Data compression methods, devices, equipment, chips and chip modules

Abstract

This application relates to a data compression method, apparatus, device, chip, and chip module. The method includes: acquiring data to be compressed, the data including at least one channel estimation data; for each channel estimation data, determining the target channel strength corresponding to the channel estimation data; determining a compression bit width parameter corresponding to the channel estimation data based on the target channel strength; and performing bit width compression processing on the channel estimation data based on the compression bit width parameter. This method can achieve a balance between compression efficiency and compression accuracy, improving overall storage efficiency and the quality of subsequent signal processing.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a data compression method, apparatus, device, chip, and chip module. Background Technology

[0002] With the increasing number of base station antennas, the amount of data transmitted by the system is growing exponentially, posing a significant challenge to the computing, processing, and storage capabilities of user terminals. How to stably and efficiently store such massive amounts of data has become an urgent problem to be solved.

[0003] Traditional data compression methods often employ fixed compression strategies, such as a uniform compression bit width. This approach can lead to some data not being fully compressed or potentially resulting in loss of information precision, impacting overall storage efficiency and the quality of subsequent signal processing. Summary of the Invention

[0004] Therefore, it is necessary to provide a data compression method, apparatus, device, chip, and chip module to address the aforementioned technical problems, thereby achieving a balance between compression efficiency and compression accuracy, and improving overall storage efficiency and the quality of subsequent signal processing.

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

[0006] Acquire the data to be compressed, which includes at least one channel estimation data;

[0007] For each channel estimation data, determine the target channel strength corresponding to the channel estimation data;

[0008] Based on the target channel strength, determine the compression bit width parameter corresponding to the channel estimation data;

[0009] Based on the compressed bit width parameter, the channel estimation data is subjected to bit width compression processing.

[0010] In one embodiment, the compression bit width parameter includes a target overflow bit; correspondingly, determining the compression bit width parameter corresponding to the channel estimation data based on the target channel strength includes: determining the first bit width occupied by the target channel strength; determining the second bit width occupied by the channel estimation data based on the first bit width and the reserved bit width; and determining the target overflow bit based on the second bit width and the preset compression bit width.

[0011] In one embodiment, the reserved bit width is determined according to the following steps: determining the intensity distribution data of the target channel intensity corresponding to each channel estimation data; and determining the reserved bit width based on the intensity distribution data.

[0012] In one embodiment, the intensity distribution data includes the channel intensity mean and the channel intensity extreme value; accordingly, determining the reserved bit width based on the intensity distribution data includes: determining the mean bit width occupied by the channel intensity mean; and determining the extreme bit width occupied by the channel intensity extreme value; and determining the reserved bit width based on the mean bit width and the extreme bit width.

[0013] In one embodiment, the channel estimation data includes a real part of the channel estimation and an imaginary part of the channel estimation; the target channel strength includes instantaneous channel power; accordingly, determining the target channel strength corresponding to the channel estimation data includes: determining the instantaneous channel power corresponding to the channel estimation data based on the sum of squares between the real part of the channel estimation and the imaginary part of the channel estimation.

[0014] In one embodiment, the method further includes: in response to a decompression request for the target compressed data, performing decompression processing on the corresponding compressed channel estimation data according to the compression bit width parameter corresponding to the compressed channel estimation data in the target compressed data; wherein the compressed channel estimation data is compressed data after bit width compression processing of the channel estimation data.

[0015] Secondly, this application also provides a data compression apparatus, comprising:

[0016] The acquisition module is used to acquire the data to be compressed, which includes at least one channel estimation data.

[0017] The first determining module is used to determine the target channel strength corresponding to each channel estimation data.

[0018] The second determining module is used to determine the compression bit width parameter corresponding to the channel estimation data based on the target channel strength.

[0019] The compression module is used to perform bit-width compression processing on the channel estimation data based on the compression bit-width parameter.

[0020] 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 implement the steps of the method provided in the first aspect above.

[0021] 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 the steps of the method provided in the first aspect above.

[0022] Fifthly, this application also provides a chip module, including a communication module, a power module, a storage module, and a chip, wherein:

[0023] The power module is used to provide power to the chip module;

[0024] Storage modules are used to store data and instructions;

[0025] The communication module is used for internal communication within the chip module, or for communication between the chip module and external devices;

[0026] The chip is used to perform the steps of the method provided in the first aspect above.

