Data compression method and device, computer equipment, chip and chip module

Abstract

The invention relates to a data compression method and device, computer equipment, a chip and a chip module. The method comprises the following steps: acquiring a compression reference value and a compression threshold value corresponding to data to be compressed; the compression reference value is used for determining a compression mode corresponding to the to-be-compressed data, and the compression threshold value is used for determining whether to compress the to-be-compressed data; under the condition that the to-be-compressed data meets the compression threshold value, determining a compression mode corresponding to the to-be-compressed data according to the compression reference value; and according to the compression mode, performing corresponding compression processing on the to-be-compressed data to obtain compressed data corresponding to the to-be-compressed data. By adopting the method, the data compression quality can be improved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a data compression method, apparatus, computer equipment, chip, chip module, computer-readable storage medium, and computer program product. Background Technology

[0002] Currently, data compression is crucial in order to reduce data storage overhead and transmission bandwidth usage.

[0003] In traditional technologies, data is typically compressed using a preset compression method (such as a fixed compression algorithm); however, this static processing logic is difficult to adapt to the characteristics of different data, resulting in low data compression quality. Summary of the Invention

[0004] Therefore, it is necessary to provide a data compression method, apparatus, computer equipment, chip, chip module, computer-readable storage medium, and computer program product that can improve the compression quality of data in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a data compression method, including:

[0006] Obtain the compression baseline value and compression threshold value corresponding to the data to be compressed; the compression baseline value is used to determine the compression method corresponding to the data to be compressed, and the compression threshold value is used to determine whether to compress the data to be compressed.

[0007] If the data to be compressed meets the compression threshold, the compression method corresponding to the data to be compressed is determined according to the compression reference value.

[0008] According to the compression method, the data to be compressed is subjected to corresponding compression processing to obtain the compressed data corresponding to the data to be compressed.

[0009] In one embodiment, obtaining the compression baseline value and compression threshold value corresponding to the data to be compressed includes:

[0010] Obtain the quantization level and the first storage bit width corresponding to the data to be compressed;

[0011] The quantization interval corresponding to the data to be compressed is determined based on the quantization level and the first storage bit width.

[0012] Based on the quantization interval, the quantization level, and the data to be compressed, a compression baseline value corresponding to the data to be compressed is determined, and a compression threshold value corresponding to the data to be compressed is obtained based on the quantization interval.

[0013] In one embodiment, determining the compression reference value corresponding to the data to be compressed based on the quantization interval, the quantization level, and the data to be compressed includes:

[0014] Based on the quantization interval and the quantization level, a quantization table corresponding to the data to be compressed is determined; the quantization table includes multiple preset compression reference values;

[0015] The maximum absolute value in the data set corresponding to the data to be compressed is determined. Based on the maximum absolute value, the compression reference value corresponding to the data to be compressed is determined from the plurality of preset compression reference values.

[0016] In one embodiment, determining the compression method corresponding to the data to be compressed based on the compression reference value includes:

[0017] Obtain the absolute value corresponding to the data to be compressed;

[0018] If the absolute value satisfies the compression reference value, the compression method corresponding to the data to be compressed is determined to be the first compression method;

[0019] or,

[0020] If the absolute value does not meet the compression reference value, the compression method corresponding to the data to be compressed is determined to be the second compression method.

[0021] In one embodiment, the step of performing corresponding compression processing on the data to be compressed according to the compression method to obtain compressed data corresponding to the data to be compressed includes:

[0022] According to the first compression method, the data to be compressed is compressed accordingly to obtain the first processed data corresponding to the data to be compressed. The first processed data is then quantized to obtain the first compressed data corresponding to the data to be compressed.

[0023] or,

[0024] According to the second compression method, the data to be compressed is subjected to corresponding compression processing to obtain the second processed data corresponding to the data to be compressed. The second processed data is then quantized to obtain the second compressed data corresponding to the data to be compressed.

[0025] In one embodiment, after performing corresponding compression processing on the data to be compressed according to the compression method to obtain the compressed data corresponding to the data to be compressed, the process includes:

[0026] Obtain the sign bit, compression bit, and compression method bit corresponding to the data to be compressed; the sign bit is used to indicate the sign corresponding to the data to be compressed, the compression bit is used to indicate whether the data to be compressed is to be compressed, and the compression method bit is used to indicate the compression method corresponding to the data to be compressed.

[0027] Obtain the second storage bit width corresponding to the sign bit, the third storage bit width corresponding to the compression bit, the fourth storage bit width corresponding to the compression method bit, and the fifth storage bit width corresponding to the compressed data;

[0028] The second storage bit width, the third storage bit width, the fourth storage bit width, and the fifth storage bit width are summed to obtain the target storage bit width;

[0029] The symbol bit, the compression bit, the compression method bit, and the compressed data are stored according to the target storage bit width.

[0030] Secondly, this application also provides a data compression apparatus, comprising:

[0031] The data acquisition module is used to acquire the compression reference value and compression threshold value corresponding to the data to be compressed; the compression reference value is used to determine the compression method corresponding to the data to be compressed, and the compression threshold value is used to determine whether to compress the data to be compressed.

[0032] The compression method determination module is used to determine the compression method corresponding to the data to be compressed based on the compression reference value when the data to be compressed meets the compression threshold value.

[0033] The data compression module is used to perform corresponding compression processing on the data to be compressed according to the compression method, so as to obtain the compressed data corresponding to the data to be compressed.

[0034] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0035] Obtain the compression baseline value and compression threshold value corresponding to the data to be compressed; the compression baseline value is used to determine the compression method corresponding to the data to be compressed, and the compression threshold value is used to determine whether to compress the data to be compressed.

