Data processing method and apparatus

Abstract

Disclosed in the embodiments of the present application are a data processing method and apparatus. The method comprises: determining configuration information, wherein the configuration information is used for indicating type information of priori knowledge, and the priori knowledge is obtained data or data obtained after the obtained data is processed; receiving data of the priori knowledge sent by a network device, wherein the data of the priori knowledge corresponds to the type information; and processing local data on the basis of the data of the priori knowledge. By configuring various type information of priori knowledge, a network device sends, to a terminal device, data of the priori knowledge corresponding to the type information, such that the terminal device can filter or compress data in different application scenarios or of different data types, thereby effectively reducing the data transmission volume and improving the data transmission efficiency.

Description

Data processing method and device

[0001] The present application claims priority to the Chinese patent application No. 202410905239.7, filed on July 5, 2024, with the State Intellectual Property Office of China, and entitled "Data processing method and device", the whole content of which is incorporated herein by reference. TECHNICAL FIELD

[0002] The present application relates to the field of communication technology, and in particular to a data processing method and device. BACKGROUND

[0003] In a 6-Generation (6G) native data transmission scenario, for example, artificial intelligence (AI), perception data, etc., a network device can send prior knowledge (knowledge) information to a terminal device, and the terminal device processes (for example, data filtering) the transmission data based on the knowledge.

[0004] However, since the knowledge information sent by the network device is relatively fixed at present, the terminal device may not be able to process some data based on the knowledge information, and thus cannot reduce the data transmission amount. SUMMARY

[0005] Embodiments of the present application provide a data processing method and device. The terminal device can filter or compress process data in different application scenarios or different data types, effectively reducing the data transmission amount and improving the data transmission efficiency.

[0006] In a first aspect, embodiments of the present application provide a communication method, which can be executed by a receiving end device. In the absence of special description, the "receiving end device" in the present application can refer to the receiving end device itself (for example, a network device, a terminal device), a component (for example, a processor, a chip, or a chip system, etc.) in the receiving end device, or a logic module or software capable of realizing all or part of the functions of the receiving end device. Taking the case that the method is applied to a terminal device, the method comprises:

[0007] determining configuration information, the configuration information being used to indicate type information of prior knowledge, wherein the prior knowledge is obtained data or data processed based on the obtained data; receiving data of the prior knowledge sent by a network device, the data of the prior knowledge corresponding to the type information; and processing local data based on the data of the prior knowledge.

[0008] By configuring various types of information of priori knowledge, the network device sends data of priori knowledge corresponding to the type information to the terminal device, so that the terminal device can filter or compress data of different application scenarios or different data types, effectively reducing the data transmission amount and improving the data transmission efficiency.

[0009] In a possible design, the type information includes a priori knowledge type and / or a data form. By sending data of priori knowledge corresponding to the priori knowledge type and / or the data form to the terminal device, the terminal device can filter or compress data of different application scenarios or different data types, effectively reducing the data transmission amount and improving the data transmission efficiency.

[0010] In a possible design, the type information corresponds to an application scenario, and the application scenario includes at least one of the following: channel data transmission, artificial intelligence (AI) data transmission, or perception data transmission. By configuring type information in different application scenarios, the terminal device can filter or compress data in different application scenarios, effectively reducing the data transmission amount and improving the data transmission efficiency.

[0011] In a possible design, the type information corresponds to a data type of the local data, and the data type includes at least one of the following: AI data, perception data, or channel data. By configuring type information of priori knowledge corresponding to different data types, the terminal device can filter or compress data of different data types, effectively reducing the data transmission amount and improving the data transmission efficiency.

[0012] In a possible design, the type information includes first-order type information and second-order type information, and the second-order type information is a sub-type of the first-order type information. By configuring multi-order type information, the terminal device can use more or more refined priori knowledge data to process the local data, improving the accuracy of data processing.

[0013] In a possible design, the type of prior knowledge corresponding to the perception data includes at least one of the following: a dictionary, geometry, region division, or semantics, where the sub-type of the dictionary includes a multi-dimensional weighting and a single-dimensional dictionary, the data form of the multi-dimensional weighting includes a dictionary dimension, dictionary data, and sparsity; the sub-type of the geometry includes a surface, and the data form of the surface includes a surface parameter and a scanned region on the surface; the sub-type of the region division includes an octree and a voxel, the data form of the octree includes octree data, and the data form of the voxel includes voxel data; and the sub-type of the semantics includes a 3D target box, and the data form of the 3D target box includes a center position and a range of the 3D target box and / or vertex coordinates of the 3D target box. By configuring the type information of the prior knowledge corresponding to the perception data, the terminal device can process the perception data by using different type information corresponding to the prior knowledge, thereby effectively reducing the transmission amount of the perception data and improving the data transmission efficiency.

[0014] In a possible design, the type of prior knowledge corresponding to the channel data includes at least one of the following: a dictionary or region division, where the sub-type of the dictionary includes a multi-dimensional weighting and a single-dimensional dictionary, the data form of the multi-dimensional weighting includes a dictionary dimension, dictionary data, and sparsity; and the sub-type of the region division includes a bitmap and a quadtree, the data form of the bitmap includes bitmap data, and the data form of the quadtree includes quadtree data. By configuring the type information of the prior knowledge corresponding to the channel data, the terminal device can process the channel data by using different type information corresponding to the prior knowledge, thereby effectively reducing the transmission amount of the channel data and improving the data transmission efficiency.

[0015] In a possible design, the type of prior knowledge corresponding to the AI data includes a dictionary and a pre-trained model, where the sub-type of the dictionary includes a multi-dimensional weighting and a single-dimensional dictionary, the data form of the multi-dimensional weighting includes a dictionary dimension, dictionary data, and sparsity; and the data form of the pre-trained model includes model parameters. By configuring the type information of the prior knowledge corresponding to the AI data, the terminal device can process the AI data by using different type information corresponding to the prior knowledge, thereby effectively reducing the transmission amount of the AI data and improving the data transmission efficiency.

[0016] In a possible design, the network device sends indication information, or the terminal device sends indication information to the network device, where the indication information is used to indicate the type information. The type information of the priori knowledge is determined by sending or receiving the indication information, so that the network device sends data of the priori knowledge corresponding to the type information, and the terminal device can filter or compress local data based on the data of the priori knowledge, thereby effectively reducing data transmission amount and improving data transmission efficiency.

[0017] In a possible design, the indication information includes an application scenario or a data type, or the indication information includes a first index used to indicate at least one type information in a preconfigured priori knowledge type mapping table, where the priori knowledge type mapping table includes a mapping relationship between multiple type information and indexes.

[0018] In a possible design, the terminal device sends first indication information to the network device, where the first indication information is used to indicate at least one type information of the priori knowledge supported by the terminal device; and the terminal device receives second indication information sent by the network device, where the second indication information is used to indicate type information selected from the at least one type information. That is, the network device and the terminal device determine the type information of the priori knowledge that can meet the capability requirement of the terminal device in a negotiation manner.

[0019] In a possible design, the terminal device sends third indication information to the network device, where the third indication information is used to indicate type information of the priori knowledge required by the terminal device; and the terminal device receives fourth indication information sent by the network device, where the fourth indication information is used to indicate whether there is data of the priori knowledge corresponding to the type information. That is, the network device and the terminal device determine the type information of the priori knowledge required by the terminal device in a negotiation manner.

[0020] In a possible design, the terminal device receives fifth indication information sent by the network device, where the fifth indication information is used to indicate at least one type information of the priori knowledge supported by the network device; and the terminal device sends sixth indication information to the network device, where the sixth indication information is used to indicate type information selected from the at least one type information. That is, the network device and the terminal device determine the type information of the priori knowledge that can be supported by the network device in a negotiation manner.

[0021] In a possible design, the terminal device receives seventh indication information sent by the network device, where the seventh indication information is used to indicate type information of the priori knowledge; and the terminal device sends eighth indication information to the network device, where the eighth indication information is used to indicate whether to support processing data of the priori knowledge corresponding to the type information. That is, the network device and the terminal device determine the type information of the priori knowledge that can be supported by the terminal device in a negotiation manner.

[0022] In a possible design, the type information is updated according to a preset period. By periodically updating the type information, the integrity and real-time performance of the type information are guaranteed, and the terminal device can more accurately process the local data and reduce the data transmission amount.

[0023] In a possible design, the type information is updated when a trigger condition is met, and the trigger condition includes at least one of the following: a change in an application scenario, a change in the data of the priori knowledge, or a change in the local data. By periodically updating the type information, the integrity and real-time performance of the type information are guaranteed, and the terminal device can more accurately process the local data and reduce the data transmission amount.

[0024] In a second aspect, an embodiment of the present application provides a communication method, which can be executed by a sending terminal device. In the case where no special description is made, the "sending terminal device" in the present application can refer to the sending terminal device itself (for example, a network device or a terminal device), a component (for example, a processor, a chip, or a chip system) in the sending terminal device, or a logic module or software capable of realizing all or part of the functions of the sending terminal device. Taking the case where the method is applied to a network device as an example, the method includes the following steps.

[0025] determining configuration information, the configuration information being used to indicate type information of priori knowledge, the priori knowledge being obtained data or data processed from the obtained data; and sending, to a terminal device, data of the priori knowledge, the data of the priori knowledge corresponding to the type information, and the data of the priori knowledge being used to process local data of the terminal device.

[0026] By configuring multiple types of the priori knowledge, the network device sends the data of the priori knowledge corresponding to the type information to the terminal device, so that the terminal device can filter or compress data in different application scenarios or of different data types, effectively reducing the data transmission amount and improving the data transmission efficiency.

[0027] In a possible design, the type information includes a priori knowledge type and / or a data form. By sending the data of the priori knowledge corresponding to the priori knowledge type and / or the data form to the terminal device, the terminal device can filter or compress data in different application scenarios or of different data types, effectively reducing the data transmission amount and improving the data transmission efficiency.

[0028] In a possible design, the type information corresponds to an application scenario, and the application scenario includes at least one of the following: channel data transmission, artificial intelligence (AI) data transmission, or perception data transmission. By configuring the type information in different application scenarios, the terminal device can filter or compress data in different application scenarios, effectively reducing data transmission volume and improving data transmission efficiency.

[0029] In a possible design, the type information corresponds to a data type of the local data, and the data type includes at least one of the following: AI data, perception data, or channel data. By configuring type information of prior knowledge corresponding to different data types, the terminal device can filter or compress data of different data types, effectively reducing data transmission volume and improving data transmission efficiency.

