Signal processing methods, devices, electronic equipment, chips and storage media

Abstract

This application proposes a signal processing method, apparatus, electronic device, chip, and storage medium, relating to the field of communications. The method includes: determining initial noise correlation matrices for multiple sub-bands within the bandwidth occupied by a received signal; determining target noise correlation matrices for the multiple sub-bands based on the degree of difference between the initial noise correlation matrices; and performing interference suppression on the received signal based on the target noise correlation matrices to obtain a demodulated signal. This allows for the determination of whether sub-band interference exists between multiple sub-bands based on the degree of difference between their initial noise correlation matrices, and based on the determination result, the targeted noise correlation matrices corresponding to the multiple sub-bands are specifically determined. Furthermore, interference suppression of the received signal is performed based on these target noise correlation matrices, improving the interference suppression effect and enhancing the signal demodulation capability of the receiving device. This method is applicable to variable channel environments.

Description

Technical Field

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

[0002] In practical Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the presence of interference greatly affects the received signal at the receiver. Therefore, it is essential to adopt effective channel equalization techniques to suppress interference and improve the performance of MIMO-OFDM systems.

[0003] In related technologies, when the receiving end includes only one receiving antenna, the noise correlation matrix of multiple sub-bands within the bandwidth occupied by the received signal is degraded into a scalar. The demodulation method of the received signal is as follows: the mean of the estimated values ​​of the noise correlation matrix within the multiple sub-bands is used as the estimated value of the noise correlation matrix within the bandwidth occupied by the received signal, and the received signal is demodulated based on the estimated value of the noise correlation matrix within this bandwidth.

[0004] However, the method of demodulating the received signal based on the estimated value of the noise correlation matrix over the entire bandwidth or frequency band is not suitable for the changing channel environment. Summary of the Invention

[0005] This application aims to at least partially address one of the technical problems in the related art.

[0006] Therefore, this application proposes a signal processing method, apparatus, electronic device, chip, and storage medium.

[0007] One embodiment of this application proposes a signal processing method, including:

[0008] Determine the initial noise correlation matrix for multiple sub-bands within the bandwidth occupied by the received signal;

[0009] The target noise correlation matrix of the multiple sub-bands is determined based on the degree of difference between the initial noise correlation matrices of the multiple sub-bands;

[0010] Based on the target noise correlation matrix of the multiple sub-bands, interference suppression is performed on the received signal to obtain the demodulated signal.

[0011] Another embodiment of this application provides a signal processing apparatus, including:

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

[0013] The second determining module is used to determine the target noise correlation matrix of the multiple sub-bands based on the degree of difference between the initial noise correlation matrices of the multiple sub-bands;

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

[0015] Another embodiment of this application 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, it implements the signal processing method as described in the foregoing aspect.

[0016] Another embodiment of this application proposes a chip including an interface circuit and a processing circuit coupled to each other, the interface circuit being used to input or output signals, and the processing circuit being configured to perform the signal processing method as described in the foregoing aspect.

[0017] Another embodiment of this application proposes a non-transitory computer-readable storage medium storing computer program instructions that, when executed by a processor, implement the signal processing method as described in the foregoing aspect.

[0018] Another embodiment of this application proposes a computer program product having a computer program stored thereon, which, when executed by a processor, implements the signal processing method as described in the foregoing aspect.

[0019] The signal processing method, apparatus, electronic device, chip, and storage medium proposed in this application 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 matrices corresponding to the multiple sub-bands, and perform interference suppression on the received signal based on the target noise correlation matrices of multiple sub-bands. This can improve the interference suppression effect of the signal, enhance the signal demodulation capability of the receiving device, and is applicable to variable channel environments.

[0020] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

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

[0022] Figure 1This is a schematic diagram of subband interference.

[0023] Figure 2 A schematic flowchart illustrating the first signal processing method provided in the embodiments of this application;

[0024] Figure 3 This is a flowchart illustrating the second signal processing method provided in an embodiment of this application.

