Data collection and processing method and device, communication equipment and readable storage medium

Abstract

The invention discloses a data collection and processing method and device, communication equipment and a readable storage medium, and belongs to the technical field of communication, and the data collection method comprises the steps that first equipment receives first information sent by second equipment, and the first information comprises a target identifier and target information; the target information is used for indicating N mapping data of N parameters of sensitive information of the second equipment, the target information is obtained by performing data mapping on the N parameters according to a target data mapping mode, and the target identifier is used for indicating the target data mapping mode; the first device generates a data set according to the target information; the first device executes at least one of the following items according to the target identifier and the data set: training an artificial intelligence (AI) unit, at least one of the AI unit and the data set being associated with the target identifier; performing AI unit reasoning; and the AI unit is monitored.

Description

Technical Field

[0001] The present application belongs to the field of communication technology, and specifically relates to a data collection and processing method, device, communication equipment and readable storage medium. Background Art

[0002] In millimeter wave wireless communications, communication transceivers (such as base stations and terminal devices) are configured with multiple analog beams. For the same terminal device, the channel quality measured in different transmit and receive analog beams varies. How to quickly and accurately find the transmit and receive beam group with the highest channel quality from all possible transmit and receive analog beam combinations is the key to influencing transmission quality. After introducing the artificial intelligence (AI) neural network model, the terminal device can effectively predict the transmit and receive analog beam pair with the highest channel quality based on historical channel quality information and report it to the network side.

[0003] In beam pair prediction, if detailed beam information can be provided, the prediction accuracy can be improved. However, beam information such as beam pointing, beam shape, and beam 3dB width are relatively sensitive information, and directly exposing them to the other end may expose sensitive information.

[0004] It can be seen from this that in the prior art, when using AI units, there is a risk of exposing sensitive information when sensitive information such as beam information is directly transmitted between devices. Summary of the invention

[0005] The embodiments of the present application provide a data collection and processing method, apparatus, communication equipment and readable storage medium, which can solve the problem in the prior art that, during the use of the AI ​​unit, sensitive information such as beam information is directly transmitted between devices, thereby exposing sensitive information.

[0006] In a first aspect, a data collection method is provided, comprising:

[0007] The first device receives first information sent by the second device, wherein the first information includes a target identifier and target information, the target information is used to indicate N mapping data of N parameters of sensitive information of the second device, the target information is obtained by performing data mapping on the N parameters according to a target data mapping method, and the target identifier is used to indicate the target data mapping method;

[0008] The first device generates a data set according to the target information;

[0009] The first device performs at least one of the following according to the target identifier and the data set:

[0010] Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier;

[0011] The AI ​​unit reasoning;

[0012] The AI ​​unit is monitored.

[0013] In a second aspect, a data collection method is provided, comprising:

[0014] The second device performs data mapping on N parameters of the sensitive information of the second device according to the target data mapping mode to obtain target information, wherein the target information is used to indicate N mapping data of the N parameters;

[0015] The second device sends first information to the first device, wherein the first information includes the target information and a target identifier, the target identifier is used to indicate the target data mapping mode, and the N mapping data are used to generate a data set;

[0016] The data set is used for at least one of the following:

[0017] Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier;

[0018] The AI ​​unit reasoning;

[0019] The AI ​​unit is monitored.

[0020] In a third aspect, a data collection device is provided, which is applied to a first device, and the device includes:

[0021] A first receiving module, configured to receive first information sent by a second device, wherein the first information includes a target identifier and target information, the target information is used to indicate N mapping data of N parameters of sensitive information of the second device, the target information is obtained by performing data mapping on the N parameters according to a target data mapping method, and the target identifier is used to indicate the target data mapping method;

[0022] A generating module, used for generating a data set according to the target information;

[0023] An execution module, configured to execute at least one of the following according to the target identifier and the data set:

[0024] Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier;

[0025] The AI ​​unit reasoning;

[0026] The AI ​​unit is monitored.

[0027] In a fourth aspect, a data collection device is provided, which is applied to a second device, and the device includes:

[0028] a mapping module, configured to perform data mapping on N parameters of the sensitive information of the second device according to a target data mapping mode to obtain target information, wherein the target information is used to indicate N mapping data of the N parameters;

[0029] A first sending module, configured to send first information to a first device, wherein the first information includes the target information and a target identifier, the target identifier is used to indicate the target data mapping mode, and the N mapping data are used to generate a data set;

[0030] The data set is used for at least one of the following:

[0031] Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier;

[0032] The AI ​​unit reasoning;

[0033] The AI ​​unit is monitored.

[0034] In a fifth aspect, a communication device is provided, which terminal includes a processor and a memory, wherein the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the steps of the method described in the first aspect or the second aspect are implemented.

[0035] In a sixth aspect, a communication device is provided, including a processor and a communication interface;

[0036] When the communication device serves as the first device, the communication interface is used to receive first information sent by the second device, wherein the first information includes a target identifier and target information, the target information is used to indicate N mapping data of N parameters of sensitive information of the second device, the target information is obtained by performing data mapping on the N parameters according to a target data mapping method, and the target identifier is used to indicate the target data mapping method;

[0037] The processor is used to generate a data set according to the target information;

[0038] According to the target identifier and the data set, at least one of the following is performed:

[0039] Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier;

[0040] The AI ​​unit reasoning;

[0041] Monitoring the AI ​​unit;

[0042] When the communication device serves as the second device, the processor is used to perform data mapping on N parameters of sensitive information of the second device according to a target data mapping mode to obtain target information, wherein the target information is used to indicate N mapping data of the N parameters;

[0043] The communication interface is used to send first information to the first device, wherein the first information includes the target information and a target identifier, the target identifier is used to indicate the target data mapping mode, and the N mapping data are used to generate a data set;

[0044] The data set is used for at least one of the following:

[0045] Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier;

[0046] The AI ​​unit reasoning;

[0047] The AI ​​unit is monitored.

[0048] In a seventh aspect, a communication system is provided, comprising: a first device and a second device, wherein the first device can be used to execute the steps of the method described in the first aspect, and the second device can be used to execute the steps of the method described in the second aspect.

[0049] In an eighth aspect, a readable storage medium is provided, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented, or the steps of the method described in the second aspect are implemented.

[0050] In the ninth aspect, a chip is provided, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the method described in the first aspect, or to implement the method described in the second aspect.

[0051] In the twelfth aspect, a computer program / program product is provided, wherein the computer program / program product is stored in a storage medium, and the program / program product is executed by at least one processor to implement the method as described in the first aspect, or to implement the method as described in the second aspect.

[0052] In an embodiment of the present application, the first device is capable of receiving first information including a target identifier and target information sent by the second device, and generating a data set according to the target information, where the data set is used for at least one of "training the AI ​​unit, reasoning the AI ​​unit, and monitoring the AI ​​unit", and at least one of the AI ​​unit and the data set is associated with the target identifier. The target information is used to indicate N mapping data of N parameters of sensitive information of the second device, and the target information is obtained by data mapping the N parameters according to the target data mapping method, and the target identifier is used to indicate the target data mapping method.

[0053] It can be seen that in the embodiment of the present application, the second device maps the N parameters of the sensitive information of the second device according to the target data mapping method, obtains the target information for indicating (i.e., characterizing) the N mapping data of the N parameters, and sends the target information and the target identifier for indicating the target data mapping method to the first device, so that the first device generates the above-mentioned data set applied to the AI ​​unit based on the target information. In this way, during the use of the AI ​​unit, what is transmitted between the first device and the second device is the target information of the N mapping data of the N parameters indicating the sensitive information, and the target data mapping method used to obtain the target information, rather than directly transmitting the sensitive information, thereby avoiding the risk of exposing the sensitive information. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 is a block diagram of a wireless communication system to which the embodiments of the present application can be applied;

[0055] Figure 2 is a flow chart of a data collection method in an embodiment of the present application;

[0056] Figure 3 is a flow chart of another data collection method in an embodiment of the present application;

[0057] Figure 4 is a flow chart of implementation mode 1-1 of the data collection method in the embodiment of the present application;

[0058] Figure 5 It is a flowchart of implementation mode 1-2 of the data collection method in the embodiment of the present application;

[0059] Figure 6 It is a flowchart of implementation modes 1-3 of the data collection method in the embodiments of the present application;

[0060] Figure 7 It is a flowchart of implementation mode 2-1 of the data collection method in the embodiment of the present application;

[0061] Figure 8It is a flowchart of implementation mode 2-2 of the data collection method in the embodiment of the present application;

[0062] Fig. 9 It is a flowchart of implementation mode 2-3 of the data collection method in the embodiment of the present application;

[0063] Fig.10 It is a flowchart of implementation mode 3-1 of the data collection method in the embodiment of the present application;

[0064] Fig.11 It is a flowchart of implementation mode 3-2 of the data collection method in the embodiment of the present application;

[0065] Fig.12 It is a flowchart of implementation mode 3-3 of the data collection method in the embodiment of the present application;

[0066] Fig.13 It is a flowchart of implementation mode 4-1 of the data collection method in the embodiment of the present application;

[0067] Fig.14 It is a flowchart of implementation mode 4-2 of the data collection method in the embodiment of the present application;

[0068] Fig.15 It is a flowchart of implementation mode 4-3 of the data collection method in the embodiment of the present application;

[0069] Fig.16 is a structural block diagram of a data collection device in an embodiment of the present application;

[0070] Fig.17 is a structural block diagram of another data collection device in an embodiment of the present application;

[0071] Fig.18 is a structural block diagram of a communication device in an embodiment of the present application;

[0072] Fig.19 is a structural block diagram of a terminal in an embodiment of the present application;

[0073] Fig. 20 It is a structural block diagram of a network side device in an embodiment of the present application. DETAILED DESCRIPTION

[0074] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of this application.

[0075] The terms "first", "second", etc. of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way are interchangeable where appropriate, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of one type, and the number of objects is not limited, for example, the first object can be one or more. In addition, "or" in the present application represents at least one of the connected objects. For example, "A or B" covers three schemes, namely, Scheme 1: including A but not including B; Scheme 2: including B but not including A; Scheme 3: including both A and B. The character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0076] The term "indication" in this application can be a direct indication (or explicit indication) or an indirect indication (or implicit indication). A direct indication can be understood as the sender explicitly informing the receiver of specific information, operations to be performed, or request results in the sent indication; an indirect indication can be understood as the receiver determining the corresponding information according to the indication sent by the sender, or making a judgment and determining the operation to be performed or the request result according to the judgment result.

[0077] It is worth noting that the technology described in the embodiments of the present application is not limited to the Long Term Evolution (LTE) / LTE-Advanced (LTE-A) system, but can also be used in other wireless communication systems, such as Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Frequency Division Multiple Access (FDMA), Orthogonal Frequency Division Multiple Access (OFDMA), Single-carrier Frequency-Division Multiple Access (SC-FDMA) or other systems. The terms "system" and "network" in the embodiments of the present application are often used interchangeably, and the described technology can be used for the systems and radio technologies mentioned above as well as for other systems and radio technologies. The following description describes a New Radio (NR) system for illustrative purposes, and NR terminology is used in most of the following descriptions, but these technologies can also be applied to systems other than NR systems, such as the 6th generation (6 thGeneration, 6G) communication system.

[0078] Figure 1 A block diagram of a wireless communication system applicable to an embodiment of the present application is shown. The wireless communication system includes a terminal 11 and a network side device 12. Among them, the terminal 11 can be a mobile phone, a tablet computer (Tablet Personal Computer), a laptop computer (Laptop Computer), a notebook computer, a personal digital assistant (Personal Digital Assistant, PDA), a handheld computer, a netbook, an ultra-mobile personal computer (Ultra-mobile Personal Computer, UMPC), a mobile Internet device (Mobile Internet Device, MID), an augmented reality (Augmented Reality, AR), a virtual reality (Virtual Reality, VR) device, a robot, a wearable device (Wearable Device), an aircraft (flight vehicle), a vehicle-mounted device (Vehicle User Equipment, VUE), a ship-mounted device, a pedestrian terminal (Pedestrian User Equipment, PUE), a smart home (home appliances with wireless communication functions, such as refrigerators, televisions, washing machines or furniture, etc.), a game console, a personal computer (Personal Computer, PC), a teller machine or a self-service machine and other terminal side devices. Wearable devices include: smart watches, smart bracelets, smart headphones, smart glasses, smart jewelry (smart bracelets, smart bracelets, smart rings, smart necklaces, smart anklets, smart anklets, etc.), smart wristbands, smart clothing, etc. Among them, the vehicle-mounted device can also be called a vehicle-mounted terminal, a vehicle-mounted controller, a vehicle-mounted module, a vehicle-mounted component, a vehicle-mounted chip or a vehicle-mounted unit, etc. It should be noted that the specific type of the terminal 11 is not limited in the embodiment of the present application.

