Signal processing method and device, electronic equipment, chip and storage medium

Abstract

The invention provides a signal processing method and device, electronic equipment, a chip and a storage medium, and relates to the field of communication, and the method comprises the steps: determining an initial noise correlation matrix of a plurality of sub-bands in a bandwidth occupied by a received signal; determining a target noise correlation matrix of the plurality of sub-bands according to the difference degree between the initial noise correlation matrixes of the plurality of sub-bands; and performing interference suppression on the received signal according to the target noise correlation matrix of the plurality of sub-bands to obtain a demodulation signal. Therefore, whether sub-band interference exists among the plurality of sub-bands can be judged based on the difference degree among the initial noise correlation matrixes of the plurality of sub-bands, the final target noise correlation matrix corresponding to the plurality of sub-bands is determined in a targeted manner based on the judgment result, and the target noise correlation matrix corresponding to the plurality of sub-bands is determined based on the target noise correlation matrix of the plurality of sub-bands. Interference suppression is carried out on the received signal, the interference suppression effect of the signal can be improved, the signal demodulation capability of the receiving equipment is improved, and the method can be suitable for variable channel environments.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a signal processing method, device, electronic device, chip and storage medium. Background Art

[0002] In an actual Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system, the presence of interference has a significant impact on the received signal at the receiving end. Therefore, it is necessary to adopt effective channel equalization technology to suppress interference and improve the performance of the MIMO-OFDM system.

[0003] In the related art, when the receiving end includes only one receiving antenna, the noise correlation matrix of multiple sub-bands within the bandwidth occupied by the receiving signal received by the receiving antenna degenerates into a scalar, and the demodulation method of the received signal is: taking the average of the estimated values ​​of the noise correlation matrix within the multiple sub-bands as the estimated value of the noise correlation matrix within the bandwidth occupied by the receiving signal, and demodulating the received signal based on the estimated value of the noise correlation matrix within the bandwidth.

[0004] However, the method of demodulating the received signal based on the estimated value of the noise correlation matrix within the entire bandwidth or frequency band cannot adapt to the changing channel environment. Summary of the invention

[0005] The present application aims to solve one of the technical problems in the related art at least to some extent.

[0006] To this end, the present application proposes a signal processing method, device, electronic device, chip and storage medium.

[0007] In one aspect, an embodiment of the present application provides a signal processing method, including:

[0008] determining an initial noise correlation matrix for a plurality of sub-bands within a bandwidth occupied by a received signal;

[0009] Determining target noise correlation matrices of the multiple sub-bands according to the degree of difference between the initial noise correlation matrices of the multiple sub-bands;

[0010] Interference suppression is performed on the received signal according to the target noise correlation matrices of the multiple sub-bands to obtain a demodulated signal.

[0011] Another aspect of the present application provides a signal processing device, including:

[0012] A first determination module is used to determine the initial noise correlation matrix of multiple sub-bands within the bandwidth occupied by the received signal;

[0013] A second determination module, configured to determine target noise correlation matrices of the multiple sub-bands according to the degree of difference between the initial noise correlation matrices of the multiple sub-bands;

[0014] The suppression module is used to perform interference suppression on the received signal according to the target noise correlation matrix of the multiple sub-bands to obtain a demodulated signal.

[0015] Another aspect of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the signal processing method as described in the aforementioned aspect is implemented.

[0016] Another aspect of the present application provides a chip, which includes an interface circuit and a processing circuit coupled to each other, wherein the interface circuit is used to input or output a signal, and the processing circuit is configured to execute the signal processing method as described in the aforementioned aspect.

[0017] Another aspect of the present application provides a non-temporary computer-readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the signal processing method as described in the aforementioned aspect.

[0018] Another aspect of the present application provides a computer program product on which a computer program is stored. When the program is executed by a processor, the signal processing method as described in the above aspect is implemented.

[0019] The signal processing method, device, electronic device, chip and storage medium proposed in the present application judge whether there is sub-band interference between multiple sub-bands based on the degree of difference between the initial noise correlation matrices of multiple sub-bands, and based on the judgment result, specifically determine the target noise correlation matrix that the multiple sub-bands ultimately correspond to, and based on the target noise correlation matrix of the multiple sub-bands, perform interference suppression on the received signal, which can improve the interference suppression effect of the signal and enhance the signal demodulation capability of the receiving device, and can be applicable to a variable channel environment.

