Data compression transmission method and device, equipment and storage medium

Abstract

The invention provides a data compression transmission method and device, equipment and a storage medium. The method comprises the following steps: a first communication device decomposes ith sub-data Yi into a dictionary matrix Di and a sparse matrix Xi for ith sub-data Yi in M sub-data, the sparse matrix Xi is used for expressing the ith sub-data Yi based on the dictionary matrix Di, the M sub-data is included in first data to be transmitted, M is an integer greater than or equal to 1, i is greater than or equal to 1, and M is an integer greater than or equal to 1; m is an integer which is smaller than or equal to M, performing data compression according to the dictionary matrix Di and the sparse matrix Xi to obtain compressed data Zi of the ith sub-data Yi, and sending the compressed data Zi to the second communication device. Effective and reliable data compression transmission of the first data with a large data volume is realized.

Description

Data compression transmission method, device, equipment and storage medium

[0001] The present application relates to the field of communication technology, and in particular to a data compression transmission method, device, equipment and storage medium.

[0002] At present, in some communication scenarios, such as the transmission scenario of point cloud data or the transmission scenario of artificial intelligence (AI) model data (hereinafter referred to as AI model data), when the data transmitted between communication devices is large, it will occupy more transmission resources and increase the transmission delay. Based on this, before data transmission, the data to be transmitted can be compressed by scalar quantization or vector quantization, and then the compressed data can be transmitted to save transmission resources and reduce transmission delay. However, when the data to be transmitted is compressed by scalar quantization or vector quantization, the compression rate is low and the compressed data has a large data loss. Therefore, how to achieve effective and reliable data compression transmission is a problem that needs to be solved urgently.

[0003]

[0004] The embodiments of the present application provide a data compression transmission method, device, equipment and storage medium, which can realize effective and reliable data compression transmission.

[0005] In a first aspect, the present application provides a data compression transmission method, comprising: a first communication device transmits an i-th sub-data Y among M sub-data i , the i-th sub-data Y i Decompose into dictionary matrix D i and the sparse matrix X i , the dictionary matrix D i Including the i-th sub-data Y i The features of this sparse matrix X i Based on the dictionary matrix D i Express the i-th sub-data Y i , the M sub-data are included in the first data to be transmitted, M is an integer greater than or equal to 1, i is an integer greater than or equal to 1 and less than or equal to M; the first communication device according to the dictionary matrix D i And the sparse matrix X i Perform data compression to obtain the i-th sub-data Y i The compressed data Z i The first communication device sends the compressed data Z to the second communication device i .

[0006] According to the data compression transmission method provided in the first aspect, the first communication device divides the first data to be transmitted into M sub-data, and for the i-th sub-data Y in the M sub-data i , decompose it into a dictionary matrix D i and the sparse matrix X i , and then according to the dictionary matrix D i and the sparse matrix X i Perform data compression to obtain the i-th sub-data Y i The compressed data Z i , and then send the i-th sub-data Y to the second communication device i The compressed data Z i , through the sparse matrix X i Based on the dictionary matrix D i Express the i-th sub-data Y i , so as to realize effective and reliable data compression transmission of first data with a large amount of data in a communication scenario with a large amount of data to be transmitted.

[0007] In a possible implementation manner, the first communication device uses the dictionary matrix D i And the sparse matrix X i Perform data compression to obtain the i-th sub-data Y i The compressed data Z i , including: the first communication device determines the sparse matrix X i The first position indication information and the first element sequence of the sparse matrix X are as follows; wherein the first position indication information is used to indicate the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The first element sequence includes a first capability of expressing the i-th sub-data Y i or, the first position indication information is used to indicate the sparse matrix X i Does the first element in have the expression of the i-th sub-data Y i The first capability is that the sparse matrix X i The elements in include the first element, and the first element sequence includes the expression of the i-th sub-data Y i The first element of the first capability of the first communication device to the dictionary matrix D i , and the sparse matrix X i The first position indication information and the first element sequence of , data compression is performed to obtain the i-th sub-data Y i The first compressed data Z i '.

[0008] In this embodiment, the i-th sub-data Y is retained. iThe first element of the first capability or the first element, and indicates that the ith child data Y i The first element of the capability or the position indication information of the first element is deleted without the i-th sub-data Y i The first element of the first capacity or the first element increases the first compressed data Z i Compression ratio.

[0009] In a possible implementation manner, the first position indication information is a first bitmap; the bits in the first bitmap are consistent with the sparse matrix X i The elements in the first bit map correspond one to one, and the bit in the first bit map is used to indicate the sparse matrix X i Does the corresponding element in have the expression of the i-th sub-data Y i or the first bit in the first bitmap and the sparse matrix X i The first element in the first bit map corresponds to the first element in the sparse matrix X. i Whether the first element corresponding to the expression has the i-th sub-data Y i The first ability.

[0010] In this implementation, the first bitmap is used to implement the first element sequence in the sparse matrix X. i The exact position of the

[0011] In a possible implementation manner, the first communication device determines the sparse matrix X i The first position indication information and the first element sequence of the first communication device for the sparse matrix X i For each element in , according to the element and the first capability threshold, determining whether the element has the first capability of expressing the i-th sub-data Yi; the first communication device determines whether the element has the first capability of expressing the i-th sub-data Yi according to the sparse matrix X i Whether each element in has the function of expressing the i-th sub-data Y i The first capability is to determine the first position indication information and the first element sequence.

[0012] This implementation can be used for the sparse matrix X i Whether each element in has the first ability to be accurately identified.

[0013] In one possible implementation, the sparse matrix X i The first position indication information is the i-th sub-data Y i The first position indication information and the i-1th sub-data Y i-1 The first position indication information is XORed with the difference position indication information obtained; the difference position indication information is used as the sparse matrix X i The first position indication information.

[0014] This implementation can further improve the compression performance.

[0015] In a possible implementation manner, the difference position indication information is a difference bitmap, and the difference position indication information is used as the sparse matrix X i The first position indication information of the difference bitmap includes: when the first ratio of the difference bitmap position indication information is greater than or equal to the ratio threshold, the first communication device uses the difference position indication information as the sparse matrix X i The first position indication information of the difference position indication information is the ratio of the number of bits of the first value or the second value to the number of all bits in the bits of the difference position indication information, and the first value is used to indicate the sparse matrix X i The corresponding element in has the expression of the i-th sub-data Y i The first capability of the sparse matrix X i The corresponding element in does not have the expression of the i-th sub-data Y i The first ability.

[0016] In this implementation, when the compression rate of the differential position indication information is greater than that of the first position indication information, the first position indication information is replaced with the differential position indication information to ensure that the operation of replacing the position indication information can improve the compression rate.

[0017] In a possible implementation manner, the first position indication information is used to indicate the sparse matrix X i Does the first element in have the expression of the i-th sub-data Y i The first capability is that the sparse matrix X i The elements of X include a second element, the second element is different from the first element, the method further includes: the first communication device determines the sparse matrix X i The second position indication information and the second element sequence are used to indicate the sparse matrix X i Does the second element in have the expression of the i-th sub-data Y i The first capability of the second element sequence includes the first element sequence having the function of expressing the i-th sub-data Y i The first communication device performs data compression on the second position indication information and the second element sequence to obtain the i-th sub-data Y i The second compressed data Z i ", the second compressed data Z i " and the first compressed data Z i 'different.

[0018] In this embodiment, the first communication device compresses and transmits the second element with the first capability and the second position indication information indicating the position of the second element, so as to avoid the situation where the second element sequence and the second position indication information cannot be transmitted due to limited transmission resources, or when only the first compressed data is transmitted, the content of the transmitted first data is small, resulting in a large difference between the second data constructed by the second communication device and the first data (that is, the quality of the constructed second data is poor).

[0019] In a possible implementation manner, the second position indication information is a second bitmap, and the bits in the second bitmap are consistent with the sparse matrix X i The second element in the second bitmap corresponds to each other, and the bits in the second bitmap are used to indicate the sparse matrix X i Whether the corresponding second element in has the expression of the i-th sub-data Y i The first ability.

[0020] In this embodiment, the second element with the first capability is mapped to the sparse matrix X by the second bitmap. i The position in the

[0021] In a possible implementation, the method further includes: determining, by the first communication device, the sparse matrix X i The third position indication information and the third element sequence of the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The third element sequence includes a second capability of expressing the i-th sub-data Y i The first communication device is a sparse matrix X i The third position indication information and the third element sequence are compressed to obtain the i-th sub-data Y i The third compressed data Z i ” '; The first communication device sends the third compressed data Z to the second communication device i ”'.

[0022] In this embodiment, the first communication device compresses and transmits the element with the second capability and the third position indication information indicating the element with the second capability, so as to supplement the content of the first data by transmitting the third compressed data on the basis of the first compressed data, so that the second data constructed by the second communication device is significantly different from the first data (that is, the quality of the constructed second data is poor).

[0023] In a possible implementation manner, the third position indication information is a third bitmap, and the bits in the third bitmap are consistent with the sparse matrix X iThe elements in the third bitmap correspond one to one, and the bits in the third bitmap are used to indicate the sparse matrix X i Does the corresponding element in have the expression of the i-th sub-data Y i The second ability.

[0024] In this implementation, the sparse matrix X is mapped to the sparse matrix X by the third bitmap. i The i-th sub-data Y i The elements of the second ability are accurately indicated.

[0025] In a possible implementation manner, the first communication device determines the sparse matrix X i The third position indication information and the third element sequence of the first communication device for the sparse matrix X i For each element in , according to the element, the first capability threshold and the second capability threshold, determine whether the element has the ability to express the i-th sub-data Y i The first communication device according to the sparse matrix X i Whether each element in has the function of expressing the i-th sub-data Y i The second capability determines the third position indication information and the third element sequence.

[0026] In this embodiment, the sparse matrix X i Whether the elements in have the second ability to be accurately identified.

[0027] In a possible implementation, the method further includes: determining, by the first communication device, the sparse matrix X i The third element sequence of the sparse matrix X i N elements other than the elements included in the first element sequence, where N is a positive integer; the first communication device performs data compression on the third element sequence to obtain the i-th sub-data Y i The third compressed data Z i ” '; The first communication device sends the third compressed data Z to the second communication device i ”'.

[0028] In this implementation, the second compressed data does not include location indication information, thereby reducing resource overhead.

[0029] In a possible implementation, the N elements are the sparse matrix X i Elements in a preset row / column in .

[0030] This implementation is conducive to the first communication device and the second communication device to agree on the positions of the N elements.

[0031] In a possible implementation manner, the number of columns of the matrix formed by each sub-data in the M sub-data is the same.

[0032] This implementation can reduce the complexity of data processing of the first communication device and the second communication device.

[0033] In a possible implementation, the first data includes point cloud data, and the M sub-data are obtained by dividing the first data according to the distance between each spatial point in the first data in the Euclidean space; or, the first data includes artificial intelligence AI model data, and the M sub-data are obtained by dividing the first data according to the neural network layer in which each data in the first data is located.

[0034] This implementation can reduce the complexity of data processing of the first communication device and the second communication device.

[0035] In a possible implementation, the first data includes point cloud data, and the method further includes: the first communication device uses cubes with preset side lengths to spatially divide the Euclidean space where the initial point cloud data is located, and uses the geometric center of the spatial point in each cube as the sampling point of the cube; the first communication device determines the first data based on the sampling points of each cube.

[0036] This implementation reduces the amount of point cloud data to improve the compression and transmission efficiency of the point cloud data.

[0037] In a possible implementation, the method further includes: the first communication device sending an upload request to the second communication device, the upload request carrying second indication information and first indication information, the first indication information being used to indicate a data type of the first data.

[0038] This implementation makes it easy for the second communication device to determine the time-frequency resources for transmitting compressed data of the first data based on the first indication information, so that the time-frequency resources for the compressed data of the first data configured by the second communication device meet the data type of the first data, thereby facilitating the transmission of the compressed data of the first data.

[0039] Optionally, the data type includes point cloud data or AI model data.

[0040] In a possible implementation, the method further includes: the first communication device receives resource configuration information sent by the second communication device, the resource configuration information is used to indicate the time-frequency resources of the compressed data of the M sub-data; and the first communication device sends the compressed data of the first data on the time-frequency resources.

[0041] The data compression transmission method provided in this embodiment enables flexible configuration of transmission resources for compressed data.

[0042] In a possible implementation manner, the method further includes: the first communication device determines a compression parameter according to the time-frequency resource of the first data; the first communication device performs compression on the i-th sub-data Y according to the compression parameter i Perform data compression to obtain the compressed data Z i ; Wherein, the compression parameter includes at least one of the following: a first capability threshold, the first capability threshold is used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i A first capability; a second capability threshold, the second capability threshold is used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i the second capability; the encoding method parameter; the quantization precision parameter; or the number of columns of sub-data.

[0043] Through the data compression transmission method provided by this implementation, compression parameters are determined based on the time-frequency resources of the first data, thereby reducing the signaling overhead of configuring the compression parameters.

[0044] In a possible implementation manner, the method further includes: the first communication device sending third indication information and second indication information to the second communication device, the third indication information and the second indication information are used to indicate at least one of the following: a first capability threshold, the first capability threshold is used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i A first capability; a second capability threshold, the second capability threshold is used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The second capability of sparse matrix X i The i-th sub-data Y i The proportion of elements of the first capability; the compressed data Z i Relative to the first i sub-data Y i Data loss; encoding method parameters; quantization precision parameters; number of columns of sub-data; or, the sparse matrix X i Whether the bitmap position indication information is the difference bitmap position indication information.

[0045] The data compression transmission method provided in this embodiment makes it easier for the second communication device to accurately restore the first data based on the received compressed data of the first data, thereby improving the stability of data transmission.

[0046] In a second aspect, an embodiment of the present application provides a data compression transmission method, comprising: a second communication device receives an i-th sub-data Y of M sub-data sent by a first communication device; i The compressed data Zi , the M sub-data are included in the second first data, M is an integer greater than or equal to 1, i is an integer greater than or equal to 1 and less than or equal to M; the second communication device according to the compressed data Z i Determine the dictionary matrix D i ' and the sparse matrix X i ', the dictionary matrix D i 'Including the i-th sub-data Y i ' features, the sparse matrix X i 'For the dictionary matrix D i 'Express the i-th sub-data Y i '; The second communication device according to the dictionary matrix D i ' and the sparse matrix X i ', construct the i-th sub-data Y of the M sub-data of the second data i '.

[0047] In a possible implementation, the compressed data Z i Including the first compressed data Z i ', the second communication device according to the compressed data Z i Determine the dictionary matrix D i ' and the sparse matrix X i ', comprising: the second communication device transmits the first compressed data Z i 'Unzip to get the dictionary matrix D i ', and, the sparse matrix X i 'The first position indication information and the first element sequence; wherein the first position indication information is used to indicate the sparse matrix X i 'Whether the element in has the i-th sub-data Y among the M sub-data expressing the first data i 'The first capability; the first element sequence includes a sequence having the expression of the i-th sub-data Y i 'The first capability of the element; or, the first position indication information is used to indicate the sparse matrix X i 'Whether the first element in has the expression of the i-th sub-data Y i 'The first capability, the sparse matrix X i ' includes the first element, and the first element sequence includes the expression of the i-th sub-data Y i 'The first element of the first capability; The second communication device according to the sparse matrix X i 'The first position indication information and the first element sequence determine the sparse matrix X i '.

[0048] In a possible implementation manner, the first position information is a first bitmap; the bits in the first bitmap arei The elements in the ' correspond one to one, and the bit in the first bit map is used to indicate the sparse matrix X i 'Whether the corresponding element in has the expression of the i-th sub-data Y i 'first capability; or, the bits in the first bitmap and the sparse matrix X i ' corresponds to the first element in one-to-one correspondence, and the bit in the first bit map is used to indicate the sparse matrix X i 'Whether the corresponding first element in the expression has the i-th sub-data Y i 'First ability.

[0049] In one possible implementation, the sparse matrix X i The first position indication information is the difference position indication information obtained by performing an XOR operation on the first position indication information of the i-th sub-data and the first position indication information of the i-1-th sub-data.

[0050] In a possible implementation, the compressed data Z i Also includes the second compressed data Z i ", the first position indication information is used to indicate the sparse matrix X i 'Whether the first element in has the expression of the i-th sub-data Y i ' first capability, the second communication device according to the first compressed data Z i Determine the dictionary matrix D i ' and the sparse matrix X i ', comprising: the second communication device transmits the second compressed data Z i "Unzip and get the sparse matrix X i ', the second position indication information and the second element sequence, the second position indication information is used to indicate the sparse matrix X i 'Whether the second element in has the expression of the i-th sub-data Y i ', the second element sequence includes a sequence having the function of expressing the i-th sub-data Y i 'The second element of the first capability; the second communication device according to the sparse matrix X i ', the first position indication information, the first element sequence, the second position indication information and the second element sequence, determine the sparse matrix X i '.