[0025] Figure 4 This is a schematic flowchart illustrating the third signal processing method provided in the embodiments of this application;

[0026] Figure 5 This is a schematic flowchart illustrating the fourth signal processing method provided in the embodiments of this application;

[0027] Figure 6 This is a schematic diagram illustrating a specific implementation of an embodiment of this application;

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

[0029] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0030] Figure 9 This is a schematic diagram of the structure of a chip proposed in an embodiment of this application. Detailed Implementation

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

[0032] In practical MIMO-OFDM systems, interference significantly impacts the received signal. Therefore, employing effective channel equalization techniques to suppress interference and improve the performance of the MIMO-OFDM system is essential. Channel equalization techniques are categorized into nonlinear and linear equalization. Nonlinear equalization algorithms offer excellent performance, but their computational complexity is excessive, increasing power consumption and processing time at the receiver. In contrast, linear equalization algorithms provide better performance with lower complexity.

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

[0034] In real-world wireless communication environments, there are often multiple sources of interference, which inevitably leads to correlation among the interference sources on the receiving antenna. Therefore, interference cancellation is necessary when performing channel equalization / antenna combining.

[0035] In a single-carrier system with flat Rayleigh fading, the received signal at a receiver with n antennas 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 receiver can use a combining factor W... H To suppress interference in the received signal, we obtain the suppressed signal (i.e., the demodulated signal), which can be represented as:

[0038]

[0039] When colored interference exists on multiple antennas at the receiving end, the correlation matrix of the noise vectors between 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] Here, H in the upper right corner of N represents the conjugate transpose of the matrix.

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

[0043]

[0044] While ensuring W H Under the constraint of H=1, the resulting merging factor W H for:

[0045]

[0046] The merging algorithm in formula (5) above is called the Interference Suppression Merging (IRC) algorithm, where, Its function is to whiten the channel matrix H and the received signal Y, remove the correlation between antennas, and normalize the noise.

[0047] When the receiver consists of only one antenna, the antenna's noise correlation matrix degenerates into a scalar:

[0048]

[0049] When the interference is sub-band interference, that is, when the interference intensity is inconsistent between different sub-bands in the frequency domain, such as Figure 1 As shown, the interference intensity in sub-band 2 is greater, resulting in a higher noise correlation matrix in sub-band 1. <Noise correlation matrix of subband 2 If the average of the estimated noise correlation matrices across multiple sub-bands is used as the antenna's noise correlation matrix... To suppress interference in the received signal, the estimated value of the noise correlation matrix will be affected when receiving subband 1 and subband 2. Same as the true value The difference is too large, which prevents the output signal-to-noise ratio from being maximized. However, if the estimated value of the noise correlation matrix of each sub-band is used... When interference is suppressed on the received signal, in scenarios with no interference or similar inter-subband interference intensity, the estimated value of the noise correlation matrix will be affected by the insufficient number of sampling points. Same as the true value If the difference is too large, the output signal-to-noise ratio cannot be maximized.

[0050] In related technologies, when calculating the noise correlation matrix, a relatively wide frequency band is generally used for averaging to obtain a more accurate Rw. NN The estimated value shows that this method has poor signal demodulation performance in subband interference environments. Another method uses a narrower frequency band to average the values ​​to obtain the R values ​​for each subband. NN While the estimated value avoids performance loss due to subband interference, the estimated R... NN The number of sampling points used is reduced compared to the true R. NN The error increases, resulting in poor signal demodulation performance in interference-free environments.

[0051] In response to at least one of the aforementioned problems, this application proposes a signal processing method, apparatus, electronic device, chip, and storage medium.

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

[0053] Figure 2 This is a schematic flowchart of the first signal processing method provided in the embodiments of this application.

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

[0055] In any embodiment of this application, the signal processing method can be executed by a chip, which can be integrated into the receiving device. The chip includes a Central Processing Unit (CPU), Image Signal Processing (ISP), Application-Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Field-Programmable Gate Array (FPGA), System-on-Action Chip (SOC), Reduced Instruction Set Computer (RISC), etc., which will not be listed individually here.

[0056] In this context, a terminal is a user-side entity used to receive or transmit signals, such as a mobile phone. A terminal can also be called a terminal device, user equipment (UE), mobile station (MS), or mobile terminal (MT). Terminals can be communication-enabled vehicles, smart cars, mobile phones, wearable devices, tablets, computers with wireless transceiver capabilities, virtual reality (VR) terminals, augmented reality (AR) terminals, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, and so on. The embodiments in this application do not limit the specific technology or device form used in the terminal.