[0030] In a possible design, the type information includes first-order type information and second-order type information, and the second-order type information is a sub-type of the first-order type information. By configuring multi-order type information, the terminal device can use more or more refined prior knowledge data to process the local data, improving data processing accuracy.

[0031] In a possible design, the type information corresponding to the perception data includes at least one of the following: a dictionary, geometry, region division, or semantics, where the sub-type corresponding to the dictionary includes a multi-dimensional weighting and a single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting includes a dictionary dimension, dictionary data, and sparsity; the sub-type corresponding to the geometry includes a surface, and the data form corresponding to the surface includes a surface parameter and a scanned region on the surface; the sub-type corresponding to the region division includes an octree and a voxel, the data form corresponding to the octree includes octree data, and the data form corresponding to the voxel includes voxel data; and the sub-type corresponding to the semantics includes a 3D target box, and the data form corresponding to the 3D target box includes a center position and a range of the 3D target box, and / or vertex coordinates of the 3D target box. By configuring type information of prior knowledge corresponding to the perception data, the terminal device can use different type information corresponding to prior knowledge data to process the perception data, thereby effectively reducing perception data transmission volume and improving data transmission efficiency.

[0032] In a possible design, the type of the priori knowledge corresponding to the channel data includes at least one of the following: a dictionary or a region division, where the sub-type of the dictionary includes a multi-dimensional weighting and a single-dimensional dictionary, and the data form of the multi-dimensional weighting includes a dictionary dimension, dictionary data and sparsity; and the sub-type of the region division includes a bitmap and a quadtree, the data form of the bitmap includes bitmap data, and the data form of the quadtree includes quadtree data. By configuring the type information of the priori knowledge corresponding to the channel data, the terminal device can process the channel data by using the data of the priori knowledge corresponding to different type information, thereby effectively reducing the transmission amount of the channel data and improving the data transmission efficiency.

[0033] In a possible design, the type of the priori knowledge corresponding to the AI data includes a dictionary and a pre-trained model, where the sub-type of the dictionary includes a multi-dimensional weighting and a single-dimensional dictionary, and the data form of the multi-dimensional weighting includes a dictionary dimension, dictionary data and sparsity; and the data form of the pre-trained model includes model parameters. By configuring the type information of the priori knowledge corresponding to the AI data, the terminal device can process the AI data by using the data of the priori knowledge corresponding to different type information, thereby effectively reducing the transmission amount of the AI data and improving the data transmission efficiency.

[0034] In a possible design, the terminal device sends indication information, or the network device sends indication information to the terminal device, where the indication information is used to indicate the type information. By sending or receiving the indication information, the type information of the priori knowledge is determined, so that the network device sends the data of the priori knowledge corresponding to the type information, and the terminal device can filter or compress local data based on the data of the priori knowledge, thereby effectively reducing the data transmission amount and improving the data transmission efficiency.

[0035] In a possible design, the indication information includes an application scenario or a data type, or the indication information includes a first index, where the first index is used to indicate at least one type information in a preconfigured priori knowledge type mapping table, and the priori knowledge type mapping table includes a mapping relationship between multiple type information and indexes.

[0036] In a possible design, the terminal device sends first indication information, where the first indication information is used to indicate at least one type information of the priori knowledge supported by the terminal device; and the network device sends second indication information to the terminal device, where the second indication information is used to indicate type information selected from the at least one type information. That is, the network device and the terminal device determine the type information of the priori knowledge that can meet the capability requirement of the terminal device in a negotiation manner.

[0037] In a possible design, the third indication information sent by the terminal device is received, where the third indication information is used to indicate type information of the prior knowledge required by the terminal device; and the fourth indication information is sent to the terminal device, where the fourth indication information is used to indicate whether there is data of the prior knowledge corresponding to the type information. That is, the network device and the terminal device determine the type information of the prior knowledge required by the terminal device in a negotiation manner.

[0038] In a possible design, the fifth indication information is sent to the terminal device, where the fifth indication information is used to indicate at least one type information of the prior knowledge supported by the network device to provide; and the sixth indication information sent by the terminal device is received, where the sixth indication information is used to indicate type information selected from the at least one type information. That is, the network device and the terminal device determine the type information of the prior knowledge supported by the network device to provide in a negotiation manner.

[0039] In a possible design, the seventh indication information is sent to the terminal device, where the seventh indication information is used to indicate type information of the prior knowledge; and the eighth indication information sent by the terminal device is received, where the eighth indication information is used to indicate whether to support processing data of the prior knowledge corresponding to the type information. That is, the network device and the terminal device determine the type information of the prior knowledge supported by the terminal device to process in a negotiation manner.

[0040] In a possible design, the type information is updated according to a preset period. By periodically updating the type information, the integrity and real-time performance of the type information are guaranteed, so that the terminal device can more accurately process the local data, and the data transmission amount is reduced.

[0041] In a possible design, the type information is updated when a trigger condition is met, and the trigger condition includes at least one of the following: an application scenario, data of the prior knowledge, or the local data. By periodically updating the type information, the integrity and real-time performance of the type information are guaranteed, so that the terminal device can more accurately process the local data, and the data transmission amount is reduced.

[0042] In a third aspect, an embodiment of the present application provides a data processing apparatus, which has the functions of the first aspect. For example, the data processing apparatus includes a module or unit or means corresponding to the operations of the first aspect. The module or unit or means can be implemented by software, or by hardware, or by a combination of software and hardware. The apparatus includes:

[0043] The processing module is configured to determine configuration information, wherein the configuration information is used to indicate type information of prior knowledge, and the prior knowledge is obtained data or data processed based on the obtained data.

[0044] The receiving module is configured to receive data of the prior knowledge sent by the network device, wherein the data of the prior knowledge corresponds to the type information.

[0045] The processing module is further configured to process local data based on the data of the prior knowledge.

[0046] In a possible design, the type information includes a prior knowledge type and / or a data form.

[0047] In a possible design, the type information corresponds to an application scenario, and the application scenario includes at least one of the following: channel data transmission, artificial intelligence (AI) data transmission, or perception data transmission.

[0048] In a possible design, the type information corresponds to a data type of the local data, and the data type includes at least one of the following: AI data, perception data, or channel data.

[0049] In a possible design, the type information includes first-order type information and second-order type information, and the second-order type information is a sub-type of the first-order type information.

[0050] In a possible design, the prior knowledge type corresponding to the perception data includes at least one of the following: a dictionary, geometry, region division, or semantics, wherein the sub-type corresponding to the dictionary includes a multi-dimensional weighting and a single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting includes a dictionary dimension, dictionary data, and sparsity; the sub-type corresponding to the geometry includes a surface, and the data form corresponding to the surface includes a surface parameter and a scanned region on the surface; the sub-type corresponding to the region division includes an octree and a voxel, the data form corresponding to the octree includes octree data, and the data form corresponding to the voxel includes voxel data; and the sub-type corresponding to the semantics includes a 3D target box, and the data form corresponding to the 3D target box includes a center position and a range of the 3D target box, and / or vertex coordinates of the 3D target box.

[0051] In a possible design, the prior knowledge type corresponding to the channel data includes at least one of the following: a dictionary or region division, wherein the sub-type corresponding to the dictionary includes a multi-dimensional weighting and a single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting includes a dictionary dimension, dictionary data, and sparsity; and the sub-type corresponding to the region division includes a bitmap and a quadtree, the data form corresponding to the bitmap includes bitmap data, and the data form corresponding to the quadtree includes quadtree data.

[0052] In a possible design, the type of priori knowledge corresponding to the AI data includes a dictionary and a pre-trained model, where a sub-type corresponding to the dictionary includes a multi-dimensional weighting and a single-dimensional dictionary, a data form corresponding to the multi-dimensional weighting includes a dictionary dimension, dictionary data, and sparsity, and a data form corresponding to the pre-trained model includes a model parameter.

[0053] In a possible design, the receiving module is further configured to receive indication information sent by the network device, or the sending module is configured to send indication information to the network device, where the indication information is used to indicate the type information.

[0054] In a possible design, the indication information includes an application scenario or a data type, or the indication information includes a first index, where the first index is used to indicate at least one type of information in a preconfigured priori knowledge type mapping table, and the priori knowledge type mapping table includes a mapping relationship between a plurality of types of information and indexes.

[0055] In a possible design, the sending module is configured to send first indication information to the network device, where the first indication information is used to indicate at least one type of information of the priori knowledge supported by the network device.

[0056] The receiving module is configured to receive second indication information sent by the network device, where the second indication information is used to indicate a type of information selected from the at least one type of information.

[0057] In a possible design, the sending module is configured to send third indication information to the network device, where the third indication information is used to indicate a type of information of the priori knowledge required by the network device.

[0058] The receiving module is configured to receive fourth indication information sent by the network device, where the fourth indication information is used to indicate whether there is data of the priori knowledge corresponding to the type of information.

[0059] In a possible design, the receiving module is configured to receive fifth indication information sent by the network device, where the fifth indication information is used to indicate at least one type of information of the priori knowledge supported by the network device for providing.

[0060] The sending module is configured to send sixth indication information to the network device, where the sixth indication information is used to indicate a type of information selected from the at least one type of information.

[0061] In a possible design, the receiving module is configured to receive seventh indication information sent by the network device, where the seventh indication information is used to indicate a type of information of the priori knowledge.

[0062] The sending module is configured to send eighth indication information to the network device, where the eighth indication information is used to indicate whether the data of the prior knowledge corresponding to the type information is supported.

[0063] In a possible design, the processing module is further configured to update the type information according to a preset period.

[0064] In a possible design, the processing module is further configured to update the type information when a trigger condition is met, where the trigger condition includes at least one of the following: a change in an application scenario, a change in the data of the prior knowledge, or a change in the local data.

[0065] The operations and beneficial effects of the data processing apparatus can refer to the operations and beneficial effects of the method in the first aspect, and details are not repeated.

[0066] In a fourth aspect, an embodiment of the present application provides a data processing apparatus, which has the functions of the second aspect, for example, the data processing apparatus includes a module or unit or means corresponding to the operations of the second aspect, which can be implemented by software, or by hardware, or by a combination of software and hardware. The apparatus includes:

[0067] The processing module is configured to determine configuration information, where the configuration information is used to indicate type information of prior knowledge, and the prior knowledge is obtained data or data processed from the obtained data.

[0068] The sending module is configured to send the data of the prior knowledge to a terminal device, where the data of the prior knowledge corresponds to the type information, and the data of the prior knowledge is used to process local data of the terminal device.

[0069] In a possible design, the type information includes a prior knowledge type and / or a data form.