[0036] If the data to be compressed meets the compression threshold, the compression method corresponding to the data to be compressed is determined according to the compression reference value.

[0037] According to the compression method, the data to be compressed is subjected to corresponding compression processing to obtain the compressed data corresponding to the data to be compressed.

[0038] Fourthly, this application also provides a chip, including a processor and a communication interface, wherein the processor is configured to cause the chip to perform:

[0039] Obtain the compression baseline value and compression threshold value corresponding to the data to be compressed; the compression baseline value is used to determine the compression method corresponding to the data to be compressed, and the compression threshold value is used to determine whether to compress the data to be compressed.

[0040] If the data to be compressed meets the compression threshold, the compression method corresponding to the data to be compressed is determined according to the compression reference value.

[0041] According to the compression method, the data to be compressed is subjected to corresponding compression processing to obtain the compressed data corresponding to the data to be compressed.

[0042] Fifthly, this application also provides a chip module, including a communication module, a power module, a storage module, and a chip, wherein:

[0043] The power module is used to provide power to the chip module;

[0044] The storage module is used to store data and instructions;

[0045] The communication module is used for internal communication within the chip module, or for communication between the chip module and external devices.

[0046] The chip is used to perform the steps of the method provided in the first aspect above.

[0047] Sixthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0048] Obtain the compression baseline value and compression threshold value corresponding to the data to be compressed; the compression baseline value is used to determine the compression method corresponding to the data to be compressed, and the compression threshold value is used to determine whether to compress the data to be compressed.

[0049] If the data to be compressed meets the compression threshold, the compression method corresponding to the data to be compressed is determined according to the compression reference value.

[0050] According to the compression method, the data to be compressed is subjected to corresponding compression processing to obtain the compressed data corresponding to the data to be compressed.

[0051] In a seventh aspect, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0052] Obtain the compression baseline value and compression threshold value corresponding to the data to be compressed; the compression baseline value is used to determine the compression method corresponding to the data to be compressed, and the compression threshold value is used to determine whether to compress the data to be compressed.

[0053] If the data to be compressed meets the compression threshold, the compression method corresponding to the data to be compressed is determined according to the compression reference value.

[0054] According to the compression method, the data to be compressed is subjected to corresponding compression processing to obtain the compressed data corresponding to the data to be compressed.

[0055] The aforementioned data compression method, apparatus, computer equipment, chip, chip module, computer-readable storage medium, and computer program product first obtain the compression reference value and compression threshold value corresponding to the data to be compressed. The compression reference value is used to determine the compression method corresponding to the data to be compressed, and the compression threshold value is used to determine whether to compress the data to be compressed. If the data to be compressed meets the compression threshold value, the compression method corresponding to the data to be compressed is determined according to the compression reference value. Then, according to the compression method, the data to be compressed is compressed accordingly to obtain the compressed data. In this way, when compressing data, the compression method matching the characteristics of the data to be compressed is first determined based on the compression reference value, avoiding the problem of insufficient adaptability of a single compression algorithm. Then, the data to be compressed that truly needs to be compressed is filtered out by the compression threshold value, eliminating invalid processing of data with no compression gain or data that is prone to distortion after compression. Finally, the appropriate compression method is accurately applied to the data that meets the compression conditions. While ensuring compression efficiency, it reduces distortion caused by algorithm mismatch and invalid compression, avoiding the defect of low data compression quality caused by using a preset compression method to compress data in traditional technologies, and thus improving the data compression quality. Attached Figure Description

[0056] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0057] Figure 1 This is a flowchart illustrating a data compression method in one embodiment;

[0058] Figure 2 This is a flowchart illustrating a data compression method in another embodiment;

[0059] Figure 3 This is a schematic diagram of the pilot structure in one embodiment;

[0060] Figure 4 This is a flowchart illustrating a low-storage, high-reliability data compression method applicable to a wireless communication receiver in one embodiment.

[0061] Figure 5 This is a structural block diagram of a data compression device in one embodiment;

[0062] Figure 6 This is an internal structural diagram of a computer device in one embodiment;

[0063] Figure 7 This is an internal structure diagram of a chip module in one embodiment. Detailed Implementation

[0064] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0065] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0066] In one exemplary embodiment, such as Figure 1 As shown, a data compression method is provided. This embodiment illustrates the application of this method to a server. It is understood that this method can also be applied to terminals, systems including terminals and servers, and is implemented through interaction between the terminal and server. It can also be applied to communication equipment, terminal equipment, base stations, network-side equipment, chips, and chip modules. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, and tablets; the server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. In this embodiment, the method includes the following steps:

[0067] Step S101: Obtain the compression reference value and compression threshold value corresponding to the data to be compressed; the compression reference value is used to determine the compression method corresponding to the data to be compressed, and the compression threshold value is used to determine whether to compress the data to be compressed.

[0068] In this context, the data to be compressed refers to the real or imaginary part of the complex channel parameters corresponding to each subcarrier (RE) within each resource block (RB) of the channel (such as H_filter) in the communication system. The real and imaginary parts of the data corresponding to each RB constitute a data set corresponding to the data to be compressed, with an original storage width of P bits and a value range of 0 to 2^(P-1)-1. In practical scenarios, the data to be compressed is also denoted as x(i).

[0069] The compression baseline value refers to a reference value generated based on the statistical characteristics of the dataset corresponding to the data to be compressed. In practical scenarios, the compression baseline value is also called ref'.

[0070] The compression threshold is a threshold used to determine whether data to be compressed needs to undergo compression processing. In practical scenarios, the compression threshold is also called the Threshold.

[0071] The compression method refers to the logarithmic compression algorithm designed for the data to be compressed.

