Information processing method, information transmission method, information processing device, information transmission device and related equipment

Abstract

The invention discloses an information processing method and device, an information transmission method and device and related equipment, and belongs to the technical field of communication, and the information processing method comprises the steps that first equipment receives first perception information from second equipment, the first perception information comprises auxiliary information suitable for at least one AI unit, and the auxiliary information comprises auxiliary information suitable for at least one AI unit; the first equipment is provided with a first AI unit, and at least one AI unit applicable to the first sensing information comprises the first AI unit; the first equipment inputs first input information into the first AI unit to obtain a reasoning result output by the first AI unit, and the first input information comprises the first sensing information.

Description

Technical Field

[0001] This application belongs to the field of communication technologies, and particularly relates to an information processing method, an information transmission method, a device, and related equipment. Background Art

[0002] In a communication network, methods of artificial intelligence (AI) are introduced to improve network communication performance.

[0003] In related technologies, an AI unit uses measurement values of communication measurement quantities as inputs to perform inference.

[0004] However, using only the measurement values of communication measurement quantities as inputs to the AI unit results in poor accuracy and poor generalization ability of the inference results of the AI unit. Summary of the Invention

[0005] Embodiments of this application provide an information processing method, an information transmission method, a device, and related equipment, which can use perception information as additional input information for an AI unit, improving the accuracy and generalization ability of the inference results of the AI unit.

[0006] In a first aspect, an information processing method is provided. The method includes:

[0007] A first device receives first perception information from a second device, where the first perception information includes auxiliary information applicable to at least one AI unit, the first device has a first AI unit, and the at least one AI unit to which the first perception information is applicable includes the first AI unit;

[0008] The first device inputs first input information into the first AI unit to obtain an inference result output by the first AI unit, where the first input information includes the first perception information.

[0009] In a second aspect, an information transmission method is provided. The method includes:

[0010] A second device sends first perception information to a first device, where the first perception information includes auxiliary information applicable to at least one AI unit, and the at least one AI unit to which the first perception information is applicable includes the first AI unit of the first device.

[0011] In a third aspect, an information processing device for a first device is provided. The device includes:

[0012] A first receiving module, configured to receive first sensing information from a second device, where the first sensing information includes auxiliary information applicable to at least one AI unit, the first device has a first AI unit, and the at least one AI unit to which the first sensing information is applicable includes the first AI unit;

[0013] A processing module, configured to input first input information into the first AI unit to obtain an inference result output by the first AI unit, where the first input information includes the first sensing information.

[0014] In a fourth aspect, an information transmission device for a second device is provided. The device includes:

[0015] A third sending module, configured to send first sensing information to a first device, where the first sensing information includes auxiliary information applicable to at least one AI unit, and the at least one AI unit to which the first sensing information is applicable includes the first AI unit of the first device.

[0016] In a fifth aspect, a communication device is provided. The communication device includes a processor and a memory. The memory stores a program or instruction that can run on the processor. 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.

[0017] In a sixth aspect, a communication device is provided, including a processor and a communication interface:

[0018] Wherein, when the communication device is used as the first device, the communication interface is configured to receive first sensing information from a second device, where the first sensing information includes auxiliary information applicable to at least one AI unit, the first device has a first AI unit, and the at least one AI unit to which the first sensing information is applicable includes the first AI unit; the processor is configured to input first input information into the first AI unit to obtain an inference result output by the first AI unit, where the first input information includes the first sensing information; or,

[0019] When the communication device is used as the second device, the communication interface is configured to send first sensing information to a first device, where the first sensing information includes auxiliary information applicable to at least one AI unit, and the at least one AI unit to which the first sensing information is applicable includes the first AI unit of the first device.

[0020] In a seventh aspect, a readable storage medium is provided. The readable storage medium stores a program or instruction. 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.

[0021] In an eighth aspect, a wireless communication system is provided, including: a first device and a second device. The first device can be used to perform the steps of the method described in the first aspect, and the second device can be used to perform the steps of the method described in the second aspect.

[0022] In a ninth aspect, a chip is provided. The chip includes a processor and a communication interface. The communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the method described in the first aspect or the second aspect.

[0023] In a tenth aspect, a computer program / program product is provided. 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 steps of the method described in the first aspect or the second aspect.

[0024] In an embodiment of the present application, the first device receives first perception information from the second device. The first perception information includes auxiliary information applicable to at least one AI unit. The first device has a first AI unit, and at least one AI unit applicable to the first perception information includes the first AI unit. The first device inputs first input information into the first AI unit to obtain an inference result output by the first AI unit, where the first input information includes the first perception information. When the first device uses the first AI unit for inference, it receives the first perception information applicable to the first AI unit sent by the second device. In this way, by using the first perception information obtained by the second device as additional input information for the first AI unit, the first AI unit can use the perception information as auxiliary information in the inference process, which can improve the accuracy and generalization ability of the inference result of the first AI unit. Description of the Drawings

[0025] Figure 1 is a schematic structural diagram of a wireless communication system to which the embodiments of the present application can be applied;

[0026] Figure 2 is a schematic diagram of a neural network;

[0027] Figure 3 is a schematic diagram of a neuron;

[0028] Figure 4 is a comparison diagram of the CSI mean square error (Normalized Mean Square Error, NMSE) between an AI-based CSI prediction scheme and a non-AI-based CSI prediction scheme;

[0029] Figure 5 is a flowchart of an information processing method provided by the embodiments of the present application;

[0030] Figure 6 is a flowchart of an information transmission method provided by an embodiment of the present application;

[0031] Figure 7 is a schematic structural diagram of an information processing device provided by an embodiment of the present application;

[0032] Figure 8 is a schematic structural diagram of an information transmission device provided by an embodiment of the present application;

[0033] Figure 9 is a schematic structural diagram of a communication device provided by an embodiment of the present application;

[0034] Figure 10 is a schematic structural diagram of a terminal provided by an embodiment of the present application;

[0035] Figure 11 is a schematic structural diagram of a network-side device provided by an embodiment of the present application;

[0036] Figure 12 is a schematic structural diagram of another network-side device provided by an embodiment of the present application. Detailed implementation manners

[0037] Next, the technical solutions in the embodiments of the present application will be clearly described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, rather than all, of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the present application.

[0038] The terms "first", "second", etc. in the present application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that such terms can be interchanged under appropriate circumstances 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 usually of the same type, and the number of objects is not limited. For example, the first object can be one or multiple. In addition, "or" in the present application means at least one of the connected objects. For example, "A or B" covers three scenarios, namely, Scenario 1: including A and not including B; Scenario 2: including B and not including A; Scenario 3: including both A and B. The character " / " generally indicates an "or" relationship between the associated objects before and after.

[0039] The term "indication" in this application can be either a direct indication (or an explicit indication) or an indirect indication (or an implicit indication). Among them, a direct indication can be understood as that the sender clearly tells the receiver specific information, operations to be performed, or request results, etc. in the sent indication; an indirect indication can be understood as that the receiver determines the corresponding information according to the indication sent by the sender, or makes a judgment and determines the operations to be performed or request results, etc. according to the judgment result.

[0040] It should be noted that the technology described in the embodiments of this application is not limited to the Long Term Evolution (LTE) / LTE-Advanced (LTE-A) system, and 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 this application are often used interchangeably, and the described technology can be used not only in the systems and radio technologies mentioned above, but also in other systems and radio technologies. The following description describes the New Radio (NR) system for example purposes, and uses the NR term in most of the following descriptions, but these technologies can also be applied to systems other than the NR system, such as the 6th Generation (6G) communication system. th Generation, 6G) communication system.

[0041] Figure 1A block diagram of a wireless communication system to which embodiments of the present application can be applied 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 personal computer, a laptop computer, a notebook computer, a personal digital assistant (PDA), a handheld computer, a netbook, an ultra-mobile personal computer (UMPC), a mobile internet device (MID), an augmented reality (AR), a virtual reality (VR) device, a robot, a wearable device, a flight vehicle, a vehicle user equipment (VUE), a shipborne device, a pedestrian user equipment (PUE), a smart home (home devices with wireless communication functions, such as refrigerators, TVs, washing machines or furniture, etc.), a game console, a personal computer (PC), a teller machine or a self-service machine, etc. Wearable devices include: smart watches, smart bracelets, smart earphones, smart glasses, smart jewelry (smart bracelets, smart bracelets, smart rings, smart necklaces, smart anklets, smart ankle chains, etc.), smart wristbands, smart clothing, etc. Among them, the vehicle user equipment can also be referred to as a vehicle terminal, a vehicle controller, a vehicle module, a vehicle component, a vehicle chip or a vehicle unit, etc. It should be noted that the specific type of the terminal 11 is not limited in the embodiments of the present application. The network-side device 12 can include an access network device or a core network device. Among them, the access network device can 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 can include a base station, a wireless local area network (WLAN) access point (AP) or a wireless fidelity (WiFi) node, etc.Among them, the base station can be referred to as Node B (NB), Evolved Node B (eNB), the next generation Node B (gNB), New Radio Node B (NR Node B), access point, Relay Base Station (RBS), Serving Base Station (SBS), Base Transceiver Station (BTS), radio base station, radio transceiver, Basic Service Set (BSS), Extended Service Set (ESS), home Node B (HNB), home evolved Node B, Transmission Reception Point (TRP), or some other suitable term in the art. 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 this application, only the base station in the NR system is taken as an example for introduction, and the specific type of the base station is not limited.