[0070] In a possible design, the type information corresponds to an application scenario, and the application scenario includes at least one of the following: channel data transmission, artificial intelligence (AI) data transmission, or perception data transmission.

[0071] In a possible design, the type information corresponds to a data type of the local data, and the data type includes at least one of the following: AI data, perception data, or channel data.

[0072] In a possible design, the type information includes first-order type information and second-order type information, and the second-order type information is a sub-type of the first-order type information.

[0073] In a possible design, the priori knowledge type corresponding to the perception data includes at least one of the following: a dictionary, geometry, region division, or semantics, where the sub-type corresponding to the dictionary includes a multi-dimensional weighting and a single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting includes a dictionary dimension, dictionary data, and sparsity; the sub-type corresponding to the geometry includes a plane, and the data form corresponding to the plane includes a plane parameter and a scanned region on the plane; the sub-type corresponding to the region division includes an octree and a voxel, the data form corresponding to the octree includes octree data, and the data form corresponding to the voxel includes voxel data; and the sub-type corresponding to the semantics includes a 3D target box, and the data form corresponding to the 3D target box includes a center position and a range of the 3D target box and / or vertex coordinates of the 3D target box.

[0074] In a possible design, the priori knowledge type corresponding to the channel data includes at least one of the following: a dictionary or region division, where the sub-type corresponding to the dictionary includes a multi-dimensional weighting and a single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting includes a dictionary dimension, dictionary data, and sparsity; and the sub-type corresponding to the region division includes a bitmap and a quadtree, the data form corresponding to the bitmap includes bitmap data, and the data form corresponding to the quadtree includes quadtree data.

[0075] In a possible design, the priori knowledge type corresponding to the AI data includes a dictionary and a pre-trained model, where the sub-type corresponding to the dictionary includes a multi-dimensional weighting and a single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting includes a dictionary dimension, dictionary data, and sparsity; and the data form corresponding to the pre-trained model includes model parameters.

[0076] In a possible design, a receiving module is configured to receive indication information sent by the terminal device, or a sending module is configured to send indication information to the terminal device, where the indication information is used to indicate the type information.

[0077] In a possible design, the indication information includes an application scenario or a data type, or the indication information includes a first index, where the first index is used to indicate at least one type information in a preconfigured priori knowledge type mapping table, and the priori knowledge type mapping table includes a mapping relationship between a plurality of type information and indexes.

[0078] In a possible design, a receiving module is configured to receive first indication information sent by the terminal device, where the first indication information is used to indicate at least one type information of the priori knowledge supported by the terminal device.

[0079] A sending module is configured to send second indication information to the terminal device, where the second indication information is used to indicate type information selected from the at least one type information.

[0080] In a possible design, the receiving module is configured to receive third indication information sent by the terminal device, where the third indication information is used to indicate type information of the prior knowledge required by the terminal device.

[0081] The sending module is configured to send fourth indication information to the terminal device, where the fourth indication information is used to indicate whether there is data of the prior knowledge corresponding to the type information.

[0082] In a possible design, the sending module is configured to send fifth indication information to the terminal device, where the fifth indication information is used to indicate at least one type information of the prior knowledge supported by the network device to provide.

[0083] The receiving module is configured to receive sixth indication information sent by the terminal device, where the sixth indication information is used to indicate type information selected from the at least one type information.

[0084] In a possible design, the sending module is configured to send seventh indication information to the terminal device, where the seventh indication information is used to indicate type information of the prior knowledge.

[0085] The receiving module is configured to receive eighth indication information sent by the terminal device, where the eighth indication information is used to indicate whether to support processing data of the prior knowledge corresponding to the type information.

[0086] In a possible design, the processing module is further configured to update the type information according to a preset period.

[0087] In a possible design, the processing module is further configured to update the type information when a trigger condition is met, where the trigger condition includes at least one of the following changing: an application scenario, data of the prior knowledge, or the local data.

[0088] The operations and beneficial effects of the data processing apparatus can refer to the operations and beneficial effects of the method in the second aspect and will not be repeated here.

[0089] In a fifth aspect, an embodiment of the present application provides a data processing apparatus, which comprises a memory and one or more processors. The memory is configured to store part or all of necessary computer programs or instructions for implementing the functions related to the first aspect. The one or more processors are configured to execute the computer programs or instructions, so that the data processing apparatus implements the method in any possible design or implementation manner of the first aspect.

[0090] In one possible design, the data processing device may further include an interface circuit, wherein the processor is used to communicate with other devices or components through the interface circuit.

[0091] In one possible design, the data processing device may also include the memory.

[0092] The aforementioned data processing device may be a terminal device, or a communication module in a terminal device, or a chip in a terminal device that is responsible for communication functions, such as a modem chip (also known as a baseband chip) or a SoC or SIP chip containing a modem module.

[0093] Sixthly, embodiments of this application provide a data processing apparatus, which includes a memory and one or more processors. The memory is used to store part or all of the computer program or instructions necessary to implement the functions involved in the second aspect above. The one or more processors are capable of executing the computer program or instructions, which, when executed, cause the data processing apparatus to implement the methods in any possible design or implementation of the second aspect above.

[0094] In one possible design, the data processing device may further include an interface circuit, wherein the processor is used to communicate with other devices or components through the interface circuit.

[0095] In one possible design, the data processing device may also include the memory.

[0096] The aforementioned data processing device may be a network device, a communication module in a network device, or a chip in a network device that is responsible for communication functions, such as a modem chip (also known as a baseband chip) or a SoC or SIP chip containing a modem module.

[0097] In a seventh aspect, this application provides a computer-readable storage medium for storing a computer program that, when executed, causes the method described in either the first or second aspect to be implemented.

[0098] Eighthly, this application provides a computer program product including a computer program that, when executed, causes the method described in either the first or second aspect to be implemented.

[0099] Ninthly, embodiments of this application provide a communication system including at least one terminal device and at least one network device, wherein the terminal device is used to perform the steps in the first aspect described above, and the network device is used to perform the steps in the second aspect described above.

[0100] In a tenth aspect, a chip is provided, which includes a processor and a communication interface configured to communicate with an external device or an internal device, and the processor is configured to implement the method in the above aspects.

[0101] In a possible design, the chip can further include a memory in which a computer program or instructions are stored, and the processor is configured to execute the computer program or instructions stored in the memory or other programs or instructions. When the computer program or instructions are executed, the processor is configured to implement the method in the above aspects.

[0102] In a possible design, the chip can be integrated in a terminal device or a network device. BRIEF DESCRIPTION OF DRAWINGS

[0103] FIG. 1 is a schematic diagram of an architecture of a communication system according to an embodiment of the present application;

[0104] FIG. 2 is a schematic diagram of a data processing method according to an embodiment of the present application;

[0105] FIG. 3 is a schematic diagram of processing data by using a dictionary;

[0106] FIG. 4 is a schematic diagram of processing data by using geometry;

[0107] FIG. 5 is a schematic diagram of processing data by using an octree;

[0108] FIG. 6 is a schematic diagram of processing data by using semantics;

[0109] FIG. 7 is a schematic diagram of processing data by using region division;

[0110] FIG. 8 is a schematic diagram of a structure of a data processing apparatus according to an embodiment of the present application;

[0111] FIG. 9 is a schematic diagram of a structure of another data processing apparatus according to an embodiment of the present application;

[0112] FIG. 10 is a schematic diagram of a structure of a terminal device according to an embodiment of the present application;

[0113] FIG. 11 is a schematic diagram of a structure of a network device according to an embodiment of the present application. DETAILED DESCRIPTION

[0114] As shown in FIG. 1, FIG. 1 is a schematic diagram of an architecture of a communication system provided by an embodiment of the present application. The communication system can include a network device 110 and terminal devices 101-106. It should be understood that a communication system to which the method of the embodiments of the present application can be applied can include more or fewer network devices or terminal devices. In the communication system, the network device 110 and the terminal devices 101-106 form a communication system. The terminal devices 101-106 can send uplink data to the network device 110, and the network device 110 needs to receive the uplink data sent by the terminal devices 101-106. In addition, the terminal devices 104-106 can also form a communication system. In the communication system, the network device can send downlink information to the terminal devices 101, 102 and 105, etc.; the terminal device 105 can also send downlink information to the terminal devices 104 and 106.

[0115] The technical solutions in the embodiments of the present application can be applied to various communication systems, such as a universal mobile telecommunications system (UMTS), a wireless local area network (WLAN), a wireless fidelity (Wi-Fi) system, a 4th generation (4G) mobile communication system such as a long term evolution (LTE) system, a 5th generation (5G) mobile communication system such as a new radio (NR) system, and a future evolved communication system such as a 6th generation (6G) mobile communication system, etc.

[0116] The network device can be a device or module with corresponding communication functions located at the network side of the above communication system. The network device is usually provided with a communication module, circuit or chip for performing corresponding communication functions. The network device is also provided with program instructions for performing corresponding communication functions and corresponding program instructions. The network device is a device deployed in a wireless access network to provide wireless communication functions for terminal devices. The network device can include various forms of macro base stations, micro base stations (also known as small stations), relay stations, access points, etc. In systems using different wireless access technologies, the names of network devices may vary, such as base transceiver stations (BTS) in global system for mobile communication (GSM) or code division multiple access (CDMA) networks, NB (NodeB) in wideband code division multiple access (WCDMA), eNB or eNodeB (evolutional nodeB) in long term evolution (LTE). The network device can also be a wireless controller in the cloud radio access network (CRAN) scenario. The network device can also be a base station device in the future 5G network or a network device in the future evolved PLMN network. The network device can also be a wearable device or a vehicle-mounted device. The network device can also be a transmission and reception point (TRP).

[0117] The terminal device can be an apparatus or module with corresponding communication functions for accessing the above communication system. The terminal device is usually provided with a communication module, circuit or chip for performing corresponding communication functions. The terminal device is also configured with program instructions for performing corresponding communication functions. The terminal device can include various handheld devices, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to a wireless modem with wireless communication functions. The terminal can be a mobile station (MS), a subscriber unit, a cellular phone, a smart phone, a wireless data card, a personal digital assistant (PDA) computer, a tablet computer, a wireless modem, a handset, a laptop computer, a machine type communication (MTC) terminal, etc.

[0118] As shown in FIG. 2, FIG. 2 is a flow diagram of a data processing method provided by an embodiment of the present application. The method mainly includes the following steps:

[0119] S201, the network device determines configuration information, and the terminal device determines configuration information, wherein the configuration information is used to indicate type information of prior knowledge.