[0027] Sixthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method provided in the first aspect above.

[0028] In a seventh aspect, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method provided in the first aspect above.

[0029] The aforementioned data compression method, apparatus, device, chip, and chip module acquire data to be compressed, including at least one channel estimation data point. For each channel estimation data point, the target channel strength corresponding to that data point is determined. This allows for the determination of a strength scalar that effectively characterizes the data value size of each channel estimation data point, providing a data foundation for mapping from data size to compression parameters. By determining the compression bit width parameter corresponding to the channel estimation data based on the target channel strength, a mapping mechanism is established from channel strength to data size representation, and then to adaptive compression parameters. This avoids complex calculations and facilitates the determination of compression bit width parameters that match the channel estimation data. By performing bit width compression processing on the channel estimation data based on the compression bit width parameter, adaptive compression processing for channel estimation data of different sizes is achieved, balancing compression efficiency and accuracy. This is beneficial for improving overall storage efficiency and the quality of subsequent signal processing. Attached Figure Description

[0030] 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.

[0031] Figure 1 This is a flowchart illustrating a data compression method in one embodiment;

[0032] Figure 2 A flowchart illustrating the steps for determining the reserved bit width in one embodiment;

[0033] Figure 3This is a flowchart illustrating a data compression method in another embodiment;

[0034] Figure 4 This is a structural block diagram of a data compression device in one embodiment;

[0035] Figure 5 This is an internal structural diagram of a computer device in one embodiment;

[0036] Figure 6 This is an internal structure diagram of a chip module in one embodiment. Detailed Implementation

[0037] 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.

[0038] 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.

[0039] The data compression method provided in this application can be applied to terminal devices, servers, chips or chip modules with data processing capabilities, etc. The terminal devices may include, but are not limited to, various personal computers, laptops, smartphones, tablets, and storage devices. The server may be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0040] In one embodiment, such as Figure 1 As shown, a data compression method is provided. This embodiment uses the application of this method to a storage device as an example for illustration. It can be understood that this method can also be applied to terminal devices, and can also be applied to systems including terminal devices and servers, and implemented through the interaction between the terminal device and the server. In this embodiment, the method includes the following steps:

[0041] S110. Obtain the data to be compressed, which includes at least one channel estimation data.

[0042] The data to be compressed can be understood as a dataset or data block that includes at least one channel estimation data and awaits data compression processing. The organization of the data to be compressed may include at least one of vectors or matrices, etc., and this application does not impose any limitations on this.

[0043] The channel estimation data is used to characterize the wireless channel state. For example, the channel estimation data can be data describing the propagation path characteristics between the transmit and receive antennas, based on an estimation algorithm. The channel estimation data may include at least one of channel amplitude data and channel phase data. The estimation algorithm may include at least one of least squares estimation and least mean square error estimation.

[0044] In an optional embodiment, the data to be compressed may include channel estimation data corresponding to at least one channel data point. Optionally, the data to be compressed may be in matrix form, with at least one channel data point corresponding to the matrix, and different channel data points corresponding to different channel estimation data. Optionally, the channel estimation data may be in complex form, that is, the channel estimation data may include the real part and the imaginary part of the channel estimation.

[0045] S120. For each channel estimation data, determine the target channel strength corresponding to the channel estimation data.

[0046] The target channel strength can be understood as the channel strength determined based on the channel estimation data of the channel data points, used to characterize the channel strength corresponding to the corresponding channel data points.

[0047] In an optional embodiment, the channel estimation data includes a real part of the channel estimate and an imaginary part of the channel estimate; the target channel strength includes an instantaneous channel power; accordingly, the instantaneous channel power corresponding to the channel estimation data can be determined based on the sum of squares between the real part of the channel estimate and the imaginary part of the channel estimate.

[0048] For example, the instantaneous channel power corresponding to the channel estimation data can be determined according to the following formula. :

[0049]

[0050] in, This represents the instantaneous channel power corresponding to the i-th channel estimation data; This represents the real part of the channel estimate for the i-th channel estimate data; Let i represent the imaginary part of the channel estimation for the i-th channel estimation data.