[0042] The core network device may include, but is not limited to, at least one of the following: core network node, core network function, Location Management Function (LMF), Mobility Management Entity (MME), Access and Mobility Management Function (AMF), Session Management Function (SMF), User Plane Function (UPF), Policy Control Function (PCF), Policy and Charging Rules Function (PCRF), Edge Application Server Discovery Function (EASDF), Unified Data Management (UDM), Unified Data Repository (UDR), Home Subscriber Server (HSS), Centralized network configuration (CNC), Network Repository Function (NRF), Network Exposure Function (NEF), Local NEF (L-NEF), Binding Support Function (BSF), Application Function (AF), Network Data Analytics Function (NWDAF), etc. It should be noted that in the embodiments of this application, only the core network devices in the NR system are taken as examples for introduction, and the specific types of core network devices are not limited. It should be noted that in the embodiments of this application, only the core network devices in the NR system are taken as examples for introduction, and the specific types of core network devices are not limited.

[0043] Artificial intelligence has currently been widely applied in various fields. There are multiple implementation methods for the AI unit, such as neural networks, decision trees, support vector machines, Bayesian classifiers, etc. In this application, a neural network is taken as an example for illustration, but the specific type of the AI unit is not limited.

[0044] Such asFigure 2 As shown, the neural network includes an input layer, a hidden layer, and an output layer, which can predict possible output results (Y) based on the input information (X1 to X n ) obtained by the input layer. The neural network consists of a large number of neurons. As Figure 3 shown, the parameters of a neuron include: input parameters a1 to a K , weights w, biases b, and activation function σ(z), and the output value a is obtained from these parameters. Among them, common activation functions include the sigmoid function, the hyperbolic tangent (tanh) function, the rectified linear unit (ReLU, also known as the rectified linear unit) function, etc. And z in the above function σ(z) can be calculated by the following formula:

[0045] z = z1w1 + … + a k w k + a K w K + b

[0046] where K represents the total number of input parameters.

[0047] The parameters of the neural network are optimized by an optimization algorithm. The optimization algorithm is a class of algorithms that can help us minimize or maximize the objective function (sometimes also called the loss function). And the objective function is often a mathematical combination of AI unit parameters and data. For example, given data X and its corresponding label Y, we construct a neural network f(.). After having the neural network model, based on the input x, we can obtain the predicted output f(x), and the difference between the predicted value and the true value (f(x) - Y) can be calculated, which is the loss function. Our goal is to find the appropriate W and b to minimize the value of the above loss function. The smaller the loss value, the closer our AI unit is to the real situation.

[0048] Currently, common optimization algorithms are basically based on the backpropagation algorithm. The basic idea of the backpropagation algorithm is that the learning process consists of two processes: the forward propagation of signals and the backpropagation of errors. During forward propagation, the input samples are fed into the input layer and, after being processed layer by layer through each hidden layer, are transmitted to the output layer. If the actual output of the output layer does not match the expected output, it enters the stage of error backpropagation. Error backpropagation is to transmit the output error back layer by layer through the hidden layer in a certain form and allocate the error to all units in each layer, so as to obtain the error signals of each layer's units. This error signal is used as the basis for correcting the weights of each unit. This process of adjusting the weights of each layer during the forward propagation of signals and the backpropagation of errors is carried out cyclically. The process of continuously adjusting the weights is also the learning and training process of the network. This process continues until the error of the network output is reduced to an acceptable level or until a pre-set number of learning times is reached.

[0049] Generally speaking, depending on the type of problem to be solved, the selected AI algorithms and the adopted AI units are also different. In related technologies, the main method to improve the 5G network performance with the help of AI is to enhance or replace the existing algorithms or processing modules through neural network-based algorithms and AI units. In specific scenarios, neural network-based algorithms and AI units can achieve better performance than deterministic algorithms. Commonly used neural networks include deep neural networks, convolutional neural networks, and recurrent neural networks, etc. With the help of existing AI tools, the construction, training, and verification of neural networks can be realized.

[0050] In summary, replacing non-AI processing modules in communication systems with AI or machine learning (ML) methods can effectively improve system performance. For example, taking the prediction of channel state information (CSI) as an example, historical CSI can be input into the AI unit, and the AI unit can be used to analyze the time-domain change characteristics of the channel, and based on the inference, the future CSI can be obtained. The system performance corresponding to this solution is as Figure 4 shown, based on Figure 4 it can be determined that the CSI prediction based on AI will have a very large performance gain compared to the solution without prediction. At the same time, the different future moments for prediction will result in different prediction accuracies that can be achieved.

[0051] However, although the above-mentioned gains can be obtained from AI-based CSI prediction, there are also certain drawbacks, the most important of which is the poor generalization ability of AI-based solutions. When the inference environment is quite different from the training environment, the performance of the AI unit will become very poor, that is, mismatch will occur. For example, when the CSI prediction AI unit trained with the channel of a terminal moving at a speed of 30 km / h is used to predict the CSI of a terminal moving at a speed of 60 km / h, its performance will be very poor. Therefore, it is necessary to monitor the actual inference performance of CSI prediction and trigger a series of adjustment measures according to the monitoring results.

[0052] In the embodiments of the present application, perception information can be used to assist the AI unit in inference to improve the generalization ability of the AI unit and the accuracy of inference results. For example, when the CSI prediction AI unit trained with the channel of a terminal moving at a speed of 30 km / h is used to predict the CSI of a terminal moving at a speed of 60 km / h, perception information such as the terminal moving at a speed of 60 km / h can be input into the AI unit to assist the AI in inference, improving the accuracy of the prediction result of the CSI prediction AI unit trained with the channel of a terminal moving at a speed of 30 km / h for the CSI of a terminal moving at a speed of 60 km / h.

[0053] It should be noted that the AI unit in the embodiments of the present application can be used in the above-mentioned CSI prediction scenarios, and can also be used in other scenarios, such as: AI-based CSI compression feedback, beam prediction, positioning enhancement, intelligent network selection, load balancing, energy saving, etc., which are not enumerated here.

[0054] To facilitate the understanding of the information processing method and information transmission method provided in the embodiments of the present application, the following terms in the embodiments of the present application are first explained:

[0055] 1) AI unit: The AI unit in the embodiments of the present application can also be referred to as an AI model, an AI structure, etc., or the AI unit can also refer to a processing unit capable of implementing AI-related algorithms, formulas, processing procedures, capabilities, etc., or the AI unit can be a processing method, algorithm, function, module or unit for a specific data set, or the AI unit can be a processing method, algorithm, function, module or unit running on AI-related hardware such as a Graphic Processing Unit (GPU), a Natural Processing Unit (NPU), a Tensor Processing Unit (TPU), an Application-Specific Integrated Circuit (ASIC), etc. The present application does not make specific limitations on this. Optionally, the specific data set includes the input and / or output of the AI unit.

[0056] The identification of the AI unit includes, for example, an AI model identification, an AI structure identification, an AI algorithm identification, a functionality ID, a physical identification, a logical identification, a global identification, a local identification, or the identification of a specific data set associated with the AI unit, or the identification of a specific scenario, environment, channel characteristic, or device related to the AI, or the identification of a function, feature, ability, or module related to the AI, etc.

[0057] 2) The first device: It can be a device that uses the AI unit for inference. For example, the first device can include a terminal or a network-side device.

[0058] 3) The second device: It can be a device with a sensing function and that obtains sensing information based on this sensing function. This sensing information can be one of the input information for the AI unit to assist the AI unit in making inferences. For example, the first device can include a terminal or a network-side device, where the network-side device can include at least one of an access network device and a core network device.

[0059] Among them, the combination of the above first device and second device can include any one of the combinations shown in Table 1 below:

[0060] Table 1

[0061]

[0062] It should be noted that in the embodiments of this application, for the sake of convenience of description, usually the first device is a terminal and the second device is a network-side device as an example for illustration, which does not constitute a specific limitation here.

[0063] Optionally, the first device and the second device can be physically co-located. For example, the first device can perform inference based on the first AI unit, and the first device determines the first sensing information required for input to the first AI unit through sensing measurements.

[0064] It is worth noting that in the case where the first device and the second device are physically co-located, the interaction between the first device and the second device can be omitted.

[0065] Of course, the first device and the second device can also be independently deployed. For the sake of convenience of description, in the embodiments of this application, the first device and the second device are independently deployed as an example for illustration.

[0066] 4) Wireless sensing results: The wireless sensing results in the embodiments of this application can include at least one of the following:

[0067] Measurement values of the first-level measurement quantities (received signals / original channel information), where the first-level measurement quantities include at least one of the following: received signal / channel response complex results, amplitude / phase, I-channel / Q-channel and their operation results (the operations include addition, subtraction, multiplication, division, matrix addition, subtraction, multiplication, matrix transpose, triangular relationship operations, square root operations, power operations, etc., and threshold detection results and maximum / minimum value extraction results of the above operation results; the above operations also include Fast Fourier Transform (FFT) / Inverse Fast Fourier Transform (IFFT), Discrete Fourier Transform (DFT) / Inverse Discrete Fourier Transform (IDFT), 2D-FFT, 3D-FFT, matched filtering, autocorrelation operations, wavelet transforms, digital filtering, etc., and threshold detection results and maximum / minimum value extraction results of the above operation results);

[0068] Measurement values of the second-level measurement quantities (basic measurement quantities), where the second-level measurement quantities include at least one of the following: time delay, Doppler, angle, intensity, and their multi-dimensional combined representations;

[0069] Measurement values of the third-level measurement quantities (basic attributes / status), where the third-level measurement quantities include at least one of the following: distance, speed, orientation, spatial position, acceleration;

[0070] Measurement values of the fourth-level measurement quantities (advanced attributes / status), where the fourth-level measurement quantities include at least one of the following: whether the target exists, trajectory, action, expression, vital signs, quantity, imaging result, weather, air quality, shape, material, composition.

