, characterized in that: The AI ​​model download information of the community 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.

9. The communication method according to claim 1, characterized in that: The broadcast information is broadcast information dedicated to AI operations.

10. The communication method according to claim 1, characterized in that: The broadcast information includes broadcast information of AI operation and broadcast information of non-AI operation.

11. The communication method according to claim 1, 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.

12. 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.

13. A communication method, characterized in that: Executed by a terminal, the method includes: Receive broadcast information, wherein the broadcast information includes parameters for artificial intelligence (AI) operations.

14. 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.

15. The communication method according to claim 13, characterized in that: The parameters 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.

16. The communication method according to claim 15, characterized in that: The cell parameter includes a use case of an AI feature supported by the cell, and the method further includes: 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.

17. 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.

18. 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.

19. The communication method according to claim 18, characterized in that: The data set information is used to indicate the corresponding relationship between the data set and the terminal type.

20. The communication method according to claim 15, characterized in that: The AI ​​model download information of the community 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.

21. The communication method according to claim 13, characterized in that: The broadcast information is broadcast information dedicated to AI operations.

22. 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.

23. The communication method according to claim 13, 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.

24. 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.

25. A communication device, characterized in that: Executed by a network device, the apparatus comprises: A sending unit is used to send broadcast information, wherein the broadcast information includes parameters for artificial intelligence AI operations.

26. A communication device, characterized in that: Executed by a terminal, the device includes: A receiving unit is used to receive broadcast information, wherein the broadcast information includes parameters for artificial intelligence (AI) operations.

27. A communication device, characterized in that: include: 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.

28. A storage medium, characterized in that: The storage medium stores instructions, and when the instructions in the storage medium are executed by the processor of the terminal, the terminal is enabled to execute the method described in any one of claims 1 to 12; or, when the instructions in the storage medium are executed by the processor of the network device, the network device is enabled to execute the method described in any one of claims 13 to 24.

Images