[0057] In this context, a network device is an entity on the network side used to transmit or receive signals. For example, a network device can be an evolved NodeB (eNB), a transmission reception point (TRP), a next-generation NodeB (gNB) in a 5G new radio (NR) system, a base station in other future mobile communication systems, or an access node in a wireless fidelity (WiFi) system. The embodiments of this application do not limit the specific technology or device form used in the network device. The network device provided in the embodiments of this application can be composed of a central unit (CU) and a distributed unit (DU). The CU can also be called a control unit. Using a CU-DU structure allows the protocol layer of a network device, such as a base station, to be separated. Some protocol layer functions are centrally controlled by the CU, while the remaining part or all of the protocol layer functions are distributed in the DU, which 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: Determine the initial noise correlation matrix of multiple sub-bands within the bandwidth occupied by the received signal.

[0060] The noise correlation matrix is ​​a matrix used to describe the correlation between noises in each sub-band, reflecting whether the noises in different sub-bands are independent or correlated.

[0061] In any embodiment of this application, the number of sub-bands n within the bandwidth occupied by the received signal can be set according to the application scenario. For example, the value of n can be 2 or 3.

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

[0063] Step S202: Determine the target noise correlation matrix of the multiple sub-bands based on the degree of difference between the initial noise correlation matrices of the multiple sub-bands.

[0064] The degree of difference can be characterized by ratio, difference, and absolute value of difference.

[0065] In this embodiment of the application, the degree of difference between the initial noise correlation matrices of multiple subbands can be calculated, and the degree of difference between the initial noise correlation matrices of multiple subbands can be used to determine whether there is subband interference between multiple subbands. For example, when the degree of difference is relatively large, it is determined that there is subband interference between multiple subbands, while when the degree of difference is relatively small, it is determined that there is no subband interference between multiple subbands.

[0066] In this application, the target noise correlation matrix corresponding to multiple subbands can be determined specifically based on the judgment result of whether there is subband interference between multiple subbands.

[0067] Step S203: Based on the target noise correlation matrix of multiple sub-bands, interference suppression is performed on the received signal to obtain the demodulated signal.

[0068] In this embodiment, interference suppression can be performed on the received signal based on the target noise correlation matrix of multiple sub-bands to obtain the demodulated signal. That is, based on 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 this application embodiment 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 determination result, specifically determine the target noise correlation matrix corresponding to the multiple sub-bands, and perform interference suppression on the received signal based on the target noise correlation matrix of multiple sub-bands. This can improve the interference suppression effect of the signal, enhance the signal demodulation capability of the receiving device, and is applicable to variable channel environments.

[0070] This application provides another signal processing method. Figure 3 This is a schematic flowchart of the second signal processing method provided in the embodiments of this application.

[0071] It should be noted that the signal processing method can be executed alone, or it can be executed together with any embodiment or possible implementation in the embodiment of this application, or it can be executed together with any technical solution in the related technology. The embodiments of this application do not limit this.

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

[0073] Step S301: Determine the initial noise correlation matrix of multiple sub-bands within the bandwidth occupied by the received signal.

[0074] Step S302: Determine the degree of difference between the initial noise correlation matrices of the multiple subbands.

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

[0076] Step S303: Determine the target noise correlation matrix for multiple sub-bands based on the relationship between the degree of difference and the difference threshold.

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

[0078] In the embodiments of this application, the target noise correlation matrix of multiple sub-bands can be determined based on the relationship between the degree of difference and the difference threshold.

[0079] As an example, if the difference between the initial noise correlation matrices of any two sub-bands is higher than the difference threshold, it indicates that there is sub-band interference between multiple sub-bands. In this case, in order to improve the output signal-to-noise ratio of each sub-band, the initial noise correlation matrix of each sub-band can be used as the target noise correlation matrix of the corresponding sub-band.

[0080] As another example, if the 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. In this case, the mean of the initial noise correlation matrices of multiple subbands can be used as the target noise correlation matrix of multiple subbands.

[0081] For example, taking a case where there are two sub-bands and the degree of difference is represented by a ratio, the initial noise correlation matrices of the two sub-bands are respectively... and If the difference threshold is thr, then the target noise correlation matrix of the i-th (i=1,2) sub-band can be calculated using the following formula.

[0082]

[0083] For example, taking a sub-band with three sub-bands and the degree of difference represented by a ratio, the initial noise correlation matrices for the three sub-bands are as follows: and If the difference threshold is thr, then the target noise correlation matrix of the i-th (i = 1, 2, 3) sub-band can be calculated using the following formula.