[0071] 5) Wireless statistical characteristics: The wireless statistical characteristics in the embodiments of the present application include occlusion probability, user status, user behavior, handover failure rate, etc.

[0072] I) The occlusion probability refers to the probability that the service beam is occluded;

[0073] II) The user status includes at least one of the following:

[0074] Registration status: Registration Management (RM) deregistration or RM registration (RMDEREGISTERED or RM REGISTERED);

[0075] Connection Management (CM) status: CM idle, CM connected;

[0076] Radio Resource Control (RRC) connection management states: RRC idle, RRC connected, RRC inactive;

[0077] III) User behaviors include at least one of the following:

[0078] RRC-idle model behaviors, including at least one of the following: Public Land Mobile Network (PLMN) selection, neighbor cell measurement, cell selection, cell reselection, Tracking Area (TA) update, paging monitoring, obtaining system information;

[0079] RRC-Inactive mode behaviors, including at least one of the following: neighbor cell measurement, cell reselection, cell selection, RAN notification area (RNA) update, RAN paging monitoring, obtaining system information;

[0080] RRC-Connected mode behaviors, including at least one of the following: serving cell channel quality measurement and reporting, neighbor cell measurement and measurement report reporting, Physical Downlink Control Channel (PDCCH) monitoring, monitoring the control channel related to the shared data channel (perceiving whether there is relevant scheduling), obtaining system information.

[0081] Among them, the differences between the above RRC-idle, RRC-Inactive, and RRC-Connected are shown in Table 2 below:

[0082] Table 2

[0083] RRC connection management state Between the UE and the base station Between the base station and the core network RRC-connected Connection Connection RRC-idle Release Release RRC-inactive Release Connection

[0084] IV) LiDAR-related measurement quantities, including at least one of the following:

[0085] LiDAR point cloud data, and each point in the LiDAR point cloud data includes: X / Y / Z position information, and additional information;

[0086] The angle and distance of the target obtained from the LiDAR point cloud data;

[0087] The visual features of the target identified from the LiDAR point cloud data, such as: people, vehicles, etc.;

[0088] The number of targets identified from the LiDAR point cloud data;

[0089] The additional information in the lidar point cloud data includes at least one of the following:

[0090] Intensity: The echo intensity of the laser pulse that generates the lidar point;

[0091] Number of echoes: The number of echoes is the total number of echoes of a given pulse;

[0092] Point classification: Each post-processed lidar point can have a classification that defines the type of object reflecting the lidar pulse. The lidar points can be divided into many categories, such as: ground, bare ground surface, top of the tree canopy, and water area, etc.;

[0093] Red, Green, Blue (RGB): The RGB band can be used as an attribute of the lidar data, and this attribute usually comes from the images collected during lidar measurement;

[0094] Global Positioning System (GPS) time: The GPS timestamp of the emitted laser point;

[0095] Scanning angle:

[0096] Scanning direction: The traveling direction of the laser scanning mirror, where the value 1 represents the positive scanning direction and the value 0 represents the negative scanning direction.

[0097] V) Vision-related measurement quantities, including at least one of the following:

[0098] Visual image;

[0099] Luminance of the image pixel;

[0100] RGB value of the image pixel;

[0101] Visual features of the targets identified from the image, such as: people, vehicles, etc.;

[0102] Angles and distances of the targets identified from the image (especially for binocular vision);

[0103] Number of targets identified from the image.

[0104] VI) Radar-related measurement quantities, including at least one of the following:

[0105] Radar point cloud, and each point in the point cloud includes at least one of: distance / speed / azimuth angle / pitch angle, or at least one of X / Y / Z / speed;

[0106] Distances, speeds, and angles of the identified targets;

[0107] Radar imaging;

[0108] The number of targets.

[0109] VII) Measurement quantities related to the inertial measurement unit, including at least one of the following:

[0110] Acceleration: at least one of the three directions of X / Y / Z;

[0111] Velocity: at least one of the three directions of X / Y / Z;

[0112] Angular velocity: around at least one of the three axes of X / Y / Z.

[0113] It should be noted that, in addition to the information types listed above, the first perception information in the embodiments of the present application may also include other types of perception information, such as including at least one of the following: whether a target exists, trajectory, action, expression, vital signs, quantity, imaging result, weather, air quality, shape, material, composition, hydrology, satellite image, terrain, etc.

[0114] Next, in conjunction with the accompanying drawings, through some embodiments and their application scenarios, the information processing method, information transmission method, information processing device, information transmission device, and related equipment provided by the embodiments of the present application will be described in detail.

[0115] Please refer to Figure 5 , an information processing method provided by an embodiment of the present application, the execution subject of which may be a first device, such as Figure 5 shown, the information processing method may include the following steps:

[0116] Step 501, the first device receives first perception information from the second device, where the first perception information includes auxiliary information applicable to at least one AI unit, the first device has a first AI unit, and at least one AI unit applicable to the first perception information includes the first AI unit.

[0117] It should be noted that the above first perception information includes auxiliary information applicable to at least one AI unit, which may mean that the first perception information can be input into one or at least two AI units to respectively provide auxiliary information for the inference of the AI unit.

[0118] In some embodiments, the first perception information includes at least one of the following:

[0119] Wireless perception result, wireless statistical characteristic information, geographical location information, measured values of lidar-related measurement quantities, measured values of vision-related measurement quantities, measured values of radar-related measurement quantities, measured values of inertial measurement unit-related measurement quantities.

[0120] Among them, the meanings of the contents of the above first perception information can refer to the explanations of the foregoing related terms and will not be elaborated here.

[0121] Step 502: The first device inputs the first input information into the first AI unit to obtain an inference result output by the first AI unit, where the first input information includes the first sensing information.

[0122] It should be noted that in addition to the first sensing information, the above first input information may further include measurement values of conventional communication measurement quantities, and the measurement values of the communication measurement quantities have the same meaning as the input information used to input the AI unit in the related art, which will not be elaborated here.

[0123] For example: In AI-based CSI prediction, in addition to using historical CSI as input according to traditional communication settings, sensing information such as Doppler information, radar point cloud information, image information of the transmission environment, and weather information can also be used as auxiliary information to assist the AI unit in inferring the CSI prediction result.

[0124] Another example: In AI-based positioning, in addition to using channel measurement information according to traditional communication settings, sensing information such as distance information, radar point cloud information, terminal image information, and environmental image information can also be used as auxiliary information to assist the AI unit in inferring the positioning result.

[0125] In the embodiment of the present application, the first device receives the first sensing information from the second device, where the first sensing information includes auxiliary information applicable to at least one AI unit, the first device has a first AI unit, and the at least one AI unit applicable to the first sensing information includes the first AI unit; the first device inputs the first input information into the first AI unit to obtain an inference result output by the first AI unit, where the first input information includes the first sensing information. When the first device uses the first AI unit for inference, it receives the first sensing information applicable to the first AI unit sent by the second device. In this way, by using the first sensing information obtained by the second device as additional input information for the first AI unit, the first AI unit can use the sensing information as auxiliary information in the inference process, which can improve the accuracy and generalization ability of the inference result of the first AI unit.

[0126] It should be noted that since the first sensing information can be applicable to different AI units, when the first device uses the first AI unit for inference, it is necessary to obtain the first sensing information applicable to the first AI unit and associate the first sensing information with the first AI unit so that the first device can input the first sensing information into the first AI unit.

[0127] For example, in a case where the first device has a first AI unit and a second AI unit, and the first perception information is applicable to the first AI unit but not to the second AI unit, when the first device acquires the first perception information, it can know that the AI unit to which the first perception information is applicable is the first AI unit, and thus use the first perception information to assist the first AI unit in reasoning accordingly.

[0128] As an alternative implementation manner, before the first device receives the first perception information from the second device, the method further includes:

[0129] The first device sends first information to the second device, where the first information is used to request the sending of the first perception information.

[0130] In this implementation manner, the first device actively requests the first perception information from the second device. For example, when the first device uses the first AI unit, based on the requirements of the first AI unit for the input information, it determines the first perception information that needs to be input, and thus requests the first perception information from the second device.

[0131] In some implementation manners, the identifier of the perception information can be agreed upon in the protocol, or the first device negotiates with the second device in advance about the identifier of the perception information. In this way, the above first information can indicate the identifier of the first perception information, so that the second device can determine the first perception information requested by the first device according to the identifier of the first perception information.