[0079] The network side device 12 may include an access network device or a core network device, wherein the access network device may also be referred to as a radio access network (RAN) device, a radio access network function or a radio access network unit. The access network device may include a base station, a wireless local area network (WLAN) access point (AS) or a wireless fidelity (WiFi) node, etc. Among them, the base station may be referred to as a Node B (NB), an evolved Node B (eNB), a next generation Node B (gNB), a New Radio Node B (NR Node B), an access point, a Relay Base Station (RBS), a Serving Base Station (SBS), a Base Transceiver Station (BTS), a radio base station, a radio transceiver, a Basic Service Set (BSS), an Extended Service Set (ESS), a Home Node B (HNB), a Home Evolved Node B (home evolved Node B), a Transmission Reception Point (TRP) or other appropriate terms in the field. As long as the same technical effect is achieved, the base station is not limited to specific technical terms. It should be noted that in the embodiments of the present application, only the base station in the NR system is used as an example for introduction, and the specific type of the base station is not limited.

[0080] The data collection method provided in the embodiments of the present application is described in detail below through some embodiments and their application scenarios in combination with the accompanying drawings.

[0081] First, as Figure 2 As shown, an embodiment of the present application provides a data collection method, the execution subject of the method is a first device, and the first device may be a terminal. The method includes:

[0082] Step 201: A first device receives first information sent by a second device.

[0083] Among them, the first information includes a target identifier and target information, and the target information is used to indicate N mapping data of N parameters of sensitive information of the second device, that is, the target information is used to characterize the N mapping data of the N parameters; the target information is obtained by performing data mapping on the N parameters according to a target data mapping method, and the target identifier is used to indicate the target data mapping method.

[0084] In addition, the target identifier can be represented by a data set identifier, a data collection identifier, a data collection identifier, a data processing identifier, a data privacy processing identifier, etc.

[0085] It can be seen from this that the second device performs data mapping on the N parameters of the sensitive information of the second device according to the target data mapping method, and obtains target information used to indicate (i.e., characterize) the N mapping data of the N parameters, thereby sending the target information and the target identifier used to indicate the target data mapping method to the first device.

[0086] It can be seen that the N parameters of the sensitive information of the second device are mapped according to the target data mapping method, and target information of the N mapping data used to indicate (i.e., characterize) the N parameters is obtained. In this way, what the second device sends to the first device is no longer the real N parameters, but the mapped target information. Therefore, even if the other end receives the target information, it cannot obtain the real N parameters based on the target information. Therefore, here, the target information serves as the privacy information of the N parameters of the second device, and the target data mapping method can also be called a data privacy method (i.e., a method of removing sensitive information).

[0087] Optionally, the sensitive information includes a transmission beam pointing, and the N parameters include N directional dimensions of the transmission beam pointing, wherein the N dimensions may include a horizontal pointing and a vertical pointing.

[0088] That is, the second device can perform data mapping on the N directional dimensions (e.g., horizontal and vertical directions) of the transmission beam of the second device according to the target data mapping method, and obtain target information for indicating (i.e., characterizing) the N mapping data of the N directional dimensions. In this way, what is transmitted between the first device and the second device is no longer the actual beam direction, but the mapping data of the beam direction (i.e., privacy data), which avoids exposing the actual beam direction and improves data security.

[0089] It should be noted that when data mapping is performed on N directional dimensions according to the target data mapping method, data mapping can be performed on the angles of the N directional dimensions, or data mapping can be performed on the physical identifiers of the N directional dimensions. For example, the vertical pointing includes the pointing of the four angles of 22.5, 67.5, 112.5, and 157.5, and the physical identifiers corresponding to these four angles are x1, x2, x3, and x4, respectively. Then, data mapping can be performed on the four angles of "22.5, 67.5, 112.5, and 157.5" according to the target data mapping method, or data mapping can be performed on the four physical identifiers of "x1, x2, x3, and x4".

[0090] It is understandable that the sensitive information may also include other information besides the transmission beam pointing, such as beam shape, beam 3dB width, etc.

[0091] In addition, it should be noted that the above target information may explicitly indicate N mapping data of N parameters (ie, the target information includes N mapping data), or may implicitly indicate N mapping data of N parameters.

[0092] Step 202: The first device generates a data set according to the target information.

[0093] Step 203: The first device performs at least one of the following according to the target identifier and the data set: training an artificial intelligence AI unit, reasoning the AI ​​unit, and monitoring the AI ​​unit.

[0094] Wherein, at least one of the AI ​​unit and the data set is associated with the target identifier.

[0095] The above-mentioned target information may explicitly indicate N mapping data of N parameters, or may implicitly indicate N mapping data of N parameters; when the target information explicitly indicates N mapping data, after the first device receives the above-mentioned first information, it may generate a data set for the AI ​​unit associated with the target identifier based on the N mapping data; when the target information implicitly indicates N mapping data, after the first device receives the above-mentioned first information, it may first calculate N mapping data based on the target information, and then generate a data set for the AI ​​unit associated with the target identifier based on the obtained N mapping data.

[0096] Among them, when the data set is used to train the AI ​​unit, the data set includes N mapping data, measurement results related to the functions of the AI ​​unit, and label data; here, the label data includes the actual measurement results in the regression problem, or the identification obtained based on the actual measurement results in the classification problem; wherein, the regression problem refers to inferring the output value corresponding to the AI ​​unit input, which is also called continuous variable prediction; the classification problem refers to inferring the category corresponding to the AI ​​unit input, which is also called discrete variable prediction. That is, the regression problem is an approximate prediction of the true value, and the classification problem is to discretize the true value. It can be seen that the output of the AI ​​unit in the regression problem is the measurement result, and the output of the AI ​​unit in the classification problem is an identification obtained based on the actual measurement result.

[0097] When a data set is used for AI reasoning, the data set includes N mapping data and measurement results related to the functions of the AI ​​unit, that is, the data set serves as the input of the AI ​​unit; here, the reasoning process of the AI ​​unit is the process of inputting N mapping data and measurement results related to the functions of the AI ​​unit into the AI ​​unit to obtain the output of the AI ​​unit.

[0098] When a data set is used to monitor an AI unit, the data set includes N mapping data and measurement results related to the functions of the AI ​​unit, that is, the data set serves as the input of the AI ​​unit; the data set is processed by the AI ​​unit to obtain the output of the AI ​​unit, and then a monitoring data set is generated based on the output of the AI ​​unit and the label data.

[0099] In addition, it should be noted that the AI ​​unit is associated with a target identifier, which means that the input data used when training the AI ​​unit is data mapped according to the target data mapping method indicated by the target identifier, and the data input into the AI ​​unit during the reasoning and monitoring stages of the AI ​​unit is data mapped according to the target data mapping method indicated by the target identifier.

[0100] That is, the target information is obtained according to the target data mapping method, and the data set generated based on the target information is used in the use process of the AI ​​unit associated with the target identifier of the target data mapping method, such as the training, reasoning, and monitoring stages.

[0101] In addition, the AI ​​unit is associated with a target identifier, specifically, the identifier of the AI ​​unit is associated with the target identifier. Optionally, the identifier of the AI ​​unit may be an AI unit identifier, an AI structure identifier, an AI algorithm identifier, or an identifier of a specific data set associated with the AI ​​unit, or an identifier of a specific scene, environment, channel feature, or device associated with the AI, or an identifier of a function, feature, capability, or module associated with the AI, without specific limitation.

[0102] In an embodiment of the present application, the first device is a device that performs data collection, and the collected data is used for at least one of the subsequent training, reasoning, and monitoring of the AI ​​unit. The first device can be called a data collection device; the second device cooperates with the first device to provide the first device with sensitive information of the second device. For data security reasons, the sensitive information of the second device needs to be mapped on the second device and then provided to the first device. The second device can be called an information mapping processing device.

[0103] In addition, the AI ​​unit described in the embodiments of the present application may also be referred to as an AI model, an AI structure, etc., or the AI ​​unit may also refer to a processing unit capable of implementing specific algorithms, formulas, processing procedures, capabilities, etc. related to AI, or the AI ​​unit may be a processing method, algorithm, function, module or unit for a specific data set, or the AI ​​unit may be a processing method, algorithm, function, module or unit running on AI-related hardware such as a graphics processing unit (GPU), a neural network processor (NPU), a tensor processing unit (TPU), an application-specific integrated circuit (ASIC), etc., and the present application does not make specific limitations on this. Optionally, the specific data set includes at least one of the input and output of the AI ​​unit.

[0104] It can be seen from the above steps 201 to 203 that in the embodiment of the present application, the first device can receive the first information including the target identifier and the target information sent by the second device, and generate a data set according to the target information. Here, the data set is used for at least one of "training the AI ​​unit, reasoning the AI ​​unit, and monitoring the AI ​​unit", and at least one of the AI ​​unit and the data set is associated with the target identifier. Among them, the target information is used to indicate the N mapping data of the N parameters of the sensitive information of the second device, and the target information is obtained by data mapping the N parameters according to the target data mapping method, and the target identifier is used to indicate the target data mapping method.

[0105] It can be seen that in the embodiment of the present application, the second device maps the N parameters of the sensitive information of the second device according to the target data mapping method, obtains the target information for indicating the N mapping data of the N parameters, and sends the target information and the target identifier for indicating the target data mapping method to the first device, so that the first device generates the above-mentioned data set applied to the AI ​​unit based on the target information. In this way, during the use of the AI ​​unit, what is transmitted between the first device and the second device is the target information of the N mapping data of the N parameters indicating the sensitive information, and the target data mapping method used to obtain the target information, rather than directly transmitting the sensitive information, thereby avoiding the risk of exposing the sensitive information.

[0106] In addition, in the prior art, when the UE and the base station interact, the base station sends a beam privacy indication and a virtual beam identifier to avoid exposing sensitive information.

[0107] Assume that the mapping relationship between the transmit beam pointing and the transmit beam physical identifier is as shown in Table 1.

[0108] Table 1 Example of mapping relationship between transmit beam pointing and transmit beam physical identification

[0109]

[0110] Among them, by performing a random operation on the mapping relationship shown in the above Table 1, the mapping relationship between the transmission beam and the virtual beam identifier can be obtained, as shown in Table 2.

[0111] Table 2 Example of mapping relationship between transmit beam pointing and virtual beam identification

[0112]

[0113] Then, when configuring the measurement resources, the base station sends the virtual beam identifier processed by Table 2 associated with the measurement resources, and the privacy processing identifier or data set identifier associated with Table 2 to the UE.

[0114] Among them, if the base station directly sends the mapped beam identifier to the UE according to Table 1, the beam identifier exposes the relative relationship of some beam pointing, for example, the vertical angles indicated by identifiers 1 to 4 are in order from small to large. In comparison, after mapping according to Table 2, the virtual beam identifier is sent to the UE, and identifiers 1 to 4 cannot indicate the order information from small to large between the vertical beam or horizontal beam angles, which better protects the sensitive information of the beam pointing.

[0115] However, the method of mixing the beams of the horizontal and vertical dimensions of the base station for privacy processing and mapping to obtain virtualized identifiers (i.e., the processing method from Table 1 to Table 2) loses too much relative relationship between the beams, which will cause a decrease in prediction performance.

[0116] In the data collection method of the embodiment of the present application, when performing data mapping on the horizontal and vertical directions (or the physical identifier of the horizontal and the physical identifier of the vertical) of the transmitting beam of the second device, data mapping is performed on the horizontal and vertical dimensions respectively, and the target information obtained is the mapping data that can indicate the horizontal direction and the mapping data of the vertical direction, rather than mixing the horizontal and vertical dimensions for privacy. Therefore, in the embodiment of the present application, by performing privacy processing on the horizontal and vertical dimensions of the transmitting beam respectively, it helps to retain the relative relationship between some beams, helps the terminal to extract the features of the transmitting beam, improves the accuracy of beam prediction, and ensures that sensitive information of the beam is not exposed.