[0120] The prior knowledge is data obtained by the network device or data processed from the obtained data, which is used to assist the terminal device in filtering or compressing local data. For example, the obtained data can be sensing data, and the prior knowledge can be data processed from the sensing data. The network device trains a prior dictionary information based on the sensing data, and sends the prior dictionary information to the terminal device. The terminal device compresses local data through the prior dictionary information. Alternatively, the network device divides a region based on the sensing data to obtain a plurality of voxels, and sends indication information to the terminal device, wherein the indication information is used to indicate whether each voxel contains a point. 0 can represent that the voxel does not contain a point, and 1 represents that the voxel contains a point. 0 or 1 can also indicate in reverse. The terminal device performs unequal compression processing on the voxels according to the indication information to divide a plurality of voxel regions.

[0121] The type information can include a priori knowledge type. For example, the type information can include a priori knowledge type of a dictionary, region division, or semantics. Alternatively, the type information includes data form, which can implicitly indicate the corresponding a priori knowledge type. For example, the type information can include data form of dictionary dimension, dictionary data, and sparsity, i.e., implicitly indicates that the a priori knowledge type is a dictionary when the type information does not include the a priori knowledge type. Alternatively, the type information can include a priori knowledge type and data form corresponding to the a priori knowledge type. For example, the type information can include a dictionary (a priori knowledge type) and dictionary dimension, dictionary data, and sparsity (data form), or the type information can include region division (a priori knowledge type) and voxel data (data form).

[0122] The type information includes first-order type information (a priori knowledge type) and second-order type information (a priori knowledge sub-type), and the second-order type information is a sub-type of the first-order type information. For example, the first-order type information includes a dictionary, region division, or semantics, and the second-order type information includes multi-dimensional weighting and single-dimensional dictionary corresponding to the dictionary, octree, voxel, bitmap, and coordinate corresponding to the region division, and 3D object information and semantic label (label) corresponding to the semantics. Alternatively, the type information can include first-order type information, second-order type information, and data form. For example, the first-order type information includes a dictionary, region division, or semantics, the second-order type information includes multi-dimensional weighting corresponding to the dictionary, octree, voxel, bitmap, and coordinate corresponding to the region division, and 3D object information and semantic label (label) corresponding to the semantics, and the data form includes dictionary dimension, dictionary data, and sparsity corresponding to the multi-dimensional weighting, and octree data corresponding to the octree.

[0123] It should be understood that the type information can include multi-order type information, such as first-order type information, second-order type information, and third-order type information. Type information of three or more orders is included in the protection scope of the present application.

[0124] The type information corresponds to an application scenario, and the application scenario includes at least one of channel data transmission, artificial intelligence (AI) data transmission, or perception data transmission. Further, the application scenario and the type information can be in a one-to-one mapping relationship, for example, AI model transmission and type information are in a one-to-one mapping relationship, and the prior knowledge type corresponding to the AI model transmission only includes a dictionary, and the data form corresponding to the dictionary includes dictionary dimension and dictionary data. The application scenario and the type information can also be in a one-to-many mapping relationship. For example, the perception data transmission and the type information are in a one-to-many mapping relationship, and the prior knowledge type corresponding to the perception data transmission can include geometry, region division, and a dictionary, the data form corresponding to the geometry includes two-point coordinates and three-point coordinates, the data form corresponding to the region division includes Octree data and voxel data, and the data form corresponding to the dictionary includes dictionary dimension and dictionary data.

[0125] The type information corresponds to a data type of the local data, and the data type includes at least one of AI data, perception data, or channel data. The AI data can include AI model data, AI feature data, and AI inference data. Further, the data type and the type information can be in a one-to-one mapping relationship, for example, the AI model data and the type information are in a one-to-one mapping relationship, and the prior knowledge type corresponding to the AI model data only includes a dictionary, and the data form corresponding to the dictionary includes dictionary dimension and dictionary data. The data type and the type information can be in a one-to-many mapping relationship. For example, the perception data and the type information are in a one-to-many mapping relationship, and the prior knowledge type corresponding to the perception data can include geometry, region division, and a dictionary, the data form corresponding to the geometry includes two-point coordinates and three-point coordinates, the data form corresponding to the region division includes Octree data and voxel data, and the data form corresponding to the dictionary includes dictionary dimension and dictionary data.

[0126] The type information corresponding to the local data of different data types is listed as follows:

[0127] As shown in Table 1, Table 1 is type information corresponding to perception data. The prior knowledge type corresponding to the perception data includes at least one of the following: a dictionary, geometry, region division, or semantics, wherein the sub-type corresponding to the dictionary includes multi-dimensional weighting and single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting includes dictionary dimension, dictionary data, and sparsity; the sub-type corresponding to the geometry includes a surface, and the data form corresponding to the surface includes surface parameters and a scanned region on the surface, wherein the surface parameters can be expression parameters or a plurality of point data used to indicate a surface; the sub-type corresponding to the region division includes octree and voxel, the data form corresponding to the octree includes octree data, and the data form corresponding to the voxel includes voxel data; and the sub-type corresponding to the semantics includes a 3D target box, and the data form corresponding to the 3D target box includes a center position and range of the 3D target box and / or vertex coordinates of the 3D target box.

[0128] Table 1

[0129] As shown in Table 2, Table 2 is type information corresponding to channel data. The prior knowledge type corresponding to the channel data includes at least one of the following: a dictionary or region division, wherein the sub-type corresponding to the dictionary includes multi-dimensional weighting and single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting includes dictionary dimension, dictionary data, and sparsity; and the sub-type corresponding to the region division includes a bitmap and quadtree, the data form corresponding to the bitmap includes bitmap data, and the data form corresponding to the quadtree includes quadtree data.

[0130] Table 2

[0131] As shown in Table 3, Table 2 is type information corresponding to AI data. The prior knowledge type corresponding to the AI data includes a dictionary and a pre-trained model, wherein the sub-type corresponding to the dictionary includes multi-dimensional weighting, the data form corresponding to the multi-dimensional weighting includes dictionary dimension, dictionary data, and sparsity; and the data form corresponding to the pre-trained model includes model parameters. Optionally, the transmission data of the AI data can also be perception data, channel data, etc., and therefore the AI data can also reuse the type information corresponding to the perception data or the channel data.

[0132] Table 3

[0133] Optionally, the network device or the terminal device can be preconfigured with a prior knowledge type mapping table, and the prior knowledge type mapping table includes a mapping relationship between a plurality of types of information and an index.

[0134] For example, as shown in Table 4, the prior knowledge type mapping table can include a prior knowledge type, a prior knowledge sub-type, and an index. When the prior knowledge type is geometry, the prior knowledge sub-types corresponding to the geometry include a line, a plane, and a geometric body, the line corresponds to an index 0, the plane corresponds to an index 1, and the geometric body corresponds to an index 2. When the prior knowledge type is semantics, the prior knowledge sub-types corresponding to the semantics include 2D target information, 3D target information, and a semantic label, the 2D target information corresponds to an index 0, the 3D target information corresponds to an index 1, and the semantic label corresponds to an index 2. Other similar, here will not be described one by one.

[0135] Table 4

[0136] For example, as shown in Table 5, the prior knowledge type mapping table can include a prior knowledge type, a prior knowledge sub-type, a data form, and an index. The prior knowledge type includes geometry, semantics, region division, a dictionary, and a pre-training model. When the prior knowledge type is geometry, the prior knowledge sub-type corresponding to the index 0 is a line, and the data form is an endpoint coordinate; the prior knowledge sub-type corresponding to the index 1 is a plane, and the data form is a three-point coordinate; the prior knowledge sub-type corresponding to the index 2 is a plane, and the data form is a plane parameter expression. When the prior knowledge type is semantics, the prior knowledge sub-type corresponding to the index 0 is 3D target information, and the data form is a target frame center position and range; the prior knowledge sub-type corresponding to the index 1 is a semantic label, and the data form is each data category. Other similar, here will not be described one by one.

[0137] Table 5

[0138] For example, as shown in Table 6, the prior knowledge type mapping table can include an application scenario, a prior knowledge type, a data form, and an index. When the application scenario is AI data transmission, the prior knowledge type is a dictionary, and the corresponding data form is a dictionary dimension and dictionary data, corresponding to an index 0. When the application scenario is perception data transmission, the prior knowledge type corresponding to the index 0 is geometry, and the corresponding data form is two-point coordinates; the prior knowledge type corresponding to the index 1 is geometry, and the corresponding data form is three-point coordinates; the prior knowledge type corresponding to the index 2 is region division, and the corresponding data form is Octree data; the prior knowledge type corresponding to the index 3 is region division, and the corresponding data form is voxel data. Other similar, here will not be described one by one.

[0139] Table 6

[0140] For example, as shown in Table 7, the priori knowledge type mapping table can include a data type, a priori knowledge type, a data form, and an index. When the data type is AI data, the priori knowledge type is a dictionary (corresponding to an index 0 of a nested form), the corresponding data form is a dictionary dimension and dictionary data (corresponding to an index 0 of a nested form), and the corresponding index 0. When the data type is perception data transmission, the index 0 corresponds to a geometry (corresponding to an index 0 of a nested form), the corresponding data form is two point coordinates (corresponding to an index 0 of a nested form), the index 1 corresponds to a geometry (corresponding to an index 0 of a nested form), the corresponding data form is three point coordinates (corresponding to an index 1 of a nested form); the index 2 corresponds to a region division (corresponding to an index 1 of a nested form), the corresponding data form is Octree data (corresponding to an index 0 of a nested form); the index 3 corresponds to a region division (corresponding to an index 1 of a nested form), the corresponding data form is voxel data (corresponding to an index 1 of a nested form). Other similar, not listed here.

[0141] Table 7

[0142] Optionally, the network device or the terminal device can update the priori knowledge type mapping table according to a preset period. The network device and the terminal device periodically synchronize the priori knowledge type mapping table through radio resource control (RRC) signaling or medium access control (MAC) signaling and the like.

[0143] Alternatively, when a trigger condition is met, the network device or the terminal device updates the priori knowledge type mapping table, wherein the trigger condition includes at least one of the following changes: an application scenario, data of the priori knowledge, or local data provided by the terminal device. After updating the priori knowledge type mapping table, the network device can send the updated priori knowledge type mapping table to the terminal device. Alternatively, after updating the priori knowledge type mapping table, the terminal device can send the updated priori knowledge type mapping table to the network device.