[0132] In other implementation manners, the first information includes the relevant information of the first perception information, and the relevant information of the first perception information is used to indicate at least one of the following:

[0133] 1) The information type of the first perception information, such as including at least one of wireless perception results, wireless statistical characteristic information, geographical location information, measurement quantities related to lidar, measurement quantities related to vision, measurement quantities related to radar, measurement quantities related to an inertial measurement unit, and other measurement quantities;

[0134] Optionally, the information type of the above first perception information can be indicated by an information type identifier. For example, by means of agreement in the protocol, indication by the network side, or reporting by the terminal, the information type identifier of each perception information is agreed upon. At this time, the information type identifier is carried in the first information to indicate the information type of the first perception information.

[0135] 2) The AI unit set, where the AI unit set includes at least one AI unit to which the first perception information is applicable, and the AI unit set includes at least the first AI unit;

[0136] In some implementation manners, the above AI unit set can be indicated by a set of AI unit identifiers.

[0137] Among them, the AI unit identifier may include at least one of the following: AI model identifier, AI structure identifier, AI algorithm identifier, functionality ID, physical identifier, logical identifier, global identifier, local identifier, or the identifier of a specific data set associated with the AI unit. Alternatively, the AI unit identifier may include at least one of the identifiers of specific scenarios, environments, channel characteristics, and devices related to the AI. Alternatively, the AI unit identifier may include at least one of the identifiers of functions, features, capabilities, or modules related to the AI.

[0138] 3) The use of the first perception information;

[0139] Among them, the use of the first perception information may include at least one of the following:

[0140] For training of the AI unit, for inference of the AI unit, for performance monitoring of the AI unit.

[0141] In some embodiments, the first information may indicate the use of the first perception information for the first AI unit, or may also indicate the use of the first perception information for each AI unit (i.e., the set of AI units) to which it applies.

[0142] In some embodiments, the first information may indicate that all AI units in the set of AI units have the same use for the first perception information.

[0143] In other embodiments, the first information may indicate the use of the first perception information for each AI unit in the set of AI units. For example: the first perception information is used for inference of the first AI unit and for performance monitoring of the third AI unit.

[0144] Optionally, the above-mentioned use of the first perception information may be indicated by a protocol agreement, an indication from the network side, or a use identifier reported by the terminal.

[0145] 4) The preprocessing method of the first perception information, where the first perception information is input into the first AI unit after being preprocessed by the preprocessing method.

[0146] Among them, the preprocessing method is used to indicate the processing performed on the first perception information before it is input into the AI unit. For example: after the first device receives the first perception information, it preprocesses the first perception information according to the preprocessing method corresponding to the first perception information, and inputs the preprocessed first perception information into the first AI unit.

[0147] In some embodiments, the first information may indicate the preprocessing method of the first perception information before it is input into the first AI unit, or may indicate the preprocessing method of the first perception information before it is input into each applicable AI unit (i.e., the set of AI units).

[0148] In some embodiments, the first information may indicate that all AI units in the set of AI units adopt the same preprocessing method for the first perception information.

[0149] In some other embodiments, the first information may indicate the preprocessing method of each AI unit in the set of AI units for the first perception information. For example, after the first preprocessing of the first perception information, it is input into the first AI unit, and after the second preprocessing of the first perception information, it can be input into the third AI unit.

[0150] 5) The position of the first perception information in the input information of the applicable AI unit;

[0151] In some embodiments, the first information may indicate the position of the first perception information in the input information of the first AI unit, or may indicate the position of the first perception information in the input information of each applicable AI unit (i.e., the set of AI units).

[0152] In some embodiments, there are multiple input information of an AI unit. At this time, each input information needs to be input into the AI unit in the corresponding order. For example, the position of the first perception information in the input information of each AI unit in the set of AI units may indicate that in the input information sequence of the k-th AI unit in the set of AI units, the N k th element to the M k th element is the first perception information, where N k ≥0, M k ≥N k and k is a positive integer.

[0153] For example: There are multiple input layers in a neural network, and each input layer is used to input its corresponding input information. At this time, by indicating the position of the first perception information in the input information of each AI unit in the set of AI units through the first indication information, it can be determined which input layer of each AI unit in the set of AI units the first perception information is input into.

[0154] 6) The transmission method of the first perception information;

[0155] In some embodiments, the transmission method of the first perception information may include at least one of the following: encryption method, privacy processing method, source coding method, source-channel joint coding method, semantic communication method, etc.

[0156] 7) Transmission conditions of the first sensing information;

[0157] In some embodiments, the first sensing information is transmitted periodically. At this time, the transmission conditions of the first sensing information may include the transmission period of the first sensing information. For example, how often the first sensing information is transmitted (or updated).

[0158] In some other embodiments, the first sensing information is transmitted by event triggering. At this time, the transmission conditions of the first sensing information may include the triggering conditions for triggering the transmission of the first sensing information. That is, under what conditions the second device sends the first sensing information to the first device.

[0159] 8) The format of the first sensing information, such as: the dimension, accuracy, compression format, size limit, etc. of the first sensing information;

[0160] 9) The bearer channel of the first sensing information;

[0161] In some embodiments, the bearer channel of the first sensing information may include the plane for bearing the first sensing information and the physical channel for bearing the first sensing information. Among them, the plane for bearing the first sensing information may include at least one of the user plane, control plane, and data plane; the physical channel for bearing the first sensing information may include at least one of channels such as PDCCH, PUCCH, PDSCH, and PUSCH.

[0162] 10) The bearer resource of the first sensing information.

[0163] In some embodiments, the bearer resource of the first sensing information may include at least one of the time domain position (such as a specific slot, symbol), frequency domain position (such as a specific resource block), and spatial domain position (such as an antenna port) of the resource for bearing the first sensing information.

[0164] In this embodiment, when the first device is requested by the second device for the first sensing information, informing the second device of the relevant information of the first sensing information can enable the second device to determine the first sensing information accordingly and determine how to send the first sensing information.

[0165] As another alternative embodiment, before the first device receives the first sensing information from the second device, the method further includes:

[0166] The first device receives second information from the second device, where the second information is used to instruct the first device to receive the first sensing information.

[0167] Optionally, the second information includes information related to the first sensing information, and the information related to the first sensing information is used to indicate at least one of the following:

[0168] The type of information of the first sensing information;

[0169] A set of AI units, where the set of AI units includes at least one AI unit applicable to the first sensing information;

[0170] The use of the first sensing information;

[0171] The preprocessing method of the first sensing information, where the first sensing information is input into the first AI unit after being preprocessed by the preprocessing method;

[0172] The position of the first sensing information in the input information of the applicable AI unit;

[0173] The transmission method of the first sensing information;

[0174] The transmission conditions of the first sensing information;

[0175] The format of the first sensing information;

[0176] The carrier channel of the first sensing information;

[0177] The carrier resource of the first sensing information;

[0178] Wherein, the set of AI units includes at least one AI unit applicable to the first sensing information.

[0179] The differences between this embodiment and the previous embodiment include: in the previous embodiment, the first device requests the first sensing information from the second device; while in this embodiment, the second device instructs the first device to receive the first sensing information.

[0180] It should be noted that the above two embodiments can be combined. For example: the first device first sends the first information to the second device to request the second device to send the first sensing information, and the second device then replies with the second information to the first device according to the first information.

[0181] It is worth noting that the second information can be the same as or at least partially different from the first information.

[0182] For example, the information type of the first perception information indicated by the second information may be the same as the information type of the first perception information indicated by the first information, or the information type of the first perception information indicated by the second information may be a transformed information type of the information type of the first perception information indicated by the first information. In this case, all or part of the information content of the information type of the first perception information indicated by the first information may be converted based on all or part of the information content of the information type of the first perception information indicated by the second information.

[0183] It should be noted that making the information type of the first perception information indicated by the second information be a transformed information type of the information type of the first perception information indicated by the first information can protect the mapping information of the second device. For example: The first device requests the first perception information of the first information type, but the second device is not convenient to directly display and provide the first perception information of the first information type. It can only provide the first perception information of the second information type. After the first device receives the first perception information of the second information type, it can convert it into the first perception information of the first information type by itself. Among them, the process of converting the first perception information of the second information type into the first perception information of the first information type can be regarded as a preprocessing process.

[0184] In some embodiments, after the first device activates the first AI unit, it may adjust the AI unit. For example: Based on monitoring the inference result of the AI unit, in the case where it is determined that the gain value of the inference result obtained by the AI unit based on the first perception information is less than the specified threshold or less than the gain value of the non-AI solution, the AI unit may be adjusted.

[0185] As an alternative embodiment, the method further includes:

[0186] The first device sends third information to the second device, and the third information is used to request cancellation of sending the first perception information.

[0187] In some embodiments, the first device may send the third information to the second device when it is determined that the gain value of the inference result obtained by the first AI unit based on the first perception information is less than the specified threshold or less than the gain value of the non-AI solution.

[0188] Optionally, the first device sending the third information to the second device includes:

[0189] When the first device determines that the gain of the first inference result of the first AI unit compared to the second inference result of the second AI unit is less than or equal to the target gain, the first device sends the third information to the second device;

[0190] Among them, the input information of the second AI unit does not include sensing information.

[0191] In some embodiments, the target gain can be agreed upon by protocol, indicated by the network side, or reported by the terminal, and it can be equal to 0 or any value greater than 0.

[0192] In this embodiment, when the first device determines that the gain of the inference result using the first sensing information is less than or equal to the target gain compared to the inference result without using sensing information, the first device may request the second device to cancel sending the first sensing information. Thereafter, the first device may implement the function of the first AI unit using other AI units or implement the function of the first AI unit using a non-AI solution.

