Channel smoothing method and apparatus, electronic device, and storage medium

Abstract

The present application relates to the technical field of communication, disclose a channel smoothing method, device, electronic equipment and storage medium, the present application is in response to receiving a target signal, the target signal corresponding subcarrier sequence is subjected to channel estimation, obtain the initial channel estimation value of subcarrier sequence, based on the signal-to-noise ratio estimation value of target signal, the preset smoothing coefficient library is matched, obtain target smoothing filter coefficient, wherein, the preset smoothing coefficient library includes multiple preset smoothing filter coefficients, multiple preset smoothing filter coefficients and multiple preset signal-to-noise ratio one-to-one, multiple preset smoothing filter coefficients are based on the minimum mean square error smoothing calculation obtained, based on target smoothing filter coefficient initial channel estimation value is smoothed, obtain the target channel estimation value of subcarrier sequence. So as to utilize the preset smoothing coefficient library to reduce the calculation amount of channel smoothing process, and can adopt the minimum mean square error smoothing to carry out channel smoothing, improve the channel smoothing effect.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and more specifically to channel smoothing methods, apparatus, electronic devices, and storage media. Background Technology

[0002] In broadband communication, frequency domain equalization is commonly used for demodulation. The demodulation process includes three steps: channel estimation, channel smoothing, and channel phase difference tracking. Channel smoothing is a crucial factor affecting data demodulation performance. Currently, the weighted averaging of adjacent subcarriers is commonly used for channel smoothing. While this method is computationally simple, it does not fully utilize the statistical characteristics of the channel, and the smoothing effect is not optimal. Summary of the Invention

[0003] This invention provides a channel smoothing method, apparatus, electronic device, and storage medium to address the problem that current signal smoothing methods do not fully utilize the statistical characteristics of the channel, resulting in suboptimal smoothing effects.

[0004] In a first aspect, the present invention provides a channel smoothing method, the method comprising: In response to receiving the target signal, channel estimation is performed on the subcarrier sequence corresponding to the target signal to obtain the initial channel estimate value of the subcarrier sequence; Based on the signal-to-noise ratio estimate of the target signal, the target smoothing filter coefficients are obtained by matching the preset smoothing coefficient library. The preset smoothing coefficient library includes multiple preset smoothing filter coefficients, which correspond one-to-one with multiple preset signal-to-noise ratios. The multiple preset smoothing filter coefficients are obtained by smoothing calculation based on minimum mean square error. The initial channel estimate is smoothed based on the target smoothing filter coefficients to obtain the target channel estimate of the subcarrier sequence.

[0005] In one optional implementation, channel estimation is performed on the subcarrier sequence in the target signal to obtain an initial channel estimate of the subcarrier sequence, including: Based on the least squares method, channel estimation is performed on the first sequence in the subcarrier sequence to obtain the initial channel estimate value of the first sequence, where the first sequence is the sequence in the subcarrier sequence that maps to the training sequence; Based on the initial channel estimate of the first sequence, interpolation is performed at the second sequence in the subcarrier sequence to obtain the initial channel estimate of the second sequence, where the second sequence is the subcarrier sequence that is not mapped to the training sequence and is located in the middle of the subcarrier sequence; Based on the initial channel estimate of the first sequence, a symmetric extrapolation calculation is performed on the third sequence in the subcarrier sequence to obtain the initial channel estimate of the third sequence, where the third sequence is the subcarrier sequence that is not mapped to the training sequence and is located at the edge of the subcarrier sequence.

[0006] In one optional implementation, the target smoothing filter coefficients are obtained by matching a preset smoothing coefficient library based on the signal-to-noise ratio estimate of the target signal, including: The signal-to-noise ratio (SNR) estimate is compared with multiple preset SNR values, and the preset smoothing filter coefficients corresponding to the SNR estimate are determined from the preset smoothing coefficient library. The preset intermediate smoothing filter coefficients in the preset smoothing filter coefficients corresponding to the signal-to-noise ratio estimate are used as the target intermediate smoothing filter coefficients, wherein the number of preset intermediate smoothing filter coefficients is a first preset number. The preset edge smoothing filter coefficients in the preset smoothing filter coefficients corresponding to the signal-to-noise ratio estimate are used as the target edge smoothing filter coefficients. The number of preset edge smoothing filter coefficients is the second preset number, and the first preset number is greater than the second preset number.