[0072] For example, the server inputs a reference signal into a preset signal transmission model to obtain the received signal output by the model; then, based on the input reference signal, it performs coarse channel estimation on the received signal to obtain a preliminary channel estimation result; then, it optimizes the preliminary channel estimation result through filtering to obtain the final target channel (i.e., channel H_filter); the target channel uses resource blocks (RBs) as the basic parameter grouping unit, each RB contains multiple subcarriers (REs), and each RE corresponds to a complex channel parameter characterizing the channel response characteristics. The complex channel parameters corresponding to each RE in all RBs are decomposed into real and imaginary parts, and the real or imaginary part is used as the data to be compressed; next, the data to be compressed is input into a feature extraction model for feature extraction processing to obtain the feature vector corresponding to the data to be compressed; then, the feature vector corresponding to the data to be compressed is input into a trained compression benchmark prediction model to obtain the compression benchmark value corresponding to the data to be compressed, and the feature vector corresponding to the data to be compressed is input into a trained compression threshold prediction model to obtain the compression threshold value corresponding to the data to be compressed; the compression benchmark value is used to determine the compression method corresponding to the data to be compressed, and the compression threshold value is used to determine whether to perform compression processing on the data to be compressed.

[0073] Step S102: If the data to be compressed meets the compression threshold, determine the compression method corresponding to the data to be compressed based on the compression reference value.

[0074] For example, the server obtains the absolute value of the data to be compressed and judges it based on the compression threshold. If the absolute value of the data to be compressed is greater than or equal to the compression threshold, the compression method of the data to be compressed is determined according to the relationship between the compression reference value and the absolute value of the data to be compressed. If the absolute value of the data to be compressed is less than the compression threshold, then no compression processing is required.

[0075] Step S103: According to the compression method, perform corresponding compression processing on the data to be compressed to obtain the compressed data corresponding to the data to be compressed.

[0076] Here, compressed data refers to the data obtained after the data to be compressed has been processed.

[0077] For example, the server inputs the data to be compressed into the moving average filter model to obtain the filtered data to be compressed; then, according to the compression method, the filtered data to be compressed is compressed to obtain the compressed data.

[0078] In the above data compression method, the compression baseline value and compression threshold value corresponding to the data to be compressed are first obtained. The compression baseline value is used to determine the compression method corresponding to the data to be compressed, and the compression threshold value is used to determine whether to compress the data to be compressed. If the data to be compressed meets the compression threshold value, the compression method corresponding to the data to be compressed is determined according to the compression baseline value. Then, according to the compression method, the data to be compressed is compressed accordingly to obtain the compressed data. In this way, when compressing data, the compression method matching the characteristics of the data to be compressed is first determined based on the compression baseline value, avoiding the problem of insufficient adaptability of a single compression algorithm. Then, the data to be compressed that truly needs to be compressed is filtered out by the compression threshold value, eliminating invalid processing of data with no compression gain or data that is prone to distortion after compression. Finally, the appropriate compression method is accurately applied to the data that meets the compression conditions. While ensuring compression efficiency, it reduces the distortion caused by algorithm mismatch and invalid compression, avoiding the defect of low data compression quality caused by using a preset compression method to compress data in traditional technology, which is conducive to improving the data compression quality.

[0079] In an exemplary embodiment, step S101 above, obtaining the compression reference value and compression threshold value corresponding to the data to be compressed, specifically includes the following: obtaining the quantization level and the first storage bit width corresponding to the data to be compressed; determining the quantization interval corresponding to the data to be compressed based on the quantization level and the first storage bit width; determining the compression reference value corresponding to the data to be compressed based on the quantization interval, the quantization level and the data to be compressed, and obtaining the compression threshold value corresponding to the data to be compressed based on the quantization interval.

[0080] The quantization level refers to the total number of levels used to discretize the compression reference value, denoted as L (L is a positive integer, such as 32, 64, etc.).

[0081] The first storage bit width refers to the original storage bit width of the data to be compressed, denoted as P (P is a positive integer, such as 12 bits, 16 bits, etc.).

[0082] Here, the quantization interval refers to the interval between evenly divided data segments to be compressed, denoted as step, and is calculated using the following formula: .

[0083] For example, in response to a data compression request for the data to be compressed, the server inputs the compression parameters carried in the data compression request into a trained information extraction model. The trained information extraction model then extracts the quantization level and the first storage bit width corresponding to the data to be compressed from the data compression request. Next, based on the first storage bit width, the data range corresponding to the data to be compressed (e.g., ...) is determined. The ratio between the data range and the quantization level is used as the quantization interval corresponding to the data to be compressed. Then, the quantization interval, quantization level and data to be compressed are input into the trained compression benchmark prediction model to obtain the compression benchmark value corresponding to the data to be compressed, and the quantization interval is used as the compression threshold value corresponding to the data to be compressed.

[0084] In this embodiment, by flexibly configuring the quantization level and the first storage bit width, the data storage accuracy and compression requirements under different channel scenarios are adapted. Furthermore, the quantization interval enables the coordinated correlation between the compression reference value and the compression threshold value, allowing the compression reference value to be dynamically adapted based on the actual amplitude characteristics of the data to be compressed, and the compression threshold value to accurately filter effective compressed data, thus ensuring the data compression effect.

[0085] In an exemplary embodiment, the compression reference value corresponding to the data to be compressed is determined based on the quantization interval, the quantization level, and the data to be compressed. Specifically, this includes: determining the quantization table corresponding to the data to be compressed based on the quantization interval and the quantization level; the quantization table includes multiple preset compression reference values; determining the maximum absolute value in the data set corresponding to the data to be compressed; and determining the compression reference value corresponding to the data to be compressed from the multiple preset compression reference values ​​based on the maximum absolute value.