[0051] In a possible implementation manner, the second position indication information is a second bitmap, and the bits in the second bitmap are consistent with the sparse matrix X i ' has a one-to-one correspondence with the second element in the second bitmap, and the bits in the second bitmap are used to indicate the sparse matrix X i 'Whether the corresponding second element has the expression of the i-th sub-data Y iThe first ability.

[0052] In a possible implementation, the compressed data Z i Also includes the third compressed data Z i "', the second communication device according to the first compressed data Z i Determine the dictionary matrix D i ' and the sparse matrix X i ', comprising: the second communication device transmits the third compressed data Z i ”'Unzip and get the sparse matrix X i ', the third position indication information and the third element sequence, the third position indication information is used to indicate the sparse matrix X i 'Whether the element in has the expression of the i-th sub-data Y i The second element sequence includes a second capability of expressing the i-th sub-data Y i The second communication device is based on the sparse matrix X i ', the third position indication information, the third element sequence, and at least one of the following, determine the sparse matrix X i ': The sparse matrix X i 'The first position indication information, the first element sequence; or, the sparse matrix X i 'The second position indication information, the second element sequence.

[0053] In a possible implementation manner, the third position indication information is a third bitmap, and the bits in the third bitmap are consistent with the sparse matrix X i The elements in ' correspond one to one, and the bits in the third bitmap are used to indicate the sparse matrix X i 'Whether the corresponding element in has the expression of the i-th sub-data Y i The second ability.

[0054] In a possible implementation, the compressed data Z i Also includes the third compressed data Z i "', the second communication device according to the first compressed data Z i Determine the dictionary matrix D i ' and the sparse matrix X i ', comprising: the second communication device transmits the third compressed data Z i ”'Unzip and get the sparse matrix X i ', the third element sequence includes the sparse matrix X i 'N elements other than the elements included in the first element sequence and / or the second element sequence, where N is a positive integer; the second communication device calculates the number of N elements in the sparse matrix X according to the sparse matrix X. i'The third element sequence and at least one of the following determine the sparse matrix X i ': The sparse matrix X i 'The first position indication information, the first element sequence; or, the sparse matrix X i 'The second position indication information, the second element sequence.

[0055] In a possible implementation, the N elements are the sparse matrix X i Elements in a preset row / column in .

[0056] In a possible implementation manner, the number of columns of the matrix formed by each sub-data in the M sub-data is the same.

[0057] In a possible implementation, the first data includes point cloud data, and the M sub-data are obtained by dividing the first data according to the distance between each spatial point in the first data in the Euclidean space; or, the first data includes artificial intelligence AI model data, and the M sub-data are obtained by dividing the first data according to the neural network layer in which each data in the first data is located.

[0058] In a possible implementation, the method further includes: the second communication device receiving an upload request sent by the first communication device, the upload request carrying first indication information, and the first indication information is used to indicate a data type of the first data.

[0059] In one possible implementation, the data type includes point cloud data or AI model data.

[0060] In a possible implementation manner, the method further includes: the second communication device sending first resource configuration information to the first communication device, the first resource configuration information being used to indicate a first time-frequency resource for the compressed data of the M sub-data; the second communication device transmitting and receiving the compressed data Z on the first time-frequency resource i .

[0061] In a possible implementation manner, the method further includes: the second communication device receiving third indication information and second indication information sent by the first communication device, where the third indication information and the second indication information are used to indicate at least one of the following:

[0062] A first capability threshold is used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The first ability;

[0063] The second capability threshold is used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y iThe second ability;

[0064] Sparse matrix X i The i-th sub-data Y i The proportion of the elements of the first ability;

[0065] The compressed data Z i Relative to the i-th sub-data Y of the M sub-data of the first data i data loss;

[0066] Encoding parameters;

[0067] Quantization accuracy parameters;

[0068] The number of columns of the sub-data;

[0069] The sparse matrix X i Whether the bitmap is the difference bitmap.

[0070] In a possible implementation, the second data is point cloud data, and the method further includes: when the distance between two adjacent spatial points of the second data in the Euclidean space is greater than or equal to a second distance threshold, the second communication device interpolates between the two adjacent spatial points.

[0071] In a possible implementation, the second communication device interpolates between the two adjacent spatial points, including: the second communication device adds a spatial point at the intersection of the line connecting the two adjacent spatial points and the edge line of a circle, and the circle in the Euclidean space has one of the two adjacent spatial points as the center and a third distance threshold as the radius.

[0072] The beneficial effects of the data compression transmission method provided by the second aspect and each possible implementation manner of the second aspect can be referred to the beneficial effects brought about by the first aspect and each possible implementation manner of the first aspect, and will not be repeated here.

[0073] In a third aspect, an embodiment of the present application provides a communication device, comprising: a processing module, for processing an i-th sub-data Y among M sub-data i , the i-th sub-data Y i Decompose into dictionary matrix D i and the sparse matrix X i , the dictionary matrix D i Including the i-th sub-data Y i The features of this sparse matrix X i Based on the dictionary matrix D i Express the i-th sub-data Y i, the M sub-data are included in the first data to be transmitted, M is an integer greater than or equal to 1, i is an integer greater than or equal to 1 and less than or equal to M; the processing module is also used to i And the sparse matrix X i Perform data compression to obtain the i-th sub-data Y i The compressed data Z i ; A transceiver module for sending the compressed data Z to the second communication device i .

[0074] In a possible implementation manner, the processing module is specifically used to: determine the sparse matrix X i The first position indication information and the first element sequence of the sparse matrix X are as follows; wherein the first position indication information is used to indicate the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The first element sequence includes a first capability of expressing the i-th sub-data Y i or, the first position indication information is used to indicate the sparse matrix X i Does the first element in have the expression of the i-th sub-data Y i The first capability is that the sparse matrix X i The elements in include the first element, and the first element sequence includes the expression of the i-th sub-data Y i The first element of the first capability of the dictionary matrix D i , and the sparse matrix X i The first position indication information and the first element sequence of , data compression is performed to obtain the i-th sub-data Y i The first compressed data Z i '.

[0075] In a possible implementation manner, the first position indication information is a first bitmap; the bits in the first bitmap are consistent with the sparse matrix X i The elements in the first bit map correspond one to one, and the bit in the first bit map is used to indicate the sparse matrix X i Does the corresponding element in have the expression of the i-th sub-data Y i or the first bit in the first bitmap and the sparse matrix X i The first element in the first bit map corresponds to the first element in the sparse matrix X. i Whether the first element corresponding to the expression has the i-th sub-data Y i The first ability.

[0076] In a possible implementation manner, the processing module is specifically configured to: for the sparse matrix X iFor each element in , according to the element and the first capability threshold, determine whether the element has the ability to express the i-th sub-data Y i The first capability; according to the sparse matrix X i Whether each element in has the function of expressing the i-th sub-data Y i The first capability is to determine the first position indication information and the first element sequence.

[0077] In a possible implementation manner, the processing module is further configured to: i The first position indication information and the i-1th sub-data Y i-1 The first position indication information is XORed to obtain the difference position indication information; the difference position indication information is used as the sparse matrix X i The first position indication information.

[0078] In a possible implementation manner, the processing module is specifically configured to: when the first ratio of the difference position indication information is greater than or equal to the ratio threshold, use the difference position indication information as the sparse matrix X i The first position indication information of the difference position indication information is the ratio of the number of bits of the first value or the second value to the number of all bits in the bits of the difference position indication information, and the first value is used to indicate the sparse matrix X i The corresponding element in has the expression of the i-th sub-data Y i The first capability of the sparse matrix X i The corresponding element in does not have the expression of the i-th sub-data Y i The first ability.

[0079] In a possible implementation manner, the first position indication information is used to indicate the sparse matrix X i Does the first element in have the expression of the i-th sub-data Y i The first capability is that the sparse matrix X i The elements of X include a second element, the second element is different from the first element, and the processing module is also used to determine the sparse matrix X i The second position indication information and the second element sequence are used to indicate the sparse matrix X i Does the second element in have the expression of the i-th sub-data Y i The first capability of the second element sequence includes the first element sequence having the function of expressing the i-th sub-data Y i The processing module is also used to compress the second position indication information and the second element sequence to obtain the i-th sub-data Y i The second compressed data Z i ", the second compressed data Zi " and the first compressed data Z i 'different.

[0080] In a possible implementation manner, the second position indication information is a second bitmap, and the bits in the second bitmap are consistent with the sparse matrix X i The second element in the second bitmap corresponds to each other, and the bits in the second bitmap are used to indicate the sparse matrix X i Whether the corresponding second element in has the expression of the i-th sub-data Y i The first ability.

[0081] In a possible implementation, the processing module is further configured to determine the sparse matrix X i The third position indication information and the third element sequence of the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The third element sequence includes a second capability of expressing the i-th sub-data Y i The processing module is also used to process the sparse matrix X i The third position indication information and the third element sequence are compressed to obtain the i-th sub-data Y i The third compressed data Z i The transceiver module is also used to send the third compressed data Z to the second communication device. i ”'.

[0082] In a possible implementation manner, the third position indication information is a third bitmap, and the bits in the third bitmap are consistent with the sparse matrix X i The elements in the third bitmap correspond one to one, and the bits in the third bitmap are used to indicate the sparse matrix X i Does the corresponding element in have the expression of the i-th sub-data Y i The second ability.

[0083] In a possible implementation manner, the processing module is specifically configured to: for the sparse matrix X i For each element in , according to the element, the first capability threshold and the second capability threshold, determine whether the element has the ability to express the i-th sub-data Y i The second capability; according to the sparse matrix X i Whether each element in has the function of expressing the i-th sub-data Y i The second capability determines the third position indication information and the third element sequence.

[0084] In a possible implementation, the processing module is further configured to determine the sparse matrix X i The third element sequence of the sparse matrix Xi N elements other than the elements included in the first element sequence, where N is a positive integer; the processing module is also used to perform data compression on the third element sequence to obtain the i-th sub-data Y i The third compressed data Z i The transceiver module is also used to send the third compressed data Z to the second communication device. i ”'.

[0085] In a possible implementation, the N elements are the sparse matrix X i Elements in a preset row / column in .

[0086] In a possible implementation manner, the number of columns of the matrix formed by each sub-data in the M sub-data is the same.

[0087] In a possible implementation, the first data includes point cloud data, and the M sub-data are obtained by dividing the first data according to the distance between each spatial point in the first data in the Euclidean space; or, the first data includes artificial intelligence AI model data, and the M sub-data are obtained by dividing the first data according to the neural network layer in which each data in the first data is located.

[0088] In a possible implementation, the first data includes point cloud data, and the processing module is also used to use cubes with preset side lengths to spatially divide the Euclidean space where the initial point cloud data is located, and use the geometric center of each spatial point in the cube as the sampling point of the cube; the processing unit is also used to determine the first data based on the sampling points of each cube.

[0089] In a possible implementation, the transceiver module is further used to send an upload request to the second communication device, where the upload request carries first indication information, and the first indication information is used to indicate a data type of the first data.

[0090] In one possible implementation, the data type includes point cloud data or AI model data.

[0091] In a possible implementation, the transceiver module is also used to receive resource configuration information sent by the second communication device, and the resource configuration information is used to indicate the time-frequency resources of the compressed data of the M sub-data; the transceiver module is also used to send the compressed data on the first time-frequency resources.

[0092] In a possible implementation manner, the processing module is further configured to determine a compression parameter according to the time-frequency resource of the first data; the processing module is further configured to process the i-th sub-data Y according to the compression parameter. i Perform data compression to obtain the compressed data Z i; Wherein, the compression parameter includes at least one of the following:

[0093] A first capability threshold is used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The first ability;

[0094] The second capability threshold is used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The second ability;

[0095] Encoding parameters;

[0096] Quantization accuracy parameters;

[0097] The number of columns of the subdata.

[0098] In a possible implementation manner, the transceiver module is further used to send second indication information to the second communication device, where the second indication information is used to indicate at least one of the following:

[0099] A first capability threshold is used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The first ability;

[0100] The second capability threshold is used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The second ability;

[0101] Sparse matrix X i The i-th sub-data Y i The proportion of the elements of the first ability;

[0102] The compressed data Z i Relative to the i-th sub-data Y i data loss;

[0103] Encoding parameters;

[0104] Quantization accuracy parameters;

[0105] The number of columns of the sub-data;

[0106] The sparse matrix X i Whether the position indication information is differential position indication information.

[0107] The beneficial effects of the communication device provided by the third aspect and each possible implementation manner of the third aspect can be referred to the beneficial effects brought about by the first aspect, the second aspect or each possible implementation manner, which will not be repeated here.

[0108] In a fourth aspect, an embodiment of the present application provides a communication device, comprising: a transceiver module, configured to receive the i-th sub-data Y of the M sub-data sent by the first communication device; i The compressed data Z i , the M sub-data are included in the first data, M is an integer greater than or equal to 1, i is an integer greater than or equal to 1 and less than or equal to M; a processing module is used to compress the compressed data Z i Determine the dictionary matrix D i ' and the sparse matrix X i ', the dictionary matrix D i 'Including the i-th sub-data Y i The features of this sparse matrix X i 'For the dictionary matrix D i 'Express the i-th sub-data Y i The processing module is also used to calculate the dictionary matrix D i ' and the sparse matrix X i ', construct the i-th sub-data Y of the M sub-data of the second data i '.

[0109] In a possible implementation, the compressed data Z i Including the first compressed data Z i ', the processing module is specifically used to: the first compressed data Z i 'Unzip to get the dictionary matrix D i ', and, the sparse matrix X i 'The first position indication information and the first element sequence; wherein the first position indication information is used to indicate the sparse matrix X i 'Whether the element in has the i-th sub-data Y among the M sub-data expressing the first data i The first element sequence includes a first capability of expressing the i-th sub-data Y i or, the first position indication information is used to indicate the sparse matrix X i 'Whether the first element in has the expression of the i-th sub-data Y i The first capability is that the sparse matrix X i ' includes the first element, and the first element sequence includes the expression of the i-th sub-data Y i The first element of the first capability; according to the sparse matrix X i'The first position indication information and the first element sequence determine the sparse matrix X i '.

[0110] In a possible implementation manner, the first position information is a first bitmap; the bits in the first bitmap are i The elements in the ' correspond one to one, and the bit in the first bit map is used to indicate the sparse matrix X i 'Whether the corresponding element in has the expression of the i-th sub-data Y i or the first bit in the first bitmap and the sparse matrix X i ' corresponds to the first element in one-to-one correspondence, and the bit in the first bit map is used to indicate the sparse matrix X i 'Whether the corresponding first element in the expression has the i-th sub-data Y i The first ability

[0111] In one possible implementation, the sparse matrix X i The first position indication information is the difference position indication information obtained by performing an XOR operation on the first position indication information of the i-th sub-data and the first position indication information of the i-1-th sub-data.

[0112] In a possible implementation, the compressed data Z i Also includes the second compressed data Z i ", the first position indication information is used to indicate the sparse matrix X i 'Whether the first element in has the expression of the i-th sub-data Y i The processing module is specifically used to: compress the second compressed data Z i "Unzip and get the sparse matrix X i ', the second position indication information and the second element sequence, the second position indication information is used to indicate the sparse matrix X i 'Whether the second element in has the expression of the i-th sub-data Y i The first capability of the second element sequence includes the first element sequence having the function of expressing the i-th sub-data Y i The second element of the first capacity; according to the sparse matrix X i ', the first position indication information, the first element sequence, the second position indication information and the second element sequence, determine the sparse matrix X i '.

[0113] In a possible implementation manner, the second position indication information is a second bitmap, and the bits in the second bitmap are consistent with the sparse matrix X i ' has a one-to-one correspondence with the second element in the second bitmap, and the bits in the second bitmap are used to indicate the sparse matrix X i'Whether the corresponding second element has the expression of the i-th sub-data Y i The first ability.