[0007] In one optional implementation, the initial channel estimate is smoothed based on the target smoothing filter coefficients to obtain the target channel estimate of the subcarrier sequence, including: For each subcarrier in the fourth sequence of the subcarrier sequence, the target channel estimate of the fourth sequence is obtained based on the target intermediate smoothing filter coefficients and the initial channel estimate of the first preset number of subcarriers after the subcarrier. The fourth sequence is the sequence located in the middle position of the subcarrier sequence. For each subcarrier in the fifth sequence of the subcarrier sequence, the target channel estimate of the fifth sequence is obtained based on the target edge smoothing filter coefficients and the initial channel estimate of a second preset number of subcarriers centered on the subcarrier. The fifth sequence is the sequence located at the edge of the subcarrier sequence.

[0008] In one optional implementation, the preset smoothing filter coefficients are calculated as follows: For each preset signal-to-noise ratio, a smoothing matrix is ​​calculated based on the preset signal-to-noise ratio, the number of subcarriers in the subcarrier sequence, and the correlation between the subcarriers corresponding to the subcarrier sequence. The row of matrix values ​​located at the center of the smoothing matrix is ​​used as the coefficients of the preset smoothing filter.

[0009] In one optional implementation, a smoothing matrix is ​​calculated based on a preset signal-to-noise ratio, the number of subcarriers in the subcarrier sequence, and the correlation between the corresponding subcarriers in the subcarrier sequence, including: Based on the number of subcarriers in the subcarrier sequence and the correlation of the corresponding subcarriers, the correlation matrix corresponding to the smoothing matrix is ​​calculated. The smoothing matrix is ​​calculated based on the smoothing matrix and the preset signal-to-noise ratio.

[0010] In one alternative implementation, the method further includes: Construct the smoothing matrix and its corresponding correlation matrix; Among them, the number of rows and columns of the smoothing matrix and correlation matrix corresponding to the preset intermediate smoothing filter coefficients is the first preset number, and the number of rows and columns of the smoothing matrix and correlation matrix corresponding to the preset edge smoothing filter coefficients is the second preset number.

[0011] In a second aspect, the present invention provides a channel smoothing apparatus, the apparatus comprising: The channel estimation module is used to perform channel estimation on the subcarrier sequence corresponding to the target signal in response to the received target signal, and obtain the initial channel estimation value of the subcarrier sequence; The coefficient determination module is used to match the preset smoothing coefficient library with the signal-to-noise ratio estimate of the target signal to obtain the target smoothing filter coefficients. The preset smoothing coefficient library includes multiple preset smoothing filter coefficients, which correspond one-to-one with multiple preset signal-to-noise ratios. The multiple preset smoothing filter coefficients are obtained based on the minimum mean square error smoothing calculation. The channel smoothing module is used to smooth the initial channel estimate based on the target smoothing filter coefficients to obtain the target channel estimate of the subcarrier sequence.

[0012] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the channel smoothing method of the first aspect or any corresponding embodiment described above.

[0013] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform the channel smoothing method of the first aspect or any corresponding embodiment thereof.

[0014] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the channel smoothing method of the first aspect or any corresponding embodiment thereof.

[0015] The channel smoothing method provided in this invention calculates multiple preset smoothing filter coefficients corresponding to preset signal-to-noise ratios based on minimum mean square error smoothing and constructs a preset smoothing coefficient library. During the channel smoothing process, the preset smoothing coefficient library is matched based on the estimated signal-to-noise ratio of the target signal to obtain the target smoothing filter coefficients. The initial channel estimate is then smoothed based on the target smoothing filter coefficients to obtain the target channel estimate of the subcarrier sequence. This reduces the computational load of the channel smoothing process by utilizing the preset smoothing coefficient library and enables the use of minimum mean square error smoothing to improve the channel smoothing effect. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the first type of channel smoothing method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a second process for a channel smoothing method according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the third process of the channel smoothing method according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the process for calculating the coefficients of a preset smoothing filter in the channel smoothing method according to an embodiment of the present invention; Figure 5 This is a structural block diagram of a channel smoothing device according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0020] In broadband communication, frequency domain equalization is commonly used for demodulation. The demodulation process includes three steps: channel estimation, channel smoothing, and channel tracking. Channel smoothing is an important factor affecting the performance of data demodulation. Currently, the weighted averaging of adjacent subcarriers is commonly used for channel smoothing. The specific smoothing method is shown in the following formula (1): Formula (1) in, For subcarriers The channel estimate after channel smoothing. For subcarriers The channel estimate.

