A linear equalization method, device, equipment and medium

Abstract

The present disclosure relates to a linear equalization method, device, equipment and medium, and relates to the field of communication technology. The method includes: obtaining a first noise and interference covariance matrix corresponding to a target subcarrier band according to a data symbol, wherein the target subcarrier band is a subcarrier band corresponding to a subcarrier band number to which the data symbol belongs; performing equalization processing on the data symbol according to the first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal; performing inverse scaling repair on the first equalized signal according to a repair coefficient to generate a second equalized signal, wherein the repair coefficient is a coefficient determined according to the signal-to-interference-noise ratio information; performing soft demodulation processing on the second equalized signal to obtain soft bit information corresponding to the data symbol. The present disclosure performs inverse scaling repair on the first equalized signal according to the repair coefficient to remove the influence of scaling, so that the constellation amplitude of the equalized signal is more accurate.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a linear equalization method, device, equipment and medium. Background Art

[0002] In the 5th Generation mobile networks-New Radio (5G-NR) system, a large-scale Multiple-Input Multiple-Output (MIMO) technology is proposed. For uplink reception, when there are many user terminal devices in other cells with the same frequency, the interference will be more serious. When the user terminal device has multiple antennas for reception, a special receiving algorithm can be used to eliminate interference, such as the Maximum Likelihood Detection (MLD) algorithm. Although the MLD algorithm has the best performance in theory, it is a nonlinear algorithm with high complexity and is complex to implement. Summary of the invention

[0003] The implementation method of related linear equalization is mainly to perform equalization by selecting the Maximum Ratio Combining (MRC) algorithm and the Interference Rejection Combining (IRC) algorithm to obtain the advantages of the IRC algorithm in the presence of interference and the advantages of the MRC algorithm in the absence of interference; however, the method design and device design cannot achieve the most favorable state for implementation, affecting the system performance.

[0004] In view of this, the present disclosure provides a linear equalization method, apparatus, device and medium to improve the anti-interference performance of the linear equalization scheme, reduce the bit error rate of the receiving end, and thus improve the throughput of the system.

[0005] In a first aspect, an embodiment of the present disclosure provides a linear equalization method, including:

[0006] Acquire a first noise and interference covariance matrix corresponding to a target subcarrier band according to the data symbol, wherein the target subcarrier band is a subcarrier band corresponding to a subcarrier band number to which the data symbol belongs;

[0007] Performing equalization processing on the data symbol according to a first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal;

[0008] Performing inverse scaling repair on the first equalized signal according to a repair coefficient to generate a second equalized signal, wherein the repair coefficient is a coefficient determined according to the signal to interference noise ratio information;

[0009] Soft demodulation processing is performed according to the second equalized signal to obtain soft bit information corresponding to the data symbol.

[0010] Optionally, performing equalization processing on the data symbol according to a first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal includes:

[0011] performing calculation based on the first noise and interference covariance matrix and the channel estimation value corresponding to the data symbol, so as to use the calculation result as the signal to interference plus noise ratio information;

[0012] Channel equalization is performed on the receiving antenna signal corresponding to the data symbol according to the signal to interference plus noise ratio information, the first noise and interference covariance matrix, and the channel estimation value to obtain the first equalized signal.

[0013] Optionally, the signal to interference and noise ratio information is used to scale the constellation amplitude of the first equalized signal, and before the inverse scaling and repairing of the first equalized signal according to the repair coefficient, the method further includes: determining the repair coefficient based on real data of the signal to interference and noise ratio information.

[0014] Optionally, after obtaining the signal to interference plus noise ratio information and the first equalized signal, the method further includes: estimating a power ratio according to the signal to interference plus noise ratio information to obtain a target signal to interference plus noise ratio; and weighting the soft bit information according to the target signal to interference plus noise ratio to obtain weighted confidence information.

[0015] Optionally, the obtaining, according to the data symbol, a first noise and interference covariance matrix corresponding to the target subcarrier band includes:

[0016] Extracting the subcarrier band number to which the data symbol belongs;

[0017] A corresponding noise and interference covariance inverse matrix is ​​extracted according to the subcarrier band number to serve as the first noise and interference covariance matrix.

[0018] Optionally, the subcarrier band number is a subcarrier band number, and before acquiring the first noise and interference covariance matrix corresponding to the target subcarrier band according to the data symbol, the method further includes:

[0019] Determining a noise-to-interference ratio for each subcarrier band;

[0020] If the noise-to-interference ratio of the subcarrier band is greater than the threshold value, the noise and interference covariance matrix of the subcarrier band is inverted according to the maximum ratio combining (MRC) algorithm to obtain the noise-to-interference covariance inverse matrix;

[0021] If the noise-interference ratio of the subcarrier band is not greater than the threshold value, the noise and interference covariance matrix of the subcarrier band is inverted according to the interference suppression ratio combining IRC algorithm to obtain the noise-interference covariance inverse matrix.

[0022] Optionally, performing inversion processing on the noise and interference covariance matrix of the subcarrier band according to the maximum ratio combining (MRC) algorithm to obtain the noise interference covariance inverse matrix includes:

[0023] The inverse of each main diagonal element in the noise and interference covariance matrix of the subcarrier band is obtained to obtain an inverse matrix as the noise interference covariance inverse matrix corresponding to the subcarrier band.

[0024] Optionally, the inverse processing of the noise and interference covariance matrix of the subcarrier band according to the interference suppression ratio combined IRC algorithm to obtain the noise interference covariance inverse matrix includes:

[0025] Determine the number of antennas;

[0026] If the number of antennas is equal to two, the noise and interference covariance matrix of the subcarrier band is inverted by using a determinant inversion method to obtain a corresponding inverse matrix as an inverse noise interference covariance matrix corresponding to the subcarrier band;

[0027] If the number of antennas is greater than two, the noise and interference covariance matrix of the subcarrier band is inverted using a cyclic label inversion method to obtain a corresponding inverse matrix as the noise interference covariance inverse matrix corresponding to the subcarrier band.

[0028] Optionally, determining a noise-to-interference ratio value of each subcarrier band includes:

[0029] For each subcarrier band, the ratio of the antenna noise interference energy correlation result and the antenna interference correlation result is determined as the noise interference ratio, the antenna noise interference energy correlation result is the sum of the mutual products of the elements on the target diagonal, the target diagonal is the main diagonal of the noise and interference covariance matrix of the subcarrier band, the antenna interference correlation result is the sum of the products of the mutually conjugate elements in the first triangular matrix and the second triangular matrix in the noise and interference covariance matrix of the subcarrier band, and the elements of the first triangular matrix and the elements of the second triangular matrix do not contain the elements on the main diagonal.

[0030] Optionally, before determining the noise-to-interference ratio value of each subcarrier band, the method further includes:

[0031] According to the resource block information allocated to the user terminal, subcarrier division is performed on the time-frequency domain resources of the user terminal to obtain at least two subcarrier bands;

[0032] The noise and interference covariance matrix of the subcarrier band is determined according to the noise and interference covariance matrix corresponding to the target reference symbol, and the target reference symbol is a reference symbol included in the subcarrier band.

[0033] Optionally, the resource block information includes resource block size information and resource block position information, and the subcarrier division of the time-frequency domain resources of the user terminal according to the resource block information allocated to the user terminal to obtain at least two subcarrier bands includes:

[0034] Obtaining resource block size information and resource block location information allocated to the user terminal;

[0035] Based on the resource block size information and the resource block position information, the time-frequency domain resources of the user terminal are subcarrier-divided according to the number of subcarrier resource blocks to obtain at least two subcarrier bands, and the number of subcarrier resource blocks is the number of resource blocks within a preset frequency domain bandwidth.

[0036] Optionally, determining the noise and interference covariance matrix of the subcarrier band according to the noise and interference covariance matrix corresponding to the target reference symbol includes:

[0037] Determine a target reference symbol belonging to the subcarrier band based on a subcarrier band number, wherein the subcarrier band number of the subcarrier band to which the target reference symbol belongs is related to the subcarrier number of the target reference symbol;

[0038] Accumulating noise and interference covariance matrices corresponding to target reference symbols in the subcarrier band to obtain a second noise and interference covariance matrix of the subcarrier band;

[0039] Time domain filtering is performed according to the second noise and interference covariance matrix of the subcarrier band to obtain the noise and interference covariance matrix of the subcarrier band.

[0040] Optionally, performing time domain filtering according to the second noise and interference covariance matrix of the subcarrier band to obtain the noise and interference covariance matrix of the subcarrier band includes:

[0041] Obtain a subcarrier band covariance matrix of a current time slot and a subcarrier band covariance matrix of a reference time slot, wherein the subcarrier band covariance matrix of the current time slot is a second noise and interference covariance matrix of the subcarrier band of the current time slot, and the subcarrier band covariance matrix of the reference time slot is a second noise and interference covariance matrix of the subcarrier band of a time slot before the current time slot;

[0042] According to the preset time domain filter coefficient, weighted processing is performed on the subcarrier band covariance matrix of the current time slot and the subcarrier band covariance matrix of the reference time slot.

[0043] In a second aspect, an embodiment of the present disclosure provides a linear equalization device, including:

[0044] A covariance matrix acquisition module, used to acquire a first noise and interference covariance matrix corresponding to a target subcarrier band according to a data symbol, wherein the target subcarrier band is a subcarrier band corresponding to a subcarrier band number to which the data symbol belongs;

[0045] An equalization processing module, configured to perform equalization processing according to a first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal;

[0046] an inverse scaling and repairing module, configured to perform inverse scaling and repairing on the first equalized signal according to a repair coefficient to generate a second equalized signal, wherein the repair coefficient is a coefficient determined according to the signal to interference noise ratio information;

[0047] The soft demodulation processing module is used to perform soft demodulation processing according to the second equalized signal to obtain soft bit information corresponding to the data symbol.