[0114] In a possible implementation, the compressed data Z i Also includes the third compressed data Z i ” ', the processing module is specifically used to: the third compressed data Z i ”'Unzip and get the sparse matrix X i ', the third position indication information and the third element sequence, the third position indication information is used to indicate the sparse matrix X i 'Whether the element in has the expression of the i-th sub-data Y i The second element sequence includes a second capability of expressing the i-th sub-data Y i The elements of the second capacity; according to the sparse matrix X i ', the third position indication information, the third element sequence, and at least one of the following, determine the sparse matrix X i ':

[0115] The sparse matrix X i 'First position indication information, first element sequence;

[0116] The sparse matrix X i 'The second position indication information, the second element sequence.

[0117] In a possible implementation manner, the third position indication information is a third bitmap, and the bits in the third bitmap are consistent with the sparse matrix X i The elements in ' correspond one to one, and the bits in the third bitmap are used to indicate the sparse matrix X i 'Whether the corresponding element in has the expression of the i-th sub-data Y i The second ability.

[0118] In a possible implementation, the compressed data Z i Also includes the third compressed data Z i ” ', the processing module is specifically used to: the third compressed data Z i ”'Unzip and get the sparse matrix X i ', the third element sequence includes the sparse matrix X i 'N elements other than the elements included in the first element sequence and / or the second element sequence, N is a positive integer; according to the sparse matrix X i 'The third element sequence and at least one of the following determine the sparse matrix X i ':

[0119] The sparse matrix X i'First position indication information, first element sequence;

[0120] The sparse matrix X i 'The second position indication information, the second element sequence.

[0121] In a possible implementation, the N elements are the sparse matrix X i Elements in a preset row / column in .

[0122] In a possible implementation manner, the number of columns of the matrix formed by each sub-data in the M sub-data is the same.

[0123] In a possible implementation, the first data includes point cloud data, and the M sub-data are obtained by dividing the first data according to the distance between each spatial point in the first data in the Euclidean space; or, the first data includes artificial intelligence AI model data, and the M sub-data are obtained by dividing the first data according to the neural network layer in which each data in the first data is located.

[0124] In a possible implementation, the transceiver unit is further used to receive an upload request sent by the first communication device, where the upload request carries first indication information, and the first indication information is used to indicate a data type of the first data.

[0125] In one possible implementation, the data type includes point cloud data or AI model data.

[0126] In a possible implementation manner, the transceiver module is further used to: send resource configuration information to the first communication device, the resource configuration information is used to indicate the time-frequency resource of the compressed data of the M sub-data; receive the compressed data Z on the time-frequency resource i .

[0127] In a possible implementation manner, the transceiver module is further used to: receive second indication information sent by the first communication device, where the second indication information is used to indicate at least one of the following:

[0128] A first capability threshold is used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The first ability;

[0129] The second capability threshold is used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The second ability;

[0130] Sparse matrix X i The i-th sub-data Y iThe proportion of the elements of the first ability;

[0131] The compressed data Z i Relative to the i-th sub-data Y of the M sub-data of the first data i data loss;

[0132] Encoding parameters;

[0133] Quantization accuracy parameters;

[0134] The number of columns of the sub-data;

[0135] The sparse matrix X i Whether the bitmap is the difference bitmap.

[0136] In a possible implementation, the second data is point cloud data, and the processing module is further used to: when the distance between two adjacent spatial points of the second data in the Euclidean space is greater than or equal to a second distance threshold, perform interpolation between the two adjacent spatial points.

[0137] In a possible implementation, the processing module is specifically used to: add a spatial point at the intersection of the line connecting the two adjacent spatial points and the edge line of a circle, and the circle in the Euclidean space has one of the two adjacent spatial points as the center and a third distance threshold as the radius.

[0138] The beneficial effects of the communication device provided by the fourth aspect and each possible implementation manner of the fourth aspect can be referred to the beneficial effects brought about by the first aspect, the second aspect or each possible implementation manner, and will not be repeated here.

[0139] In a fifth aspect, an embodiment of the present application provides a communication device, comprising: a processor, configured to execute a method in the first aspect, the second aspect or each possible implementation manner by running a computer program or through a logic circuit.

[0140] In a possible implementation, the communication device further includes: a memory, wherein the memory is used to store the computer program.

[0141] In a possible implementation, the communication device further includes: a communication interface, wherein the communication interface is used to input and / or output signals.

[0142] In a sixth aspect, an embodiment of the present application provides a communication system, comprising: a first communication device for executing the method in the first aspect or each possible implementation, and a second communication device for executing the method in the second aspect or each possible implementation.

[0143] In a seventh aspect, an embodiment of the present application provides a computer-readable storage medium for storing computer program instructions, wherein the computer program enables a computer to execute a method as described in the first aspect, the second aspect, or each possible implementation manner.

[0144] In an eighth aspect, an embodiment of the present application provides a computer program product, comprising computer program instructions, which enable a computer to execute a method as described in the first aspect, the second aspect, or each possible implementation manner.

[0145] In a ninth aspect, an embodiment of the present application provides a computer program, which enables a computer to execute a method as described in the first aspect, the second aspect, or each possible implementation manner.

[0146] FIG1 is a schematic diagram of the architecture of a mobile communication system to which an embodiment of the present application is applied.

[0147] FIG. 2 is a schematic diagram of a dictionary learning framework provided in an embodiment of the present application.

[0148] FIG3 is a schematic diagram of an interactive process of a data compression transmission method provided in an embodiment of the present application.

[0149] FIG4 is a schematic diagram of a process of data compression transmission provided in an embodiment of the present application.

[0150] FIG5 is a schematic diagram of data partitioning provided in an embodiment of the present application.

[0151] FIG6 is a schematic diagram of a data compression method based on dictionary learning provided in an embodiment of the present application.

[0152] FIG. 7 is a schematic diagram of a data compression method based on dictionary learning provided in an embodiment of the present application.

[0153] FIG8 is a schematic diagram of a data compression method based on dictionary learning provided in an embodiment of the present application.

[0154] FIG9 is a schematic diagram of a data compression method based on dictionary learning provided in an embodiment of the present application.

[0155] FIG10 is a schematic diagram of a data compression method based on dictionary learning provided in an embodiment of the present application.

[0156] FIG11 is a schematic diagram of a data compression method based on dictionary learning provided in an embodiment of the present application.

[0157] FIG12 is a schematic diagram of time domain resources for incremental transmission provided in an embodiment of the present application.

[0158] FIG. 13 is a schematic diagram of differential position indication information provided in an embodiment of the present application.

[0159] FIG. 14 is a schematic diagram of a layer sampling process provided in an embodiment of the present application.

[0160] FIG15 is a schematic diagram of another layer of sampling process provided in an embodiment of the present application.

[0161] FIG16 is a schematic diagram of an interpolation process provided in an embodiment of the present application.

[0162] FIG. 17 is a schematic diagram of an interactive process of another data compression transmission method provided in an embodiment of the present application.

[0163] FIG. 18 is a schematic block diagram of a communication device provided in an embodiment of the present application.

[0164] FIG. 19 is another schematic block diagram of a communication device provided in an embodiment of the present application.

[0165] The technical solution in this application will be described below in conjunction with the accompanying drawings.

[0166] FIG. 1 is a schematic diagram of the architecture of a mobile communication system used in an embodiment of the present application. As shown in FIG. 1 , the mobile communication system includes a core network device 110, a network device 120, and at least one terminal device (such as a terminal device 130 and a terminal device 140 in FIG. 1 ). The terminal device is connected to the network device wirelessly, and the network device is connected to the core network device wirelessly or by wire. The core network device and the network device may be independent and different physical devices, or the functions of the core network device and the logical functions of the network device may be integrated on the same physical device, or the functions of part of the core network device and part of the network device may be integrated on one physical device. The terminal device may be fixed or movable. FIG. 1 is only a schematic diagram, and the communication system may also include other network devices, such as wireless relay devices and wireless backhaul devices, which are not shown in FIG. The embodiment of the present application does not limit the number of core network devices, network devices, and terminal devices included in the mobile communication system.

[0167] In the embodiments of the present application, the network device may be any device with wireless transceiver functions. The network device includes, but is not limited to: an evolved Node B (eNB), a home base station (e.g., a home evolved NodeB, or a home Node B, HNB), a baseband unit (BBU), an access point (AP), a wireless relay node, a wireless backhaul node, a transmission point (TP) or a transmission and reception point (TRP) in a wireless fidelity (WiFi) system, a mobile switching center, and a device that performs base station functions in device-to-device (D2D), vehicle-to-everything (V2X), machine-to-machine (M2M) communication, and drone communication, etc., and a network device in a non-terrestrial network (NTN) communication system (i.e., it can be deployed on a high-altitude platform, a satellite, or a high-altitude aircraft). It can also be a gNB in ​​a 5G system, one or a group of antenna panels (including multiple antenna panels) of a base station in a 5G system, or it can also be a network node constituting a gNB or a transmission point, such as a BBU, or a distributed unit (DU), etc. The embodiments of the present application do not specifically limit this.

[0168] In some deployments, the gNB may include a centralized unit (CU) and a DU. The CU and DU implement some functions of the gNB respectively, and the CU and DU can communicate through the F1 interface. The gNB may also include an active antenna unit (AAU). The AAU can implement some physical layer processing functions, RF processing, and related functions of the active antenna.

[0169] It is understandable that the network device may be a device including one or more of a CU node, a DU node, and an AAU node. In addition, the CU may be classified as a network device in an access network (radio access network, RAN), or the CU may be classified as a network device in a core network (core network, CN), which is not limited in this application.

[0170] In an embodiment of the present application, the terminal device may also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent or user device.

[0171] The terminal device may be a device that provides voice / data connectivity to users, such as a handheld device or vehicle-mounted device with wireless connection function. At present, some examples of terminals can be: mobile phones, tablet computers (pads), computers with wireless transceiver functions (such as laptops, PDAs, etc.), drones, customer-premises equipment (CPE), smart point of sale (POS) machines, mobile Internet devices (MID), virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, wireless terminals in self driving, wireless terminals in remote medical, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, cellular phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), etc. assistant, PDA), handheld devices with wireless communication function, computing devices or other processing devices connected to a wireless modem, vehicle-mounted devices, wearable devices, terminal devices in 5G networks or terminal devices in systems evolved after 5G, etc.

[0172] The network device and the terminal device can communicate through the licensed spectrum, or through the unlicensed spectrum, or through both the licensed spectrum and the unlicensed spectrum. The network device and the terminal device can communicate through the spectrum below 6G, or through the spectrum of 6G and above, or through the spectrum below 6G and the spectrum of 6G and above at the same time. The embodiments of the present application do not limit the spectrum resources used between the network device and the terminal device.

[0173] It should be understood that the present application does not limit the specific forms of the network device and the terminal device.

[0174] The communication method provided in the present application can be applied to various communication systems, such as: Long Term Evolution (LTE) system, 5G mobile communication system, 6G and other mobile communication systems evolved after 5G. Among them, the 5G mobile communication system or the 6G mobile communication system may include non-standalone (NSA) and / or standalone (SA).

[0175] The communication method provided in the present application can also be applied to machine type communication (MTC), long term evolution technology for machine-to-machine communication (LTE-M), device to device (D2D) network, machine to machine (M2M) network, Internet of Things (IoT) network or other networks.

[0176] Point cloud data refers to a collection of spatial points in a three-dimensional coordinate system. For example, data is collected through a machine vision sensor and recorded in the form of points. Each spatial point contains three-dimensional coordinates and may contain color information (RGB), position information, reflection intensity information (intensity), etc. In a point cloud scene, a terminal device (such as 130 and / or 140 in FIG. 1 ) can collect data through sensors and transmit the collected data to a network device (such as 120 in FIG. 1 ), and the network device (such as 120 in FIG. 1 ) can reconstruct the point cloud data.

[0177] Federated learning is a distributed machine learning technology that builds a global model based on virtual fusion data by performing distributed model training between multiple data sources with local data, without exchanging local individual or sample data, only by exchanging model parameters or intermediate results, thereby achieving a balance between data privacy protection and data sharing calculation. The model parameters, AI gradients or intermediate results transmitted during the federated learning process can be referred to as AI model data. Of course, AI model data is only a possible naming method, and this application does not limit its name. For example, it can also be referred to as model data, AI data, etc. In a federated learning scenario, a terminal device (such as 130 and / or 140 in Figure 1) can transmit locally updated AI model data to a network device (such as 120 in Figure 1) to update a global AI model data.

[0178] Point cloud data and AI model data have large data volumes. Generally speaking, point cloud data can contain hundreds of thousands of spatial points, and AI model data can reach tens of millions of dimensions.

[0179] At present, there is a lack of effective and reliable compression transmission solutions for communication scenarios with large amounts of data transmission, such as point cloud scenarios and federated learning scenarios. In order to achieve effective and reliable data compression transmission, the embodiment of the present application divides the data to be transmitted into multiple sub-data, and converts at least one of the sub-data based on dictionary learning, and then compresses the converted data to achieve effective and reliable data compression of the data to be transmitted with a large amount of data.

[0180] It should be noted that the above examples are only used as an example to illustrate the uplink transmission of point cloud data and AI model data, but should not be understood as any limitation on the present application. For example, in a point cloud scenario, terminal device A (such as 130 in Figure 1) can send point cloud data to terminal device B (such as 140 in Figure 1) through forwarding by a network device (such as 120 in Figure 1); or, terminal device A can send point cloud data to terminal device B through a side link; for another example, in a federated learning scenario, a network device (such as 120 in Figure 1) can transmit locally updated AI model data to a terminal device (such as 130 and / or 140 in Figure 1).

[0181] To facilitate understanding of the present application, dictionary learning is firstly described by way of example.

[0182] FIG2 is a schematic diagram of a dictionary learning framework provided by an embodiment of the present application. As shown in FIG2, the source data Y can be represented by a matrix of L rows and Q columns, which can also be called a source matrix. Through the numerical iteration process of dictionary learning, the source data Y is decomposed into a dictionary matrix D and a sparse matrix X, that is, Y = DX. Each element in the matrix representation of the source data Y can be a floating point number.

[0183] The dictionary matrix D, or base, may be a matrix of L rows by L columns, and each column in the dictionary matrix D may be called a base vector. The dictionary matrix D includes features of the source data, for example, features of the source data are expressed by each base vector.

[0184] The sparse matrix X can express the source data based on the dictionary matrix D. The sparse matrix X uses a combination of basis vectors in the dictionary matrix D, for example, by weighting and combining the basis vectors in the dictionary matrix D to express the characteristics of the source data. The sparse matrix X is a matrix of L rows by Q columns, and each column vector in the sparse matrix X can express each column vector of the source matrix Y. For example, the first column vector l1 in the sparse matrix X can express y1 in the source matrix.

[0185] Each row vector in the sparse matrix X corresponds to each basis vector in the dictionary matrix D, and the values ​​of each row in a column of the sparse matrix X represent the weights of each basis vector of the dictionary matrix D. For example, the first column vector x1 in the sparse matrix X is used to express y1 in the source data Y, and the elements of each row in the first column vector of the sparse matrix X are x, 11 ,x 12, ……,x 1L , then x 11 The weight of the first basis vector d1 in the dictionary matrix used when the sparse matrix X expresses the source matrix Y.

[0186] The elements in the sparse matrix X can be represented or saved in a coordinate format. Each element can include the row, column, and value of the element in the sparse matrix X. Therefore, the elements in the sparse matrix X can also be called coordinates.

[0187] The more zero elements in the sparse matrix X, the less resources are occupied by information with low relevance to the learning task, so as to achieve better expression ability of the source data Y while reducing the overhead of storage resources and transmission resources. In this case, the sparse performance of the sparse matrix X is considered to be better.

[0188] The communication method provided in the embodiments of the present application will be described below with reference to the accompanying drawings.

[0189] It should be understood that the following is only for the convenience of understanding and explanation, and the method provided by the embodiment of the present application is explained by taking the interaction between the first communication device and the second communication device as an example. When the data compression transmission method provided by the embodiment of the present application is applied to uplink transmission, the first communication device can be any terminal device in the communication system shown in Figure 1, such as terminal device 130 or terminal device 140, and the second communication device can be the network device 120 in the communication system shown in Figure 1; when the data compression transmission method provided by the embodiment of the present application is applied to downlink transmission, the first communication device can be the network device 120 in the communication system shown in Figure 1, and the second communication device can be any terminal device in the communication system shown in Figure 1, such as terminal device 130 or terminal device 140; when the data compression transmission method provided by the embodiment of the present application is applied to side transmission, the first communication device can be any terminal device in the communication system shown in Figure 1, such as terminal device 130, and the second communication device can be any terminal device in the communication system shown in Figure 1 except the first communication device, such as terminal device 140.