[0021] As shown in formula (1), this method is simple to calculate and only requires the channel estimates of two adjacent subcarriers and the channel estimate of the subcarrier to achieve channel smoothing. However, it does not make full use of the statistical characteristics of the channel, and the smoothing effect is not optimal.

[0022] To address the aforementioned problems, this invention provides a channel smoothing method. In response to receiving a target signal, channel estimation is performed on the subcarrier sequence corresponding to the target signal to obtain an initial channel estimate. Based on the signal-to-noise ratio (SNR) estimate of the target signal, a preset smoothing coefficient library is matched to obtain target smoothing filter coefficients. The preset smoothing coefficient library includes multiple preset smoothing filter coefficients, each corresponding to a preset SNR, and these coefficients are calculated using minimum mean square error (MSE) smoothing. The initial channel estimate is then smoothed using the target smoothing filter coefficients to obtain the target channel estimate for the subcarrier sequence. Thus, by calculating preset smoothing filter coefficients corresponding to multiple preset SNRs using MSE smoothing and constructing a preset smoothing coefficient library, and during channel smoothing, matching the preset smoothing coefficient library with the target signal's SNR estimate to obtain the target smoothing filter coefficients, and then smoothing the initial channel estimate using these target smoothing filter coefficients, the target channel estimate for the subcarrier sequence is obtained. This reduces the computational load of the channel smoothing process by utilizing the preset smoothing coefficient library and improves the channel smoothing effect by employing MSE smoothing.

[0023] According to an embodiment of the present invention, a channel smoothing method embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0024] This embodiment provides a channel smoothing method. Figure 1 This is a schematic diagram of the first type of channel smoothing method according to an embodiment of the present invention, as follows: Figure 1 As shown, the process includes the following steps: Step S101: In response to receiving the target signal, channel estimation is performed on the subcarrier sequence corresponding to the target signal to obtain the initial channel estimation value of the subcarrier sequence.

[0025] In this embodiment of the invention, after receiving the target signal, the training sequence in the target signal is mapped to the corresponding position in the subcarrier to obtain the initial channel estimate value of each subcarrier in the subcarrier sequence.

[0026] Step S102: Based on the signal-to-noise ratio estimate of the target signal, match the preset smoothing coefficient library to obtain the target smoothing filter coefficients.

[0027] In this embodiment of the invention, the preset smoothing coefficient library includes multiple preset smoothing filter coefficients, which correspond one-to-one with multiple preset signal-to-noise ratios. The multiple preset smoothing filter coefficients are calculated based on minimum mean square error smoothing (MMSE), which can minimize the mean square error between the estimated value and the real channel and has excellent smoothing effect.

[0028] In this embodiment of the invention, the signal-to-noise ratio (SNR) of the target signal is estimated to obtain an estimated SNR value. The SNR estimation method can be based on the noise variance of the training sequence of the target signal, or it can utilize the time-domain or frequency-domain characteristics of the training sequence, such as the ratio of the energy of the effective subcarrier to the energy on the empty subcarrier (or guard interval). No specific limitations are imposed here. Based on the estimated SNR value, a preset smoothing coefficient library is matched to obtain the preset smoothing filter coefficients corresponding to the estimated SNR value, which are the target smoothing filter coefficients.

[0029] In one optional implementation, a preset smoothing coefficient library stores multiple preset smoothing filter coefficients that correspond one-to-one with a preset signal-to-noise ratio (SNR). When matching the SNR estimate with a preset SNR, if a preset SNR that matches the SNR estimate exists (e.g., the SNR estimate is equal to the preset SNR), or the SNR estimate is within the matching range corresponding to the preset SNR (e.g., within ±1 dB of the preset SNR), the preset smoothing filter coefficient corresponding to the matched preset SNR is determined as the target smoothing filter coefficient. If no preset SNR that matches the SNR estimate exists, the preset SNR in the preset smoothing coefficient library that is closest to the SNR estimate is determined as the preset SNR to be matched with the SNR estimate, and the corresponding preset smoothing filter coefficient is determined as the target smoothing filter coefficient.

[0030] Step S103: Smooth the initial channel estimate based on the target smoothing filter coefficients to obtain the target channel estimate of the subcarrier sequence.

[0031] In this embodiment of the invention, the initial channel estimate is smoothed using the coefficients of the target smoothing filter to obtain the target channel estimate of the subcarrier sequence.