[0048] In a third aspect, an embodiment of the present disclosure provides a communication device, including a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; the memory is used to store computer programs; and the processor is used to implement the steps of any linear equalization method described in the first aspect when executing the program stored in the memory.

[0049] Optionally, the equalization processing module may include the following submodules:

[0050] a calculation submodule, configured to perform calculation based on the first noise and interference covariance matrix and the channel estimation value corresponding to the data symbol, so as to use the calculation result as the signal to interference plus noise ratio information;

[0051] A channel equalization submodule is used to perform channel equalization according to the signal to interference plus noise ratio information, the first noise and interference covariance matrix, the channel estimation value, and the receiving antenna signal corresponding to the data symbol to obtain the first equalized signal.

[0052] Optionally, the signal to interference and noise ratio information is used to scale the constellation amplitude of the first equalized signal, and the above-mentioned linear equalization device further includes: a repair coefficient determination module, which is used to determine the repair coefficient based on the real part data of the signal to interference and noise ratio information.

[0053] Optionally, the interference estimation device may further include: a power ratio estimation module and a weighted processing module. The power ratio estimation module is used to perform power ratio estimation based on the signal to interference noise ratio information to obtain a target signal to interference noise ratio; and the weighted processing module is used to perform weighted processing on the soft bit information based on the target signal to interference noise ratio to obtain weighted confidence information.

[0054] Optionally, the covariance matrix acquisition module may include the following submodules:

[0055] A subcarrier band number extraction submodule, used to extract the subcarrier band number to which the data symbol belongs;

[0056] The noise interference covariance inverse matrix extraction submodule is used to extract the corresponding noise interference covariance inverse matrix according to the subcarrier band number to serve as the first noise and interference covariance matrix.

[0057] Optionally, the subcarrier band number is a subcarrier band number, and the linear equalization device further includes:

[0058] A noise-to-interference ratio determination module, used to determine the noise-to-interference ratio of each subcarrier band;

[0059] A first inversion processing module is used to perform inversion processing on the noise and interference covariance matrix of the subcarrier band according to the maximum ratio combining (MRC) algorithm when the noise-to-interference ratio of the subcarrier band is greater than the threshold value, so as to obtain the noise-to-interference covariance inverse matrix;

[0060] The second inversion processing module is used to perform inversion processing on the noise and interference covariance matrix of the subcarrier band according to the interference suppression ratio merging IRC algorithm when the noise-interference ratio of the subcarrier band is not greater than the threshold value, so as to obtain the noise-interference covariance inverse matrix.

[0061] Optionally, the first inversion processing module is specifically used to: calculate the inverse of each main diagonal element in the noise and interference covariance matrix of the subcarrier band to obtain the inverse matrix of the noise and interference covariance matrix as the noise interference covariance inverse matrix corresponding to the subcarrier band.

[0062] Optionally, the second inversion processing module is specifically used to: determine the number of antennas; if the number of antennas is equal to two, then use the determinant inversion method to invert the noise and interference covariance matrix of the subcarrier band to obtain the corresponding inverse matrix, which is used as the noise interference covariance inverse matrix corresponding to the subcarrier band; if the number of antennas is greater than two, then use the cyclic label inversion method to invert the noise and interference covariance matrix of the subcarrier band to obtain the corresponding inverse matrix, which is used as the noise interference covariance inverse matrix corresponding to the subcarrier band.

[0063] Optionally, the noise-interference ratio determination module is specifically used to: for each subcarrier band, determine the ratio of the antenna noise interference energy correlation result and the antenna interference correlation result as the noise-interference ratio, the antenna noise interference energy correlation result is the sum of the mutual products of the elements on the target diagonal, the target diagonal is the main diagonal of the noise and interference covariance matrix of the subcarrier band, the antenna interference correlation result is the sum of the products of the mutually conjugate elements in the first triangular matrix and the second triangular matrix in the noise and interference covariance matrix of the subcarrier band, and neither the elements of the first triangular matrix nor the elements of the second triangular matrix contain the elements on the main diagonal.

[0064] Optionally, the linear equalizer device further includes:

[0065] A subcarrier division module, configured to perform subcarrier division on the time-frequency domain resources of the user terminal according to the resource block information allocated to the user terminal, so as to obtain at least two subcarrier bands;

[0066] The subcarrier band covariance matrix determination module is used to determine the noise and interference covariance matrix of the subcarrier band according to the noise and interference covariance matrix corresponding to the target reference symbol, and the target reference symbol is a reference symbol included in the subcarrier band.

[0067] Optionally, the resource block information may include resource block size information and resource block position information, and the subcarrier division module may include the following sub-modules:

[0068] A resource block information acquisition submodule, used to acquire the resource block size information and resource block location information allocated to the user terminal;

[0069] The subcarrier division submodule is used to subcarrier divide the time-frequency domain resources of the user terminal according to the number of subcarrier resource blocks based on the resource block size information and the resource block position information, so as to obtain at least two subcarrier bands, and the number of subcarrier resource blocks is the number of resource blocks within a preset frequency domain bandwidth.

[0070] Optionally, the subcarrier band covariance matrix determination module may include the following submodules:

[0071] a target reference symbol determination submodule, configured to determine a target reference symbol belonging to the subcarrier band based on a subcarrier band number, wherein the subcarrier band number of the subcarrier band to which the target reference symbol belongs is related to the subcarrier number of the target reference symbol;

[0072] An accumulation processing submodule, used for accumulating the noise and interference covariance matrix corresponding to the target reference symbol in the subcarrier band to obtain a second noise and interference covariance matrix of the subcarrier band;

[0073] The time domain filtering submodule is used to perform time domain filtering according to the second noise and interference covariance matrix of the subcarrier band to obtain the noise and interference covariance matrix of the subcarrier band.

[0074] Optionally, the time domain filtering submodule is specifically used to: obtain the subcarrier band covariance matrix of the current time slot and the subcarrier band covariance matrix of the reference time slot, the subcarrier band covariance matrix of the current time slot is the second noise and interference covariance matrix of the subcarrier band in the current time slot, and the subcarrier band covariance matrix of the reference time slot is the second noise and interference covariance matrix of the subcarrier band in the previous time slot of the current time slot; and perform weighted processing on the subcarrier band covariance matrix of the current time slot and the subcarrier band covariance matrix of the reference time slot according to a preset time domain filtering coefficient.

[0075] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the linear equalization method as described in any one of the first aspects are implemented.

[0076] The embodiment of the present disclosure obtains the first noise and interference covariance matrix corresponding to the target subcarrier band according to the data symbol, and performs equalization processing according to the first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal, so that the repair coefficient corresponding to the data symbol can be determined according to the signal-to-interference-noise ratio information, and the first equalized signal can be inversely scaled and repaired according to the repair coefficient to remove the impact of scaling, so that the constellation amplitude of the equalized signal is more accurate; then, soft demodulation processing can be performed according to the second equalized signal generated after the repair, reducing the division operation in the soft demodulation process, and obtaining the soft bit information corresponding to the data symbol. Further, the embodiment of the present disclosure can determine the signal-to-interference-noise ratio corresponding to the data symbol according to the signal-to-interference-noise ratio information, so as to perform weighted processing on the soft bit information according to the signal-to-interference-noise ratio, improve the accuracy of the confidence when the hybrid automatic repeat request (HARQ) is combined, thereby improving the performance of soft decoding and achieving the purpose of improving system performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0078] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0079] Figure 1 A flowchart of a linear equalization method provided by an embodiment of the present disclosure;

[0080] Figure 2 A flow chart of the steps of a linear equalization method provided for an optional embodiment of the present disclosure;

[0081] Figure 3 A schematic diagram of subcarrier band division in an embodiment of the present disclosure;

[0082] Figure 4 A structural block diagram of a linear equalization device provided in an embodiment of the present disclosure;

[0083] Figure 5 A schematic diagram of the structure of a linear equalizer device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0084] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.

[0085] In order to solve the problem of inter-symbol interference caused by multipath channel fading and co-channel interference generated by UEs in other cells when 5G-NR small base stations receive physical uplink shared channel (PUSCH) signals sent by user equipment (UE), the receiving end needs to perform channel equalization on the received signal.

[0086] One of the core concepts of the embodiments of the present disclosure is to propose an improved linear equalization method so as to suppress the interference of the same-frequency cells without knowing the interference parameters of other same-frequency cells, thereby improving the anti-interference capability of the small base station for PUSCH signals and improving the throughput of the PUSCH receiving system.

[0087] Reference Figure 1 , shows a flow chart of the steps of a linear equalization method provided by an embodiment of the present disclosure. The linear equalization method provided by the present disclosure can be applied to channel equalization, and specifically may include the following steps:

[0088] Step 110: Acquire a first noise and interference covariance matrix corresponding to a target subcarrier band according to the data symbol, wherein the target subcarrier band is a subcarrier band corresponding to a subcarrier band number to which the data symbol belongs.

[0089] Specifically, for each data symbol, the embodiment of the present disclosure can determine the corresponding subcarrier band according to the subcarrier band number i to which the data symbol belongs, as the target subcarrier band, and then extract the corresponding noise and interference covariance matrix according to the subcarrier band number as the first noise and interference covariance matrix corresponding to the target subcarrier band.