[0193] As another alternative embodiment, the method further includes:

[0194] The first device receives fourth information from the second device, where the fourth information is used to instruct the first device to stop receiving the first sensing information.

[0195] The differences between this embodiment and the previous embodiment include: in this embodiment, the second device decides to cancel sending the first sensing information and instructs the first device to stop receiving the first sensing information; in the previous embodiment, the first device decides and requests the second device to cancel sending the first sensing information.

[0196] Optionally, the fourth information includes first adjustment information, where the first adjustment information is used to instruct at least one of the following:

[0197] Enable the second AI unit of the first device, where the input information of the second AI unit does not include sensing information;

[0198] Use a non-AI solution.

[0199] In this embodiment, after the second device decides to cancel sending the first sensing information, it also instructs the first device to use the second AI unit or a non-AI solution to implement the function of the first AI unit.

[0200] Please refer to Figure 6 , an information transmission method provided by an embodiment of the present application, the execution subject of which may be a second device, such as Figure 6 shown, the information transmission method may include the following steps:

[0201] Step 601, the second device sends first sensing information to the first device, where the first sensing information includes auxiliary information applicable to at least one AI unit, and at least one AI unit to which the first sensing information is applicable includes the first AI unit possessed by the first device.

[0202] In some embodiments, the above first sensing information may be sensing information measured by a second device through a corresponding sensing function.

[0203] In other embodiments, the second device may also receive the first sensing information from other devices. For example, when the second device is an access network device, in this case, the first sensing information may be calculated based on a sensing function network element of the core network, and the access network device may obtain the first sensing information from the core network device.

[0204] It should be noted that the above first sensing information and first AI unit have the same meaning and function as the first sensing information and first AI unit in the first device-side method embodiments, and will not be elaborated here.

[0205] The embodiments of the present application correspond to the first device-side method embodiments. Among them, the first device-side method embodiments are used to use the first sensing information provided by the second device as the input information of the first AI unit to assist the inference of the first AI unit, while the second device-side method embodiments are used to provide the first sensing information applicable to the first AI unit used by the second device to the first device.

[0206] In some embodiments, the first sensing information includes at least one of the following:

[0207] Wireless sensing results, wireless statistical characteristic information, geographical location information, measurement values of lidar-related measurement quantities, measurement values of vision-related measurement quantities, measurement values of radar-related measurement quantities, measurement values of inertial measurement unit-related measurement quantities.

[0208] In some embodiments, the method further includes:

[0209] The second device receives first information from the first device, where the first information is used to request the second device to send the first sensing information;

[0210] The second device sending the first sensing information to the first device includes:

[0211] The second device sends the first sensing information to the first device according to the request of the first information.

[0212] In some embodiments, before the second device sends the first sensing information to the first device, the method further includes:

[0213] The second device sends second information to the first device, where the second information is used to indicate receiving the first sensing information.

[0214] In some embodiments, the first information or the second information includes information related to the first sensing information, and the information related to the first sensing information is used to indicate at least one of the following:

[0215] The type of information of the first sensing information;

[0216] The set of AI units;

[0217] The use of the first sensing information;

[0218] The preprocessing method of the first sensing information, wherein the first sensing information is input to the first AI unit after being preprocessed by the preprocessing method;

[0219] The position of the first sensing information in the input information of the applicable AI unit;

[0220] The transmission method of the first sensing information;

[0221] The transmission conditions of the first sensing information;

[0222] The format of the first sensing information;

[0223] The carrier channel of the first sensing information;

[0224] The carrier resource of the first sensing information;

[0225] Wherein, the set of AI units includes at least one AI unit applicable to the first sensing information.

[0226] In some embodiments, the method further includes:

[0227] The second device receives third information from the first device, and the third information is used to request the second device to cancel sending the first sensing information;

[0228] The second device stops sending the first sensing information to the first device.

[0229] In some embodiments, the method further includes:

[0230] The second device stops sending the first sensing information to the first device and sends fourth information to the first device, wherein the fourth information is used to indicate stopping receiving the first sensing information.

[0231] In some embodiments, the second device stopping sending the first sensing information to the first device includes:

[0232] The second device obtains a first inference result of the first AI unit and a second inference result of the second AI unit;

[0233] When the second device determines that the gain of the first inference result compared to the second inference result is less than or equal to the target gain, it stops sending the first perception information to the first device;

[0234] Wherein, the input information of the second AI unit does not include perception information.

[0235] In some embodiments, the fourth information includes first adjustment information, wherein the first adjustment information is used to indicate at least one of the following:

[0236] Enable the second AI unit of the first device;

[0237] Use a non-AI solution.

[0238] In the embodiments of the present application, the steps executed by the second device correspond to the steps executed by the first device in the method embodiments on the first device side, and the two cooperate with each other to jointly control the sending or stopping of the first perception information applicable to the first AI unit on the first device, so that the first device can use the perception information to assist the corresponding AI unit in reasoning. In addition, the control of the switching of the AI unit on the first device can also be achieved.

[0239] For the information processing method provided in the embodiments of the present application, the execution subject may be an information processing device. In the embodiments of the present application, taking the information processing device executing the information processing method as an example, the information processing device provided in the embodiments of the present application is described.

[0240] Refer to Figure 7 , the embodiments of the present application also provide an information processing device, which is applied to the first device, as Figure 7 shown, the information processing device 700 includes:

[0241] A first receiving module 701, configured to receive first perception information from a second device, wherein the first perception information includes auxiliary information applicable to at least one AI unit, the first device has a first AI unit, and the at least one AI unit to which the first perception information is applicable includes the first AI unit;

[0242] A processing module 702, configured to input first input information into the first AI unit to obtain an inference result output by the first AI unit, wherein the first input information includes the first perception information.

[0243] Optionally, the first perception information includes at least one of the following:

[0244] Wireless sensing results, wireless statistical characteristic information, geographical location information, measured values of lidar-related measurement quantities, measured values of vision-related measurement quantities, measured values of radar-related measurement quantities, measured values of inertial measurement unit-related measurement quantities.

[0245] Optionally, the information processing device 700 further includes:

[0246] A first sending module, configured to send first information to the second device, where the first information is used to request sending of the first sensing information.

[0247] Optionally, the information processing device 700 further includes:

[0248] A second receiving module, configured to receive second information from the second device, where the second information is used to instruct the first device to receive the first sensing information.

[0249] Optionally, the first information or the second information includes information related to the first sensing information, and the information related to the first sensing information is used to indicate at least one of the following:

[0250] The information type of the first sensing information;

[0251] The set of AI units;

[0252] The use of the first sensing information;

[0253] The preprocessing method of the first sensing information, where the first sensing information is input to the first AI unit after being preprocessed by the preprocessing method;

[0254] The position of the first sensing information in the input information of the applicable AI unit;

[0255] The transmission method of the first sensing information;

[0256] The transmission conditions of the first sensing information;

[0257] The format of the first sensing information;

[0258] The carrier channel of the first sensing information;

[0259] The carrier resource of the first sensing information;

[0260] Wherein, the set of AI units includes at least one AI unit applicable to the first sensing information.

[0261] Optionally, the information processing device 700 further includes:

[0262] A second sending module, configured to send third information to the second device, where the third information is used to request cancellation of sending the first sensing information.

[0263] Optionally, the second sending module is specifically configured to:

[0264] When the processing module determines that the gain of the first inference result of the first AI unit compared to the second inference result of the second AI unit is less than or equal to the target gain, send third information to the second device;

[0265] where the input information of the second AI unit does not include sensing information.

[0266] Optionally, the information processing device 700 further includes:

[0267] A third receiving module, configured to receive fourth information from the second device, where the fourth information is used to instruct the first device to stop receiving the first sensing information.

[0268] Optionally, the fourth information includes first adjustment information, where the first adjustment information is used to instruct at least one of the following:

[0269] Enable the second AI unit of the first device, where the input information of the second AI unit does not include sensing information;

[0270] Use a non-AI solution.

[0271] The information processing device 700 provided in the embodiments of the present application can implement each process in the method embodiments on the first device side and achieve the same technical effects. To avoid repetition, details are not described here again.

[0272] In the information transmission method provided in the embodiments of the present application, the execution subject may be an information transmission device. In the embodiments of the present application, taking the information transmission device executing the information transmission method as an example, the information transmission device provided in the embodiments of the present application is described.

[0273] Refer to Figure 8 , the embodiments of the present application further provide an information transmission device, which is applied to a second device. As Figure 8 shown, the information transmission device 800 includes:

[0274] A third sending module 801, configured to send first sensing information to the first device, where the first sensing information includes auxiliary information applicable to at least one AI unit, and the at least one AI unit to which the first sensing information applies includes the first AI unit possessed by the first device.

[0275] Optionally, the first sensing information includes at least one of the following:

[0276] Wireless sensing results, wireless statistical characteristic information, geographical location information, measured values of lidar-related measurement quantities, measured values of vision-related measurement quantities, measured values of radar-related measurement quantities, measured values of inertial measurement unit-related measurement quantities.

[0277] Optionally, the information transmission device 800 further includes:

[0278] A fourth receiving module, configured to receive first information from the first device, where the first information is used to request the second device to send the first sensing information;

[0279] The third sending module 801 is specifically configured to:

[0280] Send the first sensing information to the first device according to the request of the first information.