[0086] The quantization table refers to the set of discrete reference values ​​constructed based on the quantization interval and the quantization level, denoted as LUT (Look-Up Table), and its expression is LUT={step×k|k=1,2,…,L} (step is the quantization interval, L is the quantization level, and k is a positive integer quantization index).

[0087] The preset compression reference value refers to the discrete reference value contained in the quantization table, that is, each element in the quantization table LUT.

[0088] The data set is used to represent the data combination to which the data to be compressed belongs, divided into units of resource blocks.

[0089] The maximum absolute value refers to the largest absolute value of all data to be compressed in the dataset (the real and imaginary parts of each RE).

[0090] For example, the server determines the quantization index sequence (e.g., 1, 2, ..., L) corresponding to the data to be compressed based on the quantization level, and calculates multiple preset compression benchmark values ​​corresponding to the data to be compressed based on the quantization index sequence and quantization interval. Based on the multiple preset compression benchmark values, an ordered quantization table is constructed. Then, the maximum absolute value in the data set corresponding to the data to be compressed is determined. Based on the maximum absolute value, the smallest preset compression benchmark value greater than the maximum absolute value is determined from the multiple preset compression benchmark values ​​and used as the compression benchmark value corresponding to the data to be compressed.

[0091] In this embodiment, a quantization table containing multiple preset compression benchmark values ​​is constructed by quantization interval and quantization level. The maximum absolute value of the data set is used as the core matching criterion to select the appropriate compression benchmark value. This realizes the standardization and normalization of the preset compression benchmark value, effectively solving the problem that traditional fixed benchmark values ​​cannot adapt to dynamic changes in data, and laying a reliable foundation for the subsequent accurate selection of compression methods.

[0092] In an exemplary embodiment, step S102, which determines the compression method corresponding to the data to be compressed based on the compression reference value, specifically includes the following: obtaining the absolute value corresponding to the data to be compressed; if the absolute value meets the compression reference value, determining the compression method corresponding to the data to be compressed as the first compression method; or, if the absolute value does not meet the compression reference value, determining the compression method corresponding to the data to be compressed as the second compression method.

[0093] The first compression method refers to a high-amplitude adaptive compression algorithm designed for data to be compressed where the absolute value meets the criteria for the compression baseline value.

[0094] The second compression method refers to a medium-to-low amplitude adaptive compression algorithm designed for data whose absolute value does not meet the criteria for compression benchmark value.

[0095] For example, the server obtains the absolute value corresponding to the data to be compressed; if twice the absolute value is greater than the compression reference value, the compression method corresponding to the data to be compressed is determined to be the first compression method; or, if twice the absolute value is less than or equal to the compression reference value, the compression method corresponding to the data to be compressed is determined to be the second compression method.

[0096] In this embodiment, the compression method corresponding to the data to be compressed is accurately distinguished by using the compression benchmark value as the judgment threshold. This judgment logic is simple and intuitive, and the compression method selection can be completed with only one numerical comparison. No complex calculation is required, which reduces the complexity of hardware operation and improves the overall execution efficiency of the compression process, laying a reliable foundation for the accurate implementation of subsequent compression processing.

[0097] In an exemplary embodiment, step S103 above, which involves performing corresponding compression processing on the data to be compressed according to a compression method to obtain compressed data corresponding to the data to be compressed, specifically includes the following: performing corresponding compression processing on the data to be compressed according to a first compression method to obtain first processed data corresponding to the data to be compressed, and performing quantization processing on the first processed data to obtain first compressed data corresponding to the data to be compressed; or, performing corresponding compression processing on the data to be compressed according to a second compression method to obtain second processed data corresponding to the data to be compressed, and performing quantization processing on the second processed data to obtain second compressed data corresponding to the data to be compressed.

[0098] Here, the first processed data refers to the data obtained by performing the first compression method on the absolute value of the data to be compressed.

[0099] The first compressed data refers to the data obtained after performing a quantization operation on the first processed data.

[0100] The second processed data refers to the data obtained by performing a second compression method on the absolute value of the data to be compressed.

[0101] The second compressed data refers to the data obtained after performing a quantization operation on the second processed data.

[0102] For example, the server performs compression processing on the data to be compressed according to a first compression method to obtain first processed data corresponding to the data to be compressed; then, based on the storage bit width corresponding to the first processed data, it determines the quantization parameter (e.g., Q) corresponding to the first processed data; then, based on the quantization parameter corresponding to the first processed data, it performs quantization processing on the first processed data to obtain first compressed data corresponding to the data to be compressed; or, according to a second compression method, the server performs compression processing on the data to be compressed to obtain second processed data corresponding to the data to be compressed; then, based on the storage bit width corresponding to the second processed data, it determines the quantization parameter corresponding to the second processed data; then, based on the quantization parameter corresponding to the second processed data, it performs quantization processing on the second processed data to obtain second compressed data corresponding to the data to be compressed.

[0103] For example, the data after the first processing is calculated using the following formula:

[0104] Equation (1)

[0105] in, This refers to the data to be compressed. This refers to the compression baseline value.

[0106] For example, the data after the second processing is calculated using the following formula:

[0107] Equation (2)

[0108] For example, the processed data (either the first or second processed data) can be quantified using the following formula:

[0109] Equation (3)

[0110] In this embodiment, by combining the step-by-step processing logic of compression and quantization, differentiated compression and quantization processes are matched for data to be compressed with different amplitudes. The data is first scaled to adapt to the amplitude, and then discretized and quantized. This avoids the cumulative loss of accuracy caused by direct quantization, improves the accuracy of the compressed data, and solves the problem that the traditional single compression and quantization process cannot take into account the accuracy and compression efficiency of data with different amplitudes.