[0020] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0022] Figure 1Schematic diagram of sub-band interference;

[0023] Figure 2 A flowchart of a first signal processing method provided in an embodiment of the present application;

[0024] Figure 3 A schematic diagram of a flow chart of a second signal processing method provided in an embodiment of the present application;

[0025] Figure 4 A schematic diagram of a flow chart of a third signal processing method provided in an embodiment of the present application;

[0026] Figure 5 A flowchart of a fourth signal processing method provided in an embodiment of the present application;

[0027] Figure 6 A schematic diagram of a specific implementation of an embodiment of the present application;

[0028] Figure 7 A schematic diagram of the structure of a signal processing device provided in an embodiment of the present application;

[0029] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0030] Fig. 9 It is a schematic diagram of the structure of a chip proposed in an embodiment of the present application. DETAILED DESCRIPTION

[0031] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0032] In actual MIMO-OFDM systems, the presence of interference greatly affects the received signal at the receiving end. Therefore, it is necessary to adopt effective channel equalization technology to suppress interference and improve the performance of MIMO-OFDM systems. Among them, channel equalization technology is divided into nonlinear reception and linear reception. Nonlinear reception algorithms can provide excellent performance, but their computational complexity is too large, which will increase the power loss and processing time required by the receiving end. Compared with nonlinear reception algorithms, linear reception algorithms can provide better performance and have lower complexity.

[0033] Some typical linear reception algorithms, such as the Maximum Ratio Combining (MRC) algorithm and the Interference Rejection Combining (IRC) algorithm, are widely used. Among them, the IRC algorithm is widely used in scenarios with large interference because it can suppress interference and provide better performance.

[0034] In an actual wireless communication environment, there are often multiple interference sources, which results in the interference on the receiving antenna being inevitably correlated. Therefore, interference elimination processing is required when performing channel equalization / antenna merging.

[0035] In a single-carrier system with flat Rayleigh fading, a single data stream arrives at a receiving end with n antennas. The received signal at the receiving end can be expressed as:

[0036] Y=Hx+N;(1)

[0037] Where x represents the transmitted signal vector, Y represents the received signal vector, H represents the channel matrix or channel vector, and N represents the noise vector. The receiving end can combine the factors W H , to suppress the interference of the received signal and obtain the suppressed signal (i.e., the demodulated signal), where the suppressed signal (i.e., the demodulated signal) can be expressed as:

[0038]

[0039] When there is colored interference on multiple antennas at the receiving end, the correlation matrix of the noise vectors between the antennas (referred to as the noise correlation matrix) is not a diagonal matrix, that is, the noise correlation matrix can be expressed as:

[0040]

[0041] The H in the upper right corner of N represents the conjugate transpose of the matrix.

[0042] At this time, the optimal receiving solution is to maximize the output signal-to-noise ratio:

[0043]

[0044] In ensuring W H Under the restriction of H = 1, the merging factor W is obtained H for:

[0045]

[0046] The combining algorithm of the above formula (5) is called the interference rejection combining (IRC) algorithm, where: The function is to whiten the channel matrix H and the received signal Y, remove the correlation between antennas and standardize the noise.

[0047] When the receiving end includes only one antenna, the noise correlation matrix of the antenna degenerates into a scalar:

[0048]

[0049] When the interference is sub-band interference, that is, the interference strength between different sub-bands in the frequency domain is inconsistent, such as Figure 1 As shown, the interference intensity of subband 2 is greater, resulting in the noise correlation matrix of subband 1 <Noise correlation matrix for subband 2 If the mean of the estimated values ​​of the noise correlation matrix in multiple sub-bands is used as the noise correlation matrix of the antenna To suppress the interference of the received signal, it will result in the estimated value of the noise correlation matrix when receiving sub-band 1 and sub-band 2. Same as true value The difference is too large, which makes it impossible to maximize the output signal-to-noise ratio. If the estimated value of the noise correlation matrix of each subband is used Interference suppression is performed on the received signal. In the scenario of no interference or similar interference strength between sub-bands, the estimated value of the noise correlation matrix is ​​too small due to too few sampling points. Same as true value The phase difference is too large to maximize the output signal-to-noise ratio.

[0050] That is, in the relevant technology, when calculating the noise correlation matrix, a wider frequency band is generally used for averaging to obtain a more accurate R NN The estimated value of this method is poor in signal demodulation under sub-band interference environment. Another method uses a narrower frequency band range for averaging to obtain the R of each sub-band. NN Although the estimated value avoids the performance loss under sub-band interference, due to the estimated R NN The number of sampling points used is reduced compared to the real R NN The error increases, resulting in poor signal demodulation effect in an interference-free environment.

[0051] In response to at least one of the above-mentioned problems, the present application proposes a signal processing method, device, electronic device, chip and storage medium.

[0052] The signal processing method, device, electronic device, chip and storage medium of the embodiments of the present application are described below with reference to the accompanying drawings.

[0053] Figure 2 A flowchart of the first signal processing method provided in an embodiment of the present application.