[0190] It should also be understood that this should not constitute any limitation on the execution subject of the method provided in the present application. As long as the method provided in the embodiment of the present application can be executed by running a program having the code of the method provided in the embodiment of the present application, it can be used as the execution subject of the method provided in the embodiment of the present application. For example, any of the above-mentioned communication devices can be implemented as a terminal device or a component in a terminal device, such as a chip, a chip system, or other functional modules that can call and execute programs; any of the above-mentioned communication devices can be implemented as a network device or a component in a network device, such as a chip, a chip system, or other functional modules that can call and execute programs.

[0191] FIG3 is a schematic diagram of an interactive flow of a data compression transmission method provided in an embodiment of the present application. In conjunction with FIG3 , the method 200 includes some or all of the following processes:

[0192] S210: the first communication device receives the ith sub-data Y of the M sub-data. i , the i-th sub-data Y i Decompose into dictionary matrix D i and the sparse matrix X i , the dictionary matrix D i Including the i-th sub-data Y i The features of the sparse matrix X i For the dictionary matrix D i Express the i-th sub-data Y i , M sub-data are included in the first data to be transmitted, M is an integer greater than or equal to 1, and i is an integer greater than or equal to 1 and less than or equal to M.

[0193] S220, the first communication device calculates the dictionary matrix D i and the sparse matrix X i Perform data compression to obtain the i-th sub-data Y i The compressed data Z i .

[0194] S230, the first communication device sends compressed data Z to the second communication device i Correspondingly, the second communication device receives the i-th sub-data Y among the M sub-data sent by the first communication device. i The compressed data Z i .

[0195] S240, the second communication device compresses the data Z i Determine the dictionary matrix D i ' and the sparse matrix X i ', the dictionary matrix D i 'Including the i-th sub-data Y i The features of the sparse matrix X i 'For dictionary-based matrix D i 'Express the i-th sub-data Y i .

[0196] S250, the second communication device determines the dictionary matrix D i ' and the sparse matrix X i ', construct the i-th sub-data Y of the M sub-data of the second data i '.

[0197] In the embodiment of the present application, constructing the second data can be expressed as restoring the first data to obtain the second data, and for the convenience of expression, the meaning expressed after changing the word order is consistent. For example, the above expression can also be replaced by constructing the second data or restoring the first data.

[0198] First of all, it should be noted that if the first data to be transmitted is used as the above-mentioned source data Y, data compression is performed based on dictionary learning. When the amount of the first data is large, the spatial distribution of the source data Y is relatively wide, and it is difficult to determine the dictionary matrix to obtain a sparse matrix with better sparsity, resulting in a more complex data processing process for decomposing the dictionary matrix D and the sparse matrix X, and a larger delay. Based on this, in an embodiment of the present application, the first communication device can split the first data into M sub-data, see the data splitting process in Figure 4, and then perform dictionary learning on each sub-data.

[0199] The first data may be a matrix, or in other words, the first data is expressed in the form of a matrix. The first communication device may arrange the first data into a matrix Y of L rows and Q columns. For example, when the first data is point cloud data, L is equal to the dimension of the spatial point, that is, L=3, and Q is equal to the total number of spatial points in the point cloud data; for another example, the first data is AI model data, L may be a preset value, for example, a value obtained through experiments to make the sparse performance of the sparse matrix better, then in, Indicates rounding up, Dim is the gradient dimension. In this case, LQ-Dim zeros need to be added to the first data Y.

[0200] The first communication device may split the first data into M sub-data, for example, according to the relationship between each data in the first data in space, split the first data into M sub-data. Each sub-data may be a matrix.

[0201] 5, the Q columns (such as y1 to y Q ) can be divided into M sub-data, such as y1 to y K Divide into the first sub-data Y1, y K+1 To 2K Divide into the second sub-data Y2...y Q-K+1 To Q Divide into the third sub-data Y Q / K FIG5 is only used as an example to illustrate that the number of columns of the matrix formed by each sub-data in the M sub-data is the same, but the present application is not limited to this. For example, there are at least two sub-data in the M sub-data, and the number of columns of their matrices is different. When the number of columns of the matrices formed by each sub-data is the same, the data processing complexity of the first communication device and the second communication device can be reduced.

[0202] Taking the first data as point cloud data as an example, the first communication device can divide the first data into M sub-data according to the distance between each spatial point in the first data in the Euclidean space. For example, P spatial points can be determined in the order of the distance between the spatial points from small to large, P is a preset value, and the P spatial points are divided into one sub-data; or the spatial points within a preset range are divided into one sub-value, for example, the spatial points in a circle with a spatial point as the center and R as the radius are divided into one sub-data, R is a preset value, and so on.

[0203] Taking the first data as AI model data as an example, the first communication device can divide the first data into M sub-data according to the neural network layer where each data in the first data is located, for example, dividing the data of the same neural network layer or multiple similar neural network layers into one sub-data. If the number of data in the same neural network layer exceeds the data amount limit of one sub-data, the data of the same neural network layer can be divided into two or more adjacent sub-data. Neural network layers include but are not limited to fully connected layers, convolutional layers, pooling layers, etc.

[0204] Optionally, referring to the preprocessing process in Figure 4, the first communication device can normalize the first data Y" to obtain the normalized first data Y, so as to avoid errors caused by misidentifying some categories of data as unimportant data in the subsequent process of determining the sparse matrix based on dictionary learning due to differences in numerical intervals between different types of data. Taking the first data as point cloud data as an example, the first communication device normalizes the three-dimensional data of the spatial points in the first data to the same numerical interval to avoid identifying the data in a certain dimension as unimportant data. Exemplarily, the first communication device normalizes the first data Y" to obtain the first data Y, and uses the modulus value of each row in the first data Y" as the normalized data. The first communication device can send the normalized data to the second communication device, so that the second communication device can restore the first data Y" before normalization based on the normalized data.

[0205] It should be noted that the first communication device compresses the first data and sends the compressed data of the first data to the second communication device. The second communication device constructs data based on the compressed data of the first data to obtain the second data. Generally speaking, there are differences between the second data and the first data. The smaller the difference between the second data and the first data, the better the effect of data compression and data construction. Similar to the first data, the second data also includes M sub-data, and the M sub-data of the second data are respectively decompressed from the compressed data of the M sub-data of the first data, that is, the M sub-data of the second data correspond one-to-one to the M sub-data of the first data. The i-th sub-data Y of the second data i ' is the i-th sub-data Y based on the first data i The compressed data is constructed.

[0206] It should also be understood that the second communication device is based on the compressed data Z i In the process of data construction, according to the compressed data Z i Determine the dictionary matrix D i ' and the sparse matrix X i ', respectively with the dictionary matrix D determined by the first communication device i and the sparse matrix X iCorrespondingly, considering the possible construction errors in the data construction process, a distinctive expression is made. In the following, for the dictionary matrix D i and the sparse matrix X i Various exemplary descriptions of can be used to describe the dictionary matrix D i ' and the sparse matrix X i 'For explanation, similarly, each position indication information and each element sequence described in the first communication device side are also applicable in the data construction process of the second communication device side.

[0207] It should be understood that the first communication device can perform the following compression process of S210 and S220 on all or part of the M sub-data of the first data. If the first communication device can perform the data compression process of S210 and S220 on part of the M sub-data of the first data, the other sub-data in the M sub-data can be compressed based on any other compression method, for example, the i+1th sub-data Y i+1 Data compression can be performed based on scalar quantization or vector quantization. Accordingly, for the sub-data that have undergone the data compression process of S210 and S220, the second communication device can perform the data construction process of S240 and S250 based on the received compressed data corresponding to the sub-data. The following is an exemplary description of S210 to S250.

[0208] In the above S210, the first communication device may learn the i-th sub-data Y i Decompose into dictionary matrix D i and the sparse matrix X i . As shown in FIG6 , taking the first sub-data Y1 as an example, the first communication device decomposes Y1 to obtain a dictionary matrix D1 and a sparse matrix X1. The first sub-data Y1 may be a matrix of L rows by K columns, and the decomposed dictionary matrix D1 may be a matrix of L rows by L columns, and the sparse matrix X1 may be a matrix of L rows by K columns. However, the present application does not limit the number of rows and columns of the dictionary matrix to be consistent with the number of rows of the first sub-data Y1, that is, D1 may include more or fewer elements.

[0209] In a possible implementation, the number of rows of the sparse matrix X1 is consistent with the number of columns of the dictionary matrix D1, and the number of columns of the sparse matrix X1 is consistent with the number of columns of the first sub-data Y1. As mentioned above, each column vector in the sparse matrix X1 corresponds to each column vector in the first sub-data Y1 one by one, and the value of the row element of the column vector in the sparse matrix X1 is the weight of the column vector of the dictionary matrix D1. The column vector in the sparse matrix X1 represents the column vector corresponding to the first sub-data Y1 based on the column vectors and weights of the dictionary matrix D1. However, this application is not limited to this. For example, a column vector in the sparse matrix X1 can be used to express an element corresponding to the first sub-data Y1.

[0210] In the above S220, the first communication device may i and the sparse matrix X i Perform data compression to obtain the i-th sub-data Y i The compressed data Z i Referring to the compression process in FIG4 , the first communication device may i and the sparse matrix X i Perform quantization (such as scalar quantization or vector quantization) and / or entropy coding to obtain the i-th sub-data Y i The compressed data Z i .

[0211] It should be understood that a sparse matrix X with good sparse performance i There are many elements with values ​​of zero, which achieves compression of the first data to a certain extent. In order to further improve the compression performance, the embodiment of the present application further performs the sparse matrix X i Processing is performed to obtain the position indication information and element sequence shown in FIG6. The position indication information is used to indicate the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The element sequence includes the ability to express the i-th sub-data Y i Combined with Figure 6, the sparse matrix X i The elements in the first row of column x1, the elements in the second row of column x2, the elements in the second row of column x3, etc. have the function of expressing the i-th sub-data Y i , then the element sequence includes the sparse matrix X i The elements in the first row of column x1, the elements in the second row of column x2, the elements in the second row of column x3, etc. have the function of expressing the i-th sub-data Y i The elements of the capacity, for example, the sparse matrix X i The value of the element in the first row of column x1 is 0.1, the value of the element in the second row of column x2 is -0.5, the value of the element in the second row of column x3 is 0.8... These elements have the function of expressing the i-th sub-data Y iThe element sequence can be expressed as [0.1, 0.5, 0.8…], and the sparse matrix X i Except for the elements at the above positions, the absolute values ​​of the elements at other positions are small (including elements whose values ​​are 0 or whose values ​​differ from 0 by less than a preset threshold), and the elements at these positions do not have the function of expressing the i-th sub-data Y i Ability, such as X i The value of the element in the second row of column x1 is -0.005, the value of the element in the first row of column x2 is 0.0002, and the position indication information indicates that these elements have the function of expressing the i-th sub-data Y. i The position of the element with the ability to express the i-th sub-data Y in the sparse matrix X1, or in other words, the position indication information indicates which position of the element in the sparse matrix X1 has the ability to express the i-th sub-data Y i ability.

[0212] The location indication information may include a tree structure, a bitmap, a location index, etc., which is not limited in this application. Taking the location indication information as a bitmap as an example, as shown in FIG6 , the bits in the bitmap and the sparse matrix X i The elements in the bitmap correspond one to one, and the bits in the bitmap are used to indicate the sparse matrix X i Does the corresponding element in have the expression of the i-th sub-data Y i For example, when a bit in the bitmap is 1, it indicates that the sparse matrix X i The corresponding element in has the expression of the i-th sub-data Y i When the bit in the bitmap is 0, it indicates that the sparse matrix X i The corresponding element in does not have the expression of the i-th sub-data Y i For example, when the bit in the bitmap is 0, it indicates that the sparse matrix X i The corresponding element in has the expression of the i-th sub-data Y i When the bit in the bitmap is 1, it indicates that the sparse matrix X i The corresponding element in does not have the expression of the i-th sub-data Y i ability.

[0213] The position indication information may include at least one position index, and each position index may indicate the sparse matrix X i The i-th sub-data Y i The capacity of the elements in the sparse matrix X i For example, the position index indicates a position in the i-th sub-data Y i The capacity of the elements in the sparse matrix X i The second row and the fifth column in .

[0214] When the position indication information includes a tree structure, a sparse matrix X can be constructed iThe corresponding basic tree structure, some or all of the child nodes in the basic tree structure and the sparse matrix X i For example, in the process of constructing the basic tree structure, the basic two-dimensional plane can be divided into multiple levels of intervals, each interval is used as a child node of the basic tree structure, and the number of the smallest intervals (i.e., the child nodes at the lowest level in the basic tree structure) is greater than or equal to the number of the sparse matrix X i The number of elements in the basic two-dimensional plane is not limited in this application. For example, in the process of constructing the basic tree structure, two mutually perpendicular lines are used to divide it into four intervals, and the four intervals correspond to the four child nodes of the root node in the basic tree structure. For each of the four intervals, the interval includes a data element that expresses the i-th child data Y i , the value of the child node is the third value, and the interval does not contain the value that expresses the i-th child data Y i , the value of the child node is the fourth value; further, the interval is divided into four sub-intervals by two mutually perpendicular lines, and the four sub-intervals correspond to the four sub-nodes of the next level of the sub-node corresponding to the interval in the basic tree structure. Similarly, the sub-interval includes the node that expresses the i-th sub-data Y i When the element of the ability is a sub-interval, the value of the child node corresponding to the sub-interval in the basic tree structure is the third value, otherwise it is the fourth value, and so on until the construction of the tree structure is terminated when the minimum interval is reached. The third value can be 1 and the fourth value can be 0, or the third value can be 0 and the fourth value can be 1, or the third value and the fourth value can be any two different values, and this application does not limit this.

[0215] For example, the sparse matrix X of point cloud data i The size is 3×16. In the process of constructing the basic tree structure, two perpendicular lines are used to divide it into four intervals. The four intervals correspond to the four child nodes of the root node in the tree structure. Then each interval is divided into four sub-intervals. The four sub-intervals under the interval correspond to the four child nodes of the next level of the child node corresponding to the interval in the basic tree structure. And so on. After 4 interval divisions (or 4 recursions), 16×16 minimum intervals are obtained, and the sparse matrix X is constructed at the same time. i The basic tree structure of X, some of the child nodes in the basic tree structure can be i The elements in the sparse matrix X correspond one to one. For example, the 3×16 minimum intervals located in the upper left corner of the basic two-dimensional plane correspond to the child nodes in the basic tree structure. iOptionally, the position indication information may be the basic tree structure, and the basic tree structure does not include the sparse matrix X i The values ​​of the nodes corresponding to the intervals of the elements in the basic tree structure are all fourth values; or the tree structure in the position indication information may include some child nodes in the basic tree structure, and the part of the child nodes contains the sparse matrix X in the basic two-dimensional plane. i The interval of elements in , and the corresponding child nodes.

[0216] In the above example, the minimum interval divided includes the sparse matrix X i This application does not exclude that the minimum interval includes the sparse matrix X i Multiple elements or multiple minimum intervals in the sparse matrix X i When the minimum interval includes one element, the location indicated by the location indication information is more accurate, and thus the data constructed by the second communication device based on the location indication information is more accurate. When the minimum interval includes multiple elements, the transmission resources occupied by the location indication information are smaller, saving resource overhead.

[0217] The above exemplary description of the location indication information can be applied to the following related embodiments, and the implementation methods thereof are the same or similar, and will not be described in detail for the sake of brevity.

[0218] In some embodiments, the first communication device may be configured to generate a sparse matrix X i For each element in , according to the element and the capability threshold, determine whether the element has the ability to express the i-th sub-data Y i For example, when the absolute value of the value of the element is greater than the capability threshold, the first communication device determines that the element has the ability to express the i-th data Y i When the absolute value of the data of the element is less than the capability threshold, it is determined that the element does not have the ability to express the i-th sub-data Y i When the absolute value of the data of the element is equal to the capability threshold, the element can be determined as having or not having the ability to express the i-th data Y i The first communication device further calculates the sparse matrix X according to the sparse matrix X. i Whether each element in has the function of expressing the i-th sub-data Y i The ability to determine the above position indication information and element sequence.

[0219] Continuing with the above example, the first communication device may perform a dictionary matrix D i , sparse matrix X i The position indication information and element sequence of the first communication device are compressed. For example, as shown in FIG. 4, the first communication device compresses the dictionary matrix D iand the sparse matrix X i Quantize and entropy encode, entropy encode the position indication information, and obtain the i-th sub-data Y i The compressed data Z i .