[0111] In an exemplary embodiment, step S103, after performing corresponding compression processing on the data to be compressed according to the compression method to obtain the compressed data, specifically includes the following: obtaining the sign bit, compression bit, and compression method bit corresponding to the data to be compressed; obtaining the second storage bit width corresponding to the sign bit, the third storage bit width corresponding to the compression bit, the fourth storage bit width corresponding to the compression method bit, and the fifth storage bit width corresponding to the compressed data; summing the second storage bit width, the third storage bit width, the fourth storage bit width, and the fifth storage bit width to obtain the target storage bit width; and storing the sign bit, compression bit, compression method bit, and compressed data according to the target storage bit width.

[0112] The sign bit is used to indicate the sign of the data to be compressed. Specifically, the sign bit is 1 if the data to be compressed is positive, and 0 if the data to be compressed is negative or zero.

[0113] The compression bit indicates whether the data to be compressed should be compressed. The compression bit is 1 if the data needs compression, and 0 if it does not.

[0114] The compression mode bit indicates the compression method for the data to be compressed. Specifically, the compression mode bit is 1 if twice the absolute value is greater than the compression reference value, and 0 if twice the absolute value is less than or equal to the compression reference value.

[0115] The second storage bit width refers to the bit width used to store the sign bit of the data to be compressed, which is usually configured as 1 bit.

[0116] The third storage bit width refers to the bit width used to store the compressed bits of the data to be compressed, which is usually configured as 1 bit.

[0117] The fourth storage bit width refers to the bit width used to store the compression method bits of the data to be compressed, which is usually configured as 1 bit.

[0118] The fifth storage bit width refers to the bit width used to store the data to be compressed.

[0119] The target storage bit width refers to the total bit width required to integrate the sign bit, compression bit, compression mode bit, and compressed data into a complete data frame.

[0120] For example, the server inputs the data to be compressed into a trained bit information prediction model. Through the trained bit information prediction model, the server obtains the sign bit, compression bit, and compression mode bit corresponding to the data to be compressed. Then, it obtains the second storage bit width corresponding to the sign bit, the third storage bit width corresponding to the compression bit, and the fourth storage bit width corresponding to the compression mode bit. Next, based on the compression mode of the data to be compressed, it queries the correspondence between the compression mode and the storage bit width to obtain the storage bit width corresponding to the compression mode of the data to be compressed, which is used as the fifth storage bit width corresponding to the compressed data. Then, it sums the second, third, fourth, and fifth storage bit widths to obtain the target storage bit width. Finally, it stores the sign bit, compression bit, compression mode bit, and compressed data according to the target storage bit width.

[0121] It should be noted that if the data to be compressed does not meet the compression threshold, the sign bit and compression bit corresponding to the data to be compressed are obtained; the storage bit width corresponding to the sign bit, the storage bit width corresponding to the compression bit, and the storage bit width corresponding to the compressed data are obtained; the storage bit width corresponding to the sign bit, the storage bit width corresponding to the compression bit, and the storage bit width corresponding to the compressed data are summed to obtain the processed storage bit width; the sign bit, compression bit, and compressed data are stored according to the processed storage bit width.

[0122] In this embodiment, fine-grained storage management of data with different attributes is achieved by configuring bit widths by type, which avoids the waste of storage resources caused by uniform redundant bit widths. Furthermore, by clarifying the bit width ratio of each data segment, it ensures that key information such as symbols, compression status, and compression methods are not lost, providing a complete identification basis for subsequent data restoration.

[0123] In one exemplary embodiment, such as Figure 2 As shown, another data compression method is provided. Taking the application of this method to a server as an example, the specific steps include:

[0124] Step S201: Obtain the quantization level and the first storage bit width corresponding to the data to be compressed.

[0125] Step S202: Determine the quantization interval corresponding to the data to be compressed based on the quantization level and the first storage bit width.

[0126] Step S203: Determine the quantization table corresponding to the data to be compressed based on the quantization interval and quantization level; the quantization table includes multiple preset compression reference values.

[0127] Step S204: Determine the maximum absolute value in the data set corresponding to the data to be compressed, and determine the compression reference value corresponding to the data to be compressed from multiple preset compression reference values ​​based on the maximum absolute value; the compression reference value is used to determine the compression method corresponding to the data to be compressed.

[0128] Step S205: Based on the quantization interval, obtain the compression threshold value corresponding to the data to be compressed; the compression threshold value is used to determine whether to compress the data to be compressed.

[0129] Step S206: Obtain the absolute value corresponding to the data to be compressed.

[0130] Step S207: If the absolute value meets the compression reference value, determine the compression method corresponding to the data to be compressed as the first compression method.

[0131] Step S208: If the absolute value does not meet the compression reference value, determine the compression method corresponding to the data to be compressed as the second compression method.

[0132] Step S209: According to the first compression method, perform corresponding compression processing on the data to be compressed to obtain the first processed data corresponding to the data to be compressed, and perform quantization processing on the first processed data to obtain the first compressed data corresponding to the data to be compressed.

[0133] Step S210: According to the second compression method, perform corresponding compression processing on the data to be compressed to obtain the second processed data corresponding to the data to be compressed, and perform quantization processing on the second processed data to obtain the second compressed data corresponding to the data to be compressed.