[0090] In an optional embodiment, the corresponding noise and interference covariance matrix extracted according to the subcarrier band number i may be an inverse noise-interference covariance matrix corresponding to the subcarrier band number. Further, the embodiment of the present disclosure obtains the first noise and interference covariance matrix corresponding to the target subcarrier band based on the data symbol, which may specifically include: extracting the subcarrier band number to which the data symbol belongs; extracting the corresponding inverse noise-interference covariance matrix according to the subcarrier band number as the first noise and interference covariance matrix. Among them, the inverse noise-interference covariance matrix may refer to the inverse matrix of the noise and interference covariance matrix of the subcarrier band.

[0091] In a specific implementation, a suitable linear equalization algorithm can be selected according to the noise-interference ratio of the subcarrier band as the target linear equalization algorithm corresponding to the subcarrier band, so that the noise and interference covariance matrix of the subcarrier band can be inverted according to the target linear equalization algorithm to obtain the noise-interference covariance inverse matrix. Furthermore, the linear equalization method provided in the embodiment of the present disclosure also includes: determining the noise-interference ratio of each subcarrier band before obtaining the first noise and interference covariance matrix corresponding to the target subcarrier band according to the data symbol; if the noise-interference ratio of the subcarrier band is greater than the threshold value, then inverting the noise and interference covariance matrix of the subcarrier band according to the maximum ratio combining MRC algorithm to obtain the noise-interference covariance inverse matrix; if the noise-interference ratio of the subcarrier band is not greater than the threshold value, then inverting the noise and interference covariance matrix of the subcarrier band according to the interference suppression ratio combining IRC algorithm to obtain the noise-interference covariance inverse matrix. It can be seen that the embodiment of the present disclosure can determine the target linear equalization algorithm corresponding to each subcarrier band according to the noise-to-interference ratio of each subcarrier band respectively; then, for each subcarrier band, the noise and interference covariance matrix of the subcarrier band can be inverted according to the target linear equalization algorithm to obtain the noise-interference covariance inverse matrix, so as to subsequently extract the noise-interference covariance inverse matrix according to the subcarrier band number as the first noise and interference covariance matrix corresponding to the target subcarrier band. Wherein, the target subcarrier band is the subcarrier band corresponding to the subcarrier band number, and the subcarrier band number is the number of the subcarrier band.

[0092] Step 120: Perform equalization processing according to a first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal.

[0093] Specifically, after obtaining the first noise and interference covariance matrix corresponding to the target subcarrier band, the embodiment of the present disclosure can perform equalization processing on the received data based on the first noise and interference covariance matrix to obtain an equalized signal as a first equalized signal, and at the same time, the signal to noise ratio information generated during the equalization process can be retained, so that the repair coefficient corresponding to the data symbol can be determined later based on the signal to noise ratio information. The signal to noise ratio information refers to the power ratio information of the signal to the noise and interference.

[0094] Step 130: Perform inverse scaling repair on the first equalized signal according to a repair coefficient to generate a second equalized signal, wherein the repair coefficient is a coefficient determined according to the signal to interference noise ratio information.

[0095] Specifically, after obtaining the signal to noise ratio information, the embodiment of the present disclosure can determine the repair coefficient corresponding to the data symbol according to the signal to noise ratio information, and can perform inverse scaling repair on the first equalized signal according to the repair coefficient to remove the influence of scaling, so that the constellation amplitude of the equalized signal is more accurate. Further, the signal to noise ratio information in the embodiment of the present disclosure can be used to scale the constellation amplitude of the first equalized signal. Optionally, before performing inverse scaling repair on the first equalized signal according to the repair coefficient, the embodiment of the present disclosure can also include determining the repair coefficient based on the real part data of the signal to noise ratio information.

[0096] Specifically, in the equalization process, the signal-to-noise ratio information generated by the calculation process can be used to calculate the coefficient for constellation amplitude repair of each data symbol, that is, to calculate the repair coefficient corresponding to the data symbol, so that the repair coefficient corresponding to the data symbol can be used later to perform inverse scaling repair on the equalized signal (i.e., the first equalized signal) to generate a second equalized signal. Among them, the second equalized signal may refer to an equalized signal generated after inverse scaling repair of the first equalized signal according to the repair coefficient. For example, the calculation formula for constellation amplitude repair can be used: X2 = X1.*β, and the repair coefficient β can be used to perform constellation amplitude repair on the first equalized signal to obtain a second equalized signal; it should be noted that constellation amplitude repair is one of the inverse scaling repairs; X2 can represent the second equalized signal generated after repair, X1 can represent the first equalized signal before repair, and the .* in the formula can represent matrix dot multiplication, and the repair coefficient β can be a constellation amplitude repair coefficient, which is not specifically limited in this example.

[0097] Step 140: Perform soft demodulation processing according to the second equalized signal to obtain soft bit information corresponding to the data symbol.

[0098] Specifically, after obtaining the second equalized signal generated by inverse scaling and repairing the first equalized signal according to the repair coefficient, the embodiment of the present disclosure can perform soft demodulation processing based on the second equalized signal according to a preset soft demodulation formula to obtain soft bit information corresponding to the data symbol. The soft bit information can be used to represent the soft bit after soft demodulation, and specifically can include the soft bit information after soft demodulation of the data symbol.

[0099] For example, when the channel equalization outputs the second equalized signal X2, the preset soft demodulation formula may be used: Perform soft demodulation to obtain soft bit information Among them, the soft bit information It may be the confidence of the probability that the i-th bit of the received signal of the v-th layer of the transmitted signal corresponding to the second equalized signal X2 is 0; and A set of vectors in which the i-th bit of the transmitted symbol of the v-th layer can be represented as 1 and 0 respectively.

[0100] It can be seen that the embodiment of the present disclosure obtains the first noise and interference covariance matrix corresponding to the target subcarrier band according to the data symbol, and performs equalization processing according to the first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal, so that the repair coefficient corresponding to the data symbol can be determined according to the signal-to-interference-noise ratio information, and the first equalized signal can be inversely scaled and repaired according to the repair coefficient to remove the impact of scaling, so that the constellation amplitude of the equalized signal is more accurate; then, soft demodulation processing can be performed according to the second equalized signal generated after the repair, thereby reducing the division operation in the soft demodulation process and obtaining the soft bit information corresponding to the data symbol.

[0101] In a specific implementation, the signal to interference and noise ratio information generated during the equalization process can be used to determine the signal to interference and noise ratio corresponding to the soft bit information, so that the signal to interference and noise ratio can be used to perform weighted processing on the soft bits corresponding to the data symbols at different positions, thereby improving the accuracy of the confidence of the soft bits corresponding to the redundant versions of different HARQ processes. Furthermore, after obtaining the signal to interference and noise ratio information and the first equalization signal, the linear equalization method provided in the embodiment of the present disclosure may also include: estimating the power ratio based on the signal to interference and noise ratio information to obtain a target signal to interference and noise ratio; and performing weighted processing on the soft bit information based on the target signal to interference and noise ratio to obtain weighted confidence information. Among them, the target signal to interference and noise ratio may refer to the signal to interference and noise ratio corresponding to the soft bit information.

[0102] Specifically, the target signal to noise ratio calculated in the channel equalization process of this embodiment can represent the estimated value of the useful signal power and the power of interference and noise at each data symbol position, and can be a kind of a posteriori information. This means that the soft bit information after soft demodulation of data symbols at different positions should have different confidences. For example, the larger the signal to noise ratio, the greater the confidence of the corresponding log likelihood ratio (LLR) at the position. After obtaining the demodulated soft bit information, the disclosed embodiment can perform weighted processing on the demodulated soft bit information according to the signal to noise ratio, so as to use the weighted processing result as confidence information, thereby improving the accuracy of the confidence during HARQ merging and improving the performance of soft decoding.

[0103] It can be seen that the embodiment of the present disclosure obtains the first noise and interference covariance matrix corresponding to the target subcarrier band according to the data symbol, and performs equalization processing according to the first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal, so that the repair coefficient corresponding to the data symbol and the signal-to-interference-noise ratio corresponding to the soft bit information can be determined according to the signal-to-interference-noise ratio information, so as to perform inverse scaling repair on the first equalized signal according to the repair coefficient, remove the influence caused by scaling, and make the constellation amplitude of the equalized signal more accurate; then, soft demodulation processing can be performed according to the second equalized signal generated after the repair, thereby reducing the division operation in the soft demodulation process, and obtaining the soft bit information corresponding to the data symbol, and the soft bit information can be weighted according to the signal-to-interference-noise ratio to improve the accuracy of the confidence during HARQ merging, thereby improving the performance of soft decoding and achieving the purpose of improving system performance.

[0104] In a specific implementation, the embodiment of the present disclosure can extract a channel estimation value from the channel estimation result for each of the data symbols in the received data, and can extract a receiving antenna signal from an orthogonal frequency division multiplexing (OFDM) demodulation processing result, so as to perform channel equalization according to the signal to interference noise ratio information, the first noise and interference covariance matrix, the channel estimation value, and the receiving antenna signal to obtain a first equalized signal. Optionally, on the basis of the above embodiment, the embodiment of the present disclosure performs equalization processing according to the first noise and interference covariance matrix corresponding to the target subcarrier band to obtain the signal to interference noise ratio information and the first equalized signal, which can specifically include: calculating based on the first noise and interference covariance matrix and the channel estimation value corresponding to the data symbol, so as to use the calculation result as the signal to interference noise ratio information; performing channel equalization according to the signal to interference noise ratio information, the first noise and interference covariance matrix, the channel estimation value, and the receiving antenna signal corresponding to the data symbol to obtain the first equalized signal.