[0117] The following specifically describes a method of performing data mapping on N parameters according to the target data mapping method to obtain target information, as described in the following method 1 or method 2:

[0118] Method 1: Optionally, the target information includes the N mapping data, the target data mapping method includes N first data mapping methods, the i-th mapping data is the i-th parameter in the sensitive information, obtained by the i-th first data mapping method, and i is an integer from 1 to N.

[0119] It can be understood that the N first data mapping modes may be the same or different.

[0120] When the N first data mapping modes are the same, the target data mapping mode includes the first data mapping mode, and the N parameters are all data mapped by the first data mapping mode to obtain N mapping data;

[0121] When the N first data mapping modes are different, data mapping is performed on the ith parameter using the ith first data mapping mode to obtain the ith mapping data.

[0122] For example, when the N parameters include the horizontal pointing and vertical pointing of the transmitting beam of the second device, the horizontal pointing (or the physical identifier of the horizontal pointing) and the vertical pointing (or the physical identifier of the vertical pointing) can be data mapped through the same first data mapping method to obtain mapping data corresponding to the horizontal pointing and mapping data corresponding to the vertical pointing.

[0123] Among them, the mapping data corresponding to the horizontal pointing is used to identify the horizontal pointing; the mapping data corresponding to the vertical pointing is used to identify the vertical pointing; therefore, the mapping data corresponding to the horizontal pointing can also be called a horizontal virtual identification, and the mapping data corresponding to the vertical pointing is used to identify the vertical pointing and can also be called a vertical virtual identification.

[0124] The following takes N parameters as a horizontally pointing physical identifier and a vertically pointing physical identifier, N mapping data including a horizontal virtual identifier and a vertical virtual identifier, and N first data mapping methods being the same as an example, and explains method one based on the following example.

[0125] It is assumed that the mapping relationship between horizontal orientation and physical identification is shown in Table 3 below.

[0126] Table 3 Example of mapping relationship between horizontal orientation and physical identification

[0127] Horizontal pointing -78.75 -56.25 -33.75 -11.25 11.25 33.75 56.25 78.75 Physical identification 1 2 3 4 5 6 7 8

[0128] After the horizontally pointing physical identifiers in Table 1 are processed by the first data mapping method (for example, randomly disrupting the order), the mapping relationship between the horizontal pointing and the horizontal virtual identifier is shown in Table 4 below.

[0129] Table 4 Example of mapping relationship between horizontal orientation and horizontal virtual identification

[0130] Horizontal pointing -78.75 -56.25 -33.75 -11.25 11.25 33.75 56.25 78.75 Virtual ID 6 1 5 3 7 2 8 4

[0131] Assume that the mapping relationship between vertical orientation and physical identification is as shown in Table 5 below.

[0132] Table 5 Example of mapping relationship between vertical orientation and physical identification

[0133] Horizontal pointing 22.5 67.5 112.5 157.5 Physical identification 1 2 3 4

[0134] After the vertically pointing physical identifiers in Table 5 are processed by the first data mapping method (for example, randomly disrupting the order), the mapping relationship between the vertical pointing and the vertical virtual identifier is shown in Table 6 below.

[0135] Table 6 Example of mapping relationship between vertical orientation and vertical virtual identification

[0136] Horizontal pointing 22.5 67.5 112.5 157.5 Virtual ID 2 3 4 1

[0137] It can be seen that the base station's beam pointing of (horizontal pointing, vertical pointing) = (-33.75, 67.5), or (horizontal physical identifier, vertical physical identifier) ​​= (3, 2), is mapped through the first data mapping method to obtain (virtual horizontal identifier, virtual vertical identifier) ​​= (5, 3), where 5 is the horizontal virtual identifier and 3 is the vertical virtual identifier.

[0138] Mode 2: Optionally, the target information includes first data and second information, and the second information is used to indicate a mapping relationship between the first data and the N mapping data;

[0139] The first device generates a data set according to the target information, including:

[0140] The first device determines the N mapping data according to the mapping relationship indicated by the second information and the first data;

[0141] The first device generates the data set according to the N mapping data.

[0142] Here, the first data is one-dimensional data mapped from N-dimensional data constituted by the N mapping data, the N mapping data are N parameters of the sensitive information respectively obtained through the second data mapping method, the second information is used to indicate the mapping relationship between the first data and the N mapping data, the i-th mapping data corresponds to the i-th parameter in the sensitive information, and i is an integer from 1 to N.

[0143] From this, it can be seen that the second device can also perform data mapping on N parameters through a second data mapping method to obtain N mapping data, and then convert the N-dimensional data composed of the N mapping data into one-dimensional data to obtain the first data, thereby sending the first data and the second information used to indicate the mapping relationship between the first data and the N mapping data to the first device.

[0144] Among them, the first data is obtained by converting N-dimensional data composed of N mapping data. Therefore, there is a mapping relationship between the N mapping data and the first data. It can be seen that after obtaining the N mapping data, the second device may not directly send the N mapping data to the first device, but send the first data and the second information indicating the mapping relationship between the first data and the N mapping data. In this way, the first device can determine the N mapping data based on the mapping relationship indicated by the second information and the first data.

[0145] For example, when the N parameters include the horizontal pointing and vertical pointing of the transmitting beam of the second device, the second device can perform data mapping on the horizontal pointing (or the physical identifier of the horizontal pointing) and the vertical pointing (or the physical identifier of the vertical pointing) through a second data mapping method to obtain the horizontal virtual identifier and the vertical virtual identifier; then convert the two-dimensional data consisting of the horizontal virtual identifier and the vertical virtual identifier into one-dimensional data to obtain the first data, which can also be called the target virtual identifier; thereby sending the target virtual identifier and the second information indicating the mapping relationship between the target virtual identifier and the horizontal virtual identifier and the vertical virtual identifier to the first device, so that the first device can obtain the horizontal virtual identifier and the vertical virtual identifier based on the mapping relationship and the target virtual identifier.

[0146] Optionally, the second information includes a reference parameter, the number of values ​​of the reference parameter, and a functional relationship between the first data and the N mapping data; wherein the reference parameter is at least part of the N parameters.

[0147] Here, the number of values ​​of the reference parameter and the first data are variables in the above functional relationship. Therefore, by substituting the number of values ​​of the reference parameter and the first data into the functional relationship between the first data and N mapping data, N mapping data can be calculated.

[0148] The following takes the case where the N parameters are a horizontally pointing physical identifier and a vertically pointing physical identifier, the N mapping data include a horizontal virtual identifier and a vertical virtual identifier, and the first one-dimensional data is a target virtual identifier as an example to explain the above method 2:

[0149] For example, the base station maps the beam pointing of (horizontal pointing, vertical pointing) = (-33.75, 67.5) through the second data mapping method, and obtains (virtual horizontal identifier, virtual vertical identifier) ​​= (5, 3), where 5 is the horizontal virtual identifier and 3 is the vertical virtual identifier.

[0150] At this time, if the reference parameter is vertically pointed and the number of reference parameter values ​​is 4, the base station side calculates the target virtual identifier as: (horizontal virtual identifier-1)*number of reference parameter values+vertical virtual identifier=(5-1)*4+3=19.

[0151] Assuming that the calculation formula is agreed upon in advance by the terminal and the base station, the terminal can solve the horizontal virtual identifier and the vertical virtual identifier according to the received target virtual identifier 19 and the transformed form of the above formula:

[0152] Horizontal virtual identifier = ceil (target virtual identifier / number of reference parameter values) = ceil (19 / 4) = 5;

[0153] Vertical virtual identifier = target virtual identifier – horizontal virtual identifier * number of reference parameter values ​​= 3.

[0154] Among them, ceil(19 / 4) means rounding up.

[0155] Optionally, before the first device receives the first information sent by the second device, the method further includes:

[0156] The first device sends third information to the second device;

[0157] The third information includes the target identifier and target indication information, and the target indication information is used to indicate that data mapping is performed on the N parameters respectively.

[0158] From this, it can be seen that the first device can also send third information including a target identifier and target indication information to the second device to inform the second device of the data collection requirements of the first device, so that the second device can perform data mapping on N parameters of the sensitive information of the second device according to the requirements indicated by the target indication information and according to the target data mapping method indicated by the target identifier.

[0159] Optionally, during the AI ​​unit reasoning stage, monitoring stage, and identification (ie, registration) stage, the first device sends the third information to the second device.

[0160] Optionally, in a case where the target data mapping mode includes N first data mapping modes, the target indication information includes first indication information, where the first indication information is used to indicate that the N parameters are respectively mapped to N mapping data through the N first data mapping modes;

[0161] In the case where the target data mapping method includes a second data mapping method, the target indication information includes second indication information, and the second indication information is used to indicate that through the second data mapping method, the N parameters are respectively mapped into N mapping data, and then the N-dimensional data composed of the N mapping data are mapped into one-dimensional data.

[0162] Among them, the above-mentioned first indication information can also be called the first condition, the first additional condition or the first model usage condition; the above-mentioned second indication information can also be called the second condition, the second additional condition or the second model usage condition.

[0163] It can be seen that, based on the above-mentioned method one, if the N first data mapping methods are the same, the first device can send a first identifier for identifying the first data mapping method to the second device, and instruct the second device through the first indication information how to use the first data mapping method indicated by the first identifier; if the N first data mapping methods are different, the first device can send an identifier for identifying the N first data mapping methods to the second device, and instruct the second device through the first indication information how to use the N first data mapping methods.

[0164] Based on the above-mentioned method 2, the first device can send a second identifier for identifying the second data mapping method to the second device, and instruct the second device through second indication information how to use the second data mapping method indicated by the second identifier.

[0165] It should be noted that, in the case of the above-mentioned method 2, the first device may not send the first indication information. In this way, after the second device receives the identifier for identifying the N first data mapping methods, it maps the N parameters to the N mapping data respectively by default through the N first data mapping methods;

[0166] For the scheme in which N first data mapping methods are the same in the above-mentioned method one, and the scheme in the above-mentioned method two, both use one data mapping method. In this case, the third information (i.e., the demand information) sent by the first device to the second device includes an identifier for identifying the data mapping method. Therefore, in order to distinguish between the two schemes, the above-mentioned first indication information or the second indication information can also be used to indicate how to use the data mapping method indicated by the identifier.

[0167] Optionally, the method further comprises:

[0168] In the case where the first device is a terminal device, the first device sends capability information to the second device, wherein the capability information is used to indicate that the terminal device supports the first processing mode or the second processing mode;

[0169] The first processing method is a method of mapping the N parameters into N mapping data;

[0170] The second processing method is a method in which after the N parameters are mapped into the N mapping data, the N mapping data are further mapped into one-dimensional data.

[0171] It can be seen that the first device can also report to the second device which of the first processing method and the second processing method it supports, so that the second device can use the processing method supported by the first device to perform data mapping on the N parameters of the second device.

[0172] The first processing method may also be referred to as configuration of an N-dimensional identifier, and the second processing method may also be referred to as configuration of a one-dimensional identifier.

[0173] Optionally, the first data mapping method or the second data mapping method includes any one of the following:

[0174] Bias the data;

[0175] Scale the data;

[0176] Apply polynomial function to the data;

[0177] Perform multi-dimensional mapping on a single data to obtain multiple data;

[0178] Perform random operations on a set of data;

[0179] Quantitative mapping of single data.

[0180] Second, as Figure 3 As shown, an embodiment of the present application provides a data collection method, the execution subject of the method is a second device, and the second device may be a base station. The method includes:

[0181] Step 301: The second device performs data mapping on N parameters of the sensitive information of the second device according to a target data mapping method to obtain target information.

[0182] The target information is used to indicate the N mapping data of the N parameters, that is, the target information is used to characterize the N mapping data of the N parameters.

[0183] Step 302: The second device sends first information to the first device.

[0184] The first information includes the target information and a target identifier, the target identifier is used to indicate the target data mapping method, and the N mapping data are used to generate a data set.

[0185] The data set is used for at least one of the following:

[0186] Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier;

[0187] The AI ​​unit reasoning;

[0188] The AI ​​unit is monitored.

[0189] In addition, after receiving the above-mentioned first information, the first device generates a data set for the AI ​​unit associated with the target identifier according to the target information.