[0134] In the above data compression method, when compressing data, the compression method that matches the characteristics of the data to be compressed is first determined based on the compression benchmark value, avoiding the problem of insufficient adaptability of a single compression algorithm. Then, the data that truly needs to be compressed is screened out through the compression threshold value, eliminating the invalid processing of data with no compression gain or data that is prone to distortion after compression. Finally, the appropriate compression method is accurately applied to the data that meets the compression conditions. While ensuring compression efficiency, it reduces the distortion caused by algorithm mismatch and invalid compression, avoiding the defect of low data compression quality caused by using a preset compression method to compress data in traditional technology, which is conducive to improving the data compression quality.

[0135] In an exemplary embodiment, to more clearly illustrate the data compression method provided by the embodiments of this application, the following specific embodiment will be used to describe the data compression method in detail. In one embodiment, this application also provides a low-storage, high-reliability data compression method suitable for wireless communication receivers. Specifically, it includes the following:

[0136] Consider the received signal y and reference signal The signal transmission model is written as:

[0137] Equation (4)

[0138] in, The subscript for the frequency domain subcarrier is [index], and the channel is [channel]. The noise is n , and These represent the number of antennas at the receiving and transmitting ends, respectively.

[0139] Coarse channel estimation is performed based on the LS (Least Squares) method to obtain... ,Right now:

[0140] Equation (5)

[0141] Where k is the pilot subcarrier index.

[0142] Furthermore, the filtered channel is obtained based on the MMSE (Minimum Mean Square Error) criterion. ,in Here is the filter matrix:

[0143] Equation (6)

[0144] For the The receiving antenna, the first Data from each transmitting antenna Compression is performed. Taking NR PDSCHDMRS (New Radio Physical Downlink Shared Channel Demodulation Reference Signal) configuration type Type 1 as an example, the pilot corresponding to one port has 6 RE resources in one RB. The pilot architecture is as follows: Figure 3 As shown.

[0145] The compression diagram of this scheme is shown below. Figure 4 As shown, the input is Output In the diagram, M represents the number of groups, and N represents the data in each group.

[0146] The compression steps are as follows:

[0147] 1. Grouping:

[0148] The data is grouped into N data sets. Considering that it is applicable to different scenarios, this scheme takes one RB data set as a group and compresses the real and imaginary parts together. Therefore, N=12. The data to be compressed are denoted as x(0), x(1), ..., x(N-1).

[0149] 2. Find the maximum absolute value ref:

[0150] Find the maximum absolute value of N data points, denoted as ref.

[0151] 3. Quantify the references:

[0152] The ref is quantized in L-order. Since the input data is stored using P bits, the data range is 0~ Therefore, the quantization interval is The quantization table is LUT={ }, where k is the quantization index. Taking P=12, L=32 levels as an example, step=64, LUT={64, 128, ..., 2048}.

[0153] The quantification process is as follows:

[0154] when The ref is quantized to the smallest value in the LUT that is greater than ref, denoted as ref'.

[0155] 4. Set the minimum compression threshold: Threshold= .

[0156] 5. Compression judgment:

[0157] The judgment starts from the i=0th data x(0).

[0158] The sign of x(i) is represented by a 1-bit sign bit flag1: flag1=0 means less than or equal to 0; flag1=1 means greater than 0.

[0159] Use a 1-bit compression flag2 to indicate whether the data should be compressed.

[0160] When abs(x(i)) < If so, no compression is needed, flag2=0, proceed to step 8.

[0161] Otherwise, compression is required. Set flag2 to 1 and proceed to step 6.

[0162] 6. Compression:

[0163] The compression method is indicated by the 1-bit compression mode bit flag3:

[0164] when flag3=1, and the compressed value is y(i), as shown in equation (1).

[0165] when flag3=0, and the compressed value is y(i), as shown in equation (2).

[0166] 7. Quantification:

[0167] Will The quantization is done in Q bits, as shown in equation (3).

[0168] 8. Storage:

[0169] Each data point is stored using D bits after compression. If Q=5, then D=8.

[0170] This scheme is compared with two existing schemes in terms of compression degree and performance. The two existing schemes are: Existing Scheme 1: Real and virtual parts are compressed separately & maximum value compression (L=32); Existing Scheme 2: Real and virtual parts are compressed together and maximum value compression (L=32).

[0171] Taking NR PDSCH DMRS configuration type Type 1 as an example, assuming P=12 and Q=5, the pilot data of 6 REs of one RB is compressed. The compression degree is shown in Table 1. From the table, it can be seen that the compression degree from smallest to largest is: Existing scheme 1 = This scheme < Existing scheme 2.

[0172] Table 1 Comparison of Compression Levels

[0173]

[0174] To evaluate the performance of this solution and existing solutions, five scenarios are set up in this solution, and the scenario configuration parameters are shown in Table 2:

[0175] Table 2 Parameter Configuration Table

[0176]

[0177] Table 3 shows the simulation results for the signal-to-noise ratio (SNR) of this scheme and the existing scheme (SNR_10%BLER, the SNR at 10% block error rate) and the difference between the two schemes (DifSNR_10%BLER, the SNR difference at 10% block error rate) when the service is 10% BLER (Block Error Rate). Here, "this scheme vs. existing scheme 1" represents the performance difference of this scheme relative to existing scheme 1, and "this scheme vs. existing scheme 2" represents the performance difference of this scheme relative to existing scheme 2. Positive values ​​indicate gain, and negative values ​​indicate loss. It can be seen that this scheme has a performance gain compared to both existing schemes 1 and 2. The compression performance, from worst to best, is: Existing scheme 1 < Existing scheme 2 < This scheme.

[0178] Table 3 Comparison of Compression Performance

[0179]

[0180] Therefore, based on the comparison of compression degree and compression performance, it can be seen that the existing scheme 1 has poor performance. The existing scheme 2 and this scheme are two feasible schemes to improve performance. The comparison shows that although scheme 2 requires less storage, this scheme has better performance. Therefore, this scheme can significantly improve performance without increasing storage.