[0105] In actual processing, the time-frequency domain resources of the user terminal can be subcarrier-divided according to the resource block information allocated to the user terminal to obtain one or more subcarrier bands, so that the noise and interference covariance matrix of the subcarrier band can be inverted later to obtain the noise-interference covariance inverse matrix as the first noise and interference covariance matrix corresponding to the subcarrier band. Optionally, based on the above embodiment, the linear equalization method provided in the embodiment of the present disclosure may also include: according to the resource block information allocated to the user terminal, the time-frequency domain resources of the user terminal are subcarrier-divided to obtain at least two subcarrier bands; according to the noise and interference covariance matrix corresponding to the target reference symbol, the noise and interference covariance matrix of the subcarrier band is determined, and the target reference symbol is the reference symbol contained in the subcarrier band. Among them, the resource block information allocated to the user terminal can be used to determine the size and position of the resource block (Resource Block, RB) allocated to the user terminal, such as including the resource block size information allocated to the user terminal, resource block position information, etc., and the embodiment of the present disclosure does not make specific restrictions on this. It should be noted that the resource block size information allocated to the user terminal may indicate the size of the RB allocated to the user terminal; and the resource block position information may indicate the position of the RB allocated to the user terminal.

[0106] Reference Figure 2 , shows a flow chart of the steps of a linear equalization method provided by an optional embodiment of the present disclosure. Figure 2 As shown, the linear equalization method implemented in the present disclosure may specifically include the following steps:

[0107] Step 210: divide the time-frequency domain resources of the user terminal into subcarriers according to the resource block information allocated to the user terminal to obtain at least two subcarrier bands.

[0108] Specifically, the embodiments of the present disclosure may divide the time-frequency domain resources of the user terminal into subcarrier bands based on the resource block information allocated to the user terminal and according to the size and position of the RB allocated to the user terminal, such as dividing the time domain in units of one time slot to obtain two or more subcarrier bands.

[0109] Further, the resource block information in the embodiment of the present disclosure may include resource block size information and resource block position information. The subcarrier division of the time-frequency domain resources of the user terminal according to the resource block information allocated to the user terminal to obtain at least two subcarrier bands may specifically include the following sub-steps:

[0110] Sub-step 2201, obtaining resource block size information and resource block location information allocated to the user terminal;

[0111] Sub-step 2202, based on the resource block size information and the resource block position information, subcarriers are divided into time-frequency domain resources of the user terminal according to the number of subcarrier resource blocks to obtain at least two subcarrier bands, and the number of subcarrier resource blocks is the number of resource blocks within a preset frequency domain bandwidth.

[0112] Specifically, after obtaining the resource block size information and resource block position information allocated to the user terminal, the embodiment of the present disclosure can divide the time-frequency domain resources of the user terminal into subcarrier bands according to the resource block size information and resource block position information allocated to the user terminal and the number of resource blocks within a preset frequency domain bandwidth, thereby obtaining several subcarrier bands.

[0113] For example, the frequency domain resource range currently allocated to the user terminal is RB m ~RB n In the case of , if the number of RBs in a subcarrier band is set to K in advance, m ~RB n Within the frequency domain resource range, define every K RBs in the frequency domain and each time slot in the time domain as a subcarrier band. Therefore, it can be calculated that the range of subcarrier band numbers is i∈0,1,2,…[(n-m+1) / K], and the noise and interference covariance matrix corresponding to the subcarrier band numbered i can be marked as , and the noise and interference covariance matrix corresponding to each subcarrier band can be The initial value of is set to 0. Wherein, m and n are RB offsets relative to the initial position RB0 of the current resource grid.

[0114] by Figure 3 Take the subcarrier band division as an example. Specifically, Figure 3 The frequency domain resource range in is subcarriers 0 to 47, which corresponds to 4 RBs, which can be recorded as RB0, RB1, RB2, and RB3 respectively; when the number of resource blocks K is set to 4, that is, when 4 RBs can be divided into a subcarrier band, the number i of the subcarrier band can be recorded as 0, that is, i=0, and the time domain length of the subcarrier band can be 14 OFDM symbols, and the frequency domain length can be 4 RBs, so that all data symbols or reference symbols with subcarrier numbers in the range of 0 to 47 and OFDM symbol numbers in the range of 0 to 13 can be determined as the data contained in the subcarrier band. It should be noted that Figure 3 The medium grey boxes may represent reference (RS) symbols. Figure 3 The white boxes in the figure can represent data symbols.

[0115] In actual processing, if the value of the number K of RBs in a subcarrier band is too large, there may be co-channel interference in some RBs in a subcarrier and no co-channel interference in some RBs, resulting in different interference situations in the frequency domains between the RBs in the subcarrier band; if the value of the number K of RBs in a subcarrier band is too small, for example, K=1, the number of reference symbols in the subcarrier band may be too small, and the calculation result may not meet the statistical characteristics. Therefore, the number of subcarrier resource blocks K can be set to a positive integer greater than 1, so as to take into account the more accurate statistical characteristics brought by more reference symbols and the different co-channel interference situations of the RBs in the subcarrier band.

[0116] In combination with actual conditions, preferably, the number K of RBs in a subcarrier band can be set to 4, so as to take into account the more accurate statistical characteristics brought by more reference symbols and the different co-channel interference conditions of RBs in the subcarrier band. In actual use, the number K of RBs in a subcarrier band can be adjusted according to the law of interference observed by other means, and the embodiments of the present disclosure do not impose specific restrictions on this.

[0117] Step 220, determining the noise and interference covariance matrix of the subcarrier band according to the noise and interference covariance matrix corresponding to the target reference symbol, wherein the target reference symbol is the reference symbol included in the subcarrier band.

[0118] Specifically, after dividing and obtaining one or more subcarrier bands, the embodiments of the present disclosure can count the noise and interference covariance matrices corresponding to all reference symbols contained in the subcarrier band for each subcarrier band, so as to add the counted noise and covariance matrices to the noise and covariance matrices corresponding to the subcarrier band, and can take the expectation of the noise and covariance matrix corresponding to the subcarrier band, so as to use the expected value of the noise and interference covariance matrix in the subcarrier band as the noise and interference covariance matrix of the entire subcarrier band. For example, the expected value of the noise and interference covariance matrix corresponding to the reference symbols in the subcarrier band can be counted, so as to form the noise and interference covariance matrix of the entire subcarrier band based on the expected value of the noise and interference covariance matrix corresponding to the reference symbols contained in the subcarrier band.

[0119] Furthermore, the disclosed embodiment determines the noise and interference covariance matrix of the subcarrier band according to the noise and interference covariance matrix corresponding to the target reference symbol, which may specifically include: determining the target reference symbol belonging to the subcarrier band based on the subcarrier band number, the subcarrier band number of the subcarrier band to which the target reference symbol belongs is related to the subcarrier number of the target reference symbol; performing accumulation processing on the noise and interference covariance matrix corresponding to the target reference symbol in the subcarrier band to obtain the second noise and interference covariance matrix of the subcarrier band; performing time domain filtering according to the second noise and interference covariance matrix of the subcarrier band to obtain the noise and interference covariance matrix of the subcarrier band. Wherein, the subcarrier band number is the number of the subcarrier band.

[0120] In actual processing, the formula for dividing the subcarrier band number can be i=k SC / M*K, to determine the number of the subcarrier band to which the reference symbol belongs; wherein i can be represented as the number of the subcarrier band to which the reference symbol belongs; k SC It can be expressed as the subcarrier number of the reference symbol; K can be expressed as the number of subcarrier resource blocks in a subcarrier, and the number of subcarrier resource blocks in a subcarrier can be an algorithm parameter configured according to the observed interference law; M can be expressed as the number of subcarriers in a resource block. For example, when 12 subcarriers are one RB, M can be set to 12. The formula i = k SC / M*K can also be used to calculate the number of the subcarrier band to which the data symbol belongs.

[0121] After determining the number of the subcarrier band to which the reference symbol belongs, all reference symbols contained in the subcarrier band can be determined as target reference symbols based on the number of the subcarrier band to which the reference symbol belongs, and then the noise and interference covariance matrix corresponding to each target reference symbol can be added to the noise and interference covariance matrix of the subcarrier band to which it belongs, so that the noise and interference covariance matrix of each subcarrier band can be determined. For example, according to the formula , to calculate the noise and interference covariance matrix within the subcarrier band; where, can be the expected value of the noise and interference covariance matrix within the subcarrier band numbered i, is the number of reference symbols within subcarrier band i, is the covariance matrix of noise and interference corresponding to the kth reference symbol in subcarrier band i.

[0122] As an example of the present disclosure, when calculating the subcarrier band number corresponding to each reference symbol, for a subcarrier number k SC The reference symbol to which the subcarrier band number is i=k SC / 12*K, and then the subcarrier band number of each reference symbol can be saved, so that the reference symbol contained in the subcarrier can be determined based on the subcarrier band number, that is, the reference symbol corresponding to the subcarrier band number can be determined based on the subcarrier band number. It should be noted that i=k SC The 12 in / 12*K is set based on 12 subcarriers forming one RB, that is, 12 REs (Resource Elements) form one RB.