[0084]

[0085] Step S304: Based on the target noise correlation matrix of multiple sub-bands, interference suppression is performed on the received signal to obtain the demodulated signal.

[0086] The explanation of step S304 can be found in the relevant description in any embodiment of this application, and will not be repeated here.

[0087] The signal processing method of this application embodiment indicates that when the differences between the initial noise correlation matrices of multiple sub-bands are relatively large, it indicates that the interference distribution in the current channel environment is uneven. In this case, interference suppression can be performed based on the initial noise correlation matrices of each sub-band. Conversely, when the differences between the initial noise correlation matrices of multiple sub-bands are relatively small, it indicates that the interference distribution in the current channel environment is relatively uniform. In this case, the initial noise correlation matrices of each sub-band can be further merged to obtain a more accurate estimate of the noise correlation matrix (denoted as the target noise correlation matrix in this application). By suppressing interference on the received signal based on the target noise correlation matrix of each sub-band, the signal demodulation capability of the receiving device can be improved.

[0088] This application provides another signal processing method. Figure 4 This is a flowchart illustrating the third signal processing method provided in the embodiments of this application.

[0089] It should be noted that the signal processing method can be executed alone, or it can be executed together with any embodiment or possible implementation in the embodiment of this application, or it can be executed together with any technical solution in the related technology. The embodiments of this application do not limit this.

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

[0091] Step S401: For any one of the multiple subbands within the bandwidth occupied by the received signal, determine the noise estimate of multiple sampling points of the received signal within any one subband.

[0092] In any embodiment of this application, the received signal can be obtained through a single antenna of the receiving device. Where the receiving device includes only one receiving antenna, the noise correlation matrix within the subband degenerates into a scalar σ. 2 .

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

[0094] Step S402: Determine the initial noise correlation matrix of any sub-band based on the noise estimates of multiple sampling points.

[0095] In this embodiment of the application, the initial noise correlation matrix of the above sub-band can be calculated based on the noise estimates of multiple sampling points.

[0096] As an example, the mean of the noise estimates of multiple sampling points within a subband can be used as the initial noise correlation matrix for that subband.

[0097] For example, the initial noise correlation matrix of the i-th sub-band can be calculated using the following formula.

[0098]

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

[0100] As another example, the noise estimates of multiple sampling points within a subband can be weighted and summed to obtain the initial noise correlation matrix of that subband.

[0101] It should be understood that other algorithms can also be used to calculate the initial noise correlation matrix of a sub-band based on the noise estimates of multiple sampling points within each sub-band, and the embodiments of this application do not limit this.

[0102] Step S403: Determine the target noise correlation matrix of the multiple sub-bands based on the degree of difference between the initial noise correlation matrices of the multiple sub-bands.

[0103] Step S404: Based on the target noise correlation matrix of multiple sub-bands, interference suppression is performed on the received signal to obtain the demodulated signal.

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

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

[0106] This application provides another signal processing method. Figure 5This is a flowchart illustrating the fourth signal processing method provided in the embodiments of this application.

[0107] It should be noted that the signal processing method can be executed alone, or it can be executed together with any embodiment or possible implementation in the embodiment of this application, or it can be executed together with any technical solution in the related technology. The embodiments of this application do not limit this.

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

[0109] Step S501: Determine the initial noise correlation matrix of multiple sub-bands within the bandwidth occupied by the received signal.

[0110] Step S502: Determine the target noise correlation matrix of the multiple sub-bands based on 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 this application, and will not be repeated here.

[0112] Step S503: Determine the interference suppression merging factor of multiple sub-bands based on the target noise correlation matrix of multiple sub-bands.

[0113] In the embodiments of this application, the interference suppression merging factor of each sub-band can be calculated based on the target noise correlation matrix of each sub-band.

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

[0115] For example, the interference suppression merging factor for each subband can be calculated according to the above formula (6), where R in formula (6) NN This represents the target noise correlation matrix of the sub-band. This represents the interference suppression merging factor of the subband.

[0116] Step S504: Based on the interference suppression and combining factors of multiple sub-bands, the received signal is subjected to interference suppression to obtain the demodulated signal.