[0144] For example, when the application scenario of the network device, the required local data provided by the terminal device, or the data of the obtainable priori knowledge changes, the network device updates the priori knowledge type mapping table and notifies the terminal device of the updated priori knowledge type mapping table. Alternatively, when the application scenario of the terminal device, the required local data provided by the terminal device, or the data of the obtainable priori knowledge changes, the terminal device updates the priori knowledge type mapping table and notifies the network device of the updated priori knowledge type mapping table.

[0145] Further, when updating the priori knowledge type mapping table, the priori knowledge type, the data form, and the corresponding index in the priori knowledge type mapping table can be added, deleted, or modified.

[0146] Specifically, the network device or the terminal device determines the type information of the priori knowledge can include the following several ways:

[0147] The first optional way, the network device sends indication information to the terminal device, or the terminal device sends indication information to the network device, the indication information is used to indicate the type information of the priori knowledge.

[0148] The indication information includes an application scenario or a data type. For example, in the case of one-to-one mapping relationship between the application scenario and the type information, when the indication information includes AI model transmission, the priori knowledge type indicated by the indication information is a dictionary, and the data form corresponding to the dictionary includes dictionary dimension and dictionary data. Optionally, the indication information can also include the index of the application scenario or the index of the data type. For example, the indication information can include the index of AI model transmission or the index of channel data.

[0149] The indication information can include the priori knowledge type. For example, if the priori knowledge type is 3D target information and octree, the terminal device or the network device can send the indication information through RRC signaling or MAC signaling. The indication information can include "3D target information" and "octree", and the indication information can also include { "semantic", "3D target information"} and { "region division", "octree"} (nested form). Or, the indication information can include the data form. For example, if the priori knowledge type is 3D target information and octree, corresponding to the data form of target box vertex and octree data respectively, the terminal device or the network device can send the indication information through RRC signaling or MAC signaling, and the indication information can include "target box vertex" and "octree data". Or, the indication information can also include the priori knowledge type and the data form, which is similar to the above, and will not be repeated here.

[0150] The indication information can include a first index, and the first index is used to indicate at least one type of information in a pre-configured priori knowledge type mapping table. For example, as shown in Table 7, for perception data, the indication information can include indexes (0, 4), and (0, 4) indicates that the priori knowledge type is geometry and dictionary, and the data forms are two-point coordinates and dictionary dimensions and dictionary data respectively. If the indexes in the nested form are used, the indication information can include (0, 0) and (2, 0). (0, 0) indicates that the priori knowledge type is geometry, and the data form corresponding to the geometry is two-point coordinates. (2, 0) indicates that the priori knowledge type is dictionary, and the data form corresponding to the dictionary is dictionary dimensions and dictionary data.

[0151] In a second optional mode, the terminal device sends first indication information to the network device, the first indication information is used to indicate at least one type of information of the priori knowledge supported by the terminal device; and the terminal device receives second indication information sent by the network device, the second indication information is used to indicate type information selected from the at least one type of information. That is, the network device and the terminal device determine the type information of the priori knowledge that can meet the requirement of the terminal device in a negotiation mode.

[0152] In a third optional mode, the terminal device sends third indication information to the network device, the third indication information is used to indicate type information of the priori knowledge required by the terminal device; and the terminal device receives fourth indication information sent by the network device, the fourth indication information is used to indicate whether there is data of the priori knowledge corresponding to the type information. Further, if the network device has data of the priori knowledge corresponding to the type information, the fourth indication information can be 0, and the network device sends the data of the priori knowledge corresponding to the type information to the terminal device. If the network device does not have data of the priori knowledge corresponding to the type information, the fourth indication information can be 1, and the network device or the terminal device reconfigures the type information of the priori knowledge and synchronously updates.

[0153] In a fourth optional mode, the terminal device receives fifth indication information sent by the network device, the fifth indication information is used to indicate at least one type of information of the priori knowledge supported by the network device; and the terminal device sends sixth indication information to the network device, the sixth indication information is used to indicate type information selected from the at least one type of information. That is, the network device and the terminal device determine the type information of the priori knowledge that can be supported by the network device in a negotiation mode.

[0154] In a fifth optional mode, the terminal device receives seventh indication information sent by the network device, the seventh indication information being used to indicate type information of the prior knowledge; the terminal device sends eighth indication information to the network device, the eighth indication information being used to indicate whether the terminal device supports processing data of the prior knowledge corresponding to the type information. Further, if the terminal device supports processing data of the prior knowledge corresponding to the type information, the eighth indication information can be 0, and the network device sends data of the prior knowledge corresponding to the type information to the terminal device. If the terminal device does not support processing data of the prior knowledge corresponding to the type information, the eighth indication information can be 1, and the network device or the terminal device reconfigures the type information of the prior knowledge and synchronously updates.

[0155] It should be noted that in the second to fifth optional modes, the indication mode in the first optional mode can be used to indicate the type information of the prior knowledge. For example, the type information of the prior knowledge can be indicated by indicating an application scenario or a data type, or by an index.

[0156] Optionally, the network device or the terminal device can update the type information of the prior knowledge according to a preset period. The network device and the terminal device synchronously update the type information of the prior knowledge periodically through RRC signaling or MAC signaling.

[0157] Alternatively, when a trigger condition is met, the network device or the terminal device updates the type information of the prior knowledge, wherein the trigger condition includes at least one of the following: a change in an application scenario, data of the prior knowledge, or local data. After updating the type information of the prior knowledge, the network device can send the updated type information of the prior knowledge to the terminal device. Alternatively, after updating the type information of the prior knowledge, the terminal device can send the updated type information of the prior knowledge to the network device.

[0158] For example, when an application scenario of the network device, required local data provided by the terminal device, or available data of the prior knowledge changes, the network device updates the type information of the prior knowledge and notifies the terminal device of the updated type information of the prior knowledge. Alternatively, when an application scenario of the terminal device, available local data provided by the terminal device, or required data of the prior knowledge changes, the terminal device updates the type information of the prior knowledge and notifies the network device of the updated type information of the prior knowledge.

[0159] S202, the network device sends data of the prior knowledge to the terminal device, the data of the prior knowledge corresponding to the type information.

[0160] S203, the terminal device processes the local data based on the data of the prior knowledge.

[0161] Specifically, the terminal device compresses or filters the local data based on the data of the prior knowledge. The local data can include perception data, channel data or AI data. Optionally, the terminal device can report the processed local data to the network device after processing the local data.

[0162] (1) For perception data, multiple types of information of prior knowledge can be configured, and the data of prior knowledge corresponding to different types of information can be used to process the perception data. For example:

[0163] FIG. 3 is a schematic diagram of processing data using a dictionary. For perception data, the type of prior knowledge can be a dictionary, and the subtypes corresponding to the dictionary include multi-dimensional weighting and single-dimensional dictionary. The data form corresponding to the multi-dimensional weighting includes dictionary dimension, dictionary data and sparsity. The base station can send the dictionary dimension (D, L), dictionary data and sparsity k to the UE. The UE can compress the local perception data based on the dictionary sent by the base station, and report the compressed perception data to the network device.

[0164] FIG. 4 is a schematic diagram of processing data using geometry. For perception data, the type of prior knowledge can be geometry, and the subtypes corresponding to the geometry include surface. The data form corresponding to the surface includes surface parameters and scanned regions on the surface. The base station sends the parameters of the existing surface in the environment and the scanned regions on the surface to the UE. The UE filters or low-precision compresses the local perception data of the scanned surface region, and high-precision compresses other local perception data. Finally, the UE reports the filtered / compressed local perception data to the base station.

[0165] FIG. 5 is a schematic diagram of processing data using octree. For perception data, the type of prior knowledge can be region division, and the subtypes corresponding to the region division include octree. The data form corresponding to the octree includes octree data. The UE reports the perception region R to the base station. The base station determines the octree data based on the perception region R and the environment data, and sends the octree data to the UE. The octree data is used to indicate the compression level of each leaf region. The UE performs unequal compression on the local perception data in each leaf region according to the octree data, and finally reports the compressed local perception data to the base station.

[0166] For perception data, the type of prior knowledge can be region division, and the subtypes corresponding to the region division can also include voxel. The data form corresponding to the voxel includes voxel data. The UE sends the perception region R to the base station. The base station divides the grid based on the perception region R and the environment data to obtain the voxel data, and sends the voxel data to the UE. The voxel data is used to indicate the compression level of each voxel. The UE performs unequal compression on the local perception data in each voxel according to the voxel data, and reports the compressed local perception data to the base station.

[0167] FIG. 6 is a schematic diagram of processing data by using semantics. For perception data, the type of priori knowledge can be semantics, and the subtypes corresponding to semantics include 3D target box, and the data forms corresponding to the 3D target box include the center position and range of the 3D target box, and / or the vertex coordinates of the 3D target box. The base station sends the target information of the existing target in the environment to the UE, for example, the 3D box position and range, the UE matches the target information issued with the local target information to determine the local target data, filters or low-precision compresses the local target data, high-precision compresses other target data, and finally reports the compressed target data to the base station.

[0168] (2) For channel data, multiple types of information of priori knowledge can be configured, and the data of priori knowledge corresponding to different types of information can be used to process the local channel data. For example, as follows:

[0169] For channel data, the type of priori knowledge can be dictionary, and the subtypes corresponding to the dictionary include multi-dimensional weighting and single-dimensional dictionary, and the data forms corresponding to the multi-dimensional weighting include dictionary dimension, dictionary data and sparsity. The base station can send the dictionary dimension (D, L), dictionary data and sparsity k to the UE, the UE can compress the local channel data based on the issued dictionary, and report the compressed local channel data to the base station.

[0170] For channel data, the type of priori knowledge can be region division, and the subtypes corresponding to the region division include bitmap, and the data forms corresponding to the bitmap include bitmap data. The base station sends the feedback mode map to the UE based on the bitmap form, and the feedback mode map is used to indicate which feedback mode the UE should select in different regions of the map. As shown in Table 8, Table 8 is a feedback mode table, wherein index 1 corresponds to Type II Codebook, index 2 corresponds to feedback adjacent grid, and index 3 corresponds to feedback calibration multipath. The UE feeds back the channel data according to the feedback mode map.

[0171] Table 8

[0172] FIG. 7 is a schematic diagram of processing data by using region division. For channel data, the type of priori knowledge can be region division, and the subtypes corresponding to the region division include quadtree, and the data forms corresponding to the quadtree include quadtree data. The base station sends the compression map to the UE based on the quadtree form, and the compression map is used to indicate the compression level of the data in each region, and the UE compresses the channel data according to the compression map, and reports the compressed channel data to the base station.