[0123] By traversing each reference symbol, the corresponding noise and interference covariance matrix can be , added to the noise and interference covariance matrix of the subcarrier band to which it belongs In = + , which is equivalent to For all reference symbols in the subcarrier band The accumulated result. Then, by traversing each subcarrier band i∈0,1,2,…[(n-m+1) / K], the noise and interference covariance matrices corresponding to each subcarrier band are accumulated and summed. Taking the expectation, the formula can be expressed as ,in, It can represent the number of reference symbols contained in the subcarrier band numbered i; is the expected value of the noise and interference covariance matrix corresponding to each subcarrier band. Thus, based on the expected value of the noise and interference covariance matrix corresponding to each subcarrier band, the second noise and interference covariance matrix of the subcarrier band can be determined.

[0124] In a specific implementation, each subcarrier band can be traversed, and the second noise and interference covariance matrix of each subcarrier band can be filtered in the time domain, so as to weight the second noise and interference covariance matrix of the current subcarrier band in the previous time slot and the second noise and interference covariance matrix of the current subcarrier band in the current time slot through time domain filtering, and obtain the covariance matrix of the current time slot as the interference estimation result, thereby improving the accuracy of the interference estimation. Among them, the covariance matrix of the current time slot can represent the covariance matrix of the noise interference calculated.

[0125] It can be seen that this example can flexibly divide the subcarrier band and count the expected values ​​of the noise and interference covariance matrices in the subcarrier band as the noise and interference covariance matrices of the entire subcarrier band, so that time domain filtering can be performed based on the noise and interference covariance matrices of the entire subcarrier band, which solves the problem of low interference estimation accuracy caused by the existing related technology taking one RB as a unit for interference estimation in the frequency domain.

[0126] In summary, the embodiments of the present disclosure can perform time domain filtering on the second noise and interference covariance matrix of each subcarrier band by traversing each subcarrier band, that is, filtering is performed in the time domain, and the accuracy of noise and interference estimation is improved by weighting the second noise and interference covariance matrix of the current subcarrier band in the previous time slot with the second noise and interference covariance matrix of the current subcarrier band in the current time slot. Furthermore, the embodiment of the present disclosure performs time domain filtering based on the second noise and interference covariance matrix of the subcarrier band to obtain the noise and interference covariance matrix of the subcarrier band, including: obtaining the subcarrier band covariance matrix of the current time slot and the subcarrier band covariance matrix of the reference time slot, the subcarrier band covariance matrix of the current time slot is the second noise and interference covariance matrix of the subcarrier band in the previous time slot of the current time slot; and performing weighted processing on the subcarrier band covariance matrix of the current time slot and the subcarrier band covariance matrix of the reference time slot according to a preset time domain filtering coefficient.

[0127] Specifically, the noise and interference covariance matrix of the second subcarrier band in the embodiment of the present disclosure may include the noise and interference covariance matrices of at least two time slot subcarrier bands, such as the current time slot subcarrier band covariance matrix and the reference time slot subcarrier covariance matrix, and the reference time slot subcarrier covariance matrix may be the noise and interference covariance matrix of the subcarrier band of the previous time slot corresponding to the current slot. The embodiment of the present disclosure may perform weighted processing on the subcarrier band covariance matrix of the current time slot and the subcarrier band covariance matrix of the reference time slot based on a preset time domain filter coefficient A to obtain the noise and interference covariance matrix of the current time slot as the noise and interference covariance matrix of the subcarrier band.

[0128] For example, we can use the time domain filtering formula , the noise and interference covariance matrix of the current subcarrier band in the previous time slot is weighted with the noise and interference covariance matrix of the current subcarrier band in the current time slot to obtain the noise and interference covariance matrix of the current time slot as the interference estimation result. Among them, is the covariance matrix of the noise interference within the subcarrier band numbered i in the tth time slot, is the covariance matrix of noise and interference in the subcarrier band numbered i in the t-1th time slot, and A is the time domain filter coefficient as an algorithm parameter. For example, 0.8 can be selected as the time domain filter coefficient A, that is, A=0.8, and this example does not limit this. It can be seen that the time domain filtering in this example also counts the covariance matrix of noise and interference in the time domain, and the distribution characteristics of interference in the time domain are also reflected, thereby improving the accuracy of the calculated covariance matrix of noise and interference.

[0129] It can be seen that the embodiment of the present disclosure divides the time-frequency domain resources of the user terminal into subcarriers according to the resource block information allocated to the user terminal, thereby realizing flexible division of the subcarrier band; and determines the noise and interference covariance matrix of the subcarrier band according to the noise and interference covariance matrix corresponding to the reference symbol contained in the subcarrier band, so as to perform time domain filtering according to the noise and interference covariance matrix of the subcarrier band, and also performs statistics on the covariance matrix of noise and interference in the time domain, so that the distribution characteristics of interference in the time domain are also reflected, that is, filtering processing is performed in the time domain, which not only considers the statistical characteristics in the frequency domain, but also takes into account the statistical characteristics in the time domain, thereby improving the accuracy of the calculated noise interference covariance matrix, that is, improving the accuracy of noise and interference estimation, thereby solving the problem of poor receiver detection performance caused by the low accuracy of the existing interference covariance matrix estimation method.

[0130] Step 230, determining the noise to interference ratio of each subcarrier band.

[0131] Specifically, after determining the noise and interference covariance matrix of the subcarrier band, the embodiment of the present disclosure can be calculated according to the noise and interference covariance matrix of the subcarrier band, such as according to the formula Calculate to calculate the noise to interference ratio NIR within the subcarrier band. Can express request The complex modulus of Represents R uu,i m rows and n columns.

[0132] In actual processing, the noise-to-interference ratio of a subcarrier band may be the ratio of the noise and interference power of the subcarrier band. The disclosed embodiment may calculate the antenna noise-to-interference energy correlation result P1 and the antenna interference correlation result P2 according to the noise and interference covariance matrix of the subcarrier band, so that the ratio of the antenna noise-to-interference energy correlation result P1 to the antenna interference correlation result P2 may be determined as the noise-to-interference ratio NIR of the subcarrier band, that is, NIR= . Among them, the antenna noise interference energy correlation result P1 can represent the sum of the correlation results between the energy of noise and the energy of interference on different antennas, which can be specifically determined according to the elements on the main diagonal in the noise and interference covariance matrix of the subcarrier band; the antenna interference correlation result P2 can represent the sum of the interference cross-correlation results between different antennas, which can be specifically determined according to the elements on the upper right triangle or the lower left triangle (excluding the main diagonal) in the noise and interference covariance matrix of the subcarrier band. Optionally, this embodiment determines the noise-to-interference ratio of each subcarrier band, which may specifically include: for each subcarrier band, determining the ratio of the antenna noise-interference energy correlation result and the antenna interference correlation result as the noise-to-interference ratio, the antenna noise-interference energy correlation result is the sum of the mutual products of the elements on the target diagonal, the target diagonal is the main diagonal of the noise and interference covariance matrix of the subcarrier band, the antenna interference correlation result is the sum of the products of the mutually conjugate elements in the first triangular matrix and the second triangular matrix in the noise and interference covariance matrix of the subcarrier band, and neither the elements of the first triangular matrix nor the elements of the second triangular matrix contain the elements on the main diagonal.

[0133] For example, the noise and interference covariance matrices in the subcarrier band are The upper right triangular elements of are used as the elements of the first triangular matrix of the main embodiment of the present disclosure, and the noise and interference covariance matrix of the subcarrier band is When the lower left triangular elements of are used as the elements of the second triangular matrix of the embodiment of the present disclosure, the formula Calculate the noise and interference covariance matrix for the subcarrier band The sum of the products of the elements on the main diagonal of is taken as the antenna noise interference energy correlation result P1; and it can be calculated according to the formula Calculate the interference covariance matrix The sum of the products of the elements in the upper right triangle or lower left triangle (excluding the main diagonal) of is taken as the antenna interference correlation result P2. Then, according to NIR= , calculate the ratio of the antenna noise interference energy correlation result P1 and the antenna interference correlation result P2 as the noise-to-interference ratio NIR of the subcarrier band, and compare the relationship between the noise and interference ratio NIR of the subcarrier band and the threshold value to determine whether to use the interference suppression ratio combining algorithm IRC or the maximum ratio combining algorithm MRC to invert the noise and interference covariance matrix of the subcarrier band.

[0134] Specifically, the noise-to-interference ratio NIR can be compared with the threshold value, and the maximum ratio combining MRC algorithm or the interference suppression ratio combining algorithm IRC can be selected according to the comparison result, and the noise and interference covariance matrix of the subcarrier band is inverted. If the noise-to-interference ratio NIR of the subcarrier band is greater than the threshold value, step 240 is executed to invert the noise and interference covariance matrix of the subcarrier band according to the maximum ratio combining MRC algorithm; if the noise-to-interference ratio NIR of the subcarrier band is less than the threshold value, the step 250 is jumped to execute to invert the noise and interference covariance matrix of the subcarrier band according to the interference suppression ratio combining IRC algorithm. If the noise-to-interference ratio NIR of the subcarrier band is equal to the threshold value, the interference suppression ratio combining IRC algorithm can be selected to invert the noise and interference covariance matrix of the subcarrier band, and the embodiment of the present disclosure does not impose specific restrictions on this.

[0135] Step 240: If the noise-interference ratio of the subcarrier band is greater than the threshold value, the noise and interference covariance matrix of the subcarrier band is inverted according to the maximum ratio combining (MRC) algorithm to obtain the noise-interference covariance inverse matrix.