[0181] In summary, this solution provides a low-storage, high-reliability data compression method, namely, it designs a new data storage format, provides a modeling scheme for small signals, and presents a strategy to protect the reliable transmission of small signals, thereby solving the above-mentioned problems.

[0182] In the above embodiments, when compressing data, the compression method that matches the characteristics of the data to be compressed is first determined based on the compression benchmark value, avoiding the problem of insufficient adaptability of a single compression algorithm. Then, the data that truly needs to be compressed is screened out through the compression threshold value, eliminating invalid processing of data with no compression gain or data that is prone to distortion after compression. Finally, the appropriate compression method is accurately applied to the data that meets the compression conditions. While ensuring compression efficiency, the distortion caused by algorithm mismatch and invalid compression is reduced. This avoids the defect of using a preset compression method to compress data in traditional technology, which leads to low data compression quality and is conducive to improving the data compression quality.

[0183] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0184] Based on the same inventive concept, this application also provides a data compression apparatus for implementing the data compression method described above. This apparatus can be applied to or integrated into a chip or chip module, for example. The solution provided by this apparatus is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more data compression apparatus embodiments provided below can be found in the limitations of the data compression method described above, and will not be repeated here.

[0185] In one exemplary embodiment, such as Figure 5 As shown, a data compression device is provided, including: a data acquisition module 501, a mode determination module 502, and a data compression module 503, wherein:

[0186] The data acquisition module 501 is used to acquire the compression baseline value and compression threshold value corresponding to the data to be compressed; the compression baseline value is used to determine the compression method corresponding to the data to be compressed, and the compression threshold value is used to determine whether to compress the data to be compressed.

[0187] The method determination module 502 is used to determine the compression method corresponding to the data to be compressed based on the compression reference value, provided that the data to be compressed meets the compression threshold value.

[0188] The data compression module 503 is used to perform corresponding compression processing on the data to be compressed according to the compression method, so as to obtain the compressed data corresponding to the data to be compressed.

[0189] In an exemplary embodiment, the data acquisition module 501 is further configured to acquire the quantization level and the first storage bit width corresponding to the data to be compressed; determine the quantization interval corresponding to the data to be compressed based on the quantization level and the first storage bit width; determine the compression reference value corresponding to the data to be compressed based on the quantization interval, the quantization level and the data to be compressed; and obtain the compression threshold value corresponding to the data to be compressed based on the quantization interval.

[0190] In an exemplary embodiment, the data acquisition module 501 is further configured to determine a quantization table corresponding to the data to be compressed based on the quantization interval and the quantization level; the quantization table includes multiple preset compression reference values; determine the maximum absolute value in the data set corresponding to the data to be compressed; and determine the compression reference value corresponding to the data to be compressed from the multiple preset compression reference values ​​based on the maximum absolute value.

[0191] In an exemplary embodiment, the method determination module 502 is further configured to obtain the absolute value corresponding to the data to be compressed; if the absolute value meets the compression reference value, determine the compression method corresponding to the data to be compressed as the first compression method; or, if the absolute value does not meet the compression reference value, determine the compression method corresponding to the data to be compressed as the second compression method.

[0192] In an exemplary embodiment, the data compression module 503 is further configured to perform corresponding compression processing on the data to be compressed according to a first compression method to obtain first processed data corresponding to the data to be compressed, and perform quantization processing on the first processed data to obtain first compressed data corresponding to the data to be compressed; or, perform corresponding compression processing on the data to be compressed according to a second compression method to obtain second processed data corresponding to the data to be compressed, and perform quantization processing on the second processed data to obtain second compressed data corresponding to the data to be compressed.

[0193] In an exemplary embodiment, the data compression device further includes a data storage module, configured to acquire a sign bit, a compression bit, and a compression mode bit corresponding to the data to be compressed; the sign bit is used to represent the sign corresponding to the data to be compressed, the compression bit is used to indicate whether the data to be compressed is to be compressed, and the compression mode bit is used to represent the compression mode corresponding to the data to be compressed; the module acquires a second storage bit width corresponding to the sign bit, a third storage bit width corresponding to the compression bit, a fourth storage bit width corresponding to the compression mode bit, and a fifth storage bit width corresponding to the compressed data; the module sums the second storage bit width, the third storage bit width, the fourth storage bit width, and the fifth storage bit width to obtain a target storage bit width; and the module stores the sign bit, the compression bit, the compression mode bit, and the compressed data according to the target storage bit width.

[0194] Regarding the modules / units included in the various devices and products described in the above embodiments, they can be software modules / units, hardware modules / units, or a combination of both. For example, for various devices and products applied to or integrated into a chip, all of their modules / units can be implemented using hardware methods such as circuits, or at least some modules / units can be implemented using software programs that run on a processor integrated within the chip, while the remaining (if any) modules / units can be implemented using hardware methods such as circuits; for various devices and products applied to or integrated into a chip module, all of their modules / units can be implemented using hardware methods such as circuits, and different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components of the chip module, or at least some modules / units can be implemented using hardware methods such as circuits. The components can be implemented using software programs that run on the processor integrated within the chip module. The remaining (if any) modules / units can be implemented using hardware methods such as circuits. For various devices and products applied to or integrated into the terminal, each of its components / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or in different components within the terminal. Alternatively, at least some modules / units can be implemented using software programs that run on the processor integrated within the terminal, while the remaining (if any) modules / units can be implemented using hardware methods such as circuits.

[0195] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6 As shown, this computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores data such as compression baseline values ​​and compression threshold values. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a data compression method.