[0054] The signal processing method of the embodiment of the present application can be applied to a receiving device (or referred to as a receiving end), wherein the receiving device can be a personal computer, a terminal, a network device, etc.

[0055] In any embodiment of the present application, the signal processing method can be executed by a chip, and the chip can be integrated into the receiving device. Among them, the chip includes a central processing unit (CPU), an image signal processing (ISP), an application-specific integrated circuit (ASIC), a microprocessor (DSP), a field programmable gate array (FPGA), a system on a chip (SOC), a reduced instruction set computer (RISC), etc., which are not listed one by one this time.

[0056] Among them, the terminal is an entity on the user side for receiving or transmitting signals, such as a mobile phone. The terminal can also be called a terminal device (terminal), user equipment (UE for short), mobile station (MS for short), mobile terminal device (MT for short), etc. The terminal can be a car with communication function, a smart car, a mobile phone, a wearable device, a tablet computer (Pad), a computer with wireless transceiver function, a virtual reality (VR for short) terminal, an augmented reality (AR for short) terminal, a wireless terminal in industrial control (industrial control), a wireless terminal in self-driving, a wireless terminal in remote medical surgery, a wireless terminal in smart grid (smart grid), a wireless terminal in transportation safety (transportation safety), a wireless terminal in smart city (smart city), a wireless terminal in smart home (smart home), etc. The embodiments of the present application do not limit the specific technology and specific device form adopted by the terminal.

[0057] Among them, the network device is an entity on the network side for transmitting or receiving signals. For example, the network device can be an evolved NodeB (eNB for short), a transmission reception point (TRP for short), a next generation NodeB (gNB for short) in a 5G new radio (NR for short), a base station in other future mobile communication systems, or an access node in a wireless fidelity (WiFi for short) system, etc. The embodiments of the present application do not limit the specific technology and specific device form adopted by the network device. The network device provided in the embodiments of the present application may be composed of a centralized unit (CU for short) and a distributed unit (DU for short), wherein the CU may also be referred to as a control unit. The CU-DU structure may be used to split the protocol layer of the network device, such as the base station, and the functions of some protocol layers are placed in the CU for centralized control, and the functions of the remaining part or all of the protocol layers are distributed in the DU, and the DU is centrally controlled by the CU.

[0058] like Figure 2 As shown, the signal processing method may include the following steps S201 to S203:

[0059] Step S201, determining initial noise correlation matrices of multiple sub-bands within a bandwidth occupied by a received signal.

[0060] The noise correlation matrix refers to a matrix used to describe the correlation between noises in each sub-band, which reflects whether the noises in different sub-bands are independent of each other or correlated.

[0061] In any embodiment of the present application, the number n of subbands in the bandwidth occupied by the received signal can be set according to the application scenario. Exemplarily, the value of n can be 2 or 3.

[0062] In an embodiment of the present application, the bandwidth occupied by the received signal can be divided according to n to obtain multiple sub-bands, and based on the noise estimation value of the sampling point in each sub-band, the estimated value of the noise correlation matrix of each sub-band is calculated, which is recorded as the initial noise correlation matrix in the present application.

[0063] Step S202: determining target noise correlation matrices of the multiple sub-bands according to the degree of difference between the initial noise correlation matrices of the multiple sub-bands.

[0064] The degree of difference can be represented by a ratio, a difference, the absolute value of the difference, etc.

[0065] In an embodiment of the present application, the degree of difference between the initial noise correlation matrices of multiple subbands can be calculated, and based on the degree of difference between the initial noise correlation matrices of the multiple subbands, it can be determined whether subband interference exists between the multiple subbands. For example, when the degree of difference is relatively large, it is determined that subband interference exists between the multiple subbands, and when the degree of difference is relatively small, it is determined that no subband interference exists between the multiple subbands.

[0066] In the present application, the target noise correlation matrix ultimately corresponding to the multiple sub-bands may be determined specifically according to the result of judging whether there is sub-band interference between the multiple sub-bands.

[0067] Step S203: performing interference suppression on the received signal according to the target noise correlation matrices of the multiple sub-bands to obtain a demodulated signal.

[0068] In the embodiment of the present application, interference suppression can be performed on the received signal according to the target noise correlation matrix of multiple sub-bands to obtain a demodulated signal. That is, according to the target noise correlation matrix of multiple sub-bands, the entire frequency band of the received signal is split and interference suppression reception is performed separately to improve the overall demodulation performance of the receiving device.