[0136] Specifically, when the noise-to-interference ratio NIR of the subcarrier band is greater than the threshold value, the embodiment of the present disclosure can be based on the noise and interference covariance matrix of the subcarrier band The starting point of the MRC merging algorithm is that the maximum ratio combining MRC algorithm treats interference as white noise, so that the correlation value between different interferences can be 0, which greatly reduces the complexity of the inverse algorithm regardless of the number of receiving antennas. For example, when the noise and interference ratio NIR of a certain subcarrier band is greater than the threshold value, for all data symbols in this subcarrier band, the MRC merging algorithm is used to set the non-main diagonal elements of the covariance matrix of noise and interference to 0, that is, the noise and interference covariance matrix of the subcarrier band The non-main diagonal elements of are set to 0, so that the correlation values ​​between different interferences can be 0, which greatly reduces the complexity of the inversion algorithm regardless of the number of receiving antennas.

[0137] Furthermore, for the covariance matrix of noise and interference using the MRC combining algorithm, due to the particularity of the matrix, the inversion can be performed by using the reciprocal method to simplify the amount of calculation. Optionally, the embodiment of the present disclosure inverts the noise and interference covariance matrix of the subcarrier band according to the maximum ratio combining MRC algorithm to obtain the noise-interference covariance inverse matrix, which may specifically include: taking the inverse of each main diagonal element in the noise and interference covariance matrix of the subcarrier band to obtain an inverse matrix as the noise-interference covariance inverse matrix corresponding to the subcarrier band. Specifically, when performing the MRC algorithm, no matter how many receiving antennas there are, the embodiment of the present disclosure directly performs the inversion of the noise and interference covariance matrix of the subcarrier band. By taking the inverse of each main diagonal element of The inverse matrix , so that the inverse matrix can be As the inverse noise interference covariance matrix corresponding to the subcarrier band.

[0138] Step 250: If the noise-interference ratio of the subcarrier band is not greater than the threshold value, the noise and interference covariance matrix of the subcarrier band is inverted according to the interference suppression ratio combined IRC algorithm to obtain the noise-interference covariance inverse matrix.

[0139] Specifically, when the noise-to-interference ratio NIR of the subcarrier band is not greater than the threshold value, the embodiment of the present disclosure can be based on the noise and interference covariance matrix of the subcarrier band. Perform the IRC algorithm. For example, when the noise interference ratio NIR of a certain subcarrier band is not greater than the threshold value, the IRC merging algorithm can be used for all data symbols in this subcarrier band, and different inversion calculations can be performed according to the number of antennas to obtain the corresponding inverse matrix. , as the inverse noise interference covariance matrix corresponding to the subcarrier band.

[0140] It should be noted that for the covariance matrix of noise and interference using the IRC combining algorithm, a general matrix inversion algorithm can be used, such as using the formula method for inversion when the number of antennas is 2, and using the circular labeling method for inversion when the number of antennas is greater than 2, etc. The embodiments of the present disclosure do not impose specific restrictions on this.

[0141] Furthermore, the embodiment of the present disclosure inverts the noise and interference covariance matrix of the subcarrier band according to the interference suppression ratio combined IRC algorithm to obtain the noise-interference covariance inverse matrix, including: determining the number of antennas; if the number of antennas is equal to two, then inverting the noise and interference covariance matrix of the subcarrier band using the determinant inversion method to obtain the corresponding inverse matrix as the noise-interference covariance inverse matrix corresponding to the subcarrier band; if the number of antennas is greater than two, then inverting the noise and interference covariance matrix of the subcarrier band using the cyclic label inversion method to obtain the corresponding inverse matrix as the noise-interference covariance inverse matrix corresponding to the subcarrier band. Among them, the interference suppression ratio combined IRC algorithm can treat interference as colored noise, and the correlation value between different interferences is not 0. Specifically, when performing the interference suppression ratio combined IRC algorithm, if the number of antennas is equal to 2, the determinant inversion method can be used to obtain The inverse matrix ; If the number of antennas is greater than 2, the cyclic labeling inversion method can be used to obtain The inverse matrix .

[0142] It can be seen that the embodiment of the present disclosure can perform different inverse calculations according to different selected algorithms and the number of antennas, and when the noise interference ratio NIR of the subcarrier band is selected to belong to the MRC algorithm, due to The non-main diagonal elements of are set to 0, so that the complexity of the inversion algorithm is greatly reduced regardless of the number of receiving antennas, while also retaining the power of the noise on each receiving antenna (the corresponding feature can be expressed as a matrix The minimum mean square error (MMSE) operation is performed in the form of a signal, so that the received value processing of each antenna in the subsequent equalization operation will be more accurate, that is, the accuracy of the received value processing of each antenna in the subsequent equalization operation is improved.

[0143] Step 260: Acquire a first noise and interference covariance matrix corresponding to the target subcarrier band according to the data symbols.

[0144] Specifically, after extracting the subcarrier band number to which the data symbol belongs, the embodiment of the present disclosure can extract the corresponding noise interference covariance inverse matrix according to the subcarrier band number as the first noise and interference covariance matrix corresponding to the target subcarrier band. The target subcarrier band is the subcarrier band corresponding to the subcarrier band number to which the data symbol belongs.

[0145] Step 270: Perform equalization processing according to the first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal.

[0146] In an embodiment of the present disclosure, the signal to interference plus noise ratio information can be used to determine the signal to interference plus noise ratio and the repair coefficient corresponding to the data symbol. Specifically, the embodiment of the present disclosure can extract the channel estimation value from the channel estimation result for each data symbol in the received data, and extract the receiving antenna signal from the orthogonal frequency division multiplexing OFDM demodulation processing result, so as to perform channel equalization based on the signal to interference plus noise ratio information, the first noise and interference covariance matrix, the channel estimation value and the receiving antenna signal to obtain the signal to interference plus noise ratio information and the first equalized signal, so that the repair coefficient corresponding to the data symbol can be determined based on the signal to interference plus noise ratio information, and the power ratio can be estimated based on the signal to interference plus noise ratio information to obtain the signal to interference plus noise ratio corresponding to the soft bit information.

[0147] Further, the signal to interference and noise ratio information in the embodiment of the present disclosure may include a unit matrix, and the unit matrix may be used to scale the constellation amplitude of the first equalized signal. In order to remove the influence of the unit matrix in the signal to interference and noise ratio information on the constellation amplitude of the final equalization result, the embodiment of the present disclosure may determine a repair coefficient based on the signal to interference and noise ratio information to perform inverse scaling repair on the first equalized signal according to the repair coefficient, such as performing inverse scaling repair on the constellation amplitude of the first equalized signal, so as to perform soft demodulation processing according to the equalized signal generated after the repair, that is, execute step 280.

[0148] As an example of the present disclosure, based on the MIMO receiving model, after whitening the noise and interference, the MMSE receiving formula of the MIMO receiver can be derived according to the minimum mean square error (MMSE) principle. This formula can process the MRC algorithm and the IRC algorithm at the same time, and can be expressed as the MMSE-MRC receiving algorithm and the MMSE-IRC receiving algorithm. For example, the specific calculation formulas of the MMSE-MRC receiving algorithm and the MMSE-IRC receiving algorithm are: ; where Y is dimensional received signal, H is The channel matrix, X is Dimensional transmission signal, is the noise and interference covariance matrix of the subcarrier band where the data symbol is located. I is dimensional identity matrix.

[0149] Specifically, under white noise conditions, according to the MMSE criterion, the equalization formula that can be obtained is ; It should be noted that the equilibrium formula Y can be expressed as dimensional data symbol receiving signal on the antenna, equalization formula H can be expressed as The channel estimation value corresponding to the dimensional data symbol position, for dimensional data symbol channel equalization value, is the noise variance. Equalization formula This is the formula under white noise conditions. When the same-channel interference is taken into account, the equalization formula The derivation based on Gaussian white noise is no longer applicable. Assume that the covariance matrix of noise and interference is , based on the theory of interference whitening, for this model Y = HX + n + I i t f , changes to , the covariance of the noise and interference at this time is obtained ; Where I is the unit matrix, that is, the covariance of noise and interference is the unit matrix. Then, combined with the MMSE criterion, the MMSE equalization formula under interference whitening can be derived as follows: For this formula , if substituted is processed by MRC, it can be considered that MMSE-MRC equalization has been performed; if the If it is processed by IRC, it is considered that MMSE-IRC equalization has been performed. In addition, the MMSE receiving formula can be used to equalize the received data to obtain the equalized signal. Among them, the noise and interference covariance matrix used in the MMSE receiving formula for each received data can be the noise and interference covariance matrix of the subcarrier band where the data symbol is located, so that the formula can be obtained .

[0150] In actual processing, the formula Data symbols at different resource locations can be processed in parallel. Specifically, during the equalization process, the intermediate variables of the calculation process can be As signal-to-interference-noise ratio information, to utilize the intermediate variables of the calculation process According to the formula , calculate the estimated value of the power ratio of the signal to noise and interference at the corresponding position of each data symbol , and the estimated value Determine the signal-to-interference-noise ratio corresponding to the soft bit information so that the estimated value can be used later The soft bits corresponding to the data symbols at different positions are weighted to improve the accuracy of the confidence of the soft bits corresponding to the redundant versions of different HARQ processes. For example, the formula b = b × , using the estimated value Weight the corresponding soft bits; where b represents The M soft bits corresponding to the dimensional data symbol, M is equal to the modulation order.

[0151] It can be seen that this example can be based on the first noise and interference covariance matrix of the subcarrier band The channel estimation value H corresponding to the data symbol is calculated to convert the calculation result into As signal to interference noise ratio information; then according to the signal to interference noise ratio information, the first noise and the interference covariance matrix , the channel estimation value H and the receiving antenna signal Y corresponding to the data symbol are channel equalized to obtain a first equalized signal X1.