[0051] In another optional embodiment, channel estimation data can be input into a channel strength determination model to obtain the target channel strength corresponding to the channel estimation data. The channel strength determination model can be a traditional machine learning model or a neural network model, and this application does not impose any limitations on it. For example, when training the channel strength determination model, sample channel estimation data can be input into the final channel strength determination model. Based on the channel strength prediction results output by the channel strength determination model and the channel strength labels corresponding to the sample channel estimation data, the channel strength determination model is trained to improve its accuracy.

[0052] S130. Determine the compression bit width parameter corresponding to the channel estimation data based on the target channel strength.

[0053] The compressed bit width parameter can be understood as a compression parameter that is adaptively determined based on the target channel strength and used for bit width compression processing.

[0054] In an optional embodiment, the compression bit width parameter may include an overflow bit. Accordingly, a first bit width occupied by the target channel strength can be determined; a second bit width occupied by the channel estimation data can be determined based on the first bit width and the reserved bit width; and a target overflow bit can be determined based on the second bit width and the preset compression bit width.

[0055] The reserved bit width can be understood as the reserved bit width used to characterize the security redundancy space.

[0056] The preset compression bit width can be understood as a pre-defined bit width related to compression processing, that is, a bit width constraint target.

[0057] For example, the first bit width can be determined according to the following formula. :

[0058]

[0059] in, Indicates the width of the first bit; This represents the instantaneous channel power corresponding to the i-th channel estimation data, which is also the target channel strength; This indicates rounding up to the nearest integer.

[0060] For example, the second bit width can be determined according to the following formula. :

[0061]

[0062] in, Indicates the width of the second bit; The mean bit width represents the average channel strength. This indicates rounding up to the nearest integer.

[0063] This process involves determining the target channel strength corresponding to each channel estimation data point; averaging each target channel strength to obtain the average channel strength; and determining the average bit width occupied by the average channel strength.

[0064] For example, the target overflow bit can be determined according to the following formula. :

[0065]

[0066] in, Indicates the target overflow bit; Indicates the width of the second bit; This indicates the preset compression bit width.

[0067] The preset compression bit width can be set by technicians according to their needs or experience, or determined through a large number of experiments. This application does not impose any restrictions on this.

[0068] S140. Based on the compressed bit width parameter, perform bit width compression processing on the channel estimation data.

[0069] In an optional embodiment, for each channel estimation data, the target overflow bit corresponding to the channel estimation data can be calculated. The channel estimation data is truncated at the low end (i.e., the bit width is compressed) to obtain compressed channel estimation data. Understandably, by performing bit-width compression on the estimated data of each channel in the data to be compressed, the compressed target data can be obtained.

[0070] Optionally, before performing bit-width compression on each channel estimation data, the channel estimation data in the data to be compressed can be divided into batches to obtain channel estimation data identified by 0 or 1, and then the identified channel estimation data can be compressed sequentially according to the batches.

[0071] In an optional embodiment, in response to a decompression request for the target compressed data, the corresponding compressed channel estimation data can be decompressed according to the compression bit width parameter corresponding to the compressed channel estimation data in the target compressed data; wherein, the compressed channel estimation data is compressed data after bit width compression processing of the channel estimation data.

[0072] The compressed channel estimation data can be decompressed according to the following formula to obtain the decompressed channel estimation data. :

[0073]

[0074] in, This represents the decompressed channel estimation data; This represents compressed channel estimation data; Indicates the target overflow bit.

[0075] Among them, if Then the channel estimation data will be compressed. Shift left Position; if Then the channel estimation data will be compressed. Move right This allows for decompression by using bits.

[0076] In another optional embodiment, the target compressed data and the compression bit width parameter corresponding to the compressed channel estimation data in the target compressed data can be sent to the decompression device, so that the decompression device can perform decompression processing on the corresponding compressed channel estimation data according to the compression bit width parameter corresponding to the compressed channel estimation data in the target compressed data.