[0032] This embodiment provides a channel smoothing method. Figure 2 This is a schematic diagram of a second process for a channel smoothing method according to an embodiment of the present invention, as shown below. Figure 2 As shown, the process includes the following steps: Step S201: In response to receiving the target signal, channel estimation is performed on the subcarrier sequence corresponding to the target signal to obtain the initial channel estimation value of the subcarrier sequence.

[0033] Specifically, step S201 includes: Step S2011: Based on the least squares method, channel estimation is performed on the first sequence in the subcarrier sequence to obtain the initial channel estimation value of the first sequence.

[0034] In this embodiment of the invention, the first sequence is the sequence of subcarriers mapped to the training sequence. The length of the subcarrier sequence is 256, and the length of the training sequence is 242. These 242 sequence points are mapped to corresponding positions in the 256 subcarriers. Therefore, 14 subcarriers are not mapped to the training sequence: subcarriers 0-6, 128-130, and 252-256. The first sequence is the sequence of the 242 subcarriers mapped to the training sequence, namely the subcarrier sequences 7-127 and 131-251.

[0035] In this embodiment of the invention, channel estimation is performed on the first sequence in the subcarrier sequence based on the least squares method to obtain the initial channel estimation value of the first sequence, which can be specifically shown in the following formula (2): Formula (2) in, For subcarriers The initial channel estimate, For training sequences on subcarriers Frequency domain values, This refers to the frequency domain received signal corresponding to the received signal.

[0036] Step S2012: Based on the initial channel estimate of the first sequence, interpolation calculation is performed at the second sequence in the subcarrier sequence to obtain the initial channel estimate of the second sequence.

[0037] In this embodiment of the invention, the second sequence is the subcarrier sequence that is not mapped to the training sequence and is located in the middle of the subcarrier sequence, that is, subcarriers 128-130 in the subcarrier sequence. Based on the initial channel estimate of the first sequence, linear interpolation is performed on the second sequence to obtain the initial channel estimate of the second sequence.

[0038] Step S2013: Based on the initial channel estimate of the first sequence, perform symmetric extrapolation calculation on the third sequence in the subcarrier sequence to obtain the initial channel estimate of the third sequence.

[0039] In this embodiment of the invention, the third sequence is the sequence in the subcarrier sequence that is not mapped to the training sequence and is located at the edge of the subcarrier sequence, that is, subcarriers 0-6 and 252-256 in the subcarrier sequence. Based on the initial channel estimate of the first sequence, the third sequence is calculated by symmetric extrapolation to obtain the initial channel estimate of the third sequence. For subcarriers 0-6 in the subcarrier sequence, the specific calculation method can be shown in the following formula (3), and for subcarriers 252-256 in the subcarrier sequence, the specific calculation method can be shown in the following formula (4).

[0040] Formula (3) Formula (4) Step S202: Based on the estimated signal-to-noise ratio of the target signal, match the preset smoothing coefficient library to obtain the target smoothing filter coefficients. For details, please refer to [link to relevant documentation]. Figure 1 Step S102 of the illustrated embodiment will not be described again here.

[0041] Step S203: Smooth the initial channel estimate based on the target smoothing filter coefficients to obtain the target channel estimate for the subcarrier sequence. For details, please refer to [link to details]. Figure 1Step S103 of the illustrated embodiment will not be described again here.

[0042] This embodiment provides a channel smoothing method. Figure 3 This is a schematic diagram of the third process of the channel smoothing method according to an embodiment of the present invention, as follows: Figure 3 As shown, the process includes the following steps: Step S301: In response to receiving the target signal, channel estimation is performed on the subcarrier sequence corresponding to the target signal to obtain the initial channel estimate value of the subcarrier sequence. For details, please refer to [link to details]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0043] Step S302: Based on the signal-to-noise ratio estimate of the target signal, match the preset smoothing coefficient library to obtain the target smoothing filter coefficients.