[0281] Optionally, the information transmission device 800 further includes:

[0282] A fourth sending module, configured to send second information to the first device, where the second information is used to indicate receiving the first sensing information.

[0283] Optionally, the first information or the second information includes related information of the first sensing information, and the related information of the first sensing information is used to indicate at least one of the following:

[0284] The information type of the first sensing information;

[0285] The set of AI units;

[0286] The use of the first sensing information;

[0287] The preprocessing method of the first sensing information, where the first sensing information is input to the first AI unit after being preprocessed by the preprocessing method;

[0288] The position of the first sensing information in the input information of the applicable AI unit;

[0289] The transmission method of the first sensing information;

[0290] The transmission condition of the first sensing information;

[0291] The format of the first sensing information;

[0292] The bearer channel of the first sensing information;

[0293] The bearer resource of the first sensing information;

[0294] Among them, the set of AI units includes at least one AI unit applicable to the first perception information.

[0295] Optionally, the information transmission device 800 further includes:

[0296] A fifth receiving module, configured to receive third information from the first device, where the third information is used to request the second device to cancel sending the first perception information;

[0297] A first control module, configured to control the third sending module to stop sending the first perception information to the first device.

[0298] Optionally, the information transmission device 800 further includes:

[0299] A second control module, configured to control the third sending module to stop sending the first perception information to the first device, and send fourth information to the first device, where the fourth information is used to indicate to stop receiving the first perception information.

[0300] Optionally, the second control module includes:

[0301] An acquisition unit, configured to acquire a first inference result of the first AI unit and a second inference result of the second AI unit;

[0302] A control unit, configured to control the third sending module to stop sending the first perception information to the first device when it is determined that the gain of the first inference result compared to the second inference result is less than or equal to a target gain;

[0303] Among them, the input information of the second AI unit does not include perception information.

[0304] Optionally, the fourth information includes first adjustment information, where the first adjustment information is used to indicate at least one of the following:

[0305] Enable the second AI unit of the first device;

[0306] Use a non-AI solution.

[0307] The information transmission device 800 provided in the embodiments of the present application can implement each process in the method embodiments on the second device side and achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0308] The information processing device or information transmission device in the embodiments of the present application may 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 may be a terminal or a network-side device. Exemplarily, the terminal may include, but is not limited to, the types of the terminal 11 listed above, and the network-side device includes, but is not limited to, the types of the access network device or core network device listed above, etc., which are not specifically limited in the embodiments of the present application.

[0309] Optionally, as Figure 9 shown, the embodiments of the present application further provide a communication device 900, including a processor 901 and a memory 902. A program or instruction that can run on the processor 901 is stored on the memory 902. For example, when the communication device 900 is used as the first device, when the program or instruction is executed by the processor 901, it implements each step of the foregoing method embodiment on the first device side and can achieve the same technical effect; when the communication device 900 is used as the second device, when the program or instruction is executed by the processor 901, it implements each step of the foregoing method embodiment on the second device side and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0310] The embodiments of the present application further provide a communication device, including a processor and a communication interface.

[0311] In the case where the communication device is the first device, the communication interface is used to receive first sensing information from the second device, where the first sensing information includes auxiliary information applicable to at least one AI unit, the first device has a first AI unit, and at least one AI unit applicable to the first sensing information includes the first AI unit; the processor is used to input first input information into the first AI unit to obtain an inference result output by the first AI unit, where the first input information includes the first sensing information. In the case where the communication device is used as the second device, the communication interface is used to send first sensing information to the first device, where the first sensing information includes auxiliary information applicable to at least one AI unit, and at least one AI unit applicable to the first sensing information includes the first AI unit of the first device.

[0312] This embodiment of the communication device corresponds to the foregoing method embodiments of information processing on the first device side and information transmission on the second device side. Each implementation process and implementation manner of the foregoing method embodiments can be applied to this embodiment of the communication device and can achieve the same technical effect.

[0313] In some implementation manners, Figure 10 It is a schematic diagram of the hardware structure of a terminal for implementing the embodiments of the present application.

[0314] The terminal 1000 includes, but is not limited to, at least some components such as a radio frequency unit 1001, a network module 1002, an audio output unit 1003, an input unit 1004, a sensor 1005, a display unit 1006, a user input unit 1007, an interface unit 1008, a memory 1009, and a processor 1010.

[0315] Those skilled in the art can understand that the terminal 1000 may further include a power source (such as a battery) for powering each component. The power source can be logically connected to the processor 1010 through a power management system, so as to implement functions such as management of charging, discharging, and power consumption management through the power management system. Figure 10 The terminal structure shown does not limit the terminal. The terminal may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0316] It should be understood that in the embodiments of the present application, the input unit 1004 may include a graphics processing unit (GPU) 10041 and a microphone 10042. The graphics processor 10041 processes the image data of static pictures or videos obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 1006 may include a display panel 10061, and the display panel 10061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 1007 includes at least one of a touch panel 10071 and other input devices 10072. The touch panel 10071 is also called a touch screen. The touch panel 10071 may include two parts: a touch detection device and a touch controller. The other input devices 10072 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 elaborated here.

[0317] In the embodiments of the present application, after the radio frequency unit 1001 receives downlink data from a network side device, it can be transmitted to the processor 1010 for processing; in addition, the radio frequency unit 1001 can send uplink data to the network side device. Generally, the radio frequency unit 1001 includes, but is not limited to, an antenna, an amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, etc.

[0318] The memory 1009 can be used to store software programs or instructions and various data. The memory 1009 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data. Among them, the first storage area may store an operating system, application programs or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). In addition, the memory 1009 may include volatile memory or 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 (DDR SDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM), and a direct rambus random access memory (DRRAM). The memory 1009 in the embodiments of the present application includes but is not limited to these and any other suitable types of memory.

[0319] The processor 1010 may include one or more processing units; optionally, the processor 1010 integrates an application processor and a modem processor. Among them, the application processor mainly processes operations related to the operating system, user interface, and application programs, etc., and the modem processor mainly processes wireless communication signals, such as a baseband processor. It can be understood that the above modem processor may not be integrated into the processor 1010.

[0320] In one implementation, the terminal 1000 serves as the first device.

[0321] The radio frequency unit 1001 is configured to receive first sensing information from a second device, where the first sensing information includes auxiliary information applicable to at least one AI unit, the first device has a first AI unit, and the at least one AI unit to which the first sensing information is applicable includes the first AI unit;

[0322] The processor 1010 is configured to input the first input information into the first AI unit to obtain the inference result output by the first AI unit, where the first input information includes the first sensing information.

[0323] Optionally, the first sensing information includes at least one of the following:

[0324] Wireless sensing result, wireless statistical characteristic information, geographical location information, measured values of lidar-related measurement quantities, measured values of vision-related measurement quantities, measured values of radar-related measurement quantities, measured values of inertial measurement unit-related measurement quantities.

[0325] Optionally, before receiving the first sensing information from the second device, the radio frequency unit 1001 is further configured to send a first message to the second device, where the first message is used to request the transmission of the first sensing information.

[0326] Optionally, before receiving the first sensing information from the second device, the radio frequency unit 1001 is further configured to receive a second message from the second device, where the second message is used to instruct the first device to receive the first sensing information.

[0327] Optionally, the first message or the second message includes relevant information of the first sensing information, and the relevant information of the first sensing information is used to indicate at least one of the following:

[0328] The information type of the first sensing information;

[0329] Set of AI units;

[0330] The use of the first sensing information;

[0331] The preprocessing method of the first sensing information, where the first sensing information is input to the first AI unit after being preprocessed by the preprocessing method;

[0332] The position of the first sensing information in the input information of the applicable AI unit;

[0333] The transmission method of the first sensing information;

[0334] The transmission conditions of the first sensing information;

[0335] The format of the first sensing information;

[0336] The bearer channel of the first sensing information;

[0337] The bearer resource of the first sensing information;

[0338] Among them, the set of AI units includes at least one AI unit applicable to the first perception information.

[0339] Optionally, the radio frequency unit 1001 is further configured to send third information to the second device, where the third information is used to request cancellation of sending the first perception information.

[0340] Optionally, the radio frequency unit 1001 performing the sending of the third information to the second device includes:

[0341] When the processor 1010 determines that the gain of the first inference result of the first AI unit compared to the second inference result of the second AI unit is less than or equal to the target gain, send the third information to the second device through the radio frequency unit 1001;

[0342] Among them, the input information of the second AI unit does not include perception information.

[0343] Optionally, the radio frequency unit 1001 is further configured to receive fourth information from the second device, where the fourth information is used to instruct the first device to stop receiving the first perception information.

[0344] Optionally, the fourth information includes first adjustment information, where the first adjustment information is used to instruct at least one of the following:

[0345] Enable the second AI unit of the first device, where the input information of the second AI unit does not include perception information;

[0346] Use a non-AI solution.

[0347] It can be understood that the implementation processes of the various implementation manners mentioned in this embodiment can refer to the relevant descriptions of the foregoing method embodiment on the first device side and achieve the same or corresponding technical effects. To avoid repetition, they will not be elaborated here.

[0348] In another implementation manner, the above terminal 1000 serves as the second device.