[0220] The capability threshold may be determined by the compression requirement, and the capability thresholds corresponding to different data compression rate requirements may be different. For example, the compression rate requirement may be determined according to the resource configuration sent by the second communication device. The first capability threshold and the second capability threshold are similar and will not be described in detail below.

[0221] In the above S230, the first communication device may use the compressed data Z determined in any of the above examples i Optionally, the first communication device may send the compressed data of each of the M sub-data separately, for example, the compressed data of each sub-data is separately encapsulated by the protocol and then sent, or the first communication device may send the compressed data of each of the M sub-data as the same data, for example, the compressed data of each sub-data is encapsulated by the protocol and then sent. In some embodiments, the first communication device transmits the compressed data of the first data in an incremental manner, and the compressed data Z i It can refer to the i-th sub-data Y in the initial transmission process i The compressed data, or compressed data Z i It can include the initial transmission process and the i-th sub-data Y in the incremental transmission process i If the compressed data Z i It can include the initial transmission process and the i-th sub-data Y in the incremental transmission process i If the compressed data is transmitted, the compressed data is encapsulated by the protocol and then sent during the initial transmission process and the incremental transmission process.

[0222] In the above S240, the second communication device may compress the data Z i Decompress and get the dictionary matrix D i ' and the sparse matrix X i '. Its decompression method is the same as that of the first communication device for the i-th sub-data Y i In some embodiments, the first communication device may send an instruction message to the second communication device to instruct the compressed data Z to be compressed. i The compression parameters (for example, including at least one of the encoding mode parameters, the quantization accuracy parameters, and the number of sub-data columns) are indicated in the following description.

[0223] For example, if the first communication device receives the i-th sub-data Y i The sparse matrix X iAfter further processing, the position indication information and element sequence shown in FIG6 are obtained, and the second communication device performs the compressed data Z i Decompress and get the dictionary matrix D i ', position indication information and element sequence, and then determine the sparse matrix X according to the position indication information and element sequence i '.

[0224] In the above S250, the second communication device may obtain the dictionary matrix D based on the obtained i ' and the sparse matrix X i ', according to the sparse matrix X i 'Based on the dictionary matrix D i 'The i-th sub-data Y expressed i , construct the i-th sub-data Y i '.

[0225] The second communication device decompresses each sub-data according to the compression method used by other sub-data in the M sub-data and constructs each sub-data, and then constructs the second data to achieve data compression transmission between the first communication device and the second communication device.

[0226] In some embodiments, after the M sub-data of the first data are compressed, if there is still a large amount of data that occupies a lot of transmission resources, or if the second communication device needs the first communication device to transmit a more complete and rich content of the first data, the M sub-data of the first data can be compressed and transmitted in an incremental manner. The following three possible implementations may be included but are not limited to:

[0227] Method 1: The first communication device converts the sparse matrix X i A part of the elements in is determined as the first element, and the sparse matrix X i The first communication device determines the i-th sub-data Y for the first element. i The first compressed data Z i ', determine the i-th sub-data Y for the second element i The second compressed data Z i ". Then, the first compressed data Z is transmitted in the initial transmission stage. i ', transmit the second compressed data Z in the incremental transmission phase i ”.

[0228] Exemplarily, the first communication device determines the first position indication information and the first element sequence based on the first element, and performs a dictionary matrix D i , sparse matrix X i The first position indication information and the first element sequence are compressed to obtain the i-th sub-data Y iThe first compressed data Z i ', the first compressed data Z i 'Transmitted during the initial transmission process; the first communication device determines the second position indication information and the second element sequence based on the second element, and performs the sparse matrix X i The second position indication information and the second element sequence are compressed to obtain the i-th sub-data Y i The second compressed data Z i ", the second compressed data Z i ” is transmitted during incremental transmission.

[0229] Correspondingly, the second communication device receives the ith sub-data Y i The first compressed data Z i 'Decompress and get the dictionary matrix D i ', and, sparse matrix X i ' first position indication information and the first element sequence, and determine the sparse matrix X according to the first position indication information and the first element sequence i '; The second communication device receives the i-th sub-data Y i The second compressed data Z i "Decompress it and get the sparse matrix X i ' and the second position indication information and the second element sequence, and updating the sparse matrix X according to the second position indication information and the second element sequence i ', or in other words, determine the sparse matrix X according to the first position indication information, the first element sequence, the second position indication information and the second element sequence i '; Then according to the dictionary matrix D i ' and the sparse matrix X i 'Construct i sub-data Y i '.

[0230] The first element may be preset or configured by the network device, which is not limited in this application. The first element may be a sparse matrix X i The elements in the preset columns (such as the first K1 columns shown in FIG. 7 ), or the first element may be a sparse matrix X i The elements in the preset rows (e.g., the 1st row, the 3rd row, the 8th row) in the matrix X, or the first element may be a sparse matrix X. i The elements in the preset positions (such as the 1st row and 1st column, the 2nd row and 2nd column, the 3rd row and 3rd column...) are not limited in this application.

[0231] The first position indication information is used to indicate the sparse matrix X i Does the first element in have the expression of the i-th sub-data Y i The first element sequence includes the first element Y having the expression i-th sub-datai The first element of the first capability. Similar to the position indication information in the above example, the first position indication information may include a tree structure, a bitmap, a position index, etc., which is not limited in this application. Taking the first position indication information as the first bitmap as an example, in combination with FIG. 7, the bits in the first bitmap and the sparse matrix X i The first element in the first bitmap corresponds to the first element in the sparse matrix X. i Whether the first element corresponding to the expression has the i-th sub-data Y i For example, when the bit in the first bitmap is 1, it indicates that the sparse matrix X i The first element corresponding to the expression of the i-th sub-data Y i The first capability; when the bit in the first bitmap is 0, it indicates that the sparse matrix X i The first element corresponding to does not have the expression of the i-th sub-data Y i For another example (not shown in FIG. 7 ), when the bit in the first bitmap is 0, it indicates that the sparse matrix X i The first element corresponding to the expression of the i-th sub-data Y i The first capability; when the bit in the first bitmap is 1, it indicates that the sparse matrix X i The first element corresponding to does not have the expression of the i-th sub-data Y i The first ability.

[0232] The second position indication information is used to indicate the sparse matrix X i Does the second element in have the expression of the i-th sub-data Y i The first capability, the second element sequence includes the i-th sub-data Y i The second element of the first capability. Similar to the first position indication information, the second position indication information may include a tree structure, a bitmap, a position index, etc., which is not limited in this application. Taking the second position indication information as the second bitmap as an example, in combination with FIG. 7, the bits in the second bitmap and the sparse matrix X i The second element in the second bitmap corresponds one to one, and the bits in the second bitmap are used to indicate the sparse matrix X i Whether the corresponding second element in has the expression of the i-th sub-data Y i For example, when the bit in the second bitmap is 1, it indicates that the sparse matrix X i The corresponding second element in has the expression of the i-th sub-data Y i The first capability; when the bit in the second bitmap is 0, it indicates that the sparse matrix X i The corresponding second element does not have the expression of the i-th sub-data Y i For another example, when the bit in the second bitmap is 0, it indicates that the sparse matrix X iThe corresponding second element in has the expression of the i-th sub-data Y i The first capability; when the bit in the second bitmap is 1, it indicates that the sparse matrix X i The corresponding second element does not have the expression of the i-th sub-data Y i The first ability.

[0233] Exemplarily, the first communication device may be configured to generate a sparse matrix X i For each first element in , according to the first element and the first capability threshold, determine whether the first element has the ability to express the i-th sub-data Y i For example, when the absolute value of the value of the first element is greater than the first capability threshold, the first communication device determines that the first element has the ability to express the i-th data Y i When the absolute value of the value of the first element is less than the first capability threshold, it is determined that the first element does not have the ability to express the i-th sub-data Y i When the absolute value of the value of the first element is equal to the first capability threshold, the first element can be determined as having or not having the ability to express the i-th data Y according to the application scenario. i The first element of the first capability of the present application is not limited to this. i Does each first element in have the expression of the i-th sub-data Y i The first capability is to determine the first position indication information and the first element sequence.

[0234] Exemplarily, the first communication device may be configured to generate a sparse matrix X i For each second element in , according to the second element and the first capability threshold, determine whether the second element has the ability to express the i-th sub-data Y i For example, when the absolute value of the value of the second element is greater than the first capability threshold, the first communication device determines that the second element has the ability to express the i-th data Y i When the absolute value of the data of the second element is less than the capability threshold, it is determined that the second element does not have the ability to express the i-th sub-data Y i When the absolute value of the data of the second element is equal to the first capability threshold, the second element can be determined as having or not having the ability to express the i-th data Y according to the application scenario. i The second element of the first capability of the present application is not limited to this. i Whether each second element in has the expression of the i-th sub-data Y i The first capability determines the second position indication information and the second element sequence.

[0235] As shown in FIG7 , the elements in the first K1 columns of the sparse matrix X1 are the first elements, and the elements in the last K2 columns are the second elements. i The element value of each first element in the first K1 columns determines the first element with the first ability to express Y1, and the first elements with the first ability to express Y1 are organized into a first element sequence, and the first position indication information indicating the first element with the first ability to express Y1 is determined, and then the first compressed data of Y1 is determined according to the first position indication information, the first element sequence and the dictionary matrix D1.

[0236] Still in combination with FIG. 7 , the first communication device uses the sparse matrix X i The element value of each second element in the middle and rear K2 columns determines the second element with the first ability to express Y1, and the second elements with the first ability to express Y1 are organized into a second element sequence, and the second position indication information indicating the second element with the first ability to express Y1 is determined, and then the second compressed data of Y1 is determined according to the second position indication information and the second element sequence.

[0237] It should be noted that the incremental transmission process does not need to repeatedly transmit the dictionary matrix D i , in order to reduce the waste of transmission resources.

[0238] In the above-mentioned method 1, the first communication device can determine whether to transmit the i-th sub-data Y to the first communication device based on the preset or pre-configured time-frequency resources. i The elements in are divided into first elements and second elements, and then the first position indication information and the first element sequence corresponding to the first element are determined, and the second position indication information and the second element sequence corresponding to the second element are determined; or the first communication device may first determine the i-th sub-data Y i The elements in Y that meet the first capacity threshold are determined based on the number of elements that meet the first capacity threshold. i Can the compressed data be transmitted on the preset or pre-configured time-frequency resources? If the i-th sub-data Y i The time-frequency resources occupied by the compressed data are greater than the preset or pre-configured time-frequency resources and cannot be transmitted, then the i-th sub-data Y i The elements in are divided into first elements and second elements, thereby determining first position indication information and a first element sequence corresponding to the first element, and second position indication information and a second element sequence corresponding to the second element.

[0239] For example, referring to FIG. 12 , the first communication device needs to transmit the i-th sub-data Y on a transmission resource block (TB). i The compressed data Z i , in the sparse matrix Xi All sub-data Y with expression i i The compressed data Z is obtained by compressing the element sequence composed of i , when the size of a TB exceeds one TB (for example, a TB size is 3824 bits), the first communication device determines a TB except for the dictionary matrix D i In addition, the remaining resource size is determined according to the remaining resource size in the one TB, and the number of first elements is determined (for example, the value of K1 in FIG. 7 is determined), and then the first position indication information determined based on the first element, the first element sequence, and the dictionary matrix D i After data compression, the i-th sub-data Y i The first compressed data Z i 'Carried on the one TB and sent to the second communication device; in the incremental transmission process, the second position indication information determined based on the second element and the second element sequence are compressed, and the obtained i-th sub-data Y i The second compressed data Z i " is carried on another TB and sent to the second communication device.

[0240] For ease of understanding, the above method only takes the sparse matrix X as i The first communication device may also divide the sparse matrix X into the first element and the second element. i The elements are divided into more types, such as the first element, the second element, the third element, etc.; as another understanding, the first communication device can further divide the second element into the third element, the fourth element, etc., for further incremental transmission. The division of element types and the determination of the position indication information and element sequence under each element type are similar to the implementation of the first method, and will not be repeated for the sake of brevity.

[0241] Method 2: The first communication device performs the following operations on the sparse matrix X: i Y i The first element of the capability determines the i-th sub-data Y i The first compressed data Z i ', for the sparse matrix X i Y i The elements of the second capability or the N elements at the preset position determine the i-th sub-data Y i The third compressed data Z i ” '. Then, the first compressed data Z is transmitted in the initial transmission stage i ', transmit the third compressed data Z in the incremental transmission phase i ”'.

[0242] Exemplarily, in the initial transmission phase, the first communication device determines the sparse matrix X i Y i The first element of the ability, and according to the expression Y i The element of the first capability determines the first position indication information and the first element sequence.

[0243] Correspondingly, the second communication device receives the ith sub-data Y i The first compressed data Z i 'Decompress and get the dictionary matrix D i ', and, sparse matrix X i In some embodiments, the second communication device may determine the sparse matrix X according to the first position indication information and the first element sequence. i '.

[0244] The first position indication information is used to indicate the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The first element sequence includes the first element Y having the expression i-th sub-data i The first position indication information may include a tree structure, a bitmap, a position index, etc., which is not limited in this application. Taking the first position indication information as the first bitmap as an example, in combination with FIG. 8 or FIG. 9, the bits in the first bitmap and the sparse matrix X i The elements in the first bit map correspond one to one, and the bit in the first bit map is used to indicate the sparse matrix X i Does the corresponding element in have the expression of the i-th sub-data Y i The first capability is similar to the example related to FIG7 and will not be described in detail here.

[0245] Exemplarily, the first communication device is for the sparse matrix X i For each element in , it can be determined whether the element has the ability to express the i-th sub-data Y according to the element and the first capability threshold. i Determine whether the element has the ability to express the i-th sub-data Y i The first capability of determining the first element is similar to the first capability of determining the first element in the above example, and will not be described in detail here. i Whether each element in has the function of expressing the i-th sub-data Y i The first capability is to determine the first position indication information and the first element sequence.

[0246] As a first example of the above-mentioned method 2, the third position indication information is used to indicate the sparse matrix X i Does the element in have the expression of the i-th sub-data Yi The second capability, the third element sequence includes the i-th sub-data Y i The third position indication information may include a tree structure, a bitmap, a position index, etc., similar to the first position indication information, which is not limited in this application. Taking the third position indication information as a third bitmap as an example, as shown in FIG8 , the bits in the third bitmap and the sparse matrix X i The elements in the third bitmap correspond one to one, and the bits in the third bitmap are used to indicate the sparse matrix X i Does the corresponding element in have the expression of the i-th sub-data Y i The second ability.

[0247] Based on the first example above, the first communication device performs the following operations on the sparse matrix X: i For each element in , it can be determined whether the element has the ability to express the i-th sub-data Y according to the element and the first capability threshold and the second capability threshold. i For example, when the absolute value of the value of the element is less than the first capability threshold and greater than the second capability threshold, the first communication device determines that the element has the ability to express the i-th data Y i When the absolute value of the value of the element is greater than the first capability threshold or less than the second capability threshold, it is determined that the element does not have the ability to express the i-th sub-data Y i When the absolute value of the value of the element is equal to the first capability threshold or equal to the second capability threshold, the element can be determined as having or not having the ability to express the i-th data Y i The first communication device further calculates the second capability of the sparse matrix X. i Whether each element in has the function of expressing the i-th sub-data Y i The second capability determines the above-mentioned third position indication information and third element sequence.

[0248] In some possible implementations, the first capability threshold is greater than the second capability threshold. For example, the first capability threshold is 10 -4 , the second ability threshold is 10 -5 , a sparse matrix X i The absolute value of the element is greater than 10 -4 The element is the one that expresses the i-th sub-data Y i The first element of the sparse matrix X i The absolute value of the element in [10 -5 ,10 -4 ] is an element in the numerical interval that expresses the i-th sub-data Y i The element of the second ability.

[0249] Accordingly, the second communication device can i The third compressed data Z i ”'Decompress and get the sparse matrix X i In some embodiments, the second communication device may update the sparse matrix X according to the third position indication information and the third element sequence. i '; In some other embodiments, the second communication device may determine the sparse matrix X according to the first position indication information, the first element sequence, the third position indication information and the third element sequence. i '. Then, the second communication device uses the dictionary matrix D i ' and the sparse matrix X i 'Construct i sub-data Y i '.

[0250] In the first example of the above-mentioned method 2, the transmitted second compressed data is helpful to reduce the construction error when the second communication device constructs data.

[0251] As a second example of the above-mentioned method 2, the third element sequence includes a sparse matrix X i N elements other than the elements included in the first element sequence in X, where N is a positive integer. It should be understood that the N elements can be distributed in the sparse matrix X i In different rows and columns, or the N elements can be a sparse matrix X i For example, as shown in FIG9 , the N elements are the elements in the first two rows of the sparse matrix X1.