[0190] It can be seen that the N parameters of the sensitive information of the second device are mapped according to the target data mapping method, and target information of the N mapping data used to indicate (i.e., characterize) the N parameters is obtained. In this way, what the second device sends to the first device is no longer the real N parameters, but the mapped target information. Therefore, even if the other end receives the target information, it cannot obtain the real N parameters based on the target information. Therefore, here, the target information serves as the privacy information of the N parameters of the second device, and the target data mapping method can also be called a data privacy method.

[0191] Optionally, the sensitive information includes a transmission beam pointing, and the N parameters include N directional dimensions of the transmission beam pointing, wherein the N dimensions may include a horizontal pointing and a vertical pointing.

[0192] That is, the second device can perform data mapping on the N directional dimensions (e.g., horizontal and vertical directions) of the transmission beam of the second device according to the target data mapping method, and obtain target information for indicating (i.e., characterizing) the N mapping data of the N directional dimensions. In this way, what is transmitted between the first device and the second device is no longer the actual beam direction, but the mapping data of the beam direction (i.e., privacy data), which avoids exposing the actual beam direction and improves data security.

[0193] It should be noted that when data mapping is performed on N directional dimensions according to the target data mapping method, data mapping may be performed on the angles of the N directional dimensions, or data mapping may be performed on the physical identifiers of the N directional dimensions.

[0194] It is understandable that the sensitive information may also include other information besides the transmission beam pointing, such as beam shape, beam 3dB width, etc.

[0195] In addition, it should be noted that the above target information may explicitly indicate N mapping data of N parameters (i.e., the target information includes N mapping data), or may implicitly indicate N mapping data of N parameters. Therefore, when the target information explicitly indicates N mapping data, after the first device receives the above first information, it may generate a data set for the AI ​​unit associated with the target identifier based on the N mapping data; when the target information implicitly indicates N mapping data, after the first device receives the above first information, it may first calculate the N mapping data based on the target information, and then generate a data set for the AI ​​unit associated with the target identifier based on the obtained N mapping data.

[0196] In addition, the AI ​​unit is associated with a target identifier, indicating that the input data used when training the AI ​​unit is data mapped according to the target data mapping method indicated by the target identifier, and that the data input into the AI ​​unit during the reasoning and monitoring stages of the AI ​​unit is data mapped according to the target data mapping method indicated by the target identifier.

[0197] That is, the target information is obtained according to the target data mapping method, and the data set generated based on the target information is used in the use process of the AI ​​unit associated with the target identifier of the target data mapping method, such as the training, reasoning, and monitoring stages.

[0198] It can be seen from the above steps 301 to 302 that in the embodiment of the present application, the second device maps the N parameters of the sensitive information of the second device according to the target data mapping method, obtains the target information for indicating (i.e., characterizing) the N mapping data of the N parameters, and sends the target information and the target identifier for indicating the target data mapping method to the first device, so that the first device generates the above data set applied to the AI ​​unit based on the target information. In this way, during the use of the AI ​​unit, what is transmitted between the first device and the second device is the target information of the N mapping data of the N parameters indicating the sensitive information, and the target data mapping method used to obtain the target information, rather than directly transmitting the sensitive information, thereby avoiding the risk of exposing the sensitive information.

[0199] The following specifically describes a method of performing data mapping on N parameters according to the target data mapping method to obtain target information, as described in the following method 1 or method 2:

[0200] Mode 1: Optionally, the target data mapping mode includes N first data mapping modes;

[0201] The second device performs data mapping on N parameters of the sensitive information of the second device according to the target data mapping mode to obtain target information, including:

[0202] The second device performs data mapping on the i-th parameter of the N parameters through the i-th first data mapping mode to obtain the i-th mapping data, where i is an integer from 1 to N.

[0203] The second device determines the obtained N mapping data as the target information.

[0204] It is understandable that the N first data mapping methods may be the same or different. When the N first data mapping methods are the same, the N parameters are all data mapped through the same first data mapping method to obtain N mapping data; when the N first data mapping methods are different, the i-th parameter is data mapped through the i-th first data mapping method to obtain the i-th mapping data.

[0205] For example, when the N parameters include the horizontal pointing and vertical pointing of the transmitting beam of the second device, the horizontal pointing (or the physical identifier of the horizontal pointing) and the vertical pointing (or the physical identifier of the vertical pointing) can be data mapped through the same first data mapping method to obtain mapping data corresponding to the horizontal pointing and mapping data corresponding to the vertical pointing.

[0206] Among them, the mapping data corresponding to the horizontal pointing is used to identify the horizontal pointing; the mapping data corresponding to the vertical pointing is used to identify the vertical pointing; therefore, the mapping data corresponding to the horizontal pointing can also be called a horizontal virtual identification, and the mapping data corresponding to the vertical pointing is used to identify the vertical pointing and can also be called a vertical virtual identification.

[0207] Mode 2: Optionally, the target data mapping mode includes a second data mapping mode;

[0208] The second device performs data mapping on N parameters of the sensitive information of the second device according to the target data mapping mode to obtain target information, including:

[0209] The second device performs data mapping on the N parameters respectively through the second data mapping mode to obtain the N mapping data;

[0210] The second device maps the N-dimensional data formed by the N mapping data to one-dimensional data to obtain first data;

[0211] The second device determines the first data and the second information as the target information;

[0212] The second information is used to indicate a mapping relationship between the first data and the N mapping data.

[0213] From this, it can be seen that the second device can also perform data mapping on N parameters through a second data mapping method to obtain N mapping data, and then convert the N-dimensional data composed of the N mapping data into one-dimensional data to obtain the first data, thereby sending the first data and the second information used to indicate the mapping relationship between the first data and the N mapping data to the first device.

[0214] Among them, the first data is obtained by converting N-dimensional data composed of N mapping data. Therefore, there is a mapping relationship between the N mapping data and the first data. It can be seen that after obtaining the N mapping data, the second device may not directly send the N mapping data to the first device, but send the first data and the second information used to indicate the mapping relationship between the first data and the N mapping data.

[0215] For example, when the N parameters include the horizontal pointing and vertical pointing of the transmitting beam of the second device, the second device can perform data mapping on the horizontal pointing (or the physical identifier of the horizontal pointing) and the vertical pointing (or the physical identifier of the vertical pointing) through a second data mapping method to obtain the horizontal virtual identifier and the vertical virtual identifier; then convert the two-dimensional data consisting of the horizontal virtual identifier and the vertical virtual identifier into one-dimensional data to obtain the first data, which can also be called the target virtual identifier; thereby sending the target virtual identifier and the second information indicating the mapping relationship between the target virtual identifier and the horizontal virtual identifier and the vertical virtual identifier to the first device.

[0216] Optionally, the second information includes a reference parameter, the number of values ​​of the reference parameter, and a functional relationship between the first data and the N mapping data;

[0217] The reference parameters are at least some of the N parameters.

[0218] Here, by substituting the reference parameter and the number of values ​​of the reference parameter into the functional relationship between the first data and the N mapping data, the N mapping data can be calculated.

[0219] Optionally, before the second device performs data mapping on N parameters of the sensitive information of the second device according to the target data mapping mode and obtains the target information, the method further includes:

[0220] The second device receives third information sent by the first device, wherein the third information includes the target identifier and target indication information, and the target indication information is used to indicate that data mapping is performed on the N parameters respectively;

[0221] The second device performs data mapping on N parameters of the sensitive information of the second device according to the target data mapping mode to obtain target information, including:

[0222] The second device performs data mapping on the N parameters based on the target indication information and through the target data mapping mode indicated by the target identifier to obtain the target information.

[0223] From this, it can be seen that the first device can also send third information including a target identifier and target indication information to the second device to inform the second device of the data collection requirements of the first device, so that the second device can perform data mapping on N parameters of the sensitive information of the second device according to the requirements indicated by the target indication information and according to the target data mapping method indicated by the target identifier.

[0224] Optionally, during the AI ​​unit reasoning stage, monitoring stage, and identification (ie, registration) stage, the first device sends the third information to the second device.

[0225] Optionally, in a case where the target data mapping mode includes N first data mapping modes, the target indication information includes first indication information, where the first indication information is used to indicate that the N parameters are respectively mapped to N mapping data through the N first data mapping modes;

[0226] In the case where the target data mapping method includes a second data mapping method, the target indication information includes second indication information, and the second indication information is used to indicate that through the second data mapping method, the N parameters are respectively mapped into N mapping data, and then the N-dimensional data composed of the N mapping data are mapped into one-dimensional data.

[0227] Among them, the above-mentioned first indication information can also be called the first additional condition or the first model usage condition; the above-mentioned second indication information can also be called the second additional condition or the second model usage condition.

[0228] It can be seen that, based on the above-mentioned method one, if the N first data mapping methods are the same, the first device can send a first identifier for identifying the first data mapping method to the second device, and instruct the second device through the first indication information how to use the first data mapping method indicated by the first identifier; if the N first data mapping methods are different, the first device can send an identifier for identifying the N first data mapping methods to the second device, and instruct the second device through the first indication information how to use the N first data mapping methods.

[0229] Based on the above-mentioned method 2, the first device can send a second identifier for identifying the second data mapping method to the second device, and instruct the second device through second indication information how to use the second data mapping method indicated by the second identifier.

[0230] It should be noted that, in the case of the above-mentioned method 2, the first device may not send the first indication information. In this way, after the second device receives the identifier for identifying the N first data mapping methods, it maps the N parameters to the N mapping data respectively by default through the N first data mapping methods;

[0231] In the above-mentioned method 1, the scheme with the same N first data mapping methods, and in the above-mentioned method 2, both adopt one data mapping method. In this case, the third information (i.e., the demand information) sent by the first device to the second device includes an identifier for identifying the data mapping method. Therefore, in order to distinguish between these two schemes, it is also necessary to use the above-mentioned first indication information or the second indication information to indicate how to use the data mapping method indicated by the identifier.

[0232] Optionally, the method further comprises:

[0233] In the case where the first device is a terminal device, the second device receives the capability information sent by the first device;

[0234] The capability information is used to indicate that the terminal device supports the first processing mode or the second processing mode;

[0235] The first processing method is that after the N parameters are mapped into the N mapping data, the N mapping data are further mapped into one-dimensional data;

[0236] The second processing manner is a manner of mapping the N parameters into N mapping data.

[0237] It can be seen that the first device can also report to the second device which of the first processing method and the second processing method it supports, so that the second device can use the processing method supported by the first device to perform data mapping on the N parameters of the second device.

[0238] The first processing method may also be referred to as configuration of an N-dimensional identifier, and the second processing method may also be referred to as configuration of a one-dimensional identifier.

[0239] In summary, the specific implementation of the data collection method of the embodiment of the present application can be described as follows:

[0240] Implementation 1-1: Data collection during training, such as Figure 4 As shown, it includes the following steps 1-1.1 to 1-1.3:

[0241] Step 1-1.1: The UE receives first information sent by the base station, wherein the first information includes a first identifier, a horizontal virtual identifier associated with the measurement resource, and a vertical virtual identifier associated with the measurement resource.

[0242] Here, the first identifier is used to indicate the first data mapping method. The horizontal virtual identifier is the horizontal pointing direction of the base station's transmitting beam (or the physical identifier of the horizontal pointing direction), which is obtained through the first data mapping method; the vertical virtual identifier is the vertical pointing direction of the base station's transmitting beam (or the physical identifier of the vertical pointing direction), which is obtained through the first data mapping method.

[0243] Step 1-1.2: The UE generates a data set for training the AI ​​unit associated with the first identifier according to the horizontal virtual identifier and the vertical virtual identifier associated with the measurement resource.

[0244] Here, the data set includes a horizontal virtual identifier associated with the measurement resource, a vertical virtual identifier associated with the measurement resource, a measurement result associated with the measurement resource, and label data.

[0245] The measurement results include at least one of the following:

[0246] Reference Signal Receiving Power (RSRP);

[0247] Reference Signal Receiving Quality (RSRQ);

[0248] Signal to Interference plus Noise Ratio (SINR);

[0249] Wireless channel.

[0250] The tag data includes at least one of the following:

[0251] Beam quality information (e.g. RSRP, RSRQ, SINR);

[0252] The beam identifier with the strongest beam quality;

[0253] Probability distribution of the beam identity with the strongest beam quality;

[0254] Confidence.

[0255] Step 1-1.3: The UE establishes an association relationship between the data set and the first identifier.