[0117] As an example, based on the above formula (2), interference suppression can be applied to the received signal according to the interference suppression merging factors of multiple sub-bands to obtain the demodulated signal. That is, based on the above formula (2), the entire frequency band of the received signal can be split into separate interference suppression receptions according to the interference suppression merging factors of multiple sub-bands to improve the overall demodulation performance of the receiving equipment.

[0118] The signal processing method in this application embodiment can perform whitening processing on the channel estimation result H and the received signal based on the Interference Suppression Combining (IRC) algorithm, remove the correlation between antennas and normalize the noise, thereby improving the demodulation effect of the received signal.

[0119] In any embodiment of this application, the signal processing method provided in this application can be applied to the field of mobile communication, 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 for a single-antenna reception scenario. It can determine whether sub-band interference exists during reception and then decide whether to split the entire frequency band for separate interference suppression reception, thereby improving the overall demodulation performance of the signal. For example, this application can be used in the field of mobile communication for interference signal judgment and suppression of terminals, adaptively identifying the type of interference in the current air interface wireless environment, improving interference suppression effectiveness, and enhancing the overall demodulation performance of the received signal.

[0121] The implementation principle of the solution provided in this application is as follows: First, the noise correlation matrix of each sub-band is calculated using a narrower bandwidth. Then, a ratio-based method is used to determine whether there are significant differences between the noise correlation matrices of each sub-band. If the differences are large, it can be assumed that there is sub-band interference, and the noise correlation matrices of each sub-band need to be used for interference suppression. If the differences are small, it can be assumed 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 as follows:

[0122]

[0123] A single frequency band can accommodate 2 or 3 sub-bands, i.e., 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, the main steps include:

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

[0126] Step 2: Divide the entire frequency band into n sub-bands based on n. If n = 2, then sub-band 1 contains subcarriers. Subband 2 contains subcarriers

[0127] Step 3: Calculate the noise correlation matrix for each sub-band:

[0128]

[0129] in, Let n be the estimated value of the noise correlation matrix of the i-th sub-band (denoted as the initial noise correlation matrix in this application). j Let M be the noise estimate of the j-th sampling point within the i-th sub-band, and M be the number of sampling points within the i-th sub-band.

[0130] Step 4: Determine if subband merging is possible. If the number of subbands is 2, then perform the following judgment:

[0131]

[0132] Where thr is the decision threshold (referred to as the difference threshold in this application).

[0133] If the number of sub-bands is 3, then the following judgment is made:

[0134]

[0135] Step 5: Determine the result of the judgment. The estimated results of the noise correlation matrix corresponding to each sub-band (denoted as the target noise correlation matrix in this application) are sent to the next-level module for interference suppression.

[0136] In summary, related technologies typically use noise estimates from all sampling points within a fixed frequency band to calculate the noise correlation matrix, which is unsuitable for varying channel environments. The solution provided in this application first calculates the noise correlation matrix for each sub-band within a narrower frequency band. Then, it uses a ratio-based method to determine if the interference between sub-bands is approximate. If the difference is too large, the noise correlation matrices of each sub-band are used for interference suppression. If the difference is small, the current environment's interference distribution is considered 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, thus improving the overall demodulation capability of the received signal.

[0137] To implement the above embodiments, this application also proposes a signal processing device.

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

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

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

[0141] The second determining module 720 is used to determine the target noise correlation matrix of multiple sub-bands based on the degree of difference between the initial noise correlation matrices of multiple sub-bands;

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

[0143] Furthermore, in one implementation of this application embodiment, the second determining module 720 is specifically used to: determine the target noise correlation matrix of multiple sub-bands based on the magnitude relationship between the degree of difference and the difference threshold.

[0144] In one implementation of this application, the second determining 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, take 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 this application, the second determining 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, take the mean of the initial noise correlation matrices of multiple sub-bands as the target noise correlation matrix of multiple sub-bands.

[0146] In one implementation of this application, the difference threshold is determined based on the difference type to which the degree of difference belongs.

[0147] In one implementation of this application, the received signal is obtained by receiving a single antenna.

[0148] In one implementation of this application, the first determining module 710 is specifically used to: determine the noise estimation values ​​of multiple sampling points of the received signal in any one of the multiple sub-bands; and determine the initial noise correlation matrix of any one sub-band based on the noise estimation values ​​of the multiple sampling points.