[0077] The aforementioned data compression method, apparatus, device, chip, and chip module acquire data to be compressed, including at least one channel estimation data point. For each channel estimation data point, the target channel strength corresponding to that data point is determined. This allows for the determination of a strength scalar that effectively characterizes the data value size of each channel estimation data point, providing a data foundation for mapping from data size to compression parameters. By determining the compression bit width parameter corresponding to the channel estimation data based on the target channel strength, a mapping mechanism is established from channel strength to data size representation, and then to adaptive compression parameters. This avoids complex calculations and facilitates the determination of compression bit width parameters that match the channel estimation data. By performing bit width compression processing on the channel estimation data based on the compression bit width parameter, adaptive compression processing for channel estimation data of different sizes is achieved, balancing compression efficiency and accuracy. This is beneficial for improving overall storage efficiency and the quality of subsequent signal processing.

[0078] Based on the technical solutions of the above embodiments, this application also provides an optional embodiment in which the steps for determining the reserved bit width are refined.

[0079] See Figure 2 The steps for determining the reserved bit width, as shown, include:

[0080] S210. Determine the intensity distribution data of the target channel intensity corresponding to each channel estimation data.

[0081] Among them, the intensity distribution data is used to characterize the overall intensity level distribution of the target channel intensity corresponding to each channel estimation data.

[0082] The intensity distribution data may include at least one of the following: channel intensity mean and channel intensity extreme values. The channel intensity mean is used to characterize the average value of the target channel intensity corresponding to each channel estimation data, and the channel intensity extreme values ​​are used to characterize the target extreme values ​​of the target channel intensity corresponding to each channel estimation data. The channel intensity extreme values ​​may include at least one of the following: channel intensity maximum and channel intensity minimum.

[0083] S220. Determine the reserved bit width based on the intensity distribution data.

[0084] In an optional embodiment, the intensity distribution data includes the channel intensity mean and the channel intensity extreme values; correspondingly, the mean bit width occupied by the channel intensity mean can be determined; and the extreme bit width occupied by the channel intensity extreme values ​​can be determined; and the reserved bit width is determined based on the mean bit width and the extreme bit width.

[0085] Optionally, the mean channel strength can be binary-converted to determine the mean bit width.

[0086] Optionally, the reserved bit width can be determined based on the average bit width and the maximum bit width corresponding to the maximum channel strength.

[0087] For example, the mean channel strength can be determined according to the following formula. :

[0088]

[0089] in, Indicates the mean channel strength; This represents the real part of the channel estimate for the i-th channel estimate data; The channel estimate is represented by the imaginary part of the channel estimate for the i-th channel estimation data; N represents the total number of channel data points; N = r b *r e r b r represents the number of row dimensions of the matrix corresponding to the data to be compressed. e This indicates the number of column dimensions of the matrix corresponding to the data to be compressed.

[0090] For example, the average bit width can be determined according to the following formula. :

[0091]

[0092] in, Indicates the average bit width; Indicates the mean channel strength; This indicates rounding up to the nearest integer.

[0093] Similarly, the maximum bit width can be determined using the following formula. :

[0094]

[0095] in, Indicates the bit width of the maximum value; Indicates the maximum value of the channel strength; This indicates rounding up to the nearest integer.

[0096] For example, the reserved bit width ResBit can be determined according to the following formula:

[0097]

[0098] in, Indicates the reserved bit width; Maximum bit width; This indicates the average bit width.

[0099] In the above steps for determining the reserved bit width, the intensity distribution data of the target channel intensity corresponding to each channel estimation data is determined, thereby obtaining the overall intensity level distribution corresponding to each target channel intensity, providing a data basis for the subsequent determination of the reserved bit width. By determining the mean bit width occupied by the mean channel intensity and the extreme bit width occupied by the extreme channel intensity, and determining the reserved bit width based on the mean bit width and the extreme bit width, dynamic and adaptive allocation of the safety redundancy bit width before compression is realized. This allocation strategy can effectively prevent the overflow risk that may be caused by individual high-intensity data points, and accurately match the average intensity level of the data block, avoiding bit width waste caused by excessive reservation, and building a stable bit width adjustment basis for the subsequent adaptive compression process.

[0100] Based on the above embodiments, this application also provides an optional embodiment in which the data compression method is described in detail.

[0101] refer to Figure 3 The diagram shown is a flowchart of a data compression method in another embodiment, including:

[0102] S301. Obtain the data to be compressed, which includes at least one channel estimation data, and the channel estimation data includes the real part of the channel estimation and the imaginary part of the channel estimation.