[0252] Based on the second example above, the first communication device performs data compression on the third element sequence to obtain the i-th sub-data Y i The third compressed data Z i It should be understood that the N elements may be preset or preconfigured, that is, the first communication device does not need to indicate to the second communication device that the N elements are in the sparse matrix X. i Therefore, there is no need to transmit position indication information.

[0253] Accordingly, the second communication device can i The third compressed data Z i ”'Decompress and get the sparse matrix X i In some embodiments, the second communication device may update the sparse matrix X according to the third element sequence. i '; In some other embodiments, the second communication device can determine the sparse matrix X according to the first position indication information, the first element sequence and the third element sequence. i'. Then, the second communication device uses the dictionary matrix D i ' and the sparse matrix X i 'Construct i sub-data Y i '.

[0254] The above method 2 is similar to the above method 1 in that the dictionary matrix D does not need to be transmitted in the incremental transmission stage. i Compared with the above-mentioned method 1, the above-mentioned method 2 can flexibly select whether to need incremental transmission. For example, in a business scenario, the second communication device transmits the first compressed data Z i 'When decompression can obtain sufficient business information in the first data, there is no need to perform incremental transmission.

[0255] In the second example of the above-mentioned method 2, the second compressed data does not include position indication information, thereby reducing resource overhead.

[0256] Method 3: The first communication device converts the sparse matrix X i A part of the elements in is determined as the first element, and the sparse matrix X i The first communication device determines the elements other than the first element in the first element as the second element. i The first element of the first capability determines the i-th sub-data Y i The first compressed data Z i ', for the second element with expression Y i The second element of the first capability determines the i-th sub-data Y i The second compressed data Z i "; Further, the first communication device is for the sparse matrix X i Y i The elements of the second capability (including the first element and the second element) or the N elements at the preset position are used to determine the i-th sub-data Y i The third compressed data Z i ” '. Then, the first compressed data Z is transmitted in the initial transmission stage i ', transmit the second compressed data Z in the incremental transmission phase i " and the third compressed data Z i ”'.

[0257] As another understanding of the above-mentioned method 3, the first communication device may determine the sparse matrix X i Y i The first element of the capability will have the expression Y i The first element of the ability is divided into the first element and the second element, and then for the expression Y i The first element of the first capability determines the i-th sub-data Y iThe first compressed data Z i ', for those with expression Y i The second element of the first capability determines the i-th sub-data Y i The second compressed data Z i ”, for the sparse matrix X i Y i The elements of the second capability or the N elements at the preset position determine the i-th sub-data Y i The third compressed data Z i ”'.

[0258] In the above-mentioned method 3, the process of the first communication device determining the capability (including the first capability and / or the second capability) of each element (including the first element and / or the second element) can refer to the above-mentioned example, and will not be repeated for the sake of brevity. In the above-mentioned method 3, the first communication device compresses and transmits the first compressed data Z i ', the second compressed data Z i " and the third compressed data Z i The process of "' can refer to the above example, which will not be described here for brevity.

[0259] In some embodiments, the second communication device may transmit the third compressed data Z i ”'Unzip and get the sparse matrix X i 'The third position indicates the information and the third element sequence, and according to the sparse matrix X i ', the third position indication information, the third element sequence, and at least one of the following, determine the sparse matrix X i ': sparse matrix X i 'The first position indication information, the first element sequence; or, the sparse matrix X i ', the second position indication information, the second element sequence. Wherein, the sparse matrix X i The determination method of the first position indication information, the first element sequence, the second position indication information and the second element sequence can refer to the above-mentioned embodiment and will not be repeated here.

[0260] In some other embodiments, the second communication device may transmit the third compressed data Z i ”'Unzip and get the sparse matrix X i ', and the third position indication information and the third element sequence, and then, the second communication device may first determine the sparse matrix X based on at least one of the following i ': sparse matrix X i 'The first position indication information, the first element sequence; or, the sparse matrix X i ', the second position indication information, the second element sequence. Further, the second communication device is based on the sparse matrix X i'The third position indication information and the third element sequence update the sparse matrix X i '.

[0261] As shown in FIG10 , the elements in the first K1 columns of the sparse matrix X1 are the first elements, and the elements in the last K2 columns are the second elements. The first communication device determines the first element having the first ability to express Y1 from the first elements in the first K1 columns, and determines the second element having the first ability to express Y1 from the second elements in the last K2 columns; and determines the first position indication information and the first element sequence according to the first element having the first ability to express Y1, and performs data compression on the dictionary matrix D1, the first position indication information and the first element sequence to obtain the i-th sub-data Y i The first compressed data Z i '; Determine the second position indication information and the second element sequence according to the second element having the first ability to express Y1, compress the second position indication information and the second element sequence, and obtain the i-th sub-data Y i The second compressed data Z i "; Further, the first communication device can determine, in response to the incremental transmission scheduling, from the elements of the sparse matrix X1 (including the first element and the second element), the element having the second ability to express Y1, and determine the third position indication information and the third element sequence according to the element having the second ability to express Y1, and perform data compression on the third position indication information and the third element sequence to obtain the i-th sub-data Y i The third compressed data Z i ”'.

[0262] As shown in FIG11 , the first communication device determines the i-th sub-data Y i The first compressed data Z i ' and the second compressed data Z i "See the description of the example shown in FIG. 10 above, which will not be repeated here; further, the first communication device can respond to the incremental transmission scheduling, determine the third element sequence according to the N elements at the preset positions in the elements (including the first element and the second element) of the sparse matrix X1, and perform data compression on the third element sequence to obtain the i-th sub-data Y i The third compressed data Z i ”'. The description of the N elements can be found in the above examples and will not be repeated here.

[0263] Compared with the above-mentioned methods 1 and 2, the above-mentioned method 3 has higher transmission reliability and is more conducive to the second communication device to construct data based on the received compressed data.

[0264] In some embodiments, at least two sub-data (e.g., the i-th sub-data and the i-1-th sub-data, or the i-th sub-data and the i+1-th sub-data, or any two non-adjacent sub-data) in the M sub-data are compressed using any of the above embodiments. In this case, in order to further improve the compression performance, the first communication device may convert the sparse matrix X into i The corresponding position indication information is based on the sparse matrix X i-1 The corresponding position indication information is XORed, and the difference position indication information obtained by XOR is used as the sparse matrix X i The corresponding location indication information.

[0265] Among them, the sparse matrix X i The corresponding position indication information may include a sparse matrix X i At least one of the first position indication information, the second position indication information and the third position indication information; the sparse matrix X i-1 The corresponding position indication information includes the sparse matrix X i-1 At least one of the first position indication information, the second position indication information and the third position indication information. For example, in the initial transmission stage, the difference position indication information may be based on the sparse matrix X i The first position indication information and the sparse matrix X i-1 The first position indication information is determined; in the incremental transmission stage, the difference position indication information can be based on the sparse matrix X i The second position indication information and the sparse matrix X i-1 The second position indication information is determined, or may be based on the sparse matrix X i The third position indicates information and the sparse matrix X i-1 The third position indication information is determined.

[0266] In this application, the sparse matrix X i-1 The corresponding position indication information can be expressed as a sparse matrix X i-1 The position indication information, the i-1th sub-data Y i-1 The position indication information is used interchangeably in this application and has the same meaning.

[0267] In some embodiments, the first communication device may first determine whether to use the difference position indication information as the sparse matrix X i Exemplarily, when the first ratio of the difference position indication information is greater than or equal to the ratio threshold, the first communication device uses the difference position indication information as the sparse matrix X iThe first position indication information of the difference position indication information is the ratio of the number of bits of the first value or the second value in the bits of the difference position indication information to the number of all bits of the difference position indication information. The first value is used to indicate the sparse matrix X i The corresponding element in has the expression of the i-th sub-data Y i The first capability and the second value are used to indicate the sparse matrix X i The corresponding element in does not have the expression of the i-th sub-data Y i It should be noted that when the first ratio is greater than or equal to the ratio threshold, it indicates that in the bits of the difference position indication information, the difference between the number of bits of the first value and the number of bits of the second data is large, then the difference position indication information has a large compressibility, and the sparse matrix X i Replacing the first position indication information with the differential position indication information can improve the compression performance of the i-th sub-data. Otherwise, the compressible amount of the differential position indication information is small, and the first communication device still compresses the i-th sub-data based on the original first position indication information.

[0268] Optionally, the ratio threshold is a preset value; or the ratio threshold may be determined according to the sparse matrix X determined by the first communication device. i The first position indication information is dynamically adjusted, for example, the first communication device adjusts the first position indication information according to the sparse matrix X i The ratio threshold is determined by calculating the ratio of the number of bits of the first value or the second value to the number of all bits of the first position indication information in the first position indication information. It should be understood that when the first ratio of the difference position indication information is greater than or equal to the ratio threshold, it indicates that the difference position indication information has a larger compressibility than the first position indication information, and the sparse matrix X determined by the first communication device is i Replacing the first position indication information with the difference position indication information can improve the compression performance of the i-th sub-data.

[0269] The above embodiment is only described by taking the position indication information being the first position indication information as an example. When the position indication information is the second position indication information or the third position indication information, the implementation process is similar to the above example and will not be repeated here.

[0270] Optionally, the first communication device may send second indication information to the second communication device, where the second indication information at least includes an indication of the sparse matrix X i For example, the second indication information may be indicated by a 1-bit field. For example, when the 1-bit field is "1", it indicates that the sparse matrix X iThe position indication information is the difference position indication information. When this 1-bit field is "0", it indicates that the sparse matrix X i The position indication information of the non-differential position indication information (that is, the position indication information determined by the first communication device and the sparse matrix X i The position indication information corresponding to the element sequence).

[0271] Optionally, the first numerical value may be "1", and / or the second numerical value may be "2".

[0272] Taking the first position indication information as the first bitmap and the difference position indication information as the difference bitmap as an example, the first communication device determines the sparse matrix X i After the first bitmap, the sparse matrix X i The first bitmap and sparse matrix X i-1 The first bitmap is XORed, and then the first communication device can use the difference bitmap as a sparse matrix X i The first bitmap of i and the sparse matrix X i The first element sequence of is compressed together to obtain the i-th sub-data Y i The first compressed data Z i '. Referring to FIG. 13, the first bitmap of the first sub-data Y1 among the M sub-data and the first bitmap of the second sub-data Y2 among the M sub-data are XORed to obtain a difference bitmap. When the difference between the first bitmap of the first sub-data Y1 and the first bitmap of the second sub-data Y2 among the M sub-data is large, the more bits with a value of "1" in the difference bitmap, and when the difference between the first bitmap of the first sub-data Y1 and the first bitmap of the second sub-data Y2 among the M sub-data is small, the more bits with a value of "0" in the difference bitmap. Assume that the ratio threshold is determined based on the bits in the first bitmap of Y2, the ratio threshold can be the ratio of the number of bits of the second value "0" (8) to the number of all bits (15), that is, 8 / 15. The first ratio of the difference bitmap is the ratio of the number of bits of the second value "0" (11) to the number of all bits (15), that is, 11 / 15. If the first ratio of the difference bitmap is greater than the ratio threshold, the difference bitmap has a higher compressibility than the first bitmap. Therefore, the first bitmap is replaced with the difference bitmap, and then the second sub-data Y2 is compressed to improve the compression performance.

[0273] In the case where the first data includes point cloud data, referring to the preprocessing process shown in FIG4 , the first communication device may sample the initial point cloud data to obtain the point cloud data in the first data. FIG14 is a schematic diagram of the first layer sampling process. In conjunction with the example shown in FIG14 , in some embodiments, the first communication device may use a cube with a preset side length to spatially divide the Euclidean space where the initial point cloud data is located, and use the geometric center of the spatial point in each cube as the sampling point of the cube.

[0274] Optionally, the coordinates of the geometric center of the space point in the cube can be the average of the coordinates of the space points in the cube. For example, if there are three space points in the cube, and the coordinates of the three space points are represented by s1, s2 and s3 respectively, then the coordinates of the geometric center of the space point in the cube can be represented by: (s1+s2+s3) / 3.

[0275] In other embodiments, the first communication device may use a cube with a preset side length to spatially divide the Euclidean space where the initial point cloud data is located, and use the weighted geometric center of the spatial point in the cube as the sampling point of the cube. The above-mentioned weighted geometric center may be the weighted average of the coordinates of each spatial point in the cube, and the weight of each spatial point may be the same or different. The value of the weight corresponding to each spatial point may be greater than or equal to 0 and less than or equal to 1, and the present application does not limit this. For example, there are 3 spatial points in the cube, and the coordinates of the 3 spatial points are represented by s1, s2 and s3, respectively, and the weights corresponding to the 3 spatial points are w1, w2 and w3, respectively. Then the coordinates of the geometric center of the spatial point in the cube can be expressed as: (w1﹡s1+w2﹡s2+w3﹡s3) / 3.

[0276] It is understandable that using the geometric center of the space point in the cube or the weighted geometric center as the sampling point of the cube can reduce the amount of point cloud data. Furthermore, using the geometric center of the space point in the cube as the sampling point of the cube reduces the processing complexity during the sampling process; using the weighted geometric center of the space point in the cube as the sampling point of the cube can adjust the sampling point by adjusting the weight, thereby achieving flexible control of sampling.

[0277] Optionally, the side length of the cube may be a preset value or a pre-configured value, which is not limited in this application.

[0278] The first communication device can send the side length of the cube to the second communication device through indication information, so that the second data constructed by the second communication device is closer to the first data, thereby improving the reliability of compressed transmission.

[0279] Generally speaking, in Euclidean space, the original point cloud data is seamlessly covered by multiple unspaced cubes. Of course, the present application is not limited to this. For example, there may be a space gap between two cubes.

[0280] It should be noted that the geometric center of a spatial point inside a cube is different from the geometric center of the cube. As shown in FIG14 , the geometric center of a cube is the intersection of two diagonals of the cube, while the geometric center of a spatial point inside a cube is the most central position of each spatial point determined based on the positions of each spatial point inside the cube.

[0281] FIG15 is a schematic diagram of the second layer sampling process. In combination with the example shown in FIG15 , in order to further improve the data compression rate, the first communication device can determine the distance between the sampling points of adjacent cubes. When the distance between the sampling points of adjacent cubes is less than or equal to the first distance threshold, the first communication device deletes the sampling points of one of the adjacent cubes. After performing the above sampling on every two adjacent cubes, the retained sampling points form the first data. For example, if the distance d1 between c1 in cube A1 and c2 in cube A2 is greater than the first distance threshold, c1 and c2 are retained. If the distance d2 between c2 in cube A2 and c3 in cube A3 is less than or equal to the first distance threshold, c2 in A2 is deleted, or c3 in A3 can also be deleted.

[0282] In some embodiments, the first communication device may not perform the second layer sampling process described above, but may compose the first data from the determined sampling points within each cube.

[0283] In the process of constructing the second data, the second communication device may interpolate the second data to make the second data closer to the first data and improve the reliability of compressed transmission. Exemplarily, when the distance between two adjacent spatial points of the second data in the Euclidean space is greater than or equal to the second distance threshold, the second communication device interpolates between the two adjacent spatial points. As shown in FIG16, if the distance d3 between c1 in cube A1 and c3 in cube A3 is greater than or equal to the second distance threshold, interpolation is performed in cube A2.

[0284] Exemplarily, the second communication device can add a spatial point (i.e., perform interpolation) at the intersection of a line connecting two adjacent spatial points and a circle edge line, where the circle has one of the two adjacent spatial points as the center and the third distance threshold as the radius in the Euclidean space. As shown in FIG16 , the second communication device adds a spatial point c2' at the intersection of a circle having c3 in cube A3 as the center and the third distance threshold d4 as the radius, and a line connecting c1 in cube A1 and c3 in cube A3.

[0285] It should be understood that, for the second communication device, there may be no cube for space division in the Euclidean space, and this application does not limit this.

[0286] FIG17 is a schematic diagram of an interactive process of another data compression transmission method provided in an embodiment of the present application. As shown in FIG17 , method 300 includes part or all of the following processes from S310 to S390:

[0287] S310, the first communication device sends an upload request to the second communication device, the upload request carries first indication information, the first indication information is used to indicate the data type of the first data. Correspondingly, the second communication device receives the upload request sent by the first communication device.

[0288] S320, the second communication device sends first resource configuration information to the first communication device, where the resource configuration information is used to indicate a first time-frequency resource of the first compressed data. Correspondingly, the first communication device receives the resource configuration information sent by the second communication device.