[0173] (3) For AI data, multiple types of information of prior knowledge can be configured, and data corresponding to prior knowledge of different types of information can be used to process local data. For example:

[0174] For AI data, the prior knowledge type can be a dictionary, and the subtypes corresponding to the dictionary include multi-dimensional weighting and single-dimensional dictionary. The data form corresponding to the multi-dimensional weighting includes dictionary dimension, dictionary data, and sparsity. The base station can send the dictionary dimension (D, L), dictionary data, and sparsity k to the UE. The UE can compress the AI data based on the dictionary issued, and report the compressed AI data to the base station.

[0175] For AI data, the prior knowledge type can also be a pre-trained model, and the data form corresponding to the pre-trained model includes model parameters. The base station sends the obtained pre-trained model to the UE. The UE fine-tunes or updates the pre-trained model, and reports the fine-tuned or updated pre-trained model to the base station.

[0176] In the embodiments of the present application, by configuring multiple types of information of prior knowledge, the network device sends data of prior knowledge corresponding to the type information to the terminal device, so that the terminal device can filter or compress data of different application scenarios or different data types, effectively reducing the data transmission amount and improving the data transmission efficiency.

[0177] It can be understood that the methods and operations implemented by the terminal device in the above-mentioned various method embodiments can also be implemented by components (such as chips or circuits) that can be used for the terminal device, and the methods and operations implemented by the network device can also be implemented by components (such as chips or circuits) that can be used for the network device.

[0178] The embodiments of the present application can divide the terminal device or the network device into functional modules according to the above-mentioned method examples. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. It should be noted that the division of modules in the embodiments of the present application is illustrative, and is only a logical functional division. When actually implemented, another division mode can be used. The following will be described taking the example of dividing each functional module according to each function.

[0179] The above describes the method provided by the embodiments of the present application in detail in combination with FIG. 2. The following describes the data processing apparatus provided by the embodiments of the present application in combination with FIGS. 8 to 9. It should be understood that the description of the apparatus embodiments corresponds to the description of the method embodiments, and therefore, the content not described in detail can be referred to the above-mentioned method embodiments. For brevity, the description is not repeated here.

[0180] Please refer to FIG. 8, which is a structural schematic diagram of a data processing apparatus provided in an embodiment of the present application. The data processing apparatus can implement the steps or processes performed by the terminal device corresponding to the method embodiments described above. In a possible design, the data processing apparatus can include a receiving module 801, a processing module 802 and a sending module 803. Optionally, the data processing apparatus can further include a storage module for storing device program codes and / or data.

[0181] The data processing apparatus can be a terminal-side apparatus in the above embodiments, for example, a terminal device or a communication module in the terminal device, or a circuit or chip responsible for the communication function in the terminal.

[0182] The processing module 802 is configured to determine configuration information, where the configuration information is used to indicate type information of prior knowledge, and the prior knowledge is obtained data or data processed from the obtained data.

[0183] The receiving module 801 is configured to receive data of the prior knowledge sent by a network device, where the data of the prior knowledge corresponds to the type information.

[0184] The processing module 802 is further configured to process local data based on the data of the prior knowledge.

[0185] Optionally, the type information includes a prior knowledge type and / or a data form.

[0186] Optionally, the type information corresponds to an application scenario, and the application scenario includes at least one of the following: channel data transmission, artificial intelligence (AI) data transmission or perception data transmission.

[0187] Optionally, the type information corresponds to a data type of the local data, and the data type includes at least one of the following: AI data, perception data or channel data.

[0188] Optionally, the type information includes first-order type information and second-order type information, and the second-order type information is a sub-type of the first-order type information.

[0189] Optionally, the priori knowledge type corresponding to the perception data comprises at least one of the following: a dictionary, geometry, region division, or semantics, wherein the sub-type corresponding to the dictionary comprises multi-dimensional weighting and single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting comprises dictionary dimension, dictionary data, and sparsity; the sub-type corresponding to the geometry comprises a surface, and the data form corresponding to the surface comprises surface parameters and a scanned region on the surface; the sub-type corresponding to the region division comprises octree and voxel, the data form corresponding to the octree comprises octree data, and the data form corresponding to the voxel comprises voxel data; and the sub-type corresponding to the semantics comprises a 3D target box, and the data form corresponding to the 3D target box comprises a center position and range of the 3D target box and / or vertex coordinates of the 3D target box.

[0190] Optionally, the priori knowledge type corresponding to the channel data comprises at least one of the following: a dictionary or region division, wherein the sub-type corresponding to the dictionary comprises multi-dimensional weighting and single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting comprises dictionary dimension, dictionary data, and sparsity; and the sub-type corresponding to the region division comprises a bitmap and quadtree, the data form corresponding to the bitmap comprises bitmap data, and the data form corresponding to the quadtree comprises quadtree data.

[0191] Optionally, the priori knowledge type corresponding to the AI data comprises a dictionary and a pre-trained model, wherein the sub-type corresponding to the dictionary comprises multi-dimensional weighting and single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting comprises dictionary dimension, dictionary data, and sparsity; and the data form corresponding to the pre-trained model comprises model parameters.

[0192] Optionally, the receiving module 801 is further configured to receive indication information sent by the network device, or the sending module 803 is configured to send indication information to the network device, wherein the indication information is used to indicate the type information.

[0193] Optionally, the indication information comprises an application scenario or data type, or the indication information comprises a first index, the first index is used to indicate at least one type information in a pre-configured priori knowledge type mapping table, and the priori knowledge type mapping table comprises a mapping relationship between multiple type information and indexes.

[0194] Optionally, the sending module 803 is configured to send first indication information to the network device, the first indication information is used to indicate at least one type information of the priori knowledge supported by itself.

[0195] The receiving module 801 is configured to receive second indication information sent by the network device, the second indication information is used to indicate type information selected from the at least one type information.

[0196] Optionally, the sending module 803 is configured to send third indication information to the network device, where the third indication information is used to indicate type information of the prior knowledge required by the network device.

[0197] The receiving module 801 is configured to receive fourth indication information sent by the network device, where the fourth indication information is used to indicate whether there is data of the prior knowledge corresponding to the type information.

[0198] Optionally, the receiving module 801 is configured to receive fifth indication information sent by the network device, where the fifth indication information is used to indicate at least one type information of the prior knowledge supported by the network device to provide;

[0199] The sending module 803 is configured to send sixth indication information to the network device, where the sixth indication information is used to indicate type information selected from the at least one type information.

[0200] Optionally, the receiving module 801 is configured to receive seventh indication information sent by the network device, where the seventh indication information is used to indicate type information of the prior knowledge.

[0201] The sending module 803 is configured to send eighth indication information to the network device, where the eighth indication information is used to indicate whether to support processing data of the prior knowledge corresponding to the type information.

[0202] Optionally, the processing module 802 is further configured to update the type information according to a preset period.

[0203] Optionally, the processing module 802 is further configured to update the type information when a trigger condition is met, where the trigger condition includes at least one of the following changes: application scenario, data of the prior knowledge, or the local data.

[0204] In a possible design, when the data processing apparatus is a terminal device or a communication module in a terminal device, the function of the processing module 802 can be implemented by one or more processors. Specifically, the processor can include a Modem chip, or a System on Chip (SoC) chip or a SIP chip containing a Modem core. The functions of the receiving module 801 and the sending module 803 can be implemented by a transceiver circuit.

[0205] In a possible design, when the data processing apparatus is a circuit or chip responsible for communication functions in a terminal device, such as a Modem chip or a System on Chip (SoC) chip or a SIP chip containing a Modem core, the function of the processing module 802 can be implemented by a circuit system including one or more processors or processor cores in the above-mentioned chip. The functions of the receiving module 801 and the sending module 803 can be implemented by an interface circuit or a data transceiver circuit on the above-mentioned chip.

[0206] It should be noted that the implementation of each module can also correspond to the description of the corresponding method embodiment shown in FIG. 2, and the method and function performed by the terminal device in the above embodiments are executed.

[0207] Please refer to FIG. 9, which is a structural schematic diagram of another data processing apparatus provided by the embodiments of the present application. The data processing apparatus can implement the steps or processes corresponding to the steps or processes performed by the network device in the above method embodiments. In a possible design, the data processing apparatus can include a sending module 901, a processing module 902, and a receiving module 903. Optionally, the data processing apparatus can further include a storage module for storing device program code and / or data.

[0208] The data processing apparatus can be the network side apparatus in the above embodiments, for example, a network device or a communication module in the network device, or a circuit or chip responsible for communication function in the network.

[0209] The processing module 902 is configured to determine configuration information, wherein the configuration information is used to indicate type information of prior knowledge, and the prior knowledge is obtained data or data processed from the obtained data.

[0210] The sending module 901 is configured to send data of the prior knowledge to a terminal device, wherein the data of the prior knowledge corresponds to the type information, and the data of the prior knowledge is used to process local data of the terminal device.

[0211] Optionally, the type information includes a prior knowledge type and / or a data form.

[0212] Optionally, the type information corresponds to an application scenario, and the application scenario includes at least one of the following: channel data transmission, artificial intelligence (AI) data transmission, or perception data transmission.

[0213] Optionally, the type information corresponds to a data type of the local data, and the data type includes at least one of the following: AI data, perception data, or channel data.

[0214] Optionally, the type information includes first-order type information and second-order type information, and the second-order type information is a sub-type of the first-order type information.

[0215] Optionally, the priori knowledge type corresponding to the perception data comprises at least one of the following: a dictionary, geometry, region division, or semantics, wherein the sub-type corresponding to the dictionary comprises multi-dimensional weighting and single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting comprises dictionary dimension, dictionary data, and sparsity; the sub-type corresponding to the geometry comprises a surface, the data form corresponding to the surface comprises surface parameters and a scanned region on the surface; the sub-type corresponding to the region division comprises octree and voxel, the data form corresponding to the octree comprises octree data, and the data form corresponding to the voxel comprises voxel data; and the sub-type corresponding to the semantics comprises a 3D target box, and the data form corresponding to the 3D target box comprises a center position and range of the 3D target box and / or vertex coordinates of the 3D target box.

[0216] Optionally, the priori knowledge type corresponding to the channel data comprises at least one of the following: a dictionary or region division, wherein the sub-type corresponding to the dictionary comprises multi-dimensional weighting and single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting comprises dictionary dimension, dictionary data, and sparsity; and the sub-type corresponding to the region division comprises a bitmap and quadtree, the data form corresponding to the bitmap comprises bitmap data, and the data form corresponding to the quadtree comprises quadtree data.