[0152] In addition, in the equilibrium process, the intermediate variables of the calculation process can be used Calculate the coefficient of constellation amplitude repair for each symbol, that is, determine the constellation amplitude repair coefficient. For example, the calculation formula of the constellation amplitude repair coefficient can be used , using the real data of the intermediate variable Determine the constellation amplitude repair coefficient , so that the constellation amplitude repair coefficient can be used to perform constellation amplitude repair on the equalized first signal to generate a second equalized signal.

[0153] Step 280, performing soft demodulation processing according to the second equalized signal to obtain soft bit information corresponding to the data symbol, wherein the second equalized signal is an equalized signal generated after inverse scaling and repairing the first equalized signal according to the repair coefficient.

[0154] Step 290: weight the soft bit information according to the target signal to interference and noise ratio to obtain weighted confidence information.

[0155] Among them, the target signal to interference and noise ratio is the signal to interference and noise ratio corresponding to the soft bit information. Specifically, the larger the signal to interference and noise ratio corresponding to the soft bit information calculated in the channel equalization process, the greater the confidence of the LLR corresponding to the position should be. At the same time, because the 5G-NR uplink PUSCH protocol stipulates the processing of the HARQ process, for data of different redundant versions of the same HARQ process, soft information merging is required. When merging, considering that the data of different redundant versions are inconsistent in transmission time, the two have different signal to noise ratios. If the soft information can be weighted, more performance gains can be obtained in the soft decoding link, and the performance of HARQ merging can be improved, thereby reducing the bit error rate and improving the system throughput. The embodiment of the present disclosure weights the signal to interference and noise ratio of the soft bit information after soft demodulation, such as according to formula b m =b m × , m = 0, 1, ..., M-1, using the estimated value of the power ratio of the signal to the noise and interference The soft bit information after soft demodulation is weighted to obtain weighted confidence information, thereby improving the accuracy of the confidence of the soft bits corresponding to the redundant versions of different HARQ processes. m express The m-th soft bit corresponding to the m-dimensional data symbol, the value of M is equal to the modulation order.

[0156] As an example of the present disclosure, in order to obtain more useful results from the noise and interference covariance matrix and the channel estimation result, it is possible to calculate The specific formula , estimate the power ratio of the signal to interference and noise corresponding to each data symbol position , as the signal-to-interference-noise ratio corresponding to the soft bit information, so that the soft bit information after soft demodulation can be subsequently Weighted.

[0157] In actual processing, the soft demodulation formula under Gaussian white noise conditions is: , where B i,v yes The confidence level of the probability that the i-th bit of the received signal at the v-th layer of the corresponding transmitted signal is 0. and Respectively represent the vector sets of 1 and 0 of the i-th bit of the transmitted symbol of the v-th layer. Different modulation modes have different sets. is the noise variance. However, the soft demodulation formula This is based on the inference under Gaussian white noise environment. In the case of interference (i.e. colored noise), the above soft demodulation formula is no longer satisfied. Since the noise and interference whitening technology is used in the embodiment of the present disclosure, the interference is changed from colored noise to white noise, and the noise variance is , that is, the channel equalization output of the embodiment of the present disclosure can be considered as the output under the white noise link, and its corresponding soft demodulation formula is: Compared with the derivation of Gaussian white noise, it is more consistent with the statistical characteristics of soft demodulation under the condition of co-channel interference, and does not require division, that is, it does not need to be divided by the signal-to-noise ratio in the soft demodulation link.

[0158] In summary, the equalization formula in the embodiment of the present disclosure is the same for both the MRC merging algorithm and the IRC merging algorithm, achieving formal unification, making the channel equalization module design simpler. In addition, the equalization formula in the embodiment of the present disclosure is derived based on the interference and noise whitening theory. In the presence of interference, the starting point is more consistent with theory and practice, and the division operation in the soft demodulation process is reduced, thereby improving the soft demodulation efficiency.

[0159] It should be noted that, for the purpose of simple description, the method embodiments are expressed as a series of action combinations, but those skilled in the art should know that the embodiments of the present disclosure are not limited to the described order of actions, because according to the embodiments of the present disclosure, certain steps may be performed in other orders or simultaneously.

[0160] Reference Figure 4 , shows a block diagram of a linear equalization device provided by an embodiment of the present disclosure. The linear equalization device 400 may include the following modules:

[0161] A covariance matrix acquisition module 410 is used to acquire a first noise and interference covariance matrix corresponding to a target subcarrier band according to a data symbol, wherein the target subcarrier band is a subcarrier band corresponding to a subcarrier band number to which the data symbol belongs;

[0162] An equalization processing module 420 is used to perform equalization processing according to a first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal;

[0163] an inverse scaling and repairing module 430, configured to perform inverse scaling and repairing on the first equalized signal according to a repair coefficient to generate a second equalized signal, wherein the repair coefficient is a coefficient determined according to the signal to interference and noise ratio information;

[0164] The soft demodulation processing module 440 is used to perform soft demodulation processing according to the second equalized signal to obtain soft bit information corresponding to the data symbol.

[0165] Optionally, the equalization processing module 420 may include the following submodules:

[0166] a calculation submodule, configured to perform calculation based on the first noise and interference covariance matrix and the channel estimation value corresponding to the data symbol, so as to use the calculation result as the signal to interference plus noise ratio information;

[0167] A channel equalization submodule is used to perform channel equalization according to the signal to interference plus noise ratio information, the first noise and interference covariance matrix, the channel estimation value, and the receiving antenna signal corresponding to the data symbol to obtain the first equalized signal.

[0168] Optionally, the signal to interference and noise ratio information in the embodiment of the present disclosure is used to scale the constellation amplitude of the first equalized signal, and the above-mentioned linear equalization device also includes a repair coefficient determination module, which is used to determine the repair coefficient based on the real part data of the signal to interference and noise ratio information.

[0169] Optionally, based on the above embodiments, the interference estimation device provided by the embodiments of the present disclosure may also include: other modules, such as an extraction module, a power ratio estimation module, a weighted processing module, etc., which are not limited by the embodiments of the present disclosure. Among them, the extraction module is used to extract the channel estimation value from the channel estimation result for each data symbol in the received data, and extract the receiving antenna signal from the orthogonal frequency division multiplexing OFDM demodulation processing result; the power ratio estimation module is used to perform power ratio estimation based on the signal to interference noise ratio information to obtain the target signal to interference noise ratio; the weighted processing is used to perform weighted processing on the soft bit information based on the target signal to interference noise ratio to obtain the weighted confidence information.

[0170] Optionally, the covariance matrix acquisition module 410 may include the following submodules:

[0171] A subcarrier band number extraction submodule, used to extract the subcarrier band number to which the data symbol belongs;

[0172] The noise interference covariance inverse matrix extraction submodule is used to extract the corresponding noise interference covariance inverse matrix according to the subcarrier band number to serve as the first noise and interference covariance matrix.

[0173] Optionally, the subcarrier band number is a subcarrier band number, and the linear equalization device 400 further includes:

[0174] A noise-to-interference ratio determination module, used to determine the noise-to-interference ratio of each subcarrier band;

[0175] A first inversion processing module is used to perform inversion processing on the noise and interference covariance matrix of the subcarrier band according to the maximum ratio combining (MRC) algorithm when the noise-to-interference ratio of the subcarrier band is greater than the threshold value, so as to obtain the noise-to-interference covariance inverse matrix;

[0176] The second inversion processing module is used to perform inversion processing on the noise and interference covariance matrix of the subcarrier band according to the interference suppression ratio merging IRC algorithm when the noise-interference ratio of the subcarrier band is not greater than the threshold value, so as to obtain the noise-interference covariance inverse matrix.

[0177] Optionally, the first inversion processing module is specifically used to: calculate the inverse of each main diagonal element in the noise and interference covariance matrix of the subcarrier band to obtain the inverse matrix of the noise and interference covariance matrix as the noise interference covariance inverse matrix corresponding to the subcarrier band.

[0178] Optionally, the second inversion processing module is specifically used to: determine the number of antennas; if the number of antennas is equal to two, then use the determinant inversion method to invert the noise and interference covariance matrix of the subcarrier band to obtain the corresponding inverse matrix, which is used as the noise interference covariance inverse matrix corresponding to the subcarrier band; if the number of antennas is greater than two, then use the cyclic label inversion method to invert the noise and interference covariance matrix of the subcarrier band to obtain the corresponding inverse matrix, which is used as the noise interference covariance inverse matrix corresponding to the subcarrier band.

[0179] Optionally, the noise-interference ratio determination module is specifically used to: for each subcarrier band, determine the ratio of the antenna noise interference energy correlation result and the antenna interference correlation result as the noise-interference ratio, the antenna noise interference energy correlation result is the sum of the mutual products of the elements on the target diagonal, the target diagonal is the main diagonal of the noise and interference covariance matrix of the subcarrier band, the antenna interference correlation result is the sum of the products of the mutually conjugate elements in the first triangular matrix and the second triangular matrix in the noise and interference covariance matrix of the subcarrier band, and neither the elements of the first triangular matrix nor the elements of the second triangular matrix contain the elements on the main diagonal.

[0180] Optionally, the linear equalizer device further includes:

[0181] A subcarrier division module, configured to perform subcarrier division on the time-frequency domain resources of the user terminal according to the resource block information allocated to the user terminal, so as to obtain at least two subcarrier bands;

[0182] The subcarrier band covariance matrix determination module is used to determine the noise and interference covariance matrix of the subcarrier band according to the noise and interference covariance matrix corresponding to the target reference symbol, and the target reference symbol is a reference symbol included in the subcarrier band.