[0044] In this embodiment of the invention, a set of preset smoothing filter coefficients includes preset intermediate smoothing filter coefficients and preset edge smoothing filter coefficients. The preset intermediate smoothing filter coefficients are used to smooth the channel of the sequence at the middle position of the subcarrier sequence, and the preset edge smoothing filter coefficients are used to smooth the channel of the sequence at the edge position of the subcarrier sequence. The number of preset intermediate smoothing filter coefficients is a first preset number, and the number of preset edge smoothing filter coefficients is a second preset number, where the first preset number is greater than the second preset number. Correspondingly, the signal-to-noise ratio (SNR) estimate is compared with multiple preset SNR values. The preset smoothing filter coefficients corresponding to the SNR estimate are determined from the preset smoothing coefficient library. The preset intermediate smoothing filter coefficients from the preset smoothing filter coefficients corresponding to the SNR estimate are used as the target intermediate smoothing filter coefficients, and the preset edge smoothing filter coefficients from the preset smoothing filter coefficients corresponding to the SNR estimate are used as the target edge smoothing filter coefficients.

[0045] Step S303: Smooth the initial channel estimate based on the target smoothing filter coefficients to obtain the target channel estimate of the subcarrier sequence.

[0046] Specifically, step S303 includes: Step S3031: For each subcarrier in the fourth sequence of the subcarrier sequence, perform smoothing filtering based on the target intermediate smoothing filter coefficients and the initial channel estimate of the first preset number of subcarriers after the subcarrier to obtain the target channel estimate of the fourth sequence.

[0047] In this embodiment of the invention, the fourth sequence is the sequence located in the middle of the subcarrier sequence, specifically subcarriers 10-247 in the subcarrier sequence. For each subcarrier in the fourth sequence of the subcarrier sequence, the target intermediate smoothing filter coefficients are used, combined with the initial channel estimate of the first preset number of subcarriers after the subcarrier, to smooth the subcarrier, specifically as shown in the following formula (5): Formula (5) in, For subcarriers The target channel estimate, The target intermediate smoothing filter coefficients contain the following number of coefficients: .

[0048] Step S3032: For each subcarrier in the fifth sequence of the subcarrier sequence, perform smoothing filtering based on the target edge smoothing filter coefficients and the initial channel estimate of the second preset number of subcarriers centered on the subcarrier to obtain the target channel estimate of the fifth sequence.

[0049] In this embodiment of the invention, the fifth sequence is the sequence located at the edge of the subcarrier sequence, specifically subcarriers 6-9 and 247-249 in the subcarrier sequence. For each subcarrier in the fifth sequence, the target edge smoothing filter coefficients are used, combined with the initial channel estimate of a second preset number of subcarriers centered on the subcarrier, to smooth the subcarrier, specifically as shown in the following formula (6): Formula (6) in, The target edge smoothing filter coefficients contain the following number of coefficients: .

[0050] The channel smoothing method provided in the above embodiments, Figure 4 This is a flowchart illustrating the calculation of preset smoothing filter coefficients in a channel smoothing method according to an embodiment of the present invention, as shown below. Figure 4 As shown, the preset smoothing filter coefficients are calculated as follows: Step S401: For each preset signal-to-noise ratio, a smoothing matrix is ​​calculated based on the preset signal-to-noise ratio, the number of subcarriers in the subcarrier sequence, and the correlation of the subcarriers corresponding to the subcarrier sequence.

[0051] In this embodiment of the invention, for each preset signal-to-noise ratio, a corresponding smoothing matrix is ​​calculated to extract the corresponding preset smoothing filter coefficients. The smoothing matrix is ​​calculated based on the preset signal-to-noise ratio, the number of subcarriers in the subcarrier sequence, and the correlation between the corresponding subcarriers.

[0052] In an optional implementation, the correlation matrix corresponding to the smoothing matrix is ​​calculated based on the number of subcarriers in the subcarrier sequence and the correlation of the subcarriers corresponding to the subcarrier sequence. The value of each element in the correlation matrix can be calculated using the following formula (7): Formula (7) in, For subcarriers and subcarriers The correlation between them This refers to the number of subcarriers. For root mean square delay spread, It can take the value 1.

[0053] In one optional implementation, the smoothing matrix is ​​calculated based on the smoothing matrix and a preset signal-to-noise ratio, as shown in the following formula (8): Formula (8) in, For smoothing matrices, For the correlation matrix, For signal-to-noise ratio, It is an identity matrix.