[0149] In one implementation of this application, the first determining module 710 is specifically used to: take the mean of the noise estimates of multiple sampling points as the initial noise correlation matrix of any sub-band; or, perform a weighted summation of the noise estimates of multiple sampling points to obtain the initial noise correlation matrix of any sub-band.

[0150] In one implementation of this application, the suppression module 730 is specifically used to: determine the interference suppression merging factor of multiple sub-bands based on the target noise correlation matrix of multiple sub-bands; and perform interference suppression on the received signal based on the interference suppression merging factor of multiple sub-bands to obtain a demodulated signal.

[0151] In one implementation of this application, the suppression module 730 is specifically used to: obtain the channel estimation results of the received signal in multiple sub-bands; and determine the interference suppression and combining factor 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 foregoing explanation of the signal processing method embodiments also applies to the signal processing apparatus of this embodiment, and will not be repeated here.

[0153] In the signal processing apparatus of this application embodiment, it is possible to 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 determination result, to specifically determine the target noise correlation matrices corresponding to the multiple sub-bands, and to perform interference suppression on the received signal based on the target noise correlation matrices of multiple sub-bands. This can improve the interference suppression effect of the signal, enhance the signal demodulation capability of the receiving device, and is applicable to variable channel environments.

[0154] To implement the above embodiments, this application also proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the signal processing method as described in any of the foregoing embodiments.

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

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

[0157] Processing component 802 typically controls the overall operation of electronic device 800, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 802 may include one or more modules to facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

[0158] Memory 804 is configured to store various types of data to support the operation of electronic device 800. Examples of this data include instructions for any application or method operating on electronic device 800, contact data, phonebook data, messages, pictures, videos, etc. 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 storage, flash memory, magnetic disk, or optical disk.

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

[0160] 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 touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 808 includes a front-facing camera and / or a rear-facing camera. When the electronic device 800 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0161] Audio component 810 is configured to output and / or input audio signals. For example, audio component 810 includes a microphone (MIC) configured to receive external audio signals when electronic device 800 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 804 or transmitted via communication component 816. In some embodiments, 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 buttons, volume buttons, power buttons, and lock buttons.

[0163] Sensor assembly 814 includes one or more sensors for providing state assessments of various aspects of electronic device 800. For example, sensor assembly 814 can detect the on / off state of electronic device 800, the relative positioning of components such as the display and keypad of electronic device 800, changes in position of electronic device 800 or a component of electronic device 800, the presence or absence of user contact with electronic device 800, orientation or acceleration / deceleration of electronic device 800, and temperature changes of electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 814 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0164] Communication component 816 is configured to facilitate wired or wireless communication between electronic device 800 and other devices. Electronic device 800 can access wireless networks based on communication standards, such as WiFi, 4G, or 5G, or combinations thereof. In one exemplary embodiment, communication component 816 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 816 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may 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 methods described above.

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

[0167] To implement the above embodiments, this application also proposes a chip, comprising: an interface circuit and a processing circuit coupled to each other; the interface circuit being used to input or output signals; and the processing circuit being configured to perform the signal processing method provided in any of the foregoing embodiments.

[0168] Figure 9 This is a schematic diagram of the structure of a chip proposed in an embodiment of this application. See also... Figure 9 The diagram shown is a schematic representation of the structure of chip 900, but it is not limited to this.

[0169] Chip 900 includes processing circuitry 901, which is configured to perform 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, the terms interface circuit, interface, transceiver pin, transceiver, etc., can be used interchangeably.

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

[0174] To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the signal processing method as described in any of the foregoing method embodiments.

[0175] To implement the above embodiments, this application also proposes a computer program product having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the signal processing method as described in any of the foregoing method embodiments.

[0176] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0177] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0178] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0179] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0180] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0181] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0182] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0183] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A signal processing method, characterized by, The method comprises the steps of: determining initial noise correlation matrices of a plurality of subbands within an occupied bandwidth of a received signal; determining target noise correlation matrices of the plurality of subbands according to a difference degree between the initial noise correlation matrices of the plurality of subbands, wherein the difference degree indicates whether there is subband interference between the plurality of subbands, if there is subband interference, the initial noise correlation matrix of each subband is taken as the target noise correlation matrix of the corresponding subband, and if there is no subband interference, a mean value of the initial noise correlation matrices of the plurality of subbands is taken as the target noise correlation matrices of the plurality of subbands; performing interference suppression on the received signal according to the target noise correlation matrices of the plurality of subbands to obtain a demodulation signal.