[0069] The signal processing method of the embodiment of the present application can determine whether there is sub-band interference between multiple sub-bands based on the degree of difference between the initial noise correlation matrices of multiple sub-bands, and based on the judgment result, specifically determine the target noise correlation matrix that the multiple sub-bands ultimately correspond to, and based on the target noise correlation matrix of the multiple sub-bands, perform interference suppression on the received signal, which can improve the interference suppression effect of the signal, enhance the signal demodulation capability of the receiving device, and can be applicable to a variable channel environment.

[0070] The present application embodiment provides another signal processing method. Figure 3 A flowchart of a second signal processing method provided in an embodiment of the present application.

[0071] It should be noted that the signal processing method can be executed alone, or it can be executed in combination with any embodiment of the present application or a possible implementation method in the embodiment, or it can be executed in combination with any technical solution in the related technology, and the embodiments of the present application are not limited to this.

[0072] like Figure 3 As shown, the signal processing method may include the following steps S301 to S304:

[0073] Step S301: determining initial noise correlation matrices of multiple sub-bands within a bandwidth occupied by a received signal.

[0074] Step S302: determining the degree of difference between the initial noise correlation matrices of the multiple sub-bands.

[0075] The explanation of steps S301 to S302 can be found in the relevant description in any embodiment of the present application and will not be repeated here.

[0076] Step S303: determining target noise correlation matrices of multiple sub-bands according to the magnitude relationship between the difference degree and the difference threshold.

[0077] In any embodiment of the present application, the difference threshold (threshold, thr for short) is related to the difference type (such as ratio, difference, absolute value of difference, etc.) to which the difference degree belongs, that is, the difference threshold is determined according to the difference type to which the difference degree belongs. It should be understood that the difference threshold may be different when the difference type is different. Exemplarily, when the difference type is the absolute value of the difference, the difference threshold may be thr1, and when the difference type is the ratio, the difference threshold may be thr2.

[0078] In the embodiment of the present application, the target noise correlation matrix of the multiple sub-bands may be determined according to the size relationship between the difference degree and the difference threshold.

[0079] As an example, when the difference between the initial noise correlation matrices of any two subbands is higher than the difference threshold, it indicates that subband interference exists between multiple subbands. At this time, in order to improve the output signal-to-noise ratio of each subband, the initial noise correlation matrix of each subband can be used as the target noise correlation matrix of the corresponding subband.

[0080] As another example, when the degree of difference between the initial noise correlation matrices of multiple subbands is not higher than the difference threshold, it indicates that there is no subband interference between the multiple subbands. At this time, the average of the initial noise correlation matrices of the multiple subbands can be used as the target noise correlation matrix of the multiple subbands.

[0081] For example, the number of sub-bands is 2, and the difference degree is represented by a ratio. The initial noise correlation matrices of the two sub-bands are marked as and The difference threshold is thr, then the following formula can be used to calculate the target noise correlation matrix of the i-th (i=1,2) subband:

[0082]

[0083] For example, the number of sub-bands is 3, and the degree of difference is represented by a ratio. The initial noise correlation matrices of the three sub-bands are marked as and The difference threshold is thr, then the following formula can be used to calculate the target noise correlation matrix of the i-th (i=1, 2, 3) subband:

[0084]

[0085] Step S304: performing interference suppression on the received signal according to the target noise correlation matrices of the multiple sub-bands to obtain a demodulated signal.

[0086] For the explanation of step S304, please refer to the relevant description in any embodiment of the present application, which will not be repeated here.

[0087] In the signal processing method of the embodiment of the present application, when the difference between the initial noise correlation matrices of multiple subbands is relatively large, it indicates that the interference distribution of the current channel environment is uneven. At this time, interference suppression can be performed based on the initial noise correlation matrices of each subband. When the difference between the initial noise correlation matrices of multiple subbands is relatively small, it indicates that the interference distribution of the current channel environment is relatively uniform. At this time, the initial noise correlation matrices of each subband can be further merged to obtain a more accurate estimate of the noise correlation matrix (referred to as the target noise correlation matrix in this application). Interference suppression of the received signal is performed based on the target noise correlation matrix of each subband, which can improve the signal demodulation capability of the receiving device.

[0088] The present application embodiment provides another signal processing method. Figure 4 A flowchart of a third signal processing method provided in an embodiment of the present application.

[0089] It should be noted that the signal processing method can be executed alone, or it can be executed in combination with any embodiment of the present application or a possible implementation method in the embodiment, or it can be executed in combination with any technical solution in the related technology, and the embodiments of the present application are not limited to this.

[0090] like Figure 4 As shown, the signal processing method may include the following steps S401 to S404:

[0091] Step S401: for any sub-band among a plurality of sub-bands within a bandwidth occupied by a received signal, determine noise estimation values ​​of a plurality of sampling points of the received signal within any sub-band.