[0349] The radio frequency unit 1001 is configured to send first perception information to the first device, where the first perception information includes auxiliary information applicable to at least one AI unit, and the at least one AI unit applicable to the first perception information includes the first AI unit of the first device.

[0350] Optionally, the first perception information includes at least one of the following:

[0351] Wireless sensing results, wireless statistical characteristic information, geographical location information, measured values of lidar-related measurement quantities, measured values of vision-related measurement quantities, measured values of radar-related measurement quantities, measured values of inertial measurement unit-related measurement quantities.

[0352] Optionally, the radio frequency unit 1001 is further configured to receive first information from the first device, where the first information is used to request the second device to send the first sensing information;

[0353] The sending of the first sensing information to the first device by the radio frequency unit 1001 includes:

[0354] Sending the first sensing information to the first device according to the request of the first information.

[0355] Optionally, before the radio frequency unit 1001 executes the sending of the first sensing information to the first device, it is further configured to:

[0356] Send second information to the first device, where the second information is used to indicate the reception of the first sensing information.

[0357] Optionally, the first information or the second information includes related information of the first sensing information, and the related information of the first sensing information is used to indicate at least one of the following:

[0358] The information type of the first sensing information;

[0359] AI unit set;

[0360] The use of the first sensing information;

[0361] The preprocessing method of the first sensing information, where the first sensing information is input to the first AI unit after being preprocessed by the preprocessing method;

[0362] The position of the first sensing information in the input information of the applicable AI unit;

[0363] The transmission method of the first sensing information;

[0364] The transmission conditions of the first sensing information;

[0365] The format of the first sensing information;

[0366] The carrier channel of the first sensing information;

[0367] The carrier resource of the first sensing information;

[0368] Wherein, the AI unit set includes at least one AI unit applicable to the first sensing information.

[0369] Optionally, the radio frequency unit 1001 is further configured to:

[0370] receiving third information from the first device, where the third information is used to request the second device to cancel sending the first perception information;

[0371] Stop sending the first perception information to the first device.

[0372] Optionally, the radio frequency unit 1001 is further configured to:

[0373] Stop sending the first perception information to the first device, and send fourth information to the first device, wherein the fourth information is used to indicate to stop receiving the first perception information.

[0374] Optionally, the stopping of sending the first perception information to the first device performed by the radio frequency unit 1001 includes:

[0375] Obtain a first reasoning result of the first AI unit and a second reasoning result of the second AI unit;

[0376] When the processor 1010 determines that the gain of the first reasoning result compared to the second reasoning result is less than or equal to the target gain, the radio frequency unit 1001 stops sending the first perception information to the first device;

[0377] The input information of the second AI unit does not include perception information.

[0378] Optionally, the fourth information includes first adjustment information, wherein the first adjustment information is used to indicate at least one of the following:

[0379] enabling the second AI unit of the first device;

[0380] Use a non-AI solution.

[0381] It can be understood that the implementation process of each implementation method mentioned in this embodiment can refer to the relevant description of the aforementioned second device side method embodiment, and achieve the same or corresponding technical effect. To avoid repetition, it will not be repeated here.

[0382] The embodiment of the present application also provides a network side device, including a processor and a communication interface, the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the steps of the method embodiment of the first device side or the second device side. The network side device embodiment corresponds to the method embodiment of the first device side or the second device side, and each implementation process and implementation method of the above method embodiment can be applied to the network side device embodiment and can achieve the same technical effect.

[0383] In one embodiment, as Figure 11 shown, the network-side device 1100 includes: an antenna 1101, a radio frequency device 1102, a baseband device 1103, a processor 1104, and a memory 1105. The antenna 1101 is connected to the radio frequency device 1102. In the uplink direction, the radio frequency device 1102 receives information through the antenna 1101 and sends the received information to the baseband device 1103 for processing. In the downlink direction, the baseband device 1103 processes the information to be sent and sends it to the radio frequency device 1102. After processing the received information, the radio frequency device 1102 sends it out through the antenna 1101.

[0384] The method executed by the network-side device in the above embodiments can be implemented in the baseband device 1103, and the baseband device 1103 includes a baseband processor.

[0385] The baseband device 1103 may include, for example, at least one baseband board, and a plurality of chips are arranged on the baseband board. As Figure 11 shown, one of the chips is, for example, a baseband processor, which is connected to the memory 1105 through a bus interface to call the program in the memory 1105 and execute the operations of the network device shown in the above method embodiments.

[0386] The network-side device may further include a network interface 1106, and the interface is, for example, a Common Public Radio Interface (CPRI).

[0387] Specifically, the network-side device 1100 in the embodiments of the present application further includes: instructions or programs stored on the memory 1105 and executable on the processor 1104. The processor 1104 calls the instructions or programs in the memory 1105 to execute Figure 7 and Figure 8 the methods executed by at least one of the modules shown in

[0388] In another embodiment, the embodiments of the present application further provide a network-side device. As Figure 12 shown, the network-side device 1200 includes: a processor 1201, a network interface 1202, and a memory 1203. Among them, the network interface 1202 is, for example, a Common Public Radio Interface (CPRI).

[0389] Specifically, the network - side device 1200 in the embodiments of the present application further includes: instructions or programs stored in the memory 1203 and executable on the processor 1201. The processor 1201 calls the instructions or programs in the memory 1203 to execute the methods performed by the modules shown in FIG. 8, and achieves the same technical effects. To avoid repetition, it will not be elaborated here.

[0390] The embodiments of the present application further provide a readable storage medium. Programs or instructions are stored on the readable storage medium. When the programs or instructions are executed by a processor, each process of the foregoing information - processing method or information - transmission method embodiment is implemented, and the same technical effects can be achieved. To avoid repetition, it will not be elaborated here.

[0391] Wherein, the processor is the processor in the terminal described in the foregoing embodiments. The readable storage medium includes computer - readable storage media, such as computer read - only memory ROM, random - access memory RAM, magnetic disks, or optical discs, etc. In some examples, the readable storage medium may be a non - transient readable storage medium.

[0392] The embodiments of the present application further provide a chip. The chip includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement each process of the foregoing information - processing method or information - transmission method embodiment, and the same technical effects can be achieved. To avoid repetition, it will not be elaborated here.

[0393] It should be understood that the chip mentioned in the embodiments of the present application may also be referred to as a system - on - chip, system chip, chip system, or system - on - a - chip, etc.

[0394] The embodiments of the present application further provide a computer program / program product. The computer program / program product is stored in a storage medium. The computer program / program product is executed by at least one processor to implement each process of the foregoing information - processing method or information - transmission method embodiment, and the same technical effects can be achieved. To avoid repetition, it will not be elaborated here.

[0395] The embodiments of the present application further provide a communication system, including: a first device and a second device. The first device can be used to execute the steps of the foregoing information - processing method embodiment, and the second device can be used to execute the steps of the foregoing information - transmission method embodiment.

[0396] It should be noted that in this text, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising a..." does not exclude the existence of additional identical elements in the process, method, article or device comprising such element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments 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 a reverse order according to the functions involved. For example, the described methods may be performed in an order different from that described, and various steps may be added, omitted or combined. Additionally, the features described with reference to certain examples may be combined in other examples.

[0397] Through the description of the above embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of computer software products plus a necessary general hardware platform, and of course, can also be implemented by hardware. The computer software products are stored in a storage medium (such as ROM, RAM, magnetic disk, optical disk, etc.) and include several instructions for causing a terminal or a network-side device to execute the methods described in the various embodiments of the present application.

[0398] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms of embodiments without departing from the purpose of the present application and the scope protected by the claims. These embodiments are all within the protection scope of the present application.

Claims

1. An information processing method, characterized in that, Including: The first device receives first sensing information from the second device, where the first sensing information includes auxiliary information applicable to at least one AI unit, the first device has a first AI unit, and the at least one AI unit to which the first sensing information is applicable includes the first AI unit; The first device inputs first input information into the first AI unit to obtain an inference result output by the first AI unit, where the first input information includes the first sensing information.

2. The method according to claim 1, wherein The first sensing information includes at least one of the following: Wireless sensing results, wireless statistical characteristic information, geographical location information, measured values of lidar-related measurement quantities, measured values of vision-related measurement quantities, measured values of radar-related measurement quantities, measured values of inertial measurement unit-related measurement quantities.

3. The method according to claim 1 or 2, characterized in that, Before the first device receives the first sensing information from the second device, the method further includes: The first device sends first information to the second device, where the first information is used to request sending the first sensing information.

4. The method according to claim 1 or 2, characterized in that, Before the first device receives the first sensing information from the second device, the method further includes: The first device receives second information from the second device, where the second information is used to instruct the first device to receive the first sensing information.

5. The method according to claim 3 or 4, characterized in that, The first information or the second information includes relevant information of the first sensing information, and the relevant information of the first sensing information is used to indicate at least one of the following: The information type of the first sensing information; The set of AI units; The use of the first sensing information; The preprocessing method of the first sensing information, where the first sensing information is input into the first AI unit after being preprocessed by the preprocessing method; The position of the first sensing information in the input information of the applicable AI unit; The transmission method of the first sensing information; The transmission conditions of the first sensing information; The format of the first sensing information; The bearer channel of the first sensing information; The bearer resources of the first sensing information; Wherein, the set of AI units includes at least one AI unit to which the first sensing information is applicable.