2. The method of claim 1, wherein, The step of determining the target noise correlation matrices of the plurality of subbands according to the difference degree between the initial noise correlation matrices of the plurality of subbands comprises the steps of: determining the target noise correlation matrices of the plurality of subbands according to a size relationship between the difference degree and a difference threshold.

3. The method of claim 2, wherein, The step of determining the target noise correlation matrices of the plurality of subbands according to the size relationship between the difference degree and the difference threshold comprises the steps of: if the difference degree between the initial noise correlation matrices of any two subbands is higher than the difference threshold, taking the initial noise correlation matrix of each subband as the target noise correlation matrix of the corresponding subband.

4. The method of claim 2, wherein, The step of determining the target noise correlation matrices of the plurality of subbands according to the size relationship between the difference degree and the difference threshold comprises the steps of: if the difference degree between the initial noise correlation matrices of the plurality of subbands is not higher than the difference threshold, taking a mean value of the initial noise correlation matrices of the plurality of subbands as the target noise correlation matrices of the plurality of subbands.

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

6. The method of claim 1, wherein, The received signal is obtained through a single antenna.

7. The method of claim 6, wherein, The step of determining the initial noise correlation matrices of a plurality of subbands within an occupied bandwidth of a received signal comprises the steps of: for any subband in the plurality of subbands, determining noise estimation values of a plurality of sampling points of the received signal within the any subband; determining the initial noise correlation matrix of the any subband according to the noise estimation values of the plurality of sampling points.

8. The method of claim 7, wherein, The step of determining the initial noise correlation matrix of the any subband according to the noise estimation values of the plurality of sampling points comprises the steps of: taking a mean value of the noise estimation values of the plurality of sampling points as the initial noise correlation matrix of the any subband; or performing weighted summation on the noise estimation values of the plurality of sampling points to obtain the initial noise correlation matrix of the any subband. The step of performing interference suppression on the received signal according to the target noise correlation matrices of the plurality of subbands to obtain a demodulation signal comprises the steps of:

9. The method of claim 1, wherein, determining interference suppression combining factors of the plurality of subbands according to the target noise correlation matrices of the plurality of subbands; performing interference suppression on the received signal according to the interference suppression combining factors of the plurality of subbands to obtain the demodulation signal. The step of determining the interference suppression combining factors of the plurality of subbands according to the target noise correlation matrices of the plurality of subbands comprises the steps of:

10. The method of claim 9, wherein, obtaining channel estimation results of the received signal within the plurality of subbands; ​ According to the channel estimation results and the target noise correlation matrix of the plurality of subbands, a interference suppression combining factor of the plurality of subbands is determined.

11. A signal processing device, characterized by The method comprises the steps of: A first determining module is configured to determine initial noise correlation matrices of a plurality of subbands within a receiving signal bandwidth; A second determining module is configured to determine target noise correlation matrices of the plurality of subbands according to a difference degree between the initial noise correlation matrices of the plurality of subbands, wherein the difference degree indicates whether there is subband interference between the plurality of subbands, if there is subband interference, the initial noise correlation matrix of each subband is taken as the target noise correlation matrix of the corresponding subband, and if there is no subband interference, the average of the initial noise correlation matrices of the plurality of subbands is taken as the target noise correlation matrix of the plurality of subbands; A suppressing module is configured to perform interference suppression on the receiving signal according to the target noise correlation matrices of the plurality of subbands to obtain a demodulation signal.

12. An electronic device, comprising: The computer program is stored in the memory and can be run on the processor, and the processor implements the steps of the method in any one of claims 1 to 10 when executing the program.

13. A chip, characterized by The chip comprises an interface circuit and a processing circuit which are coupled to each other, the interface circuit is configured to input or output signals, and the processing circuit is configured to implement the method in any one of claims 1 to 10.

14. A non-transitory computer-readable storage medium having stored thereon computer program instructions, wherein, The program instruction is executed by the processor to implement the steps of the method in any one of claims 1 to 10.

15. A computer program product, characterised in that, The computer program is executed by the processor to implement the steps of the method in any one of claims 1 to 10.

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