[0092] In any embodiment of the present application, the received signal may be received by a single antenna of a receiving device, wherein, when the receiving device includes only one receiving antenna, the noise correlation matrix within the subband degenerates into a scalar σ 2 .

[0093] In the embodiment of the present application, for any sub-band in the multiple sub-bands within the bandwidth occupied by the received signal, the noise estimation value of multiple sampling points of the received signal in the sub-band can be calculated based on the noise power estimation method. For example, the noise estimation value of the j-th sampling point in the sub-band can be marked as n j , where j is a positive integer.

[0094] Step S402: determining an initial noise correlation matrix of any subband according to noise estimation values ​​of a plurality of sampling points.

[0095] In the embodiment of the present application, the initial noise correlation matrix of the sub-band may be calculated according to the noise estimation values ​​of multiple sampling points.

[0096] As an example, the average of the noise estimation values ​​of multiple sampling points in a sub-band may be used as the initial noise correlation matrix of the sub-band.

[0097] Exemplarily, the following formula can be used to calculate the initial noise correlation matrix of the i-th subband:

[0098]

[0099] Where M is the number of sampling points in the i-th subband.

[0100] As another example, a weighted summation may be performed on noise estimation values ​​of multiple sampling points in a sub-band to obtain an initial noise correlation matrix of the sub-band.

[0101] It should be understood that other algorithms may also be used to calculate the initial noise correlation matrix of each subband based on the noise estimation values ​​of multiple sampling points in each subband, and the embodiments of the present application are not limited to this.

[0102] Step S403: determining target noise correlation matrices of the multiple sub-bands according to the degree of difference between the initial noise correlation matrices of the multiple sub-bands.

[0103] Step S404: performing interference suppression on the received signal according to the target noise correlation matrices of the multiple sub-bands to obtain a demodulated signal.

[0104] The explanation of steps S403 to S404 can be found in the relevant description in any embodiment of the present application and will not be repeated here.

[0105] The signal processing method of the embodiment of the present application can accurately and effectively calculate the initial noise correlation matrix of each sub-band according to the noise estimation values ​​of multiple sampling points in each sub-band.

[0106] The present application embodiment provides another signal processing method. Figure 5A flowchart of the fourth signal processing method provided in an embodiment of the present application.

[0107] It should be noted that the signal processing method can be executed alone, or it can be executed in combination with any embodiment of the present application or a possible implementation method in the embodiment, or it can be executed in combination with any technical solution in the related technology, and the embodiments of the present application are not limited to this.

[0108] like Figure 5 As shown, the signal processing method may include the following steps S501 to S504:

[0109] Step S501: determining initial noise correlation matrices of multiple sub-bands within a bandwidth occupied by a received signal.

[0110] Step S502: determining target noise correlation matrices of the multiple sub-bands according to the degree of difference between the initial noise correlation matrices of the multiple sub-bands.

[0111] The explanation of steps S501 to S502 can be found in the relevant description in any embodiment of the present application and will not be repeated here.

[0112] Step S503: determining interference suppression combining factors of the multiple sub-bands according to the target noise correlation matrices of the multiple sub-bands.

[0113] In the embodiment of the present application, the interference suppression combining factor of each subband may be calculated according to the target noise correlation matrix of each subband.

[0114] As an example, for any subband among multiple subbands, the channel estimation result H of the received signal in the subband can be obtained, and the interference suppression combining factor of the subband can be calculated based on the channel estimation result H in the subband and the target noise correlation matrix.

[0115] Exemplarily, the interference suppression combining factor of each subband can be calculated according to the above formula (6), where R in formula (6) is NN represents the target noise correlation matrix of the subband, Represents the interference suppression combining factor of the subband.

[0116] Step S504: perform interference suppression on the received signal according to the interference suppression combining factors of the multiple sub-bands to obtain a demodulated signal.

[0117] As an example, based on the above formula (2), according to the interference suppression combining factors of multiple sub-bands, interference suppression can be performed on the received signal to obtain a demodulated signal. That is, based on the above formula (2), according to the interference suppression combining factors of multiple sub-bands, the entire frequency band of the received signal can be split up and interference suppression reception can be performed separately to improve the overall demodulation performance of the receiving device.

[0118] The signal processing method of the embodiment of the present application can implement whitening processing on the channel estimation result H and the received signal based on the interference rejection combining (IRC) algorithm, remove the correlation between antennas and standardize the noise, thereby improving the demodulation effect of the received signal.

[0119] In any embodiment of the present application, the signal processing method provided by the present application can be applied to the field of mobile communications, including but not limited to: 2G, 3G, 4G, 5G, Bluetooth, WiFi (Wireless Fidelity), satellite and other wireless communication fields.