[0103] S302. For each channel estimation data, determine the instantaneous channel power corresponding to the channel estimation data based on the sum of squares between the real part and the imaginary part of the channel estimation data.

[0104] S303. Determine the intensity distribution data of the instantaneous channel power corresponding to each channel estimation data. The intensity distribution data includes the mean channel power and the maximum channel power.

[0105] S304. Determine the mean bit width occupied by the mean channel strength and the maximum bit width occupied by the maximum channel strength.

[0106] S305. Determine the reserved bit width based on the average bit width and the maximum bit width.

[0107] S306. For each channel estimation data, determine the first bit width occupied by the target channel strength.

[0108] S307. Determine the second bit width occupied by the channel estimation data based on the first bit width and the reserved bit width.

[0109] S308. Determine the target overflow bit based on the second bit width and the preset compressed bit width.

[0110] S309. Based on the target overflow bit, perform bit-width compression processing on the channel estimation data.

[0111] S310. In response to the decompression request for the target compressed data, decompress the corresponding compressed channel estimation data according to the compression bit width parameter corresponding to the compressed channel estimation data in the target compressed data.

[0112] Among them, compressed channel estimation data is compressed data after bit-width compression processing of channel estimation data.

[0113] It should be understood that although the steps in the flowcharts of the embodiments described above 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 embodiments described above 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.

[0114] 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.

[0115] In one exemplary embodiment, such as Figure 4 As shown, a data compression device is provided, including: an acquisition module 410, a first determination module 420, a second determination module 430, and a compression module 440, wherein:

[0116] The acquisition module 410 is used to acquire data to be compressed, which includes at least one channel estimation data.

[0117] The first determining module 420 is used to determine the target channel strength corresponding to each channel estimation data.

[0118] The second determining module 430 is used to determine the compression bit width parameter corresponding to the channel estimation data based on the target channel strength.

[0119] Compression module 440 is used to perform bit-width compression processing on channel estimation data based on compression bit-width parameters.

[0120] In one embodiment, the compressed bit width parameter includes a target overflow bit; correspondingly, the second determining module 430 includes: a first determining unit, configured to determine a first bit width occupied by the target channel strength; a second determining unit, configured to determine a second bit width occupied by the channel estimation data based on the first bit width and the reserved bit width; and a third determining unit, configured to determine the target overflow bit based on the second bit width and the preset compressed bit width.

[0121] In one embodiment, the second determining module 430 further includes: a fourth determining unit, configured to determine the intensity distribution data of the target channel intensity corresponding to each channel estimation data; and a fifth determining unit, configured to determine the reserved bit width based on the intensity distribution data.

[0122] In one embodiment, the intensity distribution data includes the channel intensity mean and the channel intensity extreme values; correspondingly, the fifth determining unit includes: a first determining subunit, used to determine the mean bit width occupied by the channel intensity mean; a second determining subunit, used to determine the extreme bit width occupied by the channel intensity extreme values; and a third determining subunit, used to determine the reserved bit width based on the mean bit width and the extreme bit width.

[0123] In one embodiment, the channel estimation data includes a real part of the channel estimation and an imaginary part of the channel estimation; the target channel strength includes instantaneous channel power; accordingly, the first determining module 420 includes: a sixth determining unit, configured to determine the instantaneous channel power corresponding to the channel estimation data based on the sum of squares between the real part of the channel estimation and the imaginary part of the channel estimation.

[0124] In one embodiment, the above apparatus further includes: a decompression processing module, configured to, in response to a decompression request for target compressed data, perform decompression processing on the corresponding compressed channel estimation data according to the compression bit width parameter corresponding to the compressed channel estimation data in the target compressed data; wherein, the compressed channel estimation data is compressed data after bit width compression processing of the channel estimation data.

[0125] 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.

[0126] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a data compression method. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0127] Those skilled in the art will understand that Figure 4 The 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.

[0128] In one exemplary embodiment, a computer device is provided, 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:

[0129] Acquire the data to be compressed, which includes at least one channel estimation data;

[0130] For each channel estimation data, determine the target channel strength corresponding to the channel estimation data;

[0131] Based on the target channel strength, determine the compression bit width parameter corresponding to the channel estimation data;

[0132] Based on the compressed bit width parameter, the channel estimation data is subjected to bit width compression processing.