[0196] Those skilled in the art will understand that Figure 6The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0197] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0198] Based on the same inventive concept, this application also provides a chip, including a processor coupled to a memory, for executing a computer program or instructions stored in the memory, and implementing the steps in the above method embodiments when the processor executes the computer program or instructions.

[0199] It is understood that the chip involved in the embodiments of this application may be a field-programmable gate array (FPGA), may include an application-specific integrated circuit (ASIC), may be a system on chip (SoC), may be a central processor unit (CPU), may be a network processor (NP), may be a digital signal processor (DSP), may be a microcontroller unit (MCU), may be a programmable logic device (PLD), or other integrated chips, etc.

[0200] Based on the same inventive concept, this application also provides a chip module, such as... Figure 7 As shown, the chip module includes a communication module, a power module, a storage module, and a chip. Among them:

[0201] The power module is used to provide power to the chip module; the storage module is used to store data and instructions; the communication module is used for internal communication within the chip module, or for communication between the chip module and external devices; this chip corresponds to the chip in the above chip embodiment.

[0202] The implementation of this chip module can be found in the relevant content of the above chip embodiment, and will not be repeated here.

[0203] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0204] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0205] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0206] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0207] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0208] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A data compression method, characterized in that, The method includes: Obtain the compression baseline value and compression threshold value corresponding to the data to be compressed; the compression baseline value is used to determine the compression method corresponding to the data to be compressed, and the compression threshold value is used to determine whether to compress the data to be compressed. If the data to be compressed meets the compression threshold, the compression method corresponding to the data to be compressed is determined according to the compression reference value. According to the compression method, the data to be compressed is subjected to corresponding compression processing to obtain the compressed data corresponding to the data to be compressed.

2. The method according to claim 1, characterized in that, The process of obtaining the compression baseline value and compression threshold value corresponding to the data to be compressed includes: Obtain the quantization level and the first storage bit width corresponding to the data to be compressed; The quantization interval corresponding to the data to be compressed is determined based on the quantization level and the first storage bit width. Based on the quantization interval, the quantization level, and the data to be compressed, a compression baseline value corresponding to the data to be compressed is determined, and a compression threshold value corresponding to the data to be compressed is obtained based on the quantization interval.

3. The method according to claim 2, characterized in that, The step of determining the compression reference value corresponding to the data to be compressed based on the quantization interval, the quantization level, and the data to be compressed includes: Based on the quantization interval and the quantization level, a quantization table corresponding to the data to be compressed is determined; the quantization table includes multiple preset compression reference values; The maximum absolute value in the data set corresponding to the data to be compressed is determined. Based on the maximum absolute value, the compression reference value corresponding to the data to be compressed is determined from the plurality of preset compression reference values.

4. The method according to claim 1, characterized in that, The step of determining the compression method corresponding to the data to be compressed based on the compression reference value includes: Obtain the absolute value corresponding to the data to be compressed; If the absolute value satisfies the compression reference value, the compression method corresponding to the data to be compressed is determined to be the first compression method; or, If the absolute value does not meet the compression reference value, the compression method corresponding to the data to be compressed is determined to be the second compression method.

5. The method according to claim 4, characterized in that, The step of performing corresponding compression processing on the data to be compressed according to the compression method to obtain the compressed data corresponding to the data to be compressed includes: According to the first compression method, the data to be compressed is compressed accordingly to obtain the first processed data corresponding to the data to be compressed. The first processed data is then quantized to obtain the first compressed data corresponding to the data to be compressed. or, According to the second compression method, the data to be compressed is subjected to corresponding compression processing to obtain the second processed data corresponding to the data to be compressed. The second processed data is then quantized to obtain the second compressed data corresponding to the data to be compressed.

6. The method according to any one of claims 1 to 5, characterized in that, After performing corresponding compression processing on the data to be compressed according to the compression method to obtain the compressed data corresponding to the data to be compressed, the process includes: Obtain the sign bit, compression bit, and compression method bit corresponding to the data to be compressed; the sign bit is used to indicate the sign corresponding to the data to be compressed, the compression bit is used to indicate whether the data to be compressed is to be compressed, and the compression method bit is used to indicate the compression method corresponding to the data to be compressed. Obtain the second storage bit width corresponding to the sign bit, the third storage bit width corresponding to the compression bit, the fourth storage bit width corresponding to the compression method bit, and the fifth storage bit width corresponding to the compressed data; The second storage bit width, the third storage bit width, the fourth storage bit width, and the fifth storage bit width are summed to obtain the target storage bit width; The symbol bit, the compression bit, the compression method bit, and the compressed data are stored according to the target storage bit width.

7. A data compression device, characterized in that, The device includes: The data acquisition module is used to acquire the compression reference value and compression threshold value corresponding to the data to be compressed; the compression reference value is used to determine the compression method corresponding to the data to be compressed, and the compression threshold value is used to determine whether to compress the data to be compressed. The compression method determination module is used to determine the compression method corresponding to the data to be compressed based on the compression reference value when the data to be compressed meets the compression threshold value. The data compression module is used to perform corresponding compression processing on the data to be compressed according to the compression method, so as to obtain the compressed data corresponding to the data to be compressed.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A chip, characterized in that, The device includes a processor and a communication interface, wherein the processor is configured to cause the chip to perform the steps of the method described in any one of claims 1 to 6.

10. A chip module, characterized in that, This includes communication modules, power modules, storage modules, and chips, among which: The power module is used to provide power to the chip module; The storage module is used to store data and instructions; The communication module is used for internal communication within the chip module, or for communication between the chip module and external devices. The chip is used to perform the steps of the method according to any one of claims 1 to 6.

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