[0120] This application proposes an adaptive interference suppression scheme in a reception scenario with one antenna, which can determine whether there is sub-band interference during reception, and then decide whether to split the entire frequency band for interference suppression reception, thereby improving the overall demodulation performance of the signal. Exemplarily, the application scenario of this application can be interference signal judgment and suppression of terminals in the field of mobile communications, adaptively identifying the interference type of the current air interface wireless environment, improving the interference suppression effect, and improving the overall demodulation effect of the received signal.

[0121] The implementation principle of the solution provided by the present application is as follows: first, a narrower frequency bandwidth is used to calculate the noise correlation matrix of each sub-band, and a ratio-based method is used to determine whether the noise correlation matrices between the sub-bands have large differences. If the difference is large, it can be considered that there is sub-band interference between the sub-bands, and the noise correlation matrix of each sub-band needs to be used for interference suppression. If the difference is small, it can be considered that the current environmental interference distribution is relatively uniform, and the noise correlation matrices of each sub-band can be further merged to obtain a more accurate estimate. The sub-band merging method is:

[0122]

[0123] A single frequency band can contain 2 or 3 sub-bands, that is, n=2 or n=3.

[0124] As an example, the specific implementation of the solution provided in this application can be as follows Figure 6 As shown, it mainly includes the following steps:

[0125] Step 1: Determine the number of subcarriers K (K ≥ 2) and the number of subbands n in the frequency band according to the application scenario, where n can be 2 or 3.

[0126] Step 2: Divide the entire frequency band into n subbands according to n. If n = 2, then subband 1 contains subcarriers Subband 2 contains subcarriers

[0127] Step 3: Calculate the noise correlation matrix of each subband:

[0128]

[0129] in, is the estimated value of the noise correlation matrix of the ith subband (referred to as the initial noise correlation matrix in this application), n j is the noise estimate of the jth sampling point in the ith subband, and M is the number of sampling points in the ith subband.

[0130] Step 4: Determine whether sub-band merging can be performed. If the number of sub-bands is 2, perform the following determination:

[0131]

[0132] Wherein, thr is the decision threshold (denoted as the difference threshold in this application).

[0133] If the number of subbands is 3, the following judgment is made:

[0134]

[0135] Step 5: The result of the judgment The estimated result of the noise correlation matrix finally corresponding to each sub-band (referred to as the target noise correlation matrix in this application) is sent to the lower-level module for interference suppression.

[0136] In summary, when calculating the noise correlation matrix, the related technology generally uses the noise estimation values ​​of all sampling points within a fixed frequency band to calculate the noise correlation matrix, which cannot adapt to the changing channel environment. The solution provided by the present application first uses a narrower frequency band to calculate the noise correlation matrix of each sub-band within the frequency band, and uses a ratio-based method to determine whether the interference between each sub-band is similar. If the difference is too large, the noise correlation matrix of each sub-band is used to suppress interference. If the difference is small, it can be considered that the current environmental interference distribution is relatively uniform, and the noise correlation matrices of each sub-band can be further merged to obtain a more accurate estimate of the noise correlation matrix, thereby improving the overall demodulation capability of the received signal.

[0137] In order to implement the above embodiment, the embodiment of the present application also proposes a signal processing device.

[0138] Figure 7 A schematic diagram of the structure of a signal processing device provided in an embodiment of the present application.

[0139] like Figure 7 As shown, the signal processing device 700 may include: a first determination module 710 , a second determination module 720 and a suppression module 730 .

[0140] Wherein, the first determination module 710 is used to determine the initial noise correlation matrix of multiple sub-bands within the bandwidth occupied by the received signal;

[0141] A second determination module 720, configured to determine target noise correlation matrices of the multiple sub-bands according to the degree of difference between the initial noise correlation matrices of the multiple sub-bands;

[0142] The suppression module 730 is used to perform interference suppression on the received signal according to the target noise correlation matrix of multiple sub-bands to obtain a demodulated signal.

[0143] Further, in an implementation of the embodiment of the present application, the second determination module 720 is specifically configured to determine target noise correlation matrices of multiple sub-bands according to a magnitude relationship between the difference degree and the difference threshold.

[0144] In one implementation of the embodiment of the present application, the second determination module 720 is specifically used to: when the difference between the initial noise correlation matrices of any two sub-bands is higher than the difference threshold, use the initial noise correlation matrix of each sub-band as the target noise correlation matrix of the corresponding sub-band.

[0145] In one implementation of the embodiment of the present application, the second determination module 720 is specifically used to: when the degree of difference between the initial noise correlation matrices of multiple sub-bands is not higher than the difference threshold, use the average of the initial noise correlation matrices of the multiple sub-bands as the target noise correlation matrix of the multiple sub-bands.