[0054] In one optional implementation, the preset intermediate smoothing filter coefficients and preset edge smoothing filter coefficients have different numbers of coefficients. Therefore, smoothing matrices of different sizes are constructed to calculate the preset intermediate smoothing filter coefficients and preset edge smoothing filter coefficients separately. Correspondingly, smoothing matrices and their corresponding correlation matrices are constructed. For the preset smoothing filter coefficients, the number of rows and columns in the smoothing matrix and correlation matrix corresponding to the preset intermediate smoothing filter coefficients is a first preset number, and the number of rows and columns in the smoothing matrix and correlation matrix corresponding to the preset edge smoothing filter coefficients is a second preset number. For example, if the number of coefficients in the preset intermediate smoothing filter coefficients is 17, then the smoothing matrix and correlation matrix are 17×17 matrices; if the number of coefficients in the preset edge smoothing filter coefficients is 9, then the smoothing matrix and correlation matrix are 9×9 matrices.

[0055] Step S402: Take the row of matrix values ​​located at the center of the smoothing matrix as the preset smoothing filter coefficients.

[0056] In this embodiment of the invention, the row of matrix values ​​located in the center of the smoothing matrix is ​​used as the preset intermediate smoothing filter coefficient. For example, for the preset intermediate smoothing filter coefficient, if the smoothing matrix is ​​a 17×17 matrix, the 9th row in the middle is selected as the preset intermediate smoothing filter coefficient. For the preset edge smoothing filter coefficient, if the smoothing matrix is ​​a 9×9 matrix, the 5th row in the middle is selected as the preset edge smoothing filter coefficient.

[0057] The channel smoothing method provided in this invention calculates multiple preset smoothing filter coefficients corresponding to preset signal-to-noise ratios based on minimum mean square error smoothing and constructs a preset smoothing coefficient library. During the channel smoothing process, the preset smoothing coefficient library is matched based on the estimated signal-to-noise ratio of the target signal to obtain the target smoothing filter coefficients. The initial channel estimate is then smoothed based on the target smoothing filter coefficients to obtain the target channel estimate of the subcarrier sequence. This reduces the computational load of the channel smoothing process by utilizing the preset smoothing coefficient library and enables the use of minimum mean square error smoothing to improve the channel smoothing effect.

[0058] This embodiment also provides a channel smoothing device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0059] This embodiment provides a channel smoothing device, such as... Figure 5 As shown, it includes: The channel estimation module 501 is used to perform channel estimation on the subcarrier sequence corresponding to the target signal in response to receiving the target signal, and obtain the initial channel estimation value of the subcarrier sequence; The coefficient determination module 502 is used to match the preset smoothing coefficient library based on the signal-to-noise ratio estimate of the target signal to obtain the target smoothing filter coefficients. The preset smoothing coefficient library includes multiple preset smoothing filter coefficients, which correspond one-to-one with multiple preset signal-to-noise ratios. The multiple preset smoothing filter coefficients are obtained based on the minimum mean square error smoothing calculation. The channel smoothing module 503 is used to smooth the initial channel estimate based on the target smoothing filter coefficients to obtain the target channel estimate of the subcarrier sequence.

[0060] In one optional implementation, the channel estimation module 501 includes: The first estimation unit is used to perform channel estimation on the first sequence in the subcarrier sequence based on the least squares method to obtain the initial channel estimation value of the first sequence, wherein the first sequence is the sequence in the subcarrier sequence that is mapped to the training sequence; The second estimation unit is used to perform interpolation calculations at the second sequence in the subcarrier sequence based on the initial channel estimation value of the first sequence to obtain the initial channel estimation value of the second sequence, wherein the second sequence is the sequence in the subcarrier sequence that is not mapped to the training sequence and is located in the middle of the subcarrier sequence; The third estimation unit is used to perform symmetric extrapolation calculation on the third sequence in the subcarrier sequence based on the initial channel estimate of the first sequence to obtain the initial channel estimate of the third sequence, wherein the third sequence is the sequence in the subcarrier sequence that is not mapped to the training sequence and is located at the edge of the subcarrier sequence.

[0061] In one optional implementation, the coefficient determination module 502 includes: The signal-to-noise ratio comparison unit is used to compare the estimated signal-to-noise ratio with multiple preset signal-to-noise ratios and determine the preset smoothing filter coefficients corresponding to the estimated signal-to-noise ratio from the preset smoothing coefficient library. The first determining unit is used to take the preset intermediate smoothing filter coefficients from the preset smoothing filter coefficients corresponding to the signal-to-noise ratio estimate as the target intermediate smoothing filter coefficients, wherein the number of preset intermediate smoothing filter coefficients is a first preset number. The second determining unit is used to take the preset edge smoothing filter coefficients in the preset smoothing filter coefficients corresponding to the signal-to-noise ratio estimate as the target edge smoothing filter coefficients, wherein the number of preset edge smoothing filter coefficients is a second preset number, and the first preset number is greater than the second preset number.