[0217] Optionally, the priori knowledge type corresponding to the AI data comprises a dictionary and a pre-trained model, wherein the sub-type corresponding to the dictionary comprises multi-dimensional weighting and single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting comprises dictionary dimension, dictionary data, and sparsity; and the data form corresponding to the pre-trained model comprises model parameters.

[0218] Optionally, the receiving module 903 is configured to receive indication information sent by the terminal device, or the sending module 901 is configured to send indication information to the terminal device, wherein the indication information is used to indicate the type information.

[0219] Optionally, the indication information comprises an application scenario or data type, or the indication information comprises a first index, the first index is used to indicate at least one type information in a pre-configured priori knowledge type mapping table, and the priori knowledge type mapping table comprises a mapping relationship between multiple type information and indexes.

[0220] Optionally, the receiving module 903 is configured to receive first indication information sent by the terminal device, the first indication information is used to indicate at least one type information of the priori knowledge supported by the terminal device.

[0221] The sending module 901 is configured to send second indication information to the terminal device, the second indication information is used to indicate type information selected from the at least one type information.

[0222] Optionally, the receiving module 903 is configured to receive third indication information sent by the terminal device, where the third indication information is used to indicate type information of the prior knowledge required by the terminal device.

[0223] The sending module 901 is configured to send fourth indication information to the terminal device, where the fourth indication information is used to indicate whether there is data of the prior knowledge corresponding to the type information.

[0224] Optionally, the sending module 901 is configured to send fifth indication information to the terminal device, where the fifth indication information is used to indicate at least one type information of the prior knowledge supported by the network device to provide.

[0225] The receiving module 903 is configured to receive sixth indication information sent by the terminal device, where the sixth indication information is used to indicate type information selected from the at least one type information.

[0226] Optionally, the sending module 901 is configured to send seventh indication information to the terminal device, where the seventh indication information is used to indicate type information of the prior knowledge.

[0227] The receiving module 903 is configured to receive eighth indication information sent by the terminal device, where the eighth indication information is used to indicate whether to support processing data of the prior knowledge corresponding to the type information.

[0228] Optionally, the processing module 902 is further configured to update the type information according to a preset period.

[0229] Optionally, the processing module 902 is further configured to update the type information when a trigger condition is met, where the trigger condition includes at least one of the following changes: an application scenario, data of the prior knowledge, or the local data.

[0230] In a possible design, when the data processing apparatus is a network device or a communication module in the network device, the function of the processing module 902 can be implemented by one or more processors. Specifically, the processor can include a Modem chip, or a System on Chip (SoC) chip or a SIP chip containing a Modem core. The functions of the sending module 901 and the receiving module 903 can be implemented by a transceiver circuit.

[0231] In a possible design, when the data processing apparatus is a circuit or chip responsible for communication functions in the network device, such as a Modem chip or a System on Chip (SoC) chip or a SIP chip containing a Modem core, the functions of the sending module 901 and the receiving module 903 can be implemented by an interface circuit or a data transceiver circuit on the chip. The function of the processing module 902 can be implemented by a circuit system including one or more processors or processor cores in the chip.

[0232] It should be noted that the implementation of each module can also correspond to the description of the corresponding method embodiment shown in FIG. 2, and the method and function performed by the network device in the above embodiments are executed.

[0233] FIG. 10 is a structural schematic diagram of a terminal device provided in an embodiment of the present application. The terminal device can be applied in the system shown in FIG. 1, and performs the function of the terminal device in the above method embodiments, or implements the steps or processes performed by the terminal device in the above method embodiments.

[0234] As shown in FIG. 10, the terminal device includes a processor 1001 and a transceiver 1002. The transceiver 1002 includes a transmitter 1021, a receiver 1022 and an antenna 1023. The receiver 1022 can be configured to receive transmission control information through the antenna 1023, and the transmitter 1021 can be configured to send transmission feedback information to the network device through the antenna 1023. Optionally, the terminal device further includes a memory 1003. The processor 1001, the transceiver 1002 and the memory 1003 can communicate with each other through internal connection paths to transfer control and / or data signals. The memory 1003 is configured to store a computer program, and the processor 1001 is configured to call and run the computer program from the memory 1003 to control the transceiver 1002 to transceive signals. Optionally, the terminal device can further include an antenna for transmitting uplink data or uplink control signaling output by the transceiver 1002 through wireless signals.

[0235] The processor 1001 and the memory 1003 can be integrated into one processing device, and the processor 1001 is configured to execute the program code stored in the memory 1003 to implement the above functions. In specific implementation, the memory 1003 can be integrated in the processor 1001 or independent of the processor 1001. The processor 1001 can correspond to the processing module in FIG. 8.

[0236] The transceiver 1002 can correspond to the receiving module and the sending module in FIG. 8, and can also be referred to as a transceiving unit or a transceiving module. The transceiver 1002 can include a receiver (or receiver, receiving circuit) and a transmitter (or transmitter, transmitting circuit). The receiver is configured to receive signals, and the transmitter is configured to transmit signals.

[0237] It should be understood that the terminal device shown in FIG. 10 can implement each process involving the terminal device in the method embodiment shown in FIG. 2. Each module in the terminal device operates and / or functions to implement the corresponding process in the above method embodiments. For details, refer to the description in the above method embodiments, and appropriate detailed description is omitted here to avoid repetition.

[0238] The processor 1001 can be configured to perform the actions described in the foregoing method embodiments as implemented by the terminal device, and the transceiver 1002 can be configured to perform the actions described in the foregoing method embodiments as transmitted or received by the terminal device to or from the network device. For details, refer to the descriptions in the foregoing method embodiments, which will not be repeated here.

[0239] The processor 1001 can be a central processing unit, a general purpose processor, a digital signal processor, an application specific integrated circuit, a field programmable gate array, or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It can implement or execute the various exemplary logical blocks, modules, and circuits described in connection with the disclosure. The processor 1001 can also be a combination of computing functions, such as a combination of one or more microprocessors, a combination of a digital signal processor and a microprocessor, and the like. The terminal device can also include a communication bus, which can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The communication bus is used to realize the connection and communication between the components. The transceiver 1002 in the embodiments of the present application is used for signaling or data communication with other node devices. The memory 1003 can include volatile memory, such as non-volatile random access memory (NVRAM), phase change RAM (PRAM), magnetoresistive RAM (MRAM), etc., and can also include non-volatile memory, such as at least one magnetic disk storage device, electrically erasable programmable read-only memory (EEPROM), a flash memory device, such as NOR flash memory or NAND flash memory, a semiconductor device, such as a solid state disk (SSD), etc. The memory 1003 can also be at least one storage device located away from the processor 1001. The memory 1003 can also optionally store a set of computer program codes or configuration information. Optionally, the processor 1001 can also execute the program stored in the memory 1003. The processor can cooperate with the memory and the transceiver to perform any of the methods and functions of the terminal device described in the foregoing embodiments.

[0240] FIG. 11 is a structural schematic diagram of a network device according to an embodiment of the present application. The network device can be applied in the system shown in FIG. 1, and can perform the functions of the network device in the above method embodiments, or implement the steps or processes performed by the network device in the above method embodiments.

[0241] As shown in FIG. 11, the network device includes a processor 1101 and a transceiver 1102. The transceiver 1102 includes a transmitter 1121, a receiver 1122 and an antenna 1123. The transmitter 1121 can be configured to send transmission control information to a terminal device through the antenna 1123, and the receiver 1122 can be configured to receive transmission feedback information sent by the terminal device through the antenna 1123. Optionally, the network device further includes a memory 1103. The processor 1101, the transceiver 1102 and the memory 1103 can communicate with each other through internal connection paths, and transfer control and / or data signals. The memory 1103 is configured to store a computer program, and the processor 1101 is configured to invoke and run the computer program stored in the memory 1103 to control the transceiver 1102 to transceive signals. Optionally, the network device can further include an antenna configured to send uplink data or uplink control signaling output by the transceiver 1102 through wireless signals.

[0242] The processor 1101 can correspond to the processing module in FIG. 9. The processor 1101 can be integrated with the memory 1103 as a processing device, and the processor 1101 is configured to execute program codes stored in the memory 1103 to implement the above functions. In specific implementation, the memory 1103 can also be integrated in the processor 1101, or independent of the processor 1101.

[0243] The transceiver 1102 can correspond to the receiving module and the sending module in FIG. 9, and can also be referred to as a transceiving unit or a transceiving module. The transceiver 1102 can include a receiver (or a receiver, a receiving circuit) and a transmitter (or a transmitter, a transmitting circuit). The receiver is configured to receive signals, and the transmitter is configured to transmit signals.

[0244] It should be understood that the network device shown in FIG. 11 can implement each process involving the network device in the method embodiment shown in FIG. 2. The operations and / or functions of each module in the network device are respectively implemented to implement the corresponding processes in the above method embodiments. For details, refer to the description in the above method embodiments, and appropriate detailed description is omitted here to avoid repetition.

[0245] The processor 1101 can be used for performing the actions described in the preceding method embodiments that are implemented internally by the network device, while the transceiver 1102 can be used for performing the actions described in the preceding method embodiments that are performed by the network device to send or receive to / from the terminal device. For details, please refer to the descriptions in the preceding method embodiments, which will not be described here again.

[0246] The processor 1101 can be various types of processing units mentioned in the foregoing description. The network device can further include a communication bus, which can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. The communication bus is used to implement the connection and communication between the components. The transceiver 1102 of the device in the embodiments of the present application is used to communicate with other devices. The memory 1103 can be various types of memories mentioned in the foregoing description. The memory 1103 can alternatively be at least one storage device located away from the aforementioned processor 1101. The memory 1103 stores a set of computer program codes or configuration information, and the processor 1101 executes the program in the memory 1103. The processor can cooperate with the memory and the transceiver to execute any one of the methods and functions of the network device described in the foregoing embodiments.

[0247] The embodiments of the present application also provide a chip system, which includes a processor for supporting a terminal device or a network device to implement the functions involved in any one of the embodiments described above, such as generating or processing the measurement results involved in the methods described above.

[0248] In a possible design, the chip system can further include a memory for the necessary computer programs and data of the terminal device or the network device. The chip system can be composed of a chip, or can include a chip and other discrete devices. The input and output of the chip system correspond to the receiving and sending operations of the terminal device or the network device in the method embodiments, respectively.

[0249] According to the method provided in the embodiments of the present application, the present application further provides a computer program product, which includes a computer program. When the computer program runs on a computer, the computer program causes the computer to execute the method of any one of the embodiments shown in FIG. 2.