[0146] In an implementation of the embodiment of the present application, the difference threshold is determined according to the difference type to which the difference degree belongs.

[0147] In one implementation of the embodiment of the present application, the received signal is received by a single antenna.

[0148] In one implementation of the embodiment of the present application, the first determination module 710 is specifically used to: determine, for any subband among multiple subbands, noise estimation values ​​of multiple sampling points of the received signal in any subband; and determine an initial noise correlation matrix of any subband based on the noise estimation values ​​of the multiple sampling points.

[0149] In one implementation of the embodiment of the present application, the first determination module 710 is specifically used to: use the mean of the noise estimation values ​​of multiple sampling points as the initial noise correlation matrix of any subband; or perform weighted summation on the noise estimation values ​​of multiple sampling points to obtain the initial noise correlation matrix of any subband.

[0150] In one implementation of an embodiment of the present application, the suppression module 730 is specifically used to: determine the interference suppression combining factors of multiple subbands according to the target noise correlation matrices of multiple subbands; and perform interference suppression on the received signal according to the interference suppression combining factors of the multiple subbands to obtain a demodulated signal.

[0151] In one implementation of an embodiment of the present application, the suppression module 730 is specifically used to: obtain channel estimation results of the received signal in multiple sub-bands; and determine the interference suppression combining factors of the multiple sub-bands based on the channel estimation results in the multiple sub-bands and the target noise correlation matrix.

[0152] It should be noted that the above explanation of the signal processing method embodiment is also applicable to the signal processing device of this embodiment, and will not be repeated here.

[0153] In the signal processing device of the embodiment of the present application, it is possible to determine whether there is sub-band interference between the multiple sub-bands based on the degree of difference between the initial noise correlation matrices of the multiple sub-bands, and based on the judgment result, specifically determine the target noise correlation matrices that the multiple sub-bands ultimately correspond to, and based on the target noise correlation matrices of the multiple sub-bands, perform interference suppression on the received signal, which can improve the interference suppression effect of the signal, enhance the signal demodulation capability of the receiving device, and can be applicable to a variable channel environment.

[0154] In order to implement the above embodiments, the present application also proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the signal processing method as described in any of the above embodiments is implemented.

[0155] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. For example, the electronic device 800 may be a vehicle, a mobile phone, a computer, a digital broadcast terminal, a message transceiver device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0156] Reference Figure 8 , the electronic device 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power component 806 , a multimedia component 808 , an audio component 810 , an input / output (I / O) interface 812 , a sensor component 814 , and a communication component 816 .

[0157] The processing component 802 generally controls the overall operation of the electronic device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0158] The memory 804 is configured to store various types of data to support operations on the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phone book data, messages, pictures, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0159] The power component 806 provides power to the various components of the electronic device 800. The power component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.

[0160] The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the electronic device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0161] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC), and when the electronic device 800 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 804 or sent via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for outputting audio signals.

[0162] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: home button, volume button, start button, and lock button.

[0163] The sensor assembly 814 includes one or more sensors for providing various aspects of status assessment for the electronic device 800. For example, the sensor assembly 814 can detect the open / closed state of the electronic device 800, the relative positioning of the components, such as the display and keypad of the electronic device 800, and the sensor assembly 814 can also detect the position change of the electronic device 800 or a component of the electronic device 800, the presence or absence of contact between the user and the electronic device 800, the orientation or acceleration / deceleration of the electronic device 800, and the temperature change of the electronic device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0164] The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 can access a wireless network based on a communication standard, such as WiFi, 4G or 5G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0165] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0166] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, and the instructions can be executed by a processor 820 of an electronic device 800 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0167] In order to implement the above embodiments, the present application also proposes a chip, including: the chip includes an interface circuit and a processing circuit coupled to each other. The interface circuit is used to input or output signals, and the processing circuit is configured to execute a signal processing method provided in any of the above embodiments.

[0168] Fig. 9 Schematic diagram of a chip structure proposed in the embodiment of the present application. Fig. 9 The structure of the chip 900 is shown, but is not limited to this.

[0169] The chip 900 includes a processing circuit 901 , and the processing circuit 901 is configured to execute any of the above signal processing methods.

[0170] In some embodiments, the chip 900 further includes one or more interface circuits 902. Optionally, the interface circuit 902 is connected to the memory 903, and the interface circuit 902 can be used to receive signals from the memory 903 or other devices, and the interface circuit 902 can be used to send signals to the memory 903 or other devices. For example, the interface circuit 902 can read instructions stored in the memory 903 and send the instructions to the processing circuit 901.

[0171] In some embodiments, the interface circuit 902 performs at least one of the communication steps such as sending and / or receiving in the above method, and the processing circuit 901 performs other steps.