[0256] Example 1-2: Data collection during training, such as Figure 5 As shown, it includes the following steps 1-2.1 to 1-2.4:

[0257] Step 1-2.1: The UE receives first information sent by the base station, wherein the first information includes the second identifier, a target virtual identifier associated with the measurement resource, and the second information.

[0258] Here, the second identifier is used to indicate the second data mapping method. The target virtual identifier is one-dimensional data obtained by mapping the two-dimensional data composed of the horizontal virtual identifier and the vertical virtual identifier. The horizontal virtual identifier is the horizontal pointing of the base station's transmitting beam (or the horizontally pointing physical identifier) ​​obtained through the second data mapping method; the vertical virtual identifier is the vertical pointing of the base station's transmitting beam (or the vertically pointing physical identifier) ​​obtained through the second data mapping method.

[0259] In addition, there is a mapping relationship between the target virtual identifier and the horizontal virtual identifier and the vertical virtual identifier. The second information is used to indicate the mapping relationship. Therefore, the second information is used to indicate that the one-dimensional data of the target virtual identifier is split into two-dimensional data consisting of the horizontal virtual identifier and the vertical virtual identifier. The second information can also be called a two-dimensional splitting indication.

[0260] The above-mentioned second information is used to indicate: the reference parameter and the number of values ​​of the reference parameter, and the functional relationship between the target virtual identifier and the horizontal virtual identifier and the vertical virtual identifier. The reference parameter is one of the horizontal pointing and the vertical pointing. For example, when the reference parameter is the horizontal pointing, the number of values ​​of the reference parameter is the number of horizontal pointing; when the reference parameter is the vertical pointing, the number of values ​​of the reference parameter is the number of vertical pointing.

[0261] Step 1-2.2: The UE determines the horizontal virtual identifier and the vertical virtual identifier according to the target virtual identifier and the second information.

[0262] Step 1-2.3: The UE generates a data set for training the AI ​​unit associated with the second identifier according to the horizontal virtual identifier and the vertical virtual identifier.

[0263] Here, the data set includes a horizontal virtual identifier associated with the measurement resource, a vertical virtual identifier associated with the measurement resource, a measurement result associated with the measurement resource, and label data.

[0264] Step 1-2.4: The UE establishes an association relationship between the data set and the second identifier.

[0265] Implementation 1-3: Data collection during training, such as Figure 6 As shown, it includes the following steps 1-3.1 to 1-3.3:

[0266] Step 1-3.1: The UE receives first information sent by the base station, wherein the first information includes a third identifier, a fourth identifier, a horizontal virtual identifier associated with the measurement resource, and a vertical virtual identifier associated with the measurement resource.

[0267] Among them, the third identifier and the fourth identifier are used to indicate different data mapping methods, for example, respectively indicate the third data mapping method and the fourth data mapping method, then the horizontal virtual identifier is the horizontal pointing of the base station's transmitting beam (or the physical identifier of the horizontal pointing) obtained through the third data mapping method; the vertical virtual identifier is the vertical pointing of the base station's transmitting beam (or the physical identifier of the vertical pointing) obtained through the fourth data mapping method.

[0268] Step 1-3.2: The UE generates a data set for training the AI ​​unit associated with the third identifier and the fourth identifier according to the horizontal virtual identifier associated with the measurement resource and the vertical virtual identifier associated with the measurement resource.

[0269] Here, the data set includes a horizontal virtual identifier associated with the measurement resource, a vertical virtual identifier associated with the measurement resource, a measurement result associated with the measurement resource, and label data.

[0270] Step 1-3.3: The UE establishes an association relationship between the data set and the third identifier and the fourth identifier.

[0271] Implementation 2-1: Data collection during inference, such as Figure 7 As shown, it includes the following steps 2-1.1 to 2-1.5:

[0272] Step 2-1.1: The UE sends third information to the base station, where the third information is used to indicate the data collection requirements of the UE when performing AI unit reasoning, and the third information includes a first identifier and first indication information.

[0273] Here, the first identifier is used to indicate the first data mapping method, and the first indication information is used to indicate that the horizontal pointing (or the physical identifier of the horizontal pointing) and the vertical pointing (or the physical identifier of the vertical pointing) of the base station's transmitting beam are respectively mapped into the horizontal virtual identifier and the vertical virtual identifier through the first data mapping method.

[0274] It should be noted that if the UE and the base station have already exchanged the first identifier and the first indication information during the model identifier interaction phase, step 2-1.1 may not be required.

[0275] Step 2-1.2: Based on the first indication information, the base station maps the horizontal pointing (or the physical identifier of the horizontal pointing) through the first data mapping method to obtain the horizontal virtual identifier associated with the measurement resource, and maps the vertical pointing (or the physical identifier of the vertical pointing) through the first data mapping method to obtain the vertical virtual identifier associated with the measurement resource.

[0276] It can be seen from step 2-1.2 that in this implementation, the horizontal virtual identifier and the vertical virtual identifier are mapped through the same data mapping method. Therefore, if the first information sent by the UE to the base station only includes an identifier for indicating the data mapping method, then the first indication information can also be used to indicate to the base station how to use the data mapping method indicated by the identifier to perform data mapping.

[0277] Step 2-1.3: The base station sends first information to the UE, where the first information includes a first identifier, a horizontal virtual identifier associated with the measurement resource, and a vertical virtual identifier associated with the measurement resource.

[0278] Step 2-1.4: The UE receives the first information sent by the base station.

[0279] Step 2-1.5: The UE generates a data set for AI unit reasoning (ie, generates input for the AI ​​unit) according to the horizontal virtual identifier and the vertical virtual identifier associated with the measurement resource.

[0280] That is, the UE uses the horizontal virtual identifier associated with the measurement resource, the vertical virtual identifier associated with the measurement resource, and the measurement result associated with the measurement resource as inputs for reasoning of the AI ​​unit associated with the first identifier.

[0281] Implementation 2-2: Data collection during inference, such as Figure 8 As shown, it includes the following steps 2-2.1 to 2-2.5:

[0282] Step 2-2.1: The UE sends third information to the base station, where the third information is used to indicate the data collection requirements of the UE when performing AI unit reasoning, and the third information includes a second identifier and second indication information.

[0283] Here, the second identifier is used to indicate the second data mapping method, and the second indication information is used to indicate that through the second data mapping method, the horizontal pointing (or the physical identifier of the horizontal pointing) and the vertical pointing (or the physical identifier of the vertical pointing) of the base station's transmitting beam are respectively mapped into the horizontal virtual identifier and the vertical virtual identifier, and then the two-dimensional data composed of the horizontal virtual identifier and the vertical virtual identifier are mapped into a one-dimensional target identifier.

[0284] It should be noted that if the UE and the base station have already exchanged the second identifier and the second indication information during the model identifier interaction phase, step 2-2.1 may not be required.

[0285] Step 2-2.2: Based on the second indication information, the base station maps the horizontal pointing (or the physical identifier of the horizontal pointing) and the vertical pointing (or the physical identifier of the vertical pointing) of the base station's transmitting beam into a horizontal virtual identifier and a vertical virtual identifier respectively through a second data mapping method, and then maps the two-dimensional data consisting of the horizontal virtual identifier and the vertical virtual identifier into a one-dimensional target virtual identifier.

[0286] Step 2-2.3: The base station sends first information to the UE, where the first information includes the second identifier, the target virtual identifier, and the second information.

[0287] There is a mapping relationship between the target virtual identifier and the horizontal virtual identifier and the vertical virtual identifier. The second information is used to indicate the mapping relationship. Therefore, the second information is used to indicate that the one-dimensional data of the target virtual identifier is split into two-dimensional data consisting of the horizontal virtual identifier and the vertical virtual identifier. The second information can also be called a two-dimensional splitting indication.

[0288] In addition, the second information is used to indicate the reference parameter and the number of values ​​of the reference parameter, as well as the functional relationship between the target virtual identifier and the horizontal virtual identifier and the vertical virtual identifier. The reference parameter is one of the horizontal pointing and the vertical pointing. For example, when the reference parameter is the horizontal pointing, the number of values ​​of the reference parameter is the number of horizontal pointing; when the reference parameter is the vertical pointing, the number of values ​​of the reference parameter is the number of vertical pointing.

[0289] Step 2-2.4: The UE determines the horizontal virtual identifier and the vertical virtual identifier according to the target virtual identifier and the second information.

[0290] Step 2-2.5: The UE generates a data set for AI unit reasoning (i.e., generates input for the AI ​​unit) based on the horizontal virtual identifier and the vertical virtual identifier.

[0291] That is, the UE uses the horizontal virtual identifier associated with the measurement resource, the vertical virtual identifier associated with the measurement resource, and the measurement result associated with the measurement resource as input for the AI ​​unit reasoning.

[0292] Implementation 2-3: Data collection during inference, such as Fig. 9 As shown, it includes the following steps 2-3.1 to 2-3.4:

[0293] Step 2-3.1: The UE sends third information to the base station, where the third information is used to indicate the data collection requirements of the UE when performing AI unit reasoning, and the third information includes a third identifier and a fourth identifier.

[0294] The third identifier and the fourth identifier are used to indicate different data mapping modes, for example, respectively indicate a third data mapping mode and a fourth data mapping mode.

[0295] It should be noted that if the UE and the base station have exchanged the third identifier and the fourth identifier during the model identifier interaction phase, step 2-3.1 may not be required.

[0296] Step 2-3.2: The base station maps the horizontal pointing (or the physical identifier of the horizontal pointing) through the third data mapping method to obtain the horizontal virtual identifier associated with the measurement resource, and maps the vertical pointing (or the physical identifier of the vertical pointing) through the fourth data mapping method to obtain the vertical virtual identifier associated with the measurement resource.

[0297] Step 2-3.3: The base station sends first information to the UE, where the first information includes the third identifier and the fourth identifier, as well as a horizontal virtual identifier associated with the measurement resource and a vertical virtual identifier associated with the measurement resource.

[0298] Step 2-3.4: The UE generates a data set for AI unit reasoning (i.e., generates input for the AI ​​unit) based on the horizontal virtual identifier and the vertical virtual identifier.

[0299] That is, the UE uses the horizontal virtual identifier associated with the measurement resource, the vertical virtual identifier associated with the measurement resource, and the measurement result associated with the measurement resource as input for the AI ​​unit reasoning.

[0300] Implementation 3-1: Data collection when monitoring an AI unit, such as Fig.10 As shown, it includes the following steps 3-1.1 to 3-1.5:

[0301] Step 3-1.1: The UE sends a third message to the base station, where the third message is used to indicate the data collection requirement of the UE when monitoring the AI ​​unit, and the third message includes a first identifier and first indication information. Here, the third message may also be referred to as a monitoring request.

[0302] Here, the first identifier is used to indicate the first data mapping method, and the first indication information is used to indicate that the horizontal pointing (or the physical identifier of the horizontal pointing) and the vertical pointing (or the physical identifier of the vertical pointing) of the base station's transmitting beam are respectively mapped into the horizontal virtual identifier and the vertical virtual identifier through the first data mapping method.

[0303] It should be noted that, if the UE has reported the first identifier and the first indication information to the network during the model identifier interaction phase, the monitoring request may not include the first identifier and the first indication information.

[0304] Step 3-1.2: Based on the first indication information, the base station maps the horizontal pointing (or the physical identifier of the horizontal pointing) through the first data mapping method to obtain the horizontal virtual identifier associated with the measurement resource, and maps the vertical pointing (or the physical identifier of the vertical pointing) through the first data mapping method to obtain the vertical virtual identifier associated with the measurement resource.

[0305] Step 3-1.3: The base station sends first information to the UE, where the first information includes a first identifier, a horizontal virtual identifier associated with the measurement resource, and a vertical virtual identifier associated with the measurement resource.

[0306] Step 3-1.4: The UE receives the first information sent by the base station.

[0307] Step 3-1.5: UE collects monitoring data, that is, UE infers the measurement resources according to the horizontal virtual identifier and the vertical virtual identifier to obtain the measurement results, generates the input data set for the AI ​​unit reasoning, and then obtains the output of the AI ​​unit after the AI ​​unit reasoning.

[0308] That is, the UE uses the horizontal virtual identifier associated with the measurement resource, the vertical virtual identifier associated with the measurement resource, and the measurement result associated with the monitoring measurement resource as inputs of the AI ​​unit, and generates a monitoring data set based on the output of the AI ​​unit and the label data.