[0289] S330: The first communication device receives the i-th sub-data Y of the M sub-data. i Perform data compression to obtain the first compressed data Z of the i-th sub-data i '.

[0290] S340, the first communication device sends the first compressed data Z in the first time-frequency resource. i ' and the third indication information. Accordingly, the second communication device receives the first compressed data Z in the first time-frequency resource i ' and the third indication information.

[0291] S350, the second communication device compresses the first data Z i ' and the third indication information to construct the i-th sub-data Y i '.

[0292] S360, the second communication device sends second resource configuration information and / or third resource configuration information to the first communication device, the second resource configuration information is used to indicate the second time-frequency resource, and the third resource configuration information is used to indicate the third time-frequency resource. Correspondingly, the first communication device receives the second resource configuration information and / or third resource configuration information sent by the second communication device.

[0293] S370: The first communication device receives the i-th sub-data Y of the M sub-data. i Perform data compression to obtain the second compressed data Z of the i-th sub-data i " and / or the third compressed data Z i ”'.

[0294] S380: The first communication device sends the second compressed data Z of the i-th sub-data to the second communication device in the second time-frequency resource. i ", and / or, sending the third compressed data Z to the second communication device in the third time-frequency resource i ”'.

[0295] S390: The second communication device updates the constructed i-th sub-data.

[0296] In the above S310, the first communication device sends an upload request to the second communication device to request compressed transmission of the first data. The upload request may carry first indication information to indicate the data type and / or size of the first data.

[0297] Optionally, the data type includes point cloud data or AI model data.

[0298] Optionally, the upload request may be a status report (SR) or a buffer status report (BSR). For example, the first communication device may send an upload request via an SR to implicitly indicate the data type, or the first communication device may send an upload request via a BSR to report the size of the first data.

[0299] The second communication device may determine the time-frequency resources for transmitting the compressed data of the first data based on the data type of the first data and / or the size of the first data. Optionally, if the first data is large and the compressed data of the first data needs to be transmitted in an incremental transmission manner, the second communication device may first determine the first time-frequency resources of the first compressed data of the first data (including the first compressed data of each sub-data) (including the first time-frequency resources of the first compressed data of each sub-data).

[0300] The second communication device may also determine whether interpolation is required during data construction based on the data type of the first data.

[0301] In the above S320, the first compressed data may include the first compressed data of each sub-data in the M sub-data, or may refer to the i-th sub-data Y i correspondingly, the first time-frequency resource may include the first time-frequency resource for transmitting the first compressed data of each sub-data in the M sub-data, or may refer to the first time-frequency resource for transmitting the i-th sub-data Y i The first time-frequency resource of the first compressed data. This application does not limit this.

[0302] In the above embodiment, the determination of the i-th sub-data Y i The first compressed data Z i The description of ' is also applicable to the above S330 and will not be repeated here.

[0303] On the basis of any of the above embodiments, in the above S330, the first communication device may determine the compression parameter according to the first time-frequency resource, and then perform compression on the i-th sub-data Y according to the compression parameter. i Perform data compression to obtain the first compressed data Z i '; Wherein, the compression parameters include at least one of the following:

[0304] First capability threshold;

[0305] Encoding parameters;

[0306] Quantization accuracy parameters;

[0307] The number of columns of the subdata.

[0308] The encoding method parameter may indicate the encoding method of the i-th sub-data Y i The dictionary matrix D i , sparse matrix X i (or sparse matrix X i The first position indication information and the first element sequence) are respectively encoded in a manner, and optionally, the encoding manner may include scalar quantization, vector quantization, entropy coding, etc.

[0309] The quantization precision parameter can indicate the quantization precision of the i-th sub-data Y i The dictionary matrix D i , sparse matrix X i (or sparse matrix X i The first position indication information and the first element sequence of the first position indication information and the first element sequence of the first position indication information and the precision of the quantization. Optionally, in the scalar quantization mode, the compression parameter may also include the quantization range of the scalar quantization; in the vector quantization mode, the compression parameter may also include the codebook information corresponding to the appropriate quantization.

[0310] Optionally, the first communication device may also determine a sampling accuracy parameter based on the first time-frequency resource, and the first communication device may determine the side length of the cube based on the sampling accuracy parameter; or the sampling accuracy parameter may directly indicate the side length of the cube.

[0311] Optionally, the first communication device may also determine at least one of the first distance threshold, the second distance threshold and the third distance threshold based on the first time-frequency resource.

[0312] In the above S340, the third indication information may be i 'Sent together on the first time-frequency resource, but this application is not limited to this, for example, the first indication information can be sent separately, and the first communication device sends the second indication information and sends the first compressed data Z i 'The execution order is not limited.

[0313] The third indication information is the second indication information used to indicate that the first compressed data Z i First, the second indication information is exemplarily described.

[0314] The second indication information is used to indicate at least one of the following:

[0315] First capability threshold;

[0316] The second capability threshold;

[0317] Sparse matrix X i The i-th sub-data Y i The proportion of the elements of the first ability;

[0318] Compressed data Z i Relative to the i-th sub-data Y i data loss;

[0319] Encoding parameters;

[0320] Quantization accuracy parameters;

[0321] The number of columns of the sub-data;

[0322] Sparse matrix X i Whether the position indication information is differential position indication information.

[0323] Among them, the first capability threshold, the second capability threshold, and the sparse matrix X i The i-th sub-data Y i The proportion of elements of the first capability, and the compressed data Z i Relative to the i-th sub-data Y i The data loss can be used by the second communication device to determine whether it is necessary to compress and transmit the first data in an incremental transmission manner; the encoding method parameter and the quantization accuracy parameter can be used by the second communication device to compress the data Z i Decompress; first capacity threshold, second capacity threshold, number of columns of sub-data, sparse matrix X i Whether the location indication information is differential location indication information can be used by the second communication device to construct data.

[0324] Optionally, the second indication information may also include the above-mentioned sampling accuracy parameter.

[0325] Optionally, the second indication information may also include at least one of the first distance threshold, the second distance threshold and the third distance threshold.

[0326] Exemplarily, the second indication information may include one or more of the fields shown in Table 1:

[0327] Table 1

[0328]

[0329] The compression state is used by the second communication device to determine whether it is necessary to perform compression transmission of the first data in an incremental transmission manner. The compression state field may include: a first capability threshold, a second capability threshold, a sparse matrix X i The i-th sub-data Y i The proportion of elements of the first capability, and the compressed data Z i Relative to the i-th sub-data Y i at least one of the data loss.

[0330] The data split indication may be the number of columns of the sub-data.

[0331] Optionally, in the second indication information shown in Table 1, the compression method of the position indication information may include (Lempel–Ziv 77, LZ77), LZ77 is a dictionary-based, "sliding window" lossless compression algorithm invented by Lempel-Ziv in 1977; (Lempel–Ziv–Markov chain algorithm, LZMA), LZMA is a compression algorithm improved based on LZ77, with the characteristics of high compression rate, high decompression speed, low memory consumption, etc. The above compression method is only an example and not a limiting description, and the compression method of the position indication information may also include any other compression algorithm, which will not be listed one by one.

[0332] In some embodiments, the sampling accuracy parameter, distance threshold field, and data split indication field in Table 1 are all optional fields, and all fields except the sampling accuracy parameter, distance threshold field, and data split indication field in Table 1 are all mandatory fields.

[0333] Based on the above example of the second indication information, the third indication information may be used to indicate at least one of the following:

[0334] First capability threshold;

[0335] Sparse matrix X i The i-th sub-data Y i The proportion of the element of the first capability (in some embodiments, the element is replaced by the first element);

[0336] The first compressed data Z i 'Relative to the i-th sub-data Y i data loss;

[0337] Encoding parameters;

[0338] Quantization accuracy parameters;

[0339] The number of columns of the sub-data;

[0340] Sparse matrix X i Whether the first position indication information is differential position indication information.

[0341] In some embodiments, the second communication device i ' and the third indication information to construct the i-th sub-data Y i 'Afterwards, you can use the i-th sub-data Y i 'The construction quality, or according to the i-th sub-data Y i 'Build quality and first compression data Z i ', sends the second resource configuration information and / or the third resource configuration information for incremental transmission, for example, the second communication device sends the second resource configuration information and / or the third resource configuration information in the i-th sub-data Y i The second resource configuration information and / or the third resource configuration information occurs when the construction quality of the first compressed data Z is poor. The compression state can be indicated by the above compression state field. Alternatively, the second communication device can i ' compression state, send the second resource configuration information and / or the third resource configuration information, for example, the second communication device indicates the first compressed data Z in the compression state field i 'Relative to the i-th sub-data Y i When the data loss exceeds a threshold, the second resource configuration information and / or the third resource configuration information is sent.

[0342] In the above embodiment, the determination of the i-th sub-data Y i The second compressed data Z i " and the third compressed data Z i The description of "' is also applicable to the above-mentioned S370 and will not be repeated here.

[0343] On the basis of any of the above embodiments, in the above S370, the first communication device may determine the compression parameter according to the second time-frequency resource, and then perform compression on the i-th sub-data Y according to the compression parameter. i Perform data compression to obtain the second compressed data Z i "; wherein the compression parameters include at least one of the following:

[0344] First capability threshold;

[0345] Encoding parameters;

[0346] Quantization accuracy parameters;

[0347] The number of columns of the subdata.

[0348] On the basis of any of the above embodiments, in the above S370, the first communication device may determine the compression parameter according to the third time-frequency resource, and then perform compression on the i-th sub-data Y according to the compression parameter. i Perform data compression to obtain the third compressed data Z i "'; wherein the compression parameters include at least one of the following:

[0349] First capability threshold;

[0350] The second capability threshold;

[0351] Encoding parameters;

[0352] Quantization accuracy parameters;

[0353] The number of columns of the subdata.

[0354] Optionally, the first communication device may send fourth indication information to the second communication device, where the fourth indication information is the second indication information and is used to indicate that the second compressed data Z i " is an implementation of the relevant parameters of the invention, the fourth indication information may be used to indicate at least one of the following:

[0355] First capability threshold;

[0356] Sparse matrix X i The i-th sub-data Y i The proportion of the elements of the first ability;

[0357] Compressed data Z i Relative to the i-th sub-data Y i data loss;

[0358] Encoding parameters;

[0359] Quantization accuracy parameters;

[0360] The number of columns of the sub-data;

[0361] Sparse matrix X i Whether the second position indication information is differential position indication information.

[0362] Optionally, the first communication device may send fifth indication information to the second communication device, where the fifth indication information is the second indication information and is used to indicate that the third compressed data Z i " is an implementation of the relevant parameters of the invention, the fifth indication information may be used to indicate at least one of the following:

[0363] First capability threshold;

[0364] The second capability threshold;

[0365] Encoding parameters;

[0366] Quantization accuracy parameters;

[0367] The number of columns of the sub-data;

[0368] Sparse matrix X i Whether the position indication information is differential position indication information.

[0369] The above S380 and S390 are explained in the above embodiments and will not be repeated here.

[0370] In some implementation scenarios of the embodiments of the present application, at least two of the first compressed data, the second compressed data, and the third compressed data may be sent together. For the at least two compressed data sent together, the second communication device may send resource configuration information corresponding to the at least two compressed data together. In this case, at least two of the first resource configuration information, the second resource configuration information, and the third resource configuration information sent together may be included in the resource configuration information.

[0371] Therefore, in the embodiment of the present application, the first communication device divides the first data to be transmitted into M sub-data, and for the i-th sub-data Y in the M sub-data i , decompose it into a dictionary matrix D i and the sparse matrix X i , and then according to the dictionary matrix D i and the sparse matrix X i Perform data compression to obtain the i-th sub-data Y i The compressed data Z i , and then send the i-th sub-data Y to the second communication device i The compressed data Z i , through the sparse matrix X i Based on the dictionary matrix D i Express the i-th sub-data Y i , so as to realize effective and reliable data compression transmission of first data with a large amount of data in a communication scenario with a large amount of data to be transmitted.

[0372] Figure 18 is a schematic block diagram of a communication device provided in an embodiment of the present application. The communication device 400 may be a terminal or a network device, or a device in a terminal device or a network device, or a device that can be used in combination with a terminal device or a network device. In one possible implementation, the communication device 400 may include a module or unit corresponding to the method / operation / step / action performed by the first communication device or the second communication device in the above method embodiment, and the unit may be a hardware circuit, or software, or a hardware circuit combined with software. In one possible implementation, as shown in Figure 18, the device 400 may include: a transceiver module 410 and a processing module 420.

[0373] Optionally, the communication device 400 may correspond to the first communication device in the above method embodiment.

[0374] When the communication device 400 is used to execute the method on the first communication device side, the processing module 420 can be used to process the i-th sub-data Y in the M sub-data. i , the i-th sub-data Y i Decompose into dictionary matrix D i and the sparse matrix X i , the dictionary matrix D i Including the i-th sub-data Y i The features of this sparse matrix X i Based on the dictionary matrix D i Express the i-th sub-data Y i , the M sub-data are included in the first data to be transmitted, M is an integer greater than or equal to 1, i is an integer greater than or equal to 1 and less than or equal to M; the processing module 420 can also be used to select the first data according to the dictionary matrix D i And the sparse matrix X i Perform data compression to obtain the i-th sub-data Y i The compressed data Z i The transceiver module 410 may be used to send the compressed data Z to the second communication device. i .

[0375] It should be understood that the specific process executed by each module has been described in detail in the above method embodiment, and for the sake of brevity, it will not be repeated here.

[0376] Optionally, the communication device 400 may correspond to the second communication device in the above method embodiment.

[0377] When the communication device 400 is used to execute the method on the second communication device side, the transceiver module 410 can be used to receive the i-th sub-data Y among the M sub-data sent by the first communication device. i The compressed data Z i, the M sub-data are included in the first data, M is an integer greater than or equal to 1, i is an integer greater than or equal to 1 and less than or equal to M; the processing module 420 can be used to compress the data Z according to the compressed data i Determine the dictionary matrix D i ' and the sparse matrix X i ', the dictionary matrix D i 'Including the i-th sub-data Y i The features of this sparse matrix X i 'For the dictionary matrix D i 'Express the i-th sub-data Y i The processing module 420 is also used to calculate the dictionary matrix D i ' and the sparse matrix X i ', construct the i-th sub-data Y of the M sub-data of the second data i '.

[0378] It should be understood that the specific process executed by each module has been described in detail in the above method embodiment, and for the sake of brevity, it will not be repeated here.

[0379] The transceiver module 410 in the communication device 400 may be implemented by a transceiver, for example, corresponding to the transceiver 520 in the communication device 500 shown in FIG. 19 . The processing module 420 in the communication device 400 may be implemented by at least one processor, for example, corresponding to the processor 510 in the communication device 500 shown in FIG. 19 .

[0380] When the communication device 400 is a chip or a chip system configured in a communication device (such as a terminal device or a network device), the transceiver module 410 in the communication device 400 can be implemented through an input / output interface, circuit, etc., and the processing module 420 in the communication device 400 can be implemented through a processor, microprocessor or integrated circuit integrated on the chip or chip system.

[0381] Fig. 19 is another schematic block diagram of a communication device provided in an embodiment of the present application. As shown in Fig. 19, the communication device 500 may include: a processor 510. The processor 510 may be used to execute the method executed by the first communication device or the second communication device in the above method embodiment.

[0382] In some possible implementations, the communication device 500 may include a transceiver 520. The transceiver 520 may communicate with the processor 510 through an internal connection path. The processor 510 may control the transceiver 520 to send and / or receive signals.

[0383] In some possible implementations, the communication device 500 may include a memory 530. The memory 530 may communicate with the processor 510 through an internal connection path. The memory 530 and the processor 510 may be integrated together or separately arranged. The memory 530 may also be a memory outside the device. The memory 530 is used to store instructions, and the processor 510 is used to execute the instructions stored in the memory 530 to execute the method in the above method embodiment.

[0384] It should be understood that the communication device 500 may correspond to the terminal device or network device in the above method embodiment, and may be used to execute the various steps and / or processes performed by the first communication device or the second communication device in the above method embodiment. Optionally, the memory 530 may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. The memory 530 may be a separate device or may be integrated in the processor 510. The processor 510 may be used to execute instructions stored in the memory 530, and when the processor 510 executes instructions stored in the memory, the processor 510 is used to execute the various steps and / or processes of the above method embodiment corresponding to the terminal device or network device.

[0385] Optionally, the communication device 500 is the first communication device in the foregoing embodiment.