[0172] In some embodiments, terms such as interface circuit, interface, transceiver pin, and transceiver may be used interchangeably.

[0173] In some embodiments, the chip 900 further includes one or more memories 903 for storing instructions. Optionally, all or part of the memory 903 may be outside the chip 900.

[0174] In order to implement the above embodiments, the present application also proposes a non-temporary computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the signal processing method as described in any of the above method embodiments is implemented.

[0175] In order to implement the above embodiments, the present application also proposes a computer program product, on which a computer program is stored. When the computer program is executed by a processor, the signal processing method as described in any of the above method embodiments is implemented.

[0176] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0177] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0178] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0179] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0180] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0181] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0182] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0183] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A signal processing method, characterized in that: include: determining an initial noise correlation matrix for a plurality of sub-bands within a bandwidth occupied by a received signal; Determining target noise correlation matrices of the multiple sub-bands according to the degree of difference between the initial noise correlation matrices of the multiple sub-bands; Interference suppression is performed on the received signal according to the target noise correlation matrices of the multiple sub-bands to obtain a demodulated signal.

2. The method according to claim 1, characterized in that The step of determining the target noise correlation matrices of the multiple sub-bands according to the degree of difference between the initial noise correlation matrices of the multiple sub-bands comprises: According to the magnitude relationship between the difference degree and the difference threshold, the target noise correlation matrix of the multiple sub-bands is determined.

3. The method according to claim 2, characterized in that The step of determining the target noise correlation matrix of the plurality of sub-bands according to the magnitude relationship between the difference degree and the difference threshold comprises: When the difference between the initial noise correlation matrices of any two sub-bands is higher than the difference threshold, the initial noise correlation matrix of each sub-band is used as the target noise correlation matrix of the corresponding sub-band.

4. The method according to claim 2, characterized in that: The step of determining the target noise correlation matrix of the plurality of sub-bands according to the magnitude relationship between the difference degree and the difference threshold comprises: When the differences between the initial noise correlation matrices of the multiple subbands are not higher than the difference threshold, the averages of the initial noise correlation matrices of the multiple subbands are used as the target noise correlation matrices of the multiple subbands.

5. The method according to any one of claims 2 to 4, characterized in that: The difference threshold is determined according to the difference type to which the difference degree belongs.

6. The method according to claim 1, characterized in that The received signal is received through a single antenna.

7. The method according to claim 6, characterized in that The step of determining the initial noise correlation matrix of multiple sub-bands within the bandwidth occupied by the received signal comprises: For any subband among the multiple subbands, determine noise estimation values ​​of a plurality of sampling points of the received signal within the any subband; An initial noise correlation matrix of any subband is determined according to the noise estimation values ​​of the multiple sampling points.

8. The method according to claim 7, characterized in that The determining, according to the noise estimation values ​​of the multiple sampling points, the initial noise correlation matrix of any subband comprises: Taking the mean of the noise estimation values ​​of the multiple sampling points as the initial noise correlation matrix of any subband; or, A weighted sum is performed on the noise estimation values ​​of the multiple sampling points to obtain an initial noise correlation matrix of any subband.

9. The method according to claim 1, characterized in that: The step of performing interference suppression on the received signal according to the target noise correlation matrix of the multiple sub-bands to obtain a demodulated signal includes: determining interference suppression combining factors for the multiple subbands according to target noise correlation matrices for the multiple subbands; Interference suppression is performed on the received signal according to the interference suppression combining factors of the multiple sub-bands to obtain the demodulated signal.

10. The method according to claim 9, characterized in that The determining, according to the target noise correlation matrices of the multiple sub-bands, interference suppression combining factors of the multiple sub-bands comprises: Obtaining channel estimation results of the received signal in the multiple sub-bands; Interference suppression combining factors of the multiple subbands are determined according to the channel estimation results in the multiple subbands and the target noise correlation matrix.

11. A signal processing device, characterized in that: include: A first determination module is used to determine the initial noise correlation matrix of multiple sub-bands within the bandwidth occupied by the received signal; A second determination module, configured to determine target noise correlation matrices of the multiple sub-bands according to the degree of difference between the initial noise correlation matrices of the multiple sub-bands; The suppression module is used to perform interference suppression on the received signal according to the target noise correlation matrix of the multiple sub-bands to obtain a demodulated signal.

12. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method according to any one of claims 1 to 10 are implemented.

13. A chip, characterized in that: The chip comprises an interface circuit and a processing circuit coupled to each other, the interface circuit is used to input or output a signal, and the processing circuit is used to implement the method according to any one of claims 1 to 10.

14. A non-transitory computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the program instructions are executed by a processor, the steps of the method described in any one of claims 1 to 10 are implemented.

15. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 10.

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