[0250] According to the method provided in the embodiments of the present application, the present application further provides a computer readable medium, which stores a computer program. When the computer program runs on a computer, the computer program causes the computer to execute the method of any one of the embodiments shown in FIG. 2.

[0251] According to the method provided in the embodiments of the present application, the present application further provides a communication system, which comprises one or more terminal devices and one or more network devices.

[0252] In the above embodiments, the method can be implemented by software, hardware, firmware or any combination thereof, in whole or in part. When implemented by software, the method can be implemented in the form of a computer program product, in whole or in part. The computer program product comprises one or more computer instructions. When the computer instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server, data center, etc. integrated with one or more available media. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a high-density digital video disc (digital video disc, DVD)), or a semiconductor medium (such as a solid state disc (solid state disc, SSD)), etc.

Claims

1. A data processing method, characterized by, The method comprises: determining configuration information, the configuration information being used to indicate type information of prior knowledge, wherein the prior knowledge is obtained data or data processed from the obtained data; receiving data of the prior knowledge sent by a network device, the data of the prior knowledge corresponding to the type information; processing local data based on the data of the prior knowledge.

2. The method of claim 1, wherein, The type information comprises a prior knowledge type and / or a data form.

3. The method of claim 1 or 2, wherein, The type information corresponds to an application scenario, the application scenario comprising at least one of channel data transmission, artificial intelligence (AI) data transmission or perception data transmission.

4. The method of claim 1 or 2, wherein, The type information corresponds to a data type of the local data, the data type comprising at least one of AI data, perception data or channel data.

5. The method according to any one of claims 1 to 4, characterized in that, The type information comprises first-order type information and second-order type information, the second-order type information being a sub-type of the first-order type information.

6. The method of claim 4, wherein, The prior knowledge type corresponding to the perception data comprises at least one of a dictionary, geometry, region division or semantics, wherein the sub-type corresponding to the dictionary comprises multi-dimensional weighting and a single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting comprising a dictionary dimension, dictionary data and sparsity; the sub-type corresponding to the geometry comprises a surface, the data form corresponding to the surface comprising a surface parameter and a scanned region on the surface; the sub-type corresponding to the region division comprises an octree and a voxel, the data form corresponding to the octree comprising octree data, the data form corresponding to the voxel comprising voxel data; the sub-type corresponding to the semantics comprises a 3D target box, the data form corresponding to the 3D target box comprising a center position and a range of the 3D target box and / or vertex coordinates of the 3D target box.

7. The method of claim 4, wherein, The prior knowledge type corresponding to the channel data comprises at least one of a dictionary or region division, wherein the sub-type corresponding to the dictionary comprises multi-dimensional weighting and a single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting comprising a dictionary dimension, dictionary data and sparsity; the sub-type corresponding to the region division comprises a bitmap and a quadtree, the data form corresponding to the bitmap comprising bitmap data, the data form corresponding to the quadtree comprising quadtree data.

8. The method of claim 4, wherein, The prior knowledge type corresponding to the AI data comprises a dictionary and a pre-trained model, wherein the sub-type corresponding to the dictionary comprises multi-dimensional weighting and a single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting comprising a dictionary dimension, dictionary data and sparsity; the data form corresponding to the pre-trained model comprising model parameters.

9. The method according to any one of claims 1 to 8, wherein, The determination of the configuration information comprises: receiving indication information sent by the network device; or, sending indication information to the network device, wherein the indication information is used to indicate the type information.

10. The method of claim 9, wherein, The indication information comprises an application scenario or a data type, or the indication information comprises a first index, the first index being used to indicate at least one type information in a pre-configured prior knowledge type mapping table, the prior knowledge type mapping table comprising a mapping relationship between multiple types of information and indexes.

11. The method of any one of claims 1-10, wherein, The determination of the configuration information comprises: sending first indication information to the network device, the first indication information being used for indicating at least one type of information of the prior knowledge supported by itself; receiving second indication information sent by the network device, the second indication information being used for indicating type information selected from the at least one type of information.

12. The method of any one of claims 1-10, wherein, The determination configuration information comprises: sending third indication information to the network device, the third indication information being used for indicating type information of the prior knowledge required by itself; receiving fourth indication information sent by the network device, the fourth indication information being used for indicating whether there is data of the prior knowledge corresponding to the type information.

13. The method of any one of claims 1-10, wherein, The determination configuration information comprises: receiving fifth indication information sent by the network device, the fifth indication information being used for indicating at least one type of information of the prior knowledge supported by the network device for providing; sending sixth indication information to the network device, the sixth indication information being used for indicating type information selected from the at least one type of information.

14. The method of any one of claims 1-10, wherein, The determination configuration information comprises: receiving seventh indication information sent by the network device, the seventh indication information being used for indicating type information of the prior knowledge; sending eighth indication information to the network device, the eighth indication information being used for indicating whether to support processing data of the prior knowledge corresponding to the type information.

15. The method of any one of claims 1-14, wherein, The method further comprises: updating the type information according to a preset period.

16. The method of any one of claims 1-14, wherein, The method further comprises: updating the type information when a trigger condition is met, the trigger condition comprising at least one of the following changing: an application scenario, data of the prior knowledge or the local data.

17. A data processing method, characterized by, The method comprises: determining configuration information, the configuration information being used for indicating type information of prior knowledge, wherein the prior knowledge is obtained data or data processed based on the obtained data; sending data of the prior knowledge to a terminal device, the data of the prior knowledge corresponding to the type information, and the data of the prior knowledge being used for processing local data of the terminal device.

18. The method of claim 17, wherein, The type information comprises a prior knowledge type and / or a data form.

19. The method of claim 17 or 18, wherein, The type information corresponds to an application scenario, and the application scenario comprises at least one of the following: channel data transmission, artificial intelligence (AI) data transmission or perception data transmission.

20. The method of claim 17 or 18, wherein, The type information corresponds to a data type of the local data, and the data type comprises at least one of the following: AI data, perception data or channel data.

21. The method of any one of claims 17-20, wherein, The type information comprises first-order type information and second-order type information, and the second-order type information is a sub-type of the first-order type information.

22. The method of claim 20, wherein, The prior knowledge type corresponding to the perception data comprises at least one of the following: a dictionary, geometry, region division or semantics, wherein the sub-type corresponding to the dictionary comprises multi-dimensional weighting and single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting comprises dictionary dimension, dictionary data and sparsity; the sub-type corresponding to the geometry comprises a surface, and the data form corresponding to the surface comprises surface parameters and a scanned region on the surface; the sub-type corresponding to the region division comprises octree and voxel, the data form corresponding to the octree comprises octree data, and the data form corresponding to the voxel comprises voxel data; and the sub-type corresponding to the semantics comprises a 3D target box, and the data form corresponding to the 3D target box comprises a center position and range of the 3D target box and / or vertex coordinates of the 3D target box.

23. The method of claim 20, wherein, The prior knowledge type corresponding to the channel data comprises at least one of the following: a dictionary or region division, wherein the sub-type corresponding to the dictionary comprises multi-dimensional weighting and single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting comprises dictionary dimension, dictionary data and sparsity; and the sub-type corresponding to the region division comprises a bit map and quadtree, the data form corresponding to the bit map comprises bit map data, and the data form corresponding to the quadtree comprises quadtree data.

24. The method of claim 20, wherein, The prior knowledge type corresponding to the AI data comprises a dictionary and a pre-trained model, wherein the sub-type corresponding to the dictionary comprises multi-dimensional weighting and single-dimensional dictionary, the data form corresponding to the multi-dimensional weighting comprises dictionary dimension, dictionary data and sparsity; and the data form corresponding to the pre-trained model comprises model parameters.

25. The method of any one of claims 17-24, wherein, The determination configuration information comprises: receiving indication information sent by the terminal device, or sending indication information to the terminal device, wherein the indication information is used to indicate the type information.

26. The method of claim 25, wherein, The indication information comprises an application scenario or a data type, or the indication information comprises a first index used to indicate at least one type information in a pre-configured prior knowledge type mapping table, and the prior knowledge type mapping table comprises a mapping relationship between multiple type information and indexes.

27. The method of any one of claims 17-26, wherein, The determination configuration information comprises: receiving first indication information sent by the terminal device, the first indication information being used to indicate at least one type information of the prior knowledge supported by the terminal device; sending second indication information to the terminal device, the second indication information being used to indicate type information selected from the at least one type information.

28. The method of any one of claims 17-26, wherein, The determination configuration information comprises: receiving third indication information sent by the terminal device, the third indication information being used to indicate type information of the prior knowledge required by the terminal device; sending fourth indication information to the terminal device, the fourth indication information being used to indicate whether there is data of the prior knowledge corresponding to the type information.

29. The method of any one of claims 17-26, wherein, The determination configuration information comprises: sending fifth indication information to the terminal device, the fifth indication information being used to indicate at least one type information of the prior knowledge supported by the network device for providing; receive sixth indication information sent by the terminal device, the sixth indication information being used for indicating type information selected from the at least one type of information.

30. The method of any one of claims 17-26, wherein, The determination configuration information comprises: send seventh indication information to the terminal device, the seventh indication information being used for indicating type information of the priori knowledge; receive eighth indication information sent by the terminal device, the eighth indication information being used for indicating whether data of the type information corresponding to the priori knowledge is supported.

31. The method of any one of claims 17-30, wherein, The method further comprises: updating the type information according to a preset period.

32. The method of any one of claims 17-30, wherein, The method further comprises: updating the type information when a trigger condition is met, the trigger condition comprising at least one of the following changing: an application scenario, data of the priori knowledge, or the local data.

33. A data processing apparatus, characterized by: comprising a memory and a processor, the memory being used for storing a computer program, and the processor running the computer program to make the data processing apparatus execute the method in any one of claims 1-16.

34. A data processing apparatus, characterized in that, comprising a memory and a processor, the memory being used for storing a computer program, and the processor running the computer program to make the data processing apparatus execute the method in any one of claims 17-32.

35. A computer readable storage medium, characterized in that, The computer readable storage medium comprises a computer program, when the computer program is run by a processor, makes the method in any one of claims 1-16, or any one of claims 17-32 be realized.

36. A chip, characterized by The chip comprises a processor and a communication interface, the communication interface being used for communicating with external devices or internal devices, and the processor being used for realizing the method in any one of claims 1-16, or any one of claims 17-32.

37. A computer program product comprising instructions, wherein: When it is run on a computer, makes the computer execute the method in any one of claims 1-16, or any one of claims 17-32.

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