[0386] Optionally, the communication device 500 is the second communication device in the foregoing embodiment.

[0387] Among them, the transceiver 520 may include a transmitter and a receiver. The transceiver 520 may further include an antenna, and the number of antennas may be one or more. The processor 510 and the memory 530 and the transceiver 520 may be devices integrated on different chips. For example, the processor 510 and the memory 530 may be integrated in a baseband chip, and the transceiver 520 may be integrated in a radio frequency chip. The processor 510 and the memory 530 and the transceiver 520 may also be devices integrated on the same chip. This application does not limit this.

[0388] Optionally, the communication device 500 is a component configured in a terminal device, such as a chip, a chip system, etc.

[0389] Optionally, the communication device 500 is a component configured in a network device, such as a chip, a chip system, etc.

[0390] The transceiver 520 may also be a communication interface, such as an input / output interface, a circuit, etc. The transceiver 520, the processor 510, and the memory 530 may be integrated into the same chip, such as a baseband chip.

[0391] The present application also provides a processing device, including at least one processor, wherein the at least one processor runs a computer program or a logic circuit so that the processing device executes the method executed by the first communication device or the second communication device in the above method embodiment. The above processing device may also include a memory, which is used to store the above computer program.

[0392] The embodiment of the present application also provides a processing device, including a processor and an input / output interface. The input / output interface is coupled to the processor. The input / output interface is used to input and / or output information. The information includes at least one of an instruction and data. The processor is used to execute a computer program so that the processing device executes the method executed by the first communication device or the second communication device in the above method embodiment.

[0393] The present application also provides a processing device, including a processor and a memory. The memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the processing device executes the method executed by the first communication device or the second communication device in the above method embodiment.

[0394] It should be understood that the above-mentioned processing device may be one or more chips. For example, the processing device may be a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on chip (SoC), a central processor unit (CPU), a network processor (NP), a digital signal processor (DSP), a microcontroller unit (MCU), a programmable logic device (PLD) or other integrated chips.

[0395] In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software. The steps of the method disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor for execution, or a combination of hardware and software modules in a processor for execution. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it is not described in detail here.

[0396] It should be noted that the processor in the embodiment of the present application can be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiment can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiment of the present application can be directly embodied as a hardware decoding processor to perform, or the hardware and software modules in the decoding processor can be combined and performed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0397] It can be understood that the memory in the embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0398] According to the method provided in the embodiments of the present application, the present application also provides a computer program product, which includes: a computer program or a set of instructions, when the computer program or a set of instructions is run on a computer, the computer executes the method executed by the first communication device or the second communication device in the above method embodiments.

[0399] According to the method provided in the embodiment of the present application, the present application also provides a computer-readable storage medium, which stores a program. When the program runs on a computer, the computer executes the method executed by the first communication device or the second communication device in the above method embodiment.

[0400] According to the method provided in the embodiment of the present application, the present application also provides a communication system, which may include the aforementioned first communication device or second communication device.

[0401] The terms "component", "module", "system", etc. used in this specification are used to represent computer-related entities, hardware, firmware, a combination of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program and / or a computer. By way of illustration, both applications running on a computing device and a computing device can be components. One or more components may reside in a process and / or an execution thread, and a component may be located on a computer and / or distributed between two or more computers. In addition, these components may be executed from various computer-readable media having various data structures stored thereon. Components may, for example, communicate through local and / or remote processes according to signals having one or more data packets (e.g., data from two components interacting with another component between a local system, a distributed system and / or a network, such as the Internet interacting with other systems through signals).

[0402] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0403] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0404] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0405] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0406] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0407] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the part of the technical solution of the present application that contributes essentially or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard drives, ROM, RAM, magnetic disks, or optical disks.

[0408] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

A data compression transmission method, characterized in that: include: The first communication device receives the i-th sub-data Y among the M sub-data. i , the i-th sub-data Y i Decompose into dictionary matrix D i and the sparse matrix X i , the dictionary matrix D i Including the i-th sub-data Y i The features of the sparse matrix X i For the dictionary matrix D i Express the i-th sub-data Y i , the M sub-data are included in the first data to be transmitted, M is an integer greater than or equal to 1, i is an integer greater than or equal to 1 and less than or equal to M; the first communication device transmits the first data according to the dictionary matrix D i and the sparse matrix X i Perform data compression to obtain the i-th sub-data Y i The compressed data Z i The first communication device sends the compressed data Z to the second communication device i . The method according to claim 1, characterized in that The first communication device obtains the i-th sub-data Y i The compressed data Z i , comprising: the first communication device determines the sparse matrix X i The first position indication information and the first element sequence of the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The first element sequence includes a first capability of expressing the i-th sub-data Y i or, the first position indication information is used to indicate the sparse matrix X i Does the first element in have the expression of the i-th sub-data Y i The first capability is that the sparse matrix X i The elements in include the first element, and the first element sequence includes the expression of the i-th sub-data Y i The first communication device has an element of the first capability of the dictionary matrix D i , and the sparse matrix X i The first position indication information and the first element sequence are compressed to obtain the i-th sub-data Y i The first compressed data Z i '. The method according to claim 2, characterized in that The first position indication information is a first bitmap; the bits in the first bitmap are consistent with the sparse matrix X i The elements in the first bitmap correspond one to one, and the bits in the first bitmap are used to indicate the sparse matrix X i Does the corresponding element in have the expression of the i-th sub-data Y i or, the bits in the first bitmap and the sparse matrix X i The first elements in the first bitmap correspond one to one, and the bits in the first bitmap are used to indicate the sparse matrix X i Whether the first element corresponding to the expression has the i-th sub-data Y i The first ability. The method according to claim 2 or 3, characterized in that The first communication device determines the sparse matrix X i The first position indication information and the first element sequence of the sparse matrix X are as follows: i For each element in , according to the element and the first capability threshold, determine whether the element has the ability to express the i-th sub-data Y i The first communication device according to the sparse matrix X i Whether each element in has the function of expressing the i-th sub-data Y i The first capability of determining the first position indication information and the first element sequence. The method according to any one of claims 2 to 4, characterized in that The sparse matrix X i The first position indication information is the i-th sub-data Y i The first position indication information and the i-1th sub-data Y i-1 The first position indication information is XORed to obtain the difference position indication information; the difference position indication information is used as the sparse matrix X i The first position indication information. The method according to claim 5, characterized in that The first ratio of the difference position indication information is greater than or equal to the ratio threshold, the first ratio is the ratio of the number of bits of the first value or the second value in the bits of the difference position indication information to the number of all bits, and the first value is used to indicate the sparse matrix X i The corresponding element in has the expression of the i-th sub-data Y i The first capability of the second value is used to indicate the sparse matrix X i The corresponding element in does not have the expression of the i-th sub-data Y i The first ability. The method according to any one of claims 2 to 6, characterized in that The first position indication information is used to indicate the sparse matrix X i Does the first element in the expression have the i-th sub-data Y i The first capability is that the sparse matrix X i The elements of X include a second element, the second element is different from the first element, and the method further includes: the first communication device determines the sparse matrix X i The second position indication information and the second element sequence, wherein the second position indication information is used to indicate the sparse matrix X i Does the second element in have the expression of the i-th sub-data Y i The first capability, the second element sequence includes a sequence having the expression of the i-th sub-data Y i The first communication device performs data compression on the second position indication information and the second element sequence to obtain the i-th sub-data Y i The second compressed data Z i ", the second compressed data Z i " and the first compressed data Z i 'different. The method according to any one of claims 2 to 7, characterized in that Also includes: The first communication device determines the sparse matrix X i The third position indication information and the third element sequence of the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i The third element sequence includes a second capability of expressing the i-th sub-data Y i The element of the second ability; The first communication device performs a i The third position indication information and the third element sequence are compressed to obtain the i-th sub-data Y i The third compressed data Z i "'; The first communication device sends the third compressed data Z to the second communication device i ”'. The method according to claim 8, characterized in that The first communication device determines the sparse matrix X i The third position indication information and the third element sequence of the sparse matrix X include: the first communication device i For each element in , according to the element, the first capability threshold and the second capability threshold, determine whether the element has the ability to express the i-th sub-data Y i The first communication device according to the sparse matrix X i Whether each element in has the function of expressing the i-th sub-data Y i The second capability determines the third position indication information and the third element sequence. The method according to any one of claims 2 to 7, characterized in that Also includes: The first communication device determines the sparse matrix X i The third element sequence of the sparse matrix X i N elements other than the elements included in the first element sequence, where N is a positive integer; the first communication device performs data compression on the third element sequence to obtain the i-th sub-data Y i The third compressed data Z i "'; The first communication device sends the third compressed data Z to the second communication device i ”'. The method according to claim 10, characterized in that The N elements are the sparse matrix X i Elements in a preset row / column in . The method according to any one of claims 1 to 11, characterized in that The number of columns of the matrix formed by each sub-data in the M sub-data is the same. The method according to any one of claims 1 to 12, characterized in that The method further includes: the first communication device determines a compression parameter according to the time-frequency resource of the first data; the first communication device performs compression on the i-th sub-data Y according to the compression parameter i Perform data compression to obtain the compressed data Z i ; Wherein, the compression parameter includes at least one of the following: a first capability threshold, the first capability threshold is used to determine the sparse matrix X i Whether the element in has the expression of the i-th sub-data Y i A first capability; a second capability threshold, wherein the second capability threshold is used to determine the sparse matrix X i Whether the element in has the expression of the i-th sub-data Y i The second capability; encoding method parameters; quantization accuracy parameters; number of columns of sub-data. The method according to any one of claims 1 to 13, characterized in that The method further includes: the first communication device sends second indication information to the second communication device, the second indication information is used to indicate at least one of the following: a first capability threshold, the first capability threshold is used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i A first capability; a second capability threshold, wherein the second capability threshold is used to determine the sparse matrix X i Whether the element in has the expression of the i-th sub-data Y i The second capability of sparse matrix X i The i-th sub-data Y i The proportion of elements of the first capability; the compressed data Z i Relative to the i-th sub-data Y i data loss; encoding method parameters; quantization precision parameters; number of columns of sub-data; the sparse matrix X i Whether the position indication information is differential position indication information. A data compression transmission method, characterized in that: include: The second communication device receives the i-th sub-data Y of the M sub-data sent by the first communication device. i The compressed data Z i , the M sub-data are included in the first data, M is an integer greater than or equal to 1, i is an integer greater than or equal to 1 and less than or equal to M; the second communication device receives the compressed data Z i Determine the dictionary matrix D i ' and the sparse matrix X i ', the dictionary matrix D i 'Including the i-th sub-data Y i The features of the sparse matrix X i 'For the dictionary matrix D i 'Express the i-th sub-data Y i The second communication device according to the dictionary matrix D i ' and the sparse matrix X i ', construct the i-th sub-data Y of the M sub-data of the second data i '. The method according to claim 15, characterized in that The compressed data Z i Including the first compressed data Z i ', the second communication device according to the compressed data Z i Determine the dictionary matrix D i ' and the sparse matrix X i ', comprising: the second communication device converts the first compressed data Z i 'Unzip to obtain the dictionary matrix D i ', and, the sparse matrix X i 'The first position indication information and the first element sequence; wherein the first position indication information is used to indicate the sparse matrix X i 'Whether the element in has the i-th sub-data Y among the M sub-data expressing the first data i The first element sequence includes a first capability of expressing the i-th sub-data Y i or, the first position indication information is used to indicate the sparse matrix X i 'Whether the first element in the expression has the i-th sub-data Y i The first capability is that the sparse matrix X i ' includes the first element, and the first element sequence includes the expression of the i-th sub-data Y i The second communication device is based on the sparse matrix X i 'The first position indication information and the first element sequence determine the sparse matrix X i '. The method according to claim 16, characterized in that The first position information is a first bitmap; the bits in the first bitmap are the same as the bits in the sparse matrix X i The elements in the first bitmap correspond one to one, and the bits in the first bitmap are used to indicate the sparse matrix X i 'Whether the corresponding element in has the expression of the i-th sub-data Y i or, the bits in the first bitmap and the sparse matrix X i ' corresponds to the first element in one-to-one correspondence, and the bits in the first bitmap are used to indicate the sparse matrix X i 'Whether the first element corresponding to the expression of the i-th sub-data Y i The first ability. The method according to claim 16 or 17, characterized in that The sparse matrix X i The first position indication information is the difference position indication information obtained by performing an XOR operation on the first position indication information of the i-th sub-data and the first position indication information of the i-1-th sub-data. The method according to any one of claims 16 to 18, characterized in that The compressed data Z i Also includes the second compressed data Z i ", the first position indication information is used to indicate the sparse matrix X i 'Whether the first element in the expression has the i-th sub-data Y i The second communication device compresses the first data Z according to the first capability of i Determine the dictionary matrix D i ' and the sparse matrix X i ', comprising: the second communication device transmits the second compressed data Z i "Unzip to get the sparse matrix X i ', the second position indication information and the second element sequence, the second position indication information is used to indicate the sparse matrix X i 'Whether the second element in has the expression of the i-th sub-data Y i The first capability, the second element sequence includes a sequence having the expression of the i-th sub-data Y i The second element of the first capability of the second communication device according to the sparse matrix X i ', the first position indication information, the first element sequence, the second position indication information and the second element sequence, determine the sparse matrix X i '. The method according to claim 19, characterized in that The compressed data Z i Also includes the third compressed data Z i "', the second communication device according to the first compressed data Z i Determine the dictionary matrix D i ' and the sparse matrix X i ', comprising: the second communication device transmits the third compressed data Z i ”'Decompress and get the sparse matrix X i ', the third position indication information and the third element sequence, the third position indication information is used to indicate the sparse matrix X i 'Whether the element in has the expression of the i-th sub-data Y i The second element sequence includes a second capability of expressing the i-th sub-data Y i The second communication device is based on the sparse matrix X i ', the third position indication information, the third element sequence, and at least one of the following, determine the sparse matrix X i ': the sparse matrix X i 'The first position indication information, the first element sequence; the sparse matrix X i 'The second position indication information and the second element sequence. The method according to claim 19, characterized in that The compressed data Z i Also includes the third compressed data Z i "', the second communication device according to the first compressed data Z i Determine the dictionary matrix D i ' and the sparse matrix X i ', comprising: the second communication device transmits the third compressed data Z i ”'Decompress and get the sparse matrix X i ', the third element sequence includes the sparse matrix X i 'N elements other than the elements included in the first element sequence and / or the second element sequence, where N is a positive integer; the second communication device according to the sparse matrix X i 'The third element sequence and at least one of the following, determine the sparse matrix X i ': the sparse matrix X i 'The first position indication information, the first element sequence; the sparse matrix X i 'The second position indication information and the second element sequence. The method according to claim 21, characterized in that The N elements are the sparse matrix X i Elements in a preset row / column in . The method according to any one of claims 15 to 22, characterized in that The number of columns of the matrix formed by each sub-data in the M sub-data is the same. The method according to any one of claims 15 to 23, characterized in that The method further includes: the second communication device receiving second indication information sent by the first communication device, the second indication information being used to indicate at least one of the following: a first capability threshold, the first capability threshold being used to determine the sparse matrix X i Does the element in have the expression of the i-th sub-data Y i A first capability; a second capability threshold, wherein the second capability threshold is used to determine the sparse matrix X i Whether the element in has the expression of the i-th sub-data Y i The second capability of sparse matrix X i The i-th sub-data Y i The proportion of elements of the first capability; the compressed data Z i Relative to the i-th sub-data Y of the M sub-data of the first data i data loss; encoding method parameters; quantization precision parameters; number of columns of sub-data; the sparse matrix X i Whether the bitmap is a difference bitmap. A communication device, characterized in that: The method comprises a module for executing the method as claimed in any one of claims 1 to 14, or comprises a module for executing the method as claimed in any one of claims 15 to 24. A communication device, characterized in that: include: A processor, wherein the processor is configured to execute the method according to any one of claims 1 to 24 by running a computer program or by a logic circuit. The device according to claim 26, characterized in that Also included is a memory for storing the computer program. The device according to claim 26 or 27, characterized in that Also included is a communication interface for inputting and / or outputting signals. A communication system, characterized in that: include: A first communication device for executing the method according to any one of claims 1 to 14, and a second communication device for executing the method according to any one of claims 15 to 24. A computer-readable storage medium, characterized in that Used to store computer program instructions, the computer program causing a computer to execute the method according to any one of claims 1 to 24. A computer program product, characterized in that The method comprises computer program instructions which cause a computer to execute the method as claimed in any one of claims 1 to 24.

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