[0183] Optionally, the resource block information in the embodiment of the present disclosure may include resource block size information and resource block position information, and the subcarrier division module may include the following sub-modules:

[0184] A resource block information acquisition submodule, used to acquire the resource block size information and resource block location information allocated to the user terminal;

[0185] The subcarrier division submodule is used to subcarrier divide the time-frequency domain resources of the user terminal according to the number of subcarrier resource blocks based on the resource block size information and the resource block position information, so as to obtain at least two subcarrier bands, and the number of subcarrier resource blocks is the number of resource blocks within a preset frequency domain bandwidth.

[0186] Optionally, the subcarrier band covariance matrix determination module may include the following submodules:

[0187] a target reference symbol determination submodule, configured to determine a target reference symbol belonging to the subcarrier band based on a subcarrier band number, wherein the subcarrier band number of the subcarrier band to which the target reference symbol belongs is related to the subcarrier number of the target reference symbol;

[0188] An accumulation processing submodule, used for accumulating the noise and interference covariance matrix corresponding to the target reference symbol in the subcarrier band to obtain a second noise and interference covariance matrix of the subcarrier band;

[0189] The time domain filtering submodule is used to perform time domain filtering according to the second noise and interference covariance matrix of the subcarrier band to obtain the noise and interference covariance matrix of the subcarrier band.

[0190] Optionally, the time domain filtering submodule is specifically used to: obtain the subcarrier band covariance matrix of the current time slot and the subcarrier band covariance matrix of the reference time slot, the subcarrier band covariance matrix of the current time slot is the second noise and interference covariance matrix of the subcarrier band in the current time slot, and the subcarrier band covariance matrix of the reference time slot is the second noise and interference covariance matrix of the subcarrier band in the previous time slot of the current time slot; and perform weighted processing on the subcarrier band covariance matrix of the current time slot and the subcarrier band covariance matrix of the reference time slot according to a preset time domain filtering coefficient.

[0191] It should be noted that the linear equalization device 400 provided above can execute the linear equalization method provided by any embodiment of the present invention, and has the corresponding functions and beneficial effects of the execution method.

[0192] In a specific implementation, the linear equalization device 400 can be integrated into a device, so that the device can be used as a linear equalization device. Figure 5 As shown, an embodiment of the present disclosure provides a linear equalization device, including a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other through the communication bus 114, and the memory 113 is used to store computer programs; the processor 111 is used to implement the steps of the linear equalization method provided by any of the aforementioned method embodiments when executing the program stored in the memory 113.

[0193] The embodiment of the present disclosure further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the linear equalization method provided in any of the aforementioned method embodiments are implemented.

[0194] It should be noted that, for the device, equipment, and storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0195] In this article, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0196] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A linear equalization method, characterized in that: include: Acquire a first noise and interference covariance matrix corresponding to a target subcarrier band according to the data symbol, wherein the target subcarrier band is a subcarrier band corresponding to a subcarrier band number to which the data symbol belongs; Performing equalization processing on the data symbol according to a first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal; Performing inverse scaling repair on the first equalized signal according to a repair coefficient to generate a second equalized signal, wherein the repair coefficient is a coefficient determined according to the signal to interference noise ratio information; Performing soft demodulation processing according to the second equalized signal to obtain soft bit information corresponding to the data symbol; The equalizing the data symbol according to the first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal includes: performing calculation based on the first noise and interference covariance matrix and the channel estimation value corresponding to the data symbol, so as to use the calculation result as the signal to interference plus noise ratio information; Performing channel equalization on the receiving antenna signal corresponding to the data symbol according to the signal to interference plus noise ratio information, the first noise and interference covariance matrix, and the channel estimation value to obtain the first equalized signal; The step of obtaining a first noise and interference covariance matrix corresponding to a target subcarrier band according to data symbols includes: Extracting the subcarrier band number to which the data symbol belongs; A corresponding noise and interference covariance inverse matrix is ​​extracted according to the subcarrier band number to serve as the first noise and interference covariance matrix.

2. The linear equalization method according to claim 1, characterized in that: The signal to interference noise ratio information is used to scale the constellation amplitude of the first equalized signal, and before the inverse scaling and repairing of the first equalized signal according to the repair coefficient, the method further includes: The repair coefficient is determined based on real data of the signal to interference plus noise ratio information.

3. The linear equalization method according to claim 1, characterized in that: After obtaining the signal to interference noise ratio information and the first equalized signal, the method further includes: Estimating a power ratio according to the signal to interference plus noise ratio information to obtain a target signal to interference plus noise ratio; The soft bit information is weighted according to the target signal to interference plus noise ratio to obtain weighted confidence information.

4. The linear equalization method according to claim 1, characterized in that: The subcarrier band number is the number of the subcarrier band, and before obtaining the first noise and interference covariance matrix corresponding to the target subcarrier band according to the data symbol, the method further includes: Determining a noise-to-interference ratio for each subcarrier band; If the noise-to-interference ratio of the subcarrier band is greater than the threshold value, the noise and interference covariance matrix of the subcarrier band is inverted according to the maximum ratio combining (MRC) algorithm to obtain the noise-to-interference covariance inverse matrix; If the noise-interference ratio of the subcarrier band is not greater than the threshold value, the noise and interference covariance matrix of the subcarrier band is inverted according to the interference suppression ratio combining IRC algorithm to obtain the noise-interference covariance inverse matrix.

5. The linear equalization method according to claim 4, characterized in that: The inverse processing of the noise and interference covariance matrix of the subcarrier band according to the maximum ratio combining (MRC) algorithm to obtain the noise interference covariance inverse matrix includes: The inverse of each main diagonal element in the noise and interference covariance matrix of the subcarrier band is obtained to obtain an inverse matrix as the noise interference covariance inverse matrix corresponding to the subcarrier band.

6. The linear equalization method according to claim 4, characterized in that: The inverse processing of the noise and interference covariance matrix of the subcarrier band according to the interference suppression ratio combined IRC algorithm to obtain the noise interference covariance inverse matrix includes: Determine the number of antennas; If the number of antennas is equal to two, the noise and interference covariance matrix of the subcarrier band is inverted by using a determinant inversion method to obtain a corresponding inverse matrix as an inverse noise interference covariance matrix corresponding to the subcarrier band; If the number of antennas is greater than two, the noise and interference covariance matrix of the subcarrier band is inverted using a cyclic label inversion method to obtain a corresponding inverse matrix as the noise interference covariance inverse matrix corresponding to the subcarrier band.

7. The linear equalization method according to claim 4, characterized in that: The determining of the noise-to-interference ratio value of each subcarrier band includes: For each subcarrier band, the ratio of the antenna noise interference energy correlation result and the antenna interference correlation result is determined as the noise interference ratio, the antenna noise interference energy correlation result is the sum of the mutual products of the elements on the target diagonal, the target diagonal is the main diagonal of the noise and interference covariance matrix of the subcarrier band, the antenna interference correlation result is the sum of the products of the mutually conjugate elements in the first triangular matrix and the second triangular matrix in the noise and interference covariance matrix of the subcarrier band, and the elements of the first triangular matrix and the elements of the second triangular matrix do not contain the elements on the main diagonal.

8. The linear equalization method according to claim 7, characterized in that: Before determining the noise-to-interference ratio value of each subcarrier band, the method further includes: According to the resource block information allocated to the user terminal, subcarrier division is performed on the time-frequency domain resources of the user terminal to obtain at least two subcarrier bands; The noise and interference covariance matrix of the subcarrier band is determined according to the noise and interference covariance matrix corresponding to the target reference symbol, and the target reference symbol is a reference symbol included in the subcarrier band.

9. A linear equalizer device, characterized in that: include: A covariance matrix acquisition module, used to acquire a first noise and interference covariance matrix corresponding to a target subcarrier band according to a data symbol, wherein the target subcarrier band is a subcarrier band corresponding to a subcarrier band number to which the data symbol belongs; The step of obtaining a first noise and interference covariance matrix corresponding to a target subcarrier band according to data symbols includes: Extracting the subcarrier band number to which the data symbol belongs; Extracting a corresponding noise and interference covariance inverse matrix according to the subcarrier band number to serve as the first noise and interference covariance matrix; An equalization processing module is used to perform equalization processing according to a first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal; the equalization processing of the data symbol according to the first noise and interference covariance matrix corresponding to the target subcarrier band to obtain signal-to-interference-noise ratio information and a first equalized signal includes: performing calculation based on the first noise and interference covariance matrix and the channel estimation value corresponding to the data symbol, so as to use the calculation result as the signal to interference plus noise ratio information; Performing channel equalization on the receiving antenna signal corresponding to the data symbol according to the signal to interference plus noise ratio information, the first noise and interference covariance matrix, and the channel estimation value to obtain the first equalized signal; an inverse scaling and repairing module, configured to perform inverse scaling and repairing on the first equalized signal according to a repair coefficient to generate a second equalized signal, wherein the repair coefficient is a coefficient determined according to the signal to interference noise ratio information; The soft demodulation processing module is used to perform soft demodulation processing according to the second equalized signal to obtain soft bit information corresponding to the data symbol.

10. A communication device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, used to implement the steps of the linear equalization method described in any one of claims 1 to 8 when executing a program stored in a memory.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the linear equalization method according to any one of claims 1 to 8 are implemented.

Images