[0133] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining a first bit width occupied by the target channel strength; determining a second bit width occupied by the channel estimation data based on the first bit width and the reserved bit width; and determining the target overflow bit based on the second bit width and the preset compressed bit width.

[0134] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining the intensity distribution data of the target channel strength corresponding to each channel estimation data; and determining the reserved bit width based on the intensity distribution data.

[0135] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining the mean bit width occupied by the mean channel strength; and determining the extreme bit width occupied by the extreme channel strength; and determining the reserved bit width based on the mean bit width and the extreme bit width.

[0136] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining the instantaneous channel power corresponding to the channel estimation data based on the sum of squares between the real part and the imaginary part of the channel estimation.

[0137] In one embodiment, when the processor executes the computer program, it further performs the following steps: decompressing the corresponding compressed channel estimation data according to the compression bit width parameter corresponding to the compressed channel estimation data in the target compressed data; wherein, the compressed channel estimation data is compressed data after bit width compression processing of the channel estimation data.

[0138] Based on the same inventive concept, this application also provides a chip, including a processor and a communication interface; the communication interface is used to receive or send data; the processor is configured to cause the chip to perform the following steps:

[0139] Acquire the data to be compressed, which includes at least one channel estimation data;

[0140] For each channel estimation data, determine the target channel strength corresponding to the channel estimation data;

[0141] Based on the target channel strength, determine the compression bit width parameter corresponding to the channel estimation data;

[0142] Based on the compressed bit width parameter, the channel estimation data is subjected to bit width compression processing.

[0143] In one embodiment, the processor is configured to cause the chip to perform the following steps: determining a first bit width occupied by the target channel strength; determining a second bit width occupied by the channel estimation data based on the first bit width and a reserved bit width; and determining a target overflow bit based on the second bit width and a preset compressed bit width.

[0144] In one embodiment, the processor is configured to cause the chip to perform the following steps: determine the intensity distribution data of the target channel intensity corresponding to each channel estimation data; and determine the reserved bit width based on the intensity distribution data.

[0145] In one embodiment, the processor is configured to cause the chip to perform the following steps: determining the mean bit width occupied by the mean channel strength; and determining the extreme bit width occupied by the extreme channel strength; and determining the reserved bit width based on the mean bit width and the extreme bit width.

[0146] In one embodiment, the processor is configured to cause the chip to perform the following steps: determining the instantaneous channel power corresponding to the channel estimation data based on the sum of squares between the real part and the imaginary part of the channel estimation.

[0147] In one embodiment, the processor is configured to cause the chip to perform the following steps: decompressing the corresponding compressed channel estimation data according to the compression bit width parameter corresponding to the compressed channel estimation data in the target compressed data; wherein, the compressed channel estimation data is compressed data after bit width compression processing of the channel estimation data.

[0148] It is understood that the chip involved in the embodiments of this application may be a field-programmable gate array (FPGA), may be 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.

[0149] Based on the same inventive concept, this application also provides a chip module, such as... Figure 5 As shown, the chip module includes a communication module, a power module, a storage module, and a chip. Among them:

[0150] 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.

[0151] The implementation of this chip module can be found in the relevant content of the above chip embodiment, and will not be repeated here.

[0152] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0153] Acquire the data to be compressed, which includes at least one channel estimation data;

[0154] For each channel estimation data, determine the target channel strength corresponding to the channel estimation data;

[0155] Based on the target channel strength, determine the compression bit width parameter corresponding to the channel estimation data;

[0156] Based on the compressed bit width parameter, the channel estimation data is subjected to bit width compression processing.

[0157] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining a first bit width occupied by the target channel strength; determining a second bit width occupied by the channel estimation data based on the first bit width and the reserved bit width; and determining the target overflow bit based on the second bit width and the preset compressed bit width.

[0158] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the intensity distribution data of the target channel strength corresponding to each channel estimation data; and determining the reserved bit width based on the intensity distribution data.

[0159] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the mean bit width occupied by the mean channel strength; and determining the extreme bit width occupied by the extreme channel strength; and determining the reserved bit width based on the mean bit width and the extreme bit width.