[0309] Implementation 3-2: Data collection when monitoring the AI ​​unit, such as Fig.11 As shown, it includes the following steps 1-2.1 to 1-2.5:

[0310] Step 3-2.1: The UE sends a third message to the base station, the third message is used to indicate the data collection requirement of the UE when monitoring the AI ​​unit, and the third message includes a second identifier and a second indication information. Here, the third message may also be referred to as a monitoring request.

[0311] It should be noted that if the UE has reported the second identifier and the second indication information to the network during the model identifier interaction phase, the monitoring request may not include the second identifier and the second indication information.

[0312] Here, the second identifier is used to indicate the second data mapping method, and the second indication information is used to indicate that through the second data mapping method, the horizontal pointing (or the physical identifier of the horizontal pointing) and the vertical pointing (or the physical identifier of the vertical pointing) of the base station's transmitting beam are respectively mapped into the horizontal virtual identifier and the vertical virtual identifier, and then the two-dimensional data composed of the horizontal virtual identifier and the vertical virtual identifier are mapped into a one-dimensional target identifier.

[0313] Step 3-2.2: Based on the second indication information, the base station maps the horizontal pointing direction (or the physical identifier of the horizontal pointing direction) and the vertical pointing direction (or the physical identifier of the vertical pointing direction) of the base station's transmitting beam into a horizontal virtual identifier and a vertical virtual identifier respectively through a second data mapping method, and then maps the two-dimensional data consisting of the horizontal virtual identifier and the vertical virtual identifier into a one-dimensional target virtual identifier.

[0314] Step 3-2.3: The base station sends first information to the UE, where the first information includes the second identifier, the target virtual identifier, and the second information.

[0315] There is a mapping relationship between the target virtual identifier and the horizontal virtual identifier and the vertical virtual identifier. The second information is used to indicate the mapping relationship. Therefore, the second information is used to indicate that the one-dimensional data of the target virtual identifier is split into two-dimensional data consisting of the horizontal virtual identifier and the vertical virtual identifier. The second information can also be called a two-dimensional splitting indication.

[0316] In addition, the second information is used to indicate the reference parameter and the number of values ​​of the reference parameter, as well as the functional relationship between the target virtual identifier and the horizontal virtual identifier and the vertical virtual identifier. The reference parameter is one of the horizontal pointing and the vertical pointing. For example, when the reference parameter is the horizontal pointing, the number of values ​​of the reference parameter is the number of horizontal pointing; when the reference parameter is the vertical pointing, the number of values ​​of the reference parameter is the number of vertical pointing.

[0317] Step 3-2.4: The UE determines the horizontal virtual identifier and the vertical virtual identifier according to the target virtual identifier and the second information.

[0318] Step 3-2.5: UE collects monitoring data, that is, UE infers the measurement resources according to the horizontal virtual identifier and the vertical virtual identifier to obtain the measurement results, generates the input data set for the AI ​​unit reasoning, and then obtains the output of the AI ​​unit after the AI ​​unit reasoning.

[0319] That is, the UE uses the horizontal virtual identifier associated with the measurement resource, the vertical virtual identifier associated with the measurement resource, and the measurement result associated with the monitoring measurement resource as inputs of the AI ​​unit, and generates a monitoring data set based on the output of the AI ​​unit and the label data.

[0320] Implementation 3-3: Data collection when monitoring the AI ​​unit, such as Fig.12 As shown, it includes the following steps 3-3.1 to 3-3.4:

[0321] Step 3-3.1: The UE sends third information to the base station, the third information is used to indicate the data collection requirements of the UE when monitoring the AI ​​unit, and the third information includes a third identifier, a fourth identifier and the first indication information. Here, the third information can also be called a monitoring request.

[0322] The third identifier and the fourth identifier are used to indicate different data mapping modes, for example, respectively indicate the third data mapping mode and the fourth data mapping mode. The first indication information is used to indicate that the horizontal pointing (or the physical identifier of the horizontal pointing) is mapped by the third data mapping mode to obtain the horizontal virtual identifier associated with the measurement resource, and the vertical pointing (or the physical identifier of the vertical pointing) is mapped by the fourth data mapping mode to obtain the vertical virtual identifier associated with the measurement resource.

[0323] It should be noted that if the UE has reported the third identifier, the fourth identifier and the first indication information to the network during the model identifier interaction phase, the monitoring request may not include the third identifier, the fourth identifier and the first indication information.

[0324] In addition, the above-mentioned third information may also not include the first indication information. In this way, after the base station receives the third identifier and the fourth identifier, it maps the horizontal pointing (or the physical identifier of the horizontal pointing) through the third data mapping method by default to obtain the horizontal virtual identifier associated with the measurement resource, and maps the vertical pointing (or the physical identifier of the vertical pointing) through the fourth data mapping method to obtain the vertical virtual identifier associated with the measurement resource.

[0325] Step 3-3.2: The base station maps the horizontal pointing (or the physical identifier of the horizontal pointing) through the third data mapping method to obtain the horizontal virtual identifier associated with the measurement resource, and maps the vertical pointing (or the physical identifier of the vertical pointing) through the fourth data mapping method to obtain the vertical virtual identifier associated with the measurement resource.

[0326] Step 3-3.3: The base station sends first information to the UE, where the first information includes the third identifier and the fourth identifier, as well as a horizontal virtual identifier associated with the measurement resource and a vertical virtual identifier associated with the measurement resource.

[0327] Step 3-3.4: UE collects monitoring data, that is, UE collects monitoring data, that is, UE infers measurement resources according to horizontal virtual identifiers and vertical virtual identifiers to obtain measurement results, generates an input data set for AI unit reasoning, and then obtains the output of the AI ​​unit after reasoning by the AI ​​unit.

[0328] That is, the UE uses the horizontal virtual identifier associated with the measurement resource, the vertical virtual identifier associated with the measurement resource, and the measurement result associated with the monitoring measurement resource as inputs of the AI ​​unit, and generates a monitoring data set based on the output of the AI ​​unit and the label data.

[0329] It should be noted that in the aforementioned implementations 3-1 to 3-3, after the UE collects the monitoring data of the AI ​​unit (i.e., the output and label data of the AI ​​unit), it can report the monitoring data to the base station, so that the base station can compare the output of the AI ​​unit with the label data, and then control whether the AI ​​unit is turned off according to the comparison result, and determine whether the AI ​​unit needs to be retrained. Or the UE determines whether the monitoring reporting event is met based on the monitoring data according to the monitoring reporting event pre-configured by the base station, and reports the corresponding monitoring event.

[0330] Implementation 4-1: Interaction phase of AI unit identification or function identification, such as Fig.13 As shown, the steps 4-1.1 are as follows:

[0331] Step 4-1.1: The UE sends a third message to the base station, where the third message is used to indicate the data collection requirements of the UE when performing AI unit reasoning or monitoring of the AI ​​unit, and the third message includes the first identifier and the first indication information. Optionally, the third message may also include an identifier of the AI ​​unit or an identifier of the AI ​​function.

[0332] Here, the first identifier is used to indicate the first data mapping method, and the first indication information is used to indicate that the horizontal pointing (or the physical identifier of the horizontal pointing) and the vertical pointing (or the physical identifier of the vertical pointing) of the base station's transmitting beam are respectively mapped into the horizontal virtual identifier and the vertical virtual identifier through the first data mapping method.

[0333] Optionally, it may also include:

[0334] Step 4-1.2: During the UE capability reporting or functionality identification phase, the terminal may indicate support for one-dimensional identification configuration or two-dimensional identification configuration through UE capability signaling;

[0335] The configuration of the two-dimensional identifier refers to: mapping the horizontal direction (or the physical identifier of the horizontal direction) and the vertical direction (or the physical identifier of the vertical direction) of the transmission beam of the base station into the horizontal virtual identifier and the vertical virtual identifier respectively;

[0336] The configuration of a one-dimensional identifier means: mapping the horizontal direction (or the physical identifier of the horizontal direction) and the vertical direction (or the physical identifier of the vertical direction) of the base station's transmitting beam into a horizontal virtual identifier and a vertical virtual identifier respectively, and then mapping the two-dimensional data composed of the horizontal virtual identifier and the vertical virtual identifier into a one-dimensional target virtual identifier.

[0337] Implementation 4-2: Interaction phase of AI unit identification or function identification, such as Fig.14 As shown, the steps 4-2.1 are as follows:

[0338] Step 4-2.1: The UE sends a third message to the base station, the third message is used to indicate the data collection requirements of the UE when performing AI unit reasoning or monitoring of the AI ​​unit, and the third message includes a second identifier and a second indication information. Optionally, the third message may also include an identifier of the AI ​​unit or an identifier of the AI ​​function.

[0339] Here, the second identifier is used to indicate the second data mapping method, and the second indication information is used to indicate that through the second data mapping method, the horizontal pointing (or the physical identifier of the horizontal pointing) and the vertical pointing (or the physical identifier of the vertical pointing) of the base station's transmitting beam are respectively mapped into the horizontal virtual identifier and the vertical virtual identifier, and then the two-dimensional data composed of the horizontal virtual identifier and the vertical virtual identifier are mapped into a one-dimensional target virtual identifier.

[0340] Optionally, it may also include:

[0341] Step 4-2.2: During the UE capability reporting or functionality identification phase, the terminal may indicate support for one-dimensional identification configuration or two-dimensional identification configuration through UE capability signaling;

[0342] The configuration of the two-dimensional identifier refers to: mapping the horizontal direction (or the physical identifier of the horizontal direction) and the vertical direction (or the physical identifier of the vertical direction) of the transmission beam of the base station into the horizontal virtual identifier and the vertical virtual identifier respectively;

[0343] The configuration of a one-dimensional identifier means: mapping the horizontal direction (or the physical identifier of the horizontal direction) and the vertical direction (or the physical identifier of the vertical direction) of the base station's transmitting beam into a horizontal virtual identifier and a vertical virtual identifier respectively, and then mapping the two-dimensional data composed of the horizontal virtual identifier and the vertical virtual identifier into a one-dimensional target virtual identifier.

[0344] Implementation 4-3: Interaction phase of AI unit identification or function identification, such as Fig.15 As shown, the steps 4-3.1 are as follows:

[0345] Step 4-3.1: The UE sends a third message to the base station, where the third message is used to indicate the data collection requirements of the UE when performing AI unit reasoning or monitoring of the AI ​​unit, and the third message includes a third identifier, a fourth identifier, and the first indication information. Optionally, the third message may also include an identifier of the AI ​​unit or an identifier of the AI ​​function.

[0346] Here, the third identifier and the fourth identifier are used to indicate different data mapping modes, for example, respectively indicate the third data mapping mode and the fourth data mapping mode. The first indication information is used to indicate that the horizontal pointing (or the physical identifier of the horizontal pointing) is mapped by the third data mapping mode to obtain the horizontal virtual identifier associated with the measurement resource, and the vertical pointing (or the physical identifier of the vertical pointing) is mapped by the fourth data mapping mode to obtain the vertical virtual identifier associated with the measurement resource.

[0347] It is understandable that the above-mentioned third information may not include the first indication information. In this way, after the base station receives the third identifier and the fourth identifier, it maps the horizontal pointing (or the physical identifier of the horizontal pointing) through the third data mapping method by default to obtain the horizontal virtual identifier associated with the measurement resource, and maps the vertical pointing (or the physical identifier of the vertical pointing) through the fourth data mapping method to obtain the vertical virtual identifier associated with the measurement resource.

[0348] Optionally, it may also include:

[0349] Step 4-3.2: During the UE capability reporting or functionality identification phase, the terminal may indicate support for one-dimensional identification configuration or two-dimensional identification configuration through UE capability signaling;

[0350] The configuration of the two-dimensional identifier refers to: mapping the horizontal direction (or the physical identifier of the horizontal direction) and the vertical direction (or the physical identifier of the vertical direction) of the transmission beam of the base station into the horizontal virtual identifier and the vertical virtual identifier respectively;

[0351] The configuration of a one-dimensional identifier means: mapping the horizontal direction (or the physical identifier of the horizontal direction) and the vertical direction (or the physical identifier of the vertical direction) of the base station's transmitting beam into a horizontal virtual identifier and a vertical virtual identifier respectively, and then mapping the two-dimensional data composed of the horizontal virtual identifier and the vertical virtual identifier into a one-dimensional target virtual identifier.