[0062] In one alternative implementation, the channel smoothing module 503 includes: The first smoothing unit is used to perform smoothing filtering on each subcarrier of the fourth sequence in the subcarrier sequence based on the target intermediate smoothing filter coefficients and the initial channel estimates of the first preset number of subcarriers after the subcarrier, to obtain the target channel estimate of the fourth sequence, wherein the fourth sequence is the sequence located in the middle position of the subcarrier sequence; The second smoothing unit is used to perform smoothing filtering on each subcarrier in the fifth sequence of the subcarrier sequence based on the target edge smoothing filter coefficients and the initial channel estimate of a second preset number of subcarriers centered on the subcarrier, to obtain the target channel estimate of the fifth sequence, wherein the fifth sequence is the sequence located at the edge position in the subcarrier sequence.

[0063] In one alternative embodiment, the device further includes: The smoothing matrix calculation module is used to calculate the smoothing matrix for each preset signal-to-noise ratio, based on the preset signal-to-noise ratio, the number of subcarriers in the subcarrier sequence, and the correlation of the subcarriers corresponding to the subcarrier sequence. The coefficient selection module is used to select the row of matrix values ​​located at the center of the smoothing matrix as the preset smoothing filter coefficients.

[0064] In one alternative implementation, the smoothing matrix calculation module includes: The correlation matrix calculation unit is used to calculate the correlation matrix corresponding to the smoothing matrix based on the number of subcarriers in the subcarrier sequence and the correlation of the subcarriers corresponding to the subcarrier sequence. The smoothing matrix calculation unit is used to calculate the smoothing matrix based on the smoothing matrix and the preset signal-to-noise ratio.

[0065] In one alternative embodiment, the device further includes: The matrix construction module is used to construct smooth matrices and their corresponding correlation matrices. Among them, the number of rows and columns of the smoothing matrix and correlation matrix corresponding to the preset intermediate smoothing filter coefficients is the first preset number, and the number of rows and columns of the smoothing matrix and correlation matrix corresponding to the preset edge smoothing filter coefficients is the second preset number.

[0066] The channel smoothing apparatus provided in this embodiment of the invention can execute the channel smoothing method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the various modules and units described above are the same as in the corresponding embodiments described above, and will not be repeated here.

[0067] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0068] The following is a detailed reference. Figure 6 This diagram illustrates a suitable structural design for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 601, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 602 or a program loaded from memory 608 into random access memory (RAM) 603. RAM 603 also stores various programs and data required for the operation of the electronic device. The processor 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0069] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0070] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a memory 608, or installed from a ROM 602. When the computer program is executed by the processor 601, it performs the functions defined in the channel smoothing method of the embodiments of the present invention.

[0071] Figure 6 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0072] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded over a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the channel smoothing method shown in the above embodiments is implemented.

[0073] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0074] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A channel smoothing method, characterized in that, The method includes: In response to receiving a target signal, channel estimation is performed on the subcarrier sequence corresponding to the target signal to obtain an initial channel estimate value for the subcarrier sequence; Based on the signal-to-noise ratio estimate of the target signal, a preset smoothing coefficient library is matched to obtain the target smoothing filter coefficients. The preset smoothing coefficient library includes multiple preset smoothing filter coefficients, each of which corresponds one-to-one with a preset signal-to-noise ratio. The multiple preset smoothing filter coefficients are obtained based on minimum mean square error smoothing calculation. The initial channel estimate is smoothed based on the target smoothing filter coefficients to obtain the target channel estimate of the subcarrier sequence.

2. The method according to claim 1, characterized in that, The step of performing channel estimation on the subcarrier sequence in the target signal to obtain the initial channel estimate value of the subcarrier sequence includes: Based on the least squares method, channel estimation is performed on the first sequence in the subcarrier sequence to obtain the initial channel estimation value of the first sequence, wherein the first sequence is the sequence in the subcarrier sequence that is mapped to the training sequence; Based on the initial channel estimate of the first sequence, interpolation is performed at the second sequence in the subcarrier sequence to obtain the initial channel estimate of the second sequence, wherein the second sequence is the sequence in the subcarrier sequence that is not mapped to the training sequence and is located in the middle of the subcarrier sequence; Based on the initial channel estimate of the first sequence, a symmetric extrapolation calculation is performed on the third sequence in the subcarrier sequence to obtain the initial channel estimate of the third sequence, wherein the third sequence is the sequence in the subcarrier sequence that is not mapped to the training sequence and is located at the edge of the subcarrier sequence.