[0160] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the instantaneous channel power corresponding to the channel estimation data based on the sum of squares between the real part and the imaginary part of the channel estimation.

[0161] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: decompressing the corresponding compressed channel estimation data according to the compression bit width parameter corresponding to the compressed channel estimation data in the target compressed data; wherein, the compressed channel estimation data is compressed data after bit width compression processing of the channel estimation data.

[0162] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0163] Acquire the data to be compressed, which includes at least one channel estimation data;

[0164] For each channel estimation data, determine the target channel strength corresponding to the channel estimation data;

[0165] Based on the target channel strength, determine the compression bit width parameter corresponding to the channel estimation data;

[0166] Based on the compressed bit width parameter, the channel estimation data is subjected to bit width compression processing.

[0167] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining a first bit width occupied by the target channel strength; determining a second bit width occupied by the channel estimation data based on the first bit width and the reserved bit width; and determining the target overflow bit based on the second bit width and the preset compressed bit width.

[0168] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the intensity distribution data of the target channel strength corresponding to each channel estimation data; and determining the reserved bit width based on the intensity distribution data.

[0169] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the mean bit width occupied by the mean channel strength; and determining the extreme bit width occupied by the extreme channel strength; and determining the reserved bit width based on the mean bit width and the extreme bit width.

[0170] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the instantaneous channel power corresponding to the channel estimation data based on the sum of squares between the real part and the imaginary part of the channel estimation.

[0171] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: decompressing the corresponding compressed channel estimation data according to the compression bit width parameter corresponding to the compressed channel estimation data in the target compressed data; wherein, the compressed channel estimation data is compressed data after bit width compression processing of the channel estimation data.

[0172] 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.

[0173] 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.

[0174] 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: Acquire data to be compressed, the data to be compressed including at least one channel estimation data; For each channel estimation data, determine the target channel strength corresponding to the channel estimation data; Based on the target channel strength, determine the compression bit width parameter corresponding to the channel estimation data; Based on the compressed bit width parameter, the channel estimation data is subjected to bit width compression processing.

2. The method according to claim 1, characterized in that, The compressed bit width parameter includes a target overflow bit; correspondingly, determining the compressed bit width parameter corresponding to the channel estimation data based on the target channel strength includes: Determine the first bit width occupied by the target channel strength; The second bit width occupied by the channel estimation data is determined based on the first bit width and the reserved bit width; The target overflow bit is determined based on the second bit width and the preset compressed bit width.

3. The method according to claim 2, characterized in that, The reserved bit width is determined according to the following steps: Determine the intensity distribution data of the target channel strength corresponding to each of the aforementioned channel estimation data; Based on the intensity distribution data, the reserved bit width is determined.

4. The method according to claim 3, characterized in that, The intensity distribution data includes the channel intensity mean and the channel intensity extreme value; correspondingly, determining the reserved bit width based on the intensity distribution data includes: Determine the average bit width occupied by the average channel strength; and, Determine the extreme bit width occupied by the extreme values ​​of the channel strength; The reserved bit width is determined based on the average bit width and the extreme bit width.

5. The method according to any one of claims 1-4, characterized in that, The channel estimation data includes a real part and an imaginary part of the channel estimation; the target channel strength includes instantaneous channel power; correspondingly, determining the target channel strength corresponding to the channel estimation data includes: The instantaneous channel power corresponding to the channel estimation data is determined based on the sum of squares between the real part and the imaginary part of the channel estimation.

6. The method according to any one of claims 1-4, characterized in that, The method further includes: In response to a decompression request for the target compressed data, the corresponding compressed channel estimation data is decompressed according to the compression bit width parameter corresponding to the compressed channel estimation data in the target compressed data. The compressed channel estimation data is the compressed data after bit-width compression processing of the channel estimation data.

7. A data compression device, characterized in that, The device includes: The acquisition module is used to acquire data to be compressed, the data to be compressed including at least one channel estimation data; The first determining module is used to determine the target channel strength corresponding to each channel estimation data. The second determining module is used to determine the compression bit width parameter corresponding to the channel estimation data based on the target channel strength; The compression module is used to perform bit-width compression processing on the channel estimation data based on the compression bit-width parameter.

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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