6. The method according to any one of claims 1 to 5, characterized in that The method further includes: The first device sends third information to the second device, and the third information is used to request canceling the sending of the first sensing information.

7. The method according to claim 6, wherein The first device sending third information to the second device includes: When the first device determines that the gain of the first inference result of the first AI unit compared to the second inference result of the second AI unit is less than or equal to the target gain, the first device sends third information to the second device; Wherein, the input information of the second AI unit does not include sensing information.

8. The method according to any one of claims 1 to 5, characterized in that, The method further includes: The first device receives fourth information from the second device, where the fourth information is used to instruct the first device to stop receiving the first sensing information.

9. The method according to claim 8, wherein The fourth information includes first adjustment information, where the first adjustment information is used to indicate at least one of the following: Enable the second AI unit of the first device, where the input information of the second AI unit does not include sensing information; Use a non-AI solution.

10. An information transmission method, characterized in that, Including: The second device sends first perception information to the first device, where the first perception information includes auxiliary information applicable to at least one AI unit, and the at least one AI unit to which the first perception information is applicable includes the first AI unit possessed by the first device.

11. The method according to claim 10, characterized in that, The first perception information includes at least one of the following: Wireless perception result, wireless statistical characteristic information, geographical location information, measured value of lidar-related measurement quantity, measured value of vision-related measurement quantity, measured value of radar-related measurement quantity, measured value of inertial measurement unit-related measurement quantity.

12. The method according to claim 10 or 11, characterized in that, The method further includes: The second device receives first information from the first device, where the first information is used to request the second device to send the first perception information; The second device sending the first perception information to the first device includes: The second device sends the first perception information to the first device according to the request of the first information.

13. The method according to claim 10 or 11, characterized in that, Before the second device sends the first perception information to the first device, the method further includes: The second device sends second information to the first device, where the second information is used to indicate receiving the first perception information.

14. The method according to claim 12 or 13, characterized in that, The first information or the second information includes relevant information of the first perception information, and the relevant information of the first perception information is used to indicate at least one of the following: The information type of the first perception information; AI unit set; The use of the first perception information; The preprocessing method of the first perception information, where the first perception information is input to the first AI unit after being preprocessed by the preprocessing method; The position of the first perception information in the input information of the applicable AI unit; The transmission method of the first perception information; The transmission condition of the first perception information; The format of the first perception information; The bearing channel of the first perception information; The bearing resource of the first perception information; Wherein, the AI unit set includes at least one AI unit to which the first perception information is applicable.

15. The method according to any one of claims 10 to 14, characterized in that, The method further includes: The second device receives third information from the first device, and the third information is used to request the second device to cancel sending the first perception information; The second device stops sending the first perception information to the first device.

16. The method according to any one of claims 10 to 14, characterized in that, The method further includes: The second device stops sending the first perception information to the first device and sends fourth information to the first device, where the fourth information is used to indicate stopping receiving the first perception information.

17. The method according to claim 16, characterized in that, The second device stopping sending the first perception information to the first device includes: The second device obtains the first inference result of the first AI unit and the second inference result of the second AI unit; The second device stops sending the first perception information to the first device when determining that the gain of the first inference result compared to the second inference result is less than or equal to the target gain; Wherein, the input information of the second AI unit does not include perception information.

18. The method according to claim 17, wherein The fourth information includes first adjustment information, where the first adjustment information is used to indicate at least one of the following: Enable the second AI unit of the first device; Use a non-AI solution.

19. An information processing apparatus, characterized in that, For a first device, the apparatus includes: A first receiving module, configured to receive first sensing information from a second device, where the first sensing information includes auxiliary information applicable to at least one AI unit, the first device has a first AI unit, and the at least one AI unit to which the first sensing information is applicable includes the first AI unit; A processing module, configured to input first input information into the first AI unit to obtain an inference result output by the first AI unit, where the first input information includes the first sensing information.

20. The device according to claim 19, wherein, The first sensing information includes at least one of the following: Wireless sensing results, wireless statistical characteristic information, geographical location information, measured values of lidar-related measurement quantities, measured values of vision-related measurement quantities, measured values of radar-related measurement quantities, measured values of inertial measurement unit-related measurement quantities.

21. The device according to claim 19 or 20, characterized in that, The apparatus further includes: A first sending module, configured to send first information to the second device, where the first information is used to request sending the first sensing information.

22. The device according to claim 19 or 20, characterized in that, The apparatus further includes: A second receiving module, configured to receive second information from the second device, where the second information is used to instruct the first device to receive the first sensing information.

23. The device according to claim 21 or 22, characterized in that, The first information or the second information includes related information of the first sensing information, and the related information of the first sensing information is used to indicate at least one of the following: The information type of the first sensing information; A set of AI units; The use of the first sensing information; The preprocessing method of the first sensing information, where the first sensing information is input into the first AI unit after being preprocessed by the preprocessing method; The position of the first sensing information in the input information of the applicable AI unit; The transmission method of the first sensing information; The transmission condition of the first sensing information; The format of the first sensing information; The carrier channel of the first sensing information; The carrier resource of the first sensing information; Wherein, the set of AI units includes at least one AI unit to which the first sensing information is applicable.

24. The device according to any one of claims 19 to 23, characterized in that, The apparatus further includes: A second sending module, configured to send third information to the second device, where the third information is used to request canceling the sending of the first sensing information.

25. The device according to claim 24, characterized in that, The second sending module is specifically configured to: Send the third information to the second device when the processing module determines that the gain of the first inference result of the first AI unit compared to the second inference result of the second AI unit is less than or equal to a target gain; Wherein, the input information of the second AI unit does not include sensing information.

26. The device according to any one of claims 19 to 23, characterized in that The apparatus further includes: A third receiving module, configured to receive fourth information from the second device, where the fourth information is used to instruct the first device to stop receiving the first sensing information.

27. The device according to claim 26, characterized in that, The fourth information includes first adjustment information, where the first adjustment information is used to indicate at least one of the following: Enable the second AI unit of the first device, where the input information of the second AI unit does not include sensing information; Use a non-AI solution.

28. An information transmission device, characterized in that, For a second device, the apparatus includes: A third sending module, configured to send first sensing information to a first device, where the first sensing information includes auxiliary information applicable to at least one AI unit, and the at least one AI unit to which the first sensing information is applicable includes a first AI unit that the first device has.

29. The device according to claim 28, characterized in that, The first sensing information includes at least one of the following: Wireless sensing results, wireless statistical characteristic information, geographical location information, measured values of lidar-related measurement quantities, measured values of vision-related measurement quantities, measured values of radar-related measurement quantities, measured values of inertial measurement unit-related measurement quantities.

30. The device according to claim 28 or 29, characterized in that, The apparatus further includes: A fourth receiving module, configured to receive first information from the first device, where the first information is used to request the second device to send the first sensing information; The third sending module is specifically configured to: Send the first sensing information to the first device according to the request of the first information.

31. The device according to claim 28 or 29, characterized in that, The apparatus further includes: A fourth sending module, configured to send second information to the first device, where the second information is used to indicate receiving the first sensing information.

32. The device according to claim 30 or 31, characterized in that, The first information or the second information includes related information of the first sensing information, and the related information of the first sensing information is used to indicate at least one of the following: The information type of the first sensing information; A set of AI units; The use of the first sensing information; The preprocessing method of the first sensing information, where the first sensing information is input to the first AI unit after being preprocessed by the preprocessing method; The position of the first sensing information in the input information of the applicable AI unit; The transmission method of the first sensing information; The transmission condition of the first sensing information; The format of the first sensing information; The carrier channel of the first sensing information; The carrier resource of the first sensing information; Wherein, the set of AI units includes at least one AI unit to which the first sensing information is applicable.

33. The device according to any one of claims 28 to 32, characterized in that, The apparatus further includes: A fifth receiving module, configured to receive third information from the first device, where the third information is used to request the second device to cancel sending the first sensing information; A first control module, configured to control the third sending module to stop sending the first sensing information to the first device.

34. The device according to any one of claims 28 to 32, characterized in that, The apparatus further includes: A second control module, configured to control the third sending module to stop sending the first sensing information to the first device and send fourth information to the first device, where the fourth information is used to indicate stopping receiving the first sensing information.

35. The device according to claim 34, characterized in that, The second control module includes: An obtaining unit, configured to obtain a first inference result of the first AI unit and a second inference result of a second AI unit; A control unit, configured to control the third sending module to stop sending the first sensing information to the first device when it is determined that the gain of the first inference result compared with the second inference result is less than or equal to a target gain; Wherein, the input information of the second AI unit does not include sensing information.

36. The device according to claim 35, characterized in that, The fourth information includes first adjustment information, where the first adjustment information is used to indicate at least one of the following: Enable the second AI unit of the first device; Use a non-AI solution.

37. A communication device, characterized in that, It includes a processor and a memory. The memory stores programs or instructions that can run on the processor. When the programs or instructions are executed by the processor, the steps of the information processing method described in any one of claims 1 to 9 are implemented, or the steps of the information transmission method described in any one of claims 10 to 18 are implemented.

38. A readable storage medium, characterized in that, Programs or instructions are stored on the readable storage medium. When the programs or instructions are executed by a processor, the steps of the information processing method described in any one of claims 1 to 9 are implemented, or the steps of the information transmission method described in any one of claims 10 to 18 are implemented.

Images