[0352] In summary, the embodiments of the present application, by performing privacy processing on the horizontal and vertical dimensions of the transmitted beam respectively, help preserve the relative relationship between some beams, help the UE to extract the features of the transmitted beam, and improve the accuracy of beam prediction. At the same time, it ensures that the sensitive information of the beam is not exposed.

[0353] For example, as shown in Table 7, it is the original beam physical identification. Among them, the beam physical identification shown in Table 7 is privatized by mixing horizontal and vertical in the prior art (i.e., one-dimensional mixed privacy method), and the virtual identification shown in Table 8 is obtained; the beam physical identification shown in Table 7 is privatized by the method described above in the embodiment of the present application (i.e., the method 2 described above, i.e., the two-dimensional separate privacy method), and the virtual identification shown in Table 9 is obtained.

[0354] Table 7 Original beam physical identifier

[0355]

[0356] Table 8 Virtual identification after one-dimensional hybrid privacy

[0357]

[0358] Table 9 Virtual identification after two-dimensional privacy protection method

[0359]

[0360] Among them, when the beam physical identification shown in Table 7 is processed by a one-dimensional hybrid deprivacy method (for example, a random scrambling method), it is necessary to change 8*4=32 corresponding relationships between the horizontal pointing, vertical pointing and the identification, while when the beam physical identification shown in Table 7 is processed by a two-dimensional separate deprivacy method, it is only necessary to scramble the 8 relationships between the horizontal pointing and the identification, and the 4 corresponding relationships between the vertical pointing and the identification, respectively, and a total of 8+4=12 corresponding relationships are changed. It can be seen that the two-dimensional separate deprivacy method only changes 12 corresponding relationships instead of 32 relationships, so that the relative relationship between some beams is retained. For example, the difference between the values ​​of two adjacent rows or columns in Table 9 is equal, while this relationship does not exist in Table 8. Therefore, by performing deprivacy processing on the horizontal and vertical dimensions of the transmitted beam separately, it is helpful to retain the relative relationship between some beams.

[0361] The data collection method provided in the embodiment of the present application can be executed by a data collection device. In the embodiment of the present application, the data collection device provided in the embodiment of the present application is described by taking the data collection method executed by the data collection device as an example.

[0362] In a third aspect, an embodiment of the present application provides a data collection device, which can be applied to a first device, such as Fig.16 As shown, the data collection device 160 includes the following modules:

[0363] A first receiving module 1601 is configured to receive first information sent by a second device, wherein the first information includes a target identifier and target information, the target information is used to indicate N mapping data of N parameters of sensitive information of the second device, the target information is obtained by performing data mapping on the N parameters according to a target data mapping method, and the target identifier is used to indicate the target data mapping method;

[0364] A generating module 1602, configured to generate a data set according to the target information;

[0365] The execution module 1603 is configured to execute at least one of the following according to the target identifier and the data set:

[0366] Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier;

[0367] The AI ​​unit reasoning;

[0368] The AI ​​unit is monitored.

[0369] Optionally, the target information includes the N mapping data, the target data mapping method includes N first data mapping methods, the i-th mapping data is the i-th parameter in the sensitive information, obtained by the i-th first data mapping method, and i is an integer from 1 to N.

[0370] Optionally, the target information includes first data and second information, where the second information is used to indicate a mapping relationship between the first data and the N mapping data; the generating module 1602 is specifically used to:

[0371] Determine the N mapping data according to the mapping relationship indicated by the second information and the first data;

[0372] The data set is generated according to the N mapping data.

[0373] Optionally, the second information includes a reference parameter, the number of values ​​of the reference parameter, and a functional relationship between the first data and the N mapping data;

[0374] The reference parameters are at least some of the N parameters.

[0375] Optionally, the device further comprises:

[0376] A second sending module, used to send third information to the second device;

[0377] The third information includes the target identifier and target indication information, and the target indication information is used to indicate that data mapping is performed on the N parameters respectively.

[0378] Optionally, in a case where the target data mapping mode includes N first data mapping modes, the target indication information includes first indication information, where the first indication information is used to indicate that the N parameters are respectively mapped to N mapping data through the N first data mapping modes;

[0379] In the case where the target data mapping method includes a second data mapping method, the target indication information includes second indication information, and the second indication information is used to indicate that through the second data mapping method, the N parameters are respectively mapped into N mapping data, and then the N-dimensional data composed of the N mapping data are mapped into one-dimensional data.

[0380] Optionally, the device further comprises:

[0381] a fourth sending module, configured to send capability information to the second device when the first device is a terminal device, wherein the capability information is used to indicate that the terminal device supports the first processing mode or the second processing mode;

[0382] The first processing method is a method of mapping the N parameters into N mapping data;

[0383] The second processing method is a method in which after the N parameters are mapped into the N mapping data, the N mapping data are further mapped into one-dimensional data.

[0384] Optionally, the sensitive information includes transmit beam pointing, and the N parameters include N directional dimensions of the transmit beam pointing.

[0385] The data collection device in the embodiment of the present application can be an electronic device, such as an electronic device with an operating system, or a component in an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal, and the terminal can include but is not limited to the types of terminals 11 listed above, which are not specifically limited in the embodiment of the present application.

[0386] The data collection device provided in the embodiment of the present application can achieve Figure 2 The various processes implemented by the method embodiment and achieving the same technical effect are not described here to avoid repetition.

[0387] In a fourth aspect, an embodiment of the present application provides a data collection device, which can be applied to a second device, such as Fig.17 As shown, the data collection device 170 includes the following modules:

[0388] A mapping module 1701 is used to perform data mapping on N parameters of the sensitive information of the second device according to a target data mapping mode to obtain target information, wherein the target information is used to indicate N mapping data of the N parameters;

[0389] A first sending module 1702 is used to send first information to a first device, wherein the first information includes the target information and a target identifier, the target identifier is used to indicate the target data mapping mode, and the N mapping data are used to generate a data set;

[0390] The data set is used for at least one of the following:

[0391] Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier;

[0392] The AI ​​unit reasoning;

[0393] The AI ​​unit is monitored.

[0394] Optionally, the target data mapping mode includes N first data mapping modes;

[0395] The mapping module 1701 is specifically used for:

[0396] By using the i-th first data mapping method, data mapping is performed on the i-th parameter of the N parameters to obtain the i-th mapping data, wherein i is an integer from 1 to N.

[0397] The obtained N mapping data are determined as the target information.

[0398] Optionally, the target data mapping mode includes a second data mapping mode;

[0399] The mapping module 1701 is specifically used for:

[0400] By using the second data mapping method, data mapping is performed on the N parameters respectively to obtain the N mapping data;

[0401] Mapping N-dimensional data formed by the N mapping data to one-dimensional data to obtain first data;

[0402] determining the first data and the second information as the target information;

[0403] The second information is used to indicate a mapping relationship between the first data and the N mapping data.

[0404] Optionally, the second information includes a reference parameter, the number of values ​​of the reference parameter, and a functional relationship between the first data and the N mapping data;

[0405] The reference parameters are at least some of the N parameters.

[0406] Optionally, the device further comprises:

[0407] A second receiving module, configured to receive third information sent by the first device, wherein the third information includes the target identifier and target indication information, and the target indication information is used to indicate that data mapping is performed on the N parameters respectively;

[0408] The mapping module 1701 is specifically used for:

[0409] Based on the target indication information, data mapping is performed on the N parameters through the target data mapping mode indicated by the target identifier to obtain the target information.

[0410] Optionally, in a case where the target data mapping mode includes N first data mapping modes, the target indication information includes first indication information, where the first indication information is used to indicate that the N parameters are respectively mapped to N mapping data through the N first data mapping modes;

[0411] In the case where the target data mapping method includes a second data mapping method, the target indication information includes second indication information, and the second indication information is used to indicate that through the second data mapping method, the N parameters are respectively mapped into N mapping data, and then the N-dimensional data composed of the N mapping data are mapped into one-dimensional data.

[0412] Optionally, the device further comprises:

[0413] A third receiving module, configured to receive capability information sent by the first device when the first device is a terminal device;

[0414] The capability information is used to indicate that the terminal device supports the first processing mode or the second processing mode;

[0415] The first processing method is that after the N parameters are mapped into the N mapping data, the N mapping data are further mapped into one-dimensional data;

[0416] The second processing manner is a manner of mapping the N parameters into N mapping data.

[0417] Optionally, the sensitive information includes transmit beam pointing, and the N parameters include N directional dimensions of the transmit beam pointing.

[0418] The data collection device in the embodiment of the present application can be an electronic device, such as an electronic device with an operating system, or a component in an electronic device, such as an integrated circuit or a chip. The electronic device can be a network-side device. Exemplarily, the network-side device can include but is not limited to the types of network-side devices 12 listed above, and the embodiment of the present application does not specifically limit this.

[0419] The data collection device provided in the embodiment of the present application can achieve Figure 3 The various processes implemented by the method embodiment and achieving the same technical effect are not described here to avoid repetition.

[0420] like Fig.18 As shown, the embodiment of the present application further provides a communication device 1800, including a processor 1801 and a memory 1802, and the memory 1802 stores a program or instruction that can be run on the processor 1801. For example, when the communication device 1800 is a first device, the program or instruction is executed by the processor 1801 to implement the various steps of the data collection method embodiment described in the first aspect above, and can achieve the same technical effect. When the communication device 1800 is a second device, the program or instruction is executed by the processor 1801 to implement the various steps of the data collection method embodiment described in the second aspect above, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0421] The embodiment of the present application also provides a terminal, including a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the following Figure 2 The steps in the method embodiment shown. This terminal embodiment corresponds to the above-mentioned terminal side method embodiment, and each implementation process and implementation method of the above-mentioned method embodiment can be applied to this terminal embodiment and can achieve the same technical effect. Specifically, Fig.19 A schematic diagram of the hardware structure of a terminal for implementing an embodiment of the present application.

[0422] The terminal 1900 includes but is not limited to: a radio frequency unit 1901, a network module 1902, an audio output unit 1903, an input unit 1904, a sensor 1905, a display unit 1906, a user input unit 1907, an interface unit 1908, a memory 1909 and at least some of the components of the processor 1910.

[0423] Those skilled in the art will appreciate that the terminal 1900 may also include a power source (such as a battery) for supplying power to each component, and the power source may be logically connected to the processor 1910 through a power management system, thereby implementing functions such as managing charging, discharging, and power consumption management through the power management system. Fig.19 The terminal structure shown in the figure does not constitute a limitation on the terminal. The terminal may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be described in detail here.

[0424] It should be understood that in the embodiment of the present application, the input unit 1904 may include a graphics processing unit (GPU) 19041 and a microphone 19042, and the graphics processor 19041 processes the image data of the static picture or video obtained by the image capture device (such as a camera) in the video capture mode or the image capture mode. The display unit 1906 may include a display panel 19061, and the display panel 19061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 1907 includes a touch panel 19071 and at least one of other input devices 19072. The touch panel 19071 is also called a touch screen. The touch panel 19071 may include two parts: a touch detection device and a touch controller. Other input devices 19 072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which will not be repeated here.

[0425] In the embodiment of the present application, after receiving downlink data from the network side device, the RF unit 1901 can transmit the data to the processor 1910 for processing; in addition, the RF unit 1901 can send uplink data to the network side device. Generally, the RF unit 1901 includes but is not limited to an antenna, an amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, etc.

[0426] The memory 1909 can be used to store software programs or instructions and various data. The memory 1909 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, an application program or instruction required for at least one function (such as a sound playback function, an image playback function, etc.), etc. In addition, the memory 1909 may include a volatile memory or a non-volatile memory. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM) and a direct memory bus random access memory (DRRAM). The memory x09 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0427] The processor 1910 may include one or more processing units; optionally, the processor 1910 integrates an application processor and a modem processor, wherein the application processor mainly processes operations related to an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communication signals, such as a baseband processor. It is understandable that the modem processor may not be integrated into the processor 1910.

[0428] The radio frequency unit 1901 is used to receive first information sent by the second device, wherein the first information includes a target identifier and target information, the target information is used to indicate N mapping data of N parameters of sensitive information of the second device, the target information is obtained by performing data mapping on the N parameters according to a target data mapping method, and the target identifier is used to indicate the target data mapping method;

[0429] The processor 1910 is used to generate a data set according to the target information;

[0430] According to the target identifier and the data set, at least one of the following is performed:

[0431] Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier;

[0432] The AI ​​unit reasoning;

[0433] The AI ​​unit is monitored.