3. The method according to claim 1, characterized in that, The step of matching the target smoothing filter coefficients to a preset smoothing coefficient library based on the signal-to-noise ratio estimate of the target signal includes: The signal-to-noise ratio estimate is compared with multiple preset signal-to-noise ratios, and the preset smoothing filter coefficients corresponding to the signal-to-noise ratio estimate are determined from the preset smoothing coefficient library. The preset intermediate smoothing filter coefficients in the preset smoothing filter coefficients corresponding to the signal-to-noise ratio estimate are taken as the target intermediate smoothing filter coefficients, wherein the number of preset intermediate smoothing filter coefficients is a first preset number. The preset edge smoothing filter coefficients in the preset smoothing filter coefficients corresponding to the signal-to-noise ratio estimate are used as the target edge smoothing filter coefficients, wherein the number of preset edge smoothing filter coefficients is a second preset number, and the first preset number is greater than the second preset number.

4. The method according to claim 3, characterized in that, The step of smoothing the initial channel estimate based on the target smoothing filter coefficients to obtain the target channel estimate of the subcarrier sequence includes: For each subcarrier in the fourth sequence of the subcarrier sequence, a smoothing filter is performed based on the target intermediate smoothing filter coefficients and the initial channel estimates of the first preset number of subcarriers after the subcarrier to obtain the target channel estimate of the fourth sequence, wherein the fourth sequence is the sequence located in the middle position of the subcarrier sequence; For each subcarrier in the fifth sequence of the subcarrier sequence, a smoothing filter is performed based on the target edge smoothing filter coefficients and the initial channel estimate of the second preset number of subcarriers centered on the subcarrier to obtain the target channel estimate of the fifth sequence, wherein the fifth sequence is the sequence located at the edge of the subcarrier sequence.

5. The method according to any one of claims 1-4, characterized in that, The preset smoothing filter coefficients are calculated in the following manner: For each preset signal-to-noise ratio, a smoothing matrix is ​​calculated based on the preset signal-to-noise ratio, the number of subcarriers in the subcarrier sequence, and the correlation of the subcarriers corresponding to the subcarrier sequence; The row of matrix values ​​located at the center of the smoothing matrix is ​​used as the coefficients of the preset smoothing filter.

6. The method according to claim 5, characterized in that, The smoothing matrix is ​​calculated based on the preset signal-to-noise ratio, the number of subcarriers in the subcarrier sequence, and the correlation of the subcarriers corresponding to the subcarrier sequence, including: Based on the number of subcarriers in the subcarrier sequence and the correlation of the subcarriers corresponding to the subcarrier sequence, the correlation matrix corresponding to the smoothing matrix is ​​calculated; The smoothing matrix is ​​calculated based on the smoothing matrix and the preset signal-to-noise ratio.

7. The method according to claim 5, characterized in that, The method further includes: Construct the smoothing matrix and the corresponding correlation matrix; Among the preset smoothing filter coefficients, the number of rows and columns of the smoothing matrix and correlation matrix corresponding to the preset intermediate smoothing filter coefficients is a first preset number, and the number of rows and columns of the smoothing matrix and correlation matrix corresponding to the preset edge smoothing filter coefficients is a second preset number.

8. A channel smoothing device, characterized in that, The device includes: The channel estimation module is used to perform channel estimation on the subcarrier sequence corresponding to the target signal in response to receiving the target signal, so as to obtain the initial channel estimation value of the subcarrier sequence; The coefficient determination module is used to match the preset smoothing coefficient library based on the signal-to-noise ratio estimate of the target signal to obtain the target smoothing filter coefficients. The preset smoothing coefficient library includes multiple preset smoothing filter coefficients, which correspond one-to-one with multiple preset signal-to-noise ratios. The multiple preset smoothing filter coefficients are obtained based on minimum mean square error smoothing calculation. The channel smoothing module is used to smooth the initial channel estimate based on the target smoothing filter coefficients to obtain the target channel estimate of the subcarrier sequence.

9. An electronic device, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform the channel smoothing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a computer to perform the channel smoothing method according to any one of claims 1 to 7.

Images