[0434] Optionally, the target information includes the N mapping data, the target data mapping method includes N first data mapping methods, the i-th mapping data is the i-th parameter in the sensitive information, obtained by the i-th first data mapping method, and i is an integer from 1 to N.

[0435] Optionally, the target information includes first data and second information, where the second information is used to indicate a mapping relationship between the first data and the N mapping data; the processor 1910 generates a data set according to the target information, including:

[0436] Determine the N mapping data according to the mapping relationship indicated by the second information and the first data;

[0437] The data set is generated according to the N mapping data.

[0438] Optionally, the second information includes a reference parameter, the number of values ​​of the reference parameter, and a functional relationship between the first data and the N mapping data;

[0439] The reference parameters are at least some of the N parameters.

[0440] Optionally, before receiving the first information sent by the second device, the radio frequency unit 1901 is further configured to:

[0441] sending third information to the second device;

[0442] The third information includes the target identifier and target indication information, and the target indication information is used to indicate that data mapping is performed on the N parameters respectively.

[0443] Optionally, in a case where the target data mapping mode includes N first data mapping modes, the target indication information includes first indication information, where the first indication information is used to indicate that the N parameters are respectively mapped to N mapping data through the N first data mapping modes;

[0444] In the case where the target data mapping method includes a second data mapping method, the target indication information includes second indication information, and the second indication information is used to indicate that through the second data mapping method, the N parameters are respectively mapped into N mapping data, and then the N-dimensional data composed of the N mapping data are mapped into one-dimensional data.

[0445] Optionally, the radio frequency unit 1901 is further configured to:

[0446] When the first device is a terminal device, sending capability information to the second device, wherein the capability information is used to indicate that the terminal device supports the first processing mode or the second processing mode;

[0447] The first processing method is a method of mapping the N parameters into N mapping data;

[0448] The second processing method is a method in which after the N parameters are mapped into the N mapping data, the N mapping data are further mapped into one-dimensional data.

[0449] Optionally, the sensitive information includes transmit beam pointing, and the N parameters include N directional dimensions of the transmit beam pointing.

[0450] It can be understood that the implementation process of each implementation method mentioned in this embodiment can refer to the relevant description of the data collection method embodiment, and achieve the same or corresponding technical effect. To avoid repetition, it will not be repeated here.

[0451] The embodiment of the present application also provides a network side device, including a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the following Figure 3 The steps of the method embodiment shown. This network side device embodiment corresponds to the above network side device method embodiment, and each implementation process and implementation mode of the above method embodiment can be applied to this network side device embodiment and can achieve the same technical effect.

[0452] Specifically, the embodiment of the present application also provides a network side device. Fig. 20 As shown, the network side device 2000 includes: an antenna 2001, a radio frequency device 2002, a baseband device 2003, a processor 2004 and a memory 2005. The antenna 2001 is connected to the radio frequency device 2002. In the uplink direction, the radio frequency device 2002 receives information through the antenna 2001 and sends the received information to the baseband device 2003 for processing. In the downlink direction, the baseband device 2003 processes the information to be sent and sends it to the radio frequency device 2002, and the radio frequency device 2002 processes the received information and sends it out through the antenna 2001.

[0453] The method executed by the network-side device in the above embodiment may be implemented in the baseband device 2003, which includes a baseband processor.

[0454] The baseband device 2003 may include, for example, at least one baseband board on which a plurality of chips are arranged. Fig. 20 As shown, one of the chips is, for example, a baseband processor, which is connected to the memory 2005 through a bus interface to call the program in the memory 2005 to execute the network device operations shown in the above method embodiment.

[0455] The network side device may further include a network interface 2006, which is, for example, a Common Public Radio Interface (CPRI).

[0456] Specifically, the network side device 20000 of the embodiment of the present invention further includes: an instruction or program stored in the memory 2005 and executable on the processor 2004, and the processor 2004 calls the instruction or program in the memory 2005 to execute Fig.17 The methods executed by the modules shown achieve the same technical effects, and therefore will not be described here in detail to avoid repetition.

[0457] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned data collection method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0458] The processor is the processor in the terminal described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk. In some examples, the readable storage medium may be a non-transient readable storage medium.

[0459] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned data collection method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0460] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0461] The embodiments of the present application further provide a computer program / program product, which is stored in a storage medium and is executed by at least one processor to implement the various processes of the above-mentioned data collection method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0462] An embodiment of the present application also provides a communication system, including: a first device and a second device, wherein the first device can be used to execute the steps of the method described in the first aspect, and the second device can be used to execute the steps of the method described in the second aspect.

[0463] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises one..." does not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the method and device in the embodiment of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0464] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of a computer software product plus a necessary general hardware platform, and of course, can also be implemented by hardware. The computer software product is stored in a storage medium (such as ROM, RAM, disk, CD, etc.), including several instructions to enable a terminal or a network-side device to execute the methods described in each embodiment of the present application.

[0465] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms of implementation methods without departing from the purpose of the present application and the scope of protection of the claims, and these implementation methods are all within the protection of the present application.

Claims

1. A data collection method, characterized in that: include: The first device receives first information sent by the second device, wherein the first information includes a target identifier and target information, the target information is used to indicate N mapping data of N parameters of sensitive information of the second device, the target information is obtained by performing data mapping on the N parameters according to a target data mapping method, and the target identifier is used to indicate the target data mapping method; The first device generates a data set according to the target information; The first device performs at least one of the following according to the target identifier and the data set: Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier; The AI ​​unit reasoning; The AI ​​unit is monitored.

2. The method according to claim 1, characterized in that The target information includes the N mapping data, the target data mapping method includes N first data mapping methods, the i-th mapping data is obtained by processing the i-th parameter of the sensitive information based on the i-th first data mapping method, and i is an integer from 1 to N.

3. The method according to claim 1, characterized in that The target information includes first data and second information, where the second information is used to indicate a mapping relationship between the first data and the N mapping data; The first device generates a data set according to the target information, including: The first device determines the N mapping data according to the mapping relationship indicated by the second information and the first data; The first device generates the data set according to the N mapping data.

4. The method according to claim 3, characterized in that The second information includes a reference parameter, the number of values ​​of the reference parameter, and a functional relationship between the first data and the N mapping data; The reference parameters are at least some of the N parameters.

5. The method according to any one of claims 1 to 4, characterized in that Before the first device receives the first information sent by the second device, the method further includes: The first device sends third information to the second device; The third information includes the target identifier and target indication information, and the target indication information is used to indicate that data mapping is performed on the N parameters respectively.

6. The method according to claim 5, characterized in that In a case where the target data mapping mode includes N first data mapping modes, the target indication information includes first indication information, and the first indication information is used to indicate that the N parameters are mapped to N mapping data respectively through the N first data mapping modes; In the case where the target data mapping method includes a second data mapping method, the target indication information includes second indication information, and the second indication information is used to indicate that through the second data mapping method, the N parameters are respectively mapped into N mapping data, and then the N-dimensional data composed of the N mapping data are mapped into one-dimensional data.

7. The method according to any one of claims 1 to 6, characterized in that The method further comprises: In the case where the first device is a terminal device, the first device sends capability information to the second device, wherein the capability information is used to indicate that the terminal device supports the first processing mode or the second processing mode; The first processing method is a method of mapping the N parameters into N mapping data; The second processing method is a method in which after the N parameters are mapped into the N mapping data, the N mapping data are further mapped into one-dimensional data.

8. The method according to any one of claims 1 to 7, characterized in that The sensitive information includes the transmission beam pointing, and the N parameters include N directional dimensions of the transmission beam pointing.

9. A data collection method, characterized in that: include: The second device performs data mapping on N parameters of the sensitive information of the second device according to the target data mapping mode to obtain target information, wherein the target information is used to indicate N mapping data of the N parameters; The second device sends first information to the first device, wherein the first information includes the target information and a target identifier, the target identifier is used to indicate the target data mapping mode, and the N mapping data are used to generate a data set; The data set is used for at least one of the following: Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier; The AI ​​unit reasoning; The AI ​​unit is monitored.

10. The method according to claim 9, characterized in that The target data mapping mode includes N first data mapping modes; The second device performs data mapping on N parameters of the sensitive information of the second device according to the target data mapping mode to obtain target information, including: The second device performs data mapping on the i-th parameter of the N parameters through the i-th first data mapping mode to obtain the i-th mapping data, where i is an integer from 1 to N. The second device determines the obtained N mapping data as the target information.

11. The method according to claim 9, characterized in that The target data mapping mode includes a second data mapping mode; The second device performs data mapping on N parameters of the sensitive information of the second device according to the target data mapping mode to obtain target information, including: The second device performs data mapping on the N parameters respectively through the second data mapping mode to obtain the N mapping data; The second device maps the N-dimensional data formed by the N mapping data to one-dimensional data to obtain first data; The second device determines the first data and the second information as the target information; The second information is used to indicate a mapping relationship between the first data and the N mapping data.

12. The method according to claim 11, characterized in that The second information includes a reference parameter, the number of values ​​of the reference parameter, and a functional relationship between the first data and the N mapping data; The reference parameters are at least some of the N parameters.

13. The method according to any one of claims 9 to 12, characterized in that Before the second device performs data mapping on N parameters of the sensitive information of the second device according to the target data mapping mode and obtains the target information, the method further includes: The second device receives third information sent by the first device, wherein the third information includes the target identifier and target indication information, and the target indication information is used to indicate that data mapping is performed on the N parameters respectively; The second device performs data mapping on N parameters of the sensitive information of the second device according to the target data mapping mode to obtain target information, including: The second device performs data mapping on the N parameters based on the target indication information and through the target data mapping mode indicated by the target identifier to obtain the target information.

14. The method according to claim 13, characterized in that In a case where the target data mapping mode includes N first data mapping modes, the target indication information includes first indication information, and the first indication information is used to indicate that the N parameters are mapped to N mapping data respectively through the N first data mapping modes; In the case where the target data mapping method includes a second data mapping method, the target indication information includes second indication information, and the second indication information is used to indicate that through the second data mapping method, the N parameters are respectively mapped into N mapping data, and then the N-dimensional data composed of the N mapping data are mapped into one-dimensional data.

15. The method according to any one of claims 9 to 14, characterized in that The method further comprises: In the case where the first device is a terminal device, the second device receives the capability information sent by the first device; The capability information is used to indicate that the terminal device supports the first processing mode or the second processing mode; The first processing method is that after the N parameters are mapped into the N mapping data, the N mapping data are further mapped into one-dimensional data; The second processing manner is a manner of mapping the N parameters into N mapping data.

16. The method according to any one of claims 9 to 15, characterized in that The sensitive information includes the transmission beam pointing, and the N parameters include N directional dimensions of the transmission beam pointing.

17. A data collection device, characterized in that: Applied to a first device, the apparatus comprises: A first receiving module, configured to receive first information sent by a second device, wherein the first information includes a target identifier and target information, the target information is used to indicate N mapping data of N parameters of sensitive information of the second device, the target information is obtained by performing data mapping on the N parameters according to a target data mapping method, and the target identifier is used to indicate the target data mapping method; A generating module, used for generating a data set according to the target information; An execution module, configured to execute at least one of the following according to the target identifier and the data set: Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier; The AI ​​unit reasoning; The AI ​​unit is monitored.

18. A data collection device, characterized in that: Applied to a second device, the apparatus comprises: a mapping module, configured to perform data mapping on N parameters of the sensitive information of the second device according to a target data mapping mode to obtain target information, wherein the target information is used to indicate N mapping data of the N parameters; A first sending module, configured to send first information to a first device, wherein the first information includes the target information and a target identifier, the target identifier is used to indicate the target data mapping mode, and the N mapping data are used to generate a data set; The data set is used for at least one of the following: Training an artificial intelligence (AI) unit, wherein at least one of the AI ​​unit and the data set is associated with the target identifier; The AI ​​unit reasoning; The AI ​​unit is monitored.

19. A communication device, characterized in that: It includes a processor and a memory, the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, it implements the steps of the data collection method as described in any one of claims 1 to 8, or implements the steps of the data collection method as described in any one of claims 9 to 16.

20. A readable storage medium, characterized in that: The readable storage medium stores programs or instructions, and when the programs or instructions are executed by the processor, the steps of the data collection method as described in any one of claims 1 to 8 are implemented, or the steps of the data collection method as described in any one of claims 9 to 16 are implemented.

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