Method, apparatus and device for channel filter design, and computer storage medium

Abstract

The application discloses a method, device and equipment for designing a channel filter and a computer storage medium, and relates to the technical field of wireless communication. The method comprises the following steps: acquiring a signal bandwidth, a baseband sampling rate, a frequency of adjacent channel interference, a noise power spectral density of adjacent channel interference and a noise power spectral density of a signal; calculating a normalized passband cutoff frequency, a normalized stopband cutoff frequency and a stopband attenuation according to the acquired parameters; determining a channel filter coefficient according to the normalized passband cutoff frequency, the normalized stopband cutoff frequency and the stopband attenuation, and obtaining a channel filter corresponding to the channel filter coefficient; inserting a preset value into the channel filter coefficient to obtain a target channel filter coefficient, updating the channel filter, and obtaining a target channel filter. The embodiment of the application realizes the design of a steep transition band channel filter while reducing the structural complexity.

Description

Technical Field

[0001] This application belongs to the field of wireless communication technology, and in particular relates to a method, apparatus, device and computer storage medium for designing channel filters. Background Technology

[0002] With the rapid development of wireless communication technology, the lightweight terminal RedCap has become an important technology branch in 5G networks. RedCap systems may be deployed in complex communication environments with numerous wireless signal sources, where the terminal is highly susceptible to interference from adjacent channel signals of high-power uplink signals from other users when receiving downlink signals.

[0003] To address the vulnerability of RedCap systems to interference from adjacent channels, channel filters are often used to remove this interference. Since adjacent channel interference may be very close to the signal in the frequency domain, channel filters typically require a steep transition band. However, existing filter design methods often result in channel filters with high orders, which require a large number of multipliers and shift registers in hardware implementation, making the structure of steep transition band channel filters quite complex. Summary of the Invention

[0004] This application provides a method, apparatus, device, and computer storage medium for designing channel filters to address the problem of complex structures in existing steep transition band channel filters.

[0005] In a first aspect, embodiments of this application provide a method for designing a channel filter, the method comprising:

[0006] Acquire the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, and noise power spectral density of the signal;

[0007] Based on the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, noise power spectral density of the signal, and preset baseband multiple, calculate the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation.

[0008] The channel filter coefficients are determined based on the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation, and the corresponding channel filter is obtained.

[0009] Insert a preset number of preset values ​​into the channel filter coefficients to obtain the target channel filter coefficients and update the channel filter to obtain the target channel filter.

[0010] Secondly, embodiments of this application provide an apparatus for designing a channel filter, the apparatus comprising:

[0011] The acquisition module is used to acquire the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, and noise power spectral density of the signal.

[0012] The calculation module is used to calculate the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation based on the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, noise power spectral density of the signal, and preset baseband multiple.

[0013] The determination module is used to determine the channel filter coefficients based on the normalized passband cutoff frequency, the normalized stopband cutoff frequency, and the stopband attenuation, and to obtain the channel filter corresponding to the channel filter coefficients.

[0014] The update module is used to insert a preset number of preset values ​​into the channel filter coefficients to obtain the target channel filter coefficients and update the channel filter to obtain the target channel filter.

[0015] Thirdly, embodiments of this application provide a terminal device, the device including: a processor and a memory storing computer program instructions; the processor executes the computer program instructions to implement the channel filter design method as described in the first aspect.

[0016] Fourthly, embodiments of this application provide a computer storage medium storing computer program instructions, which, when executed by a processor, implement the channel filter design method as described in the first aspect.

[0017] Fifthly, embodiments of this application provide a computer program product in which instructions, when executed by a processor of an electronic device, cause the electronic device to perform a channel filter design method as described in the first aspect.

[0018] This application provides a method, apparatus, device, and computer storage medium for designing a channel filter. The method first obtains the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of the adjacent channel interference, and noise power spectral density of the signal; providing parameters for filter design to ensure the filter design meets specific signal processing requirements. Based on the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of the adjacent channel interference, noise power spectral density of the signal, and a preset baseband factor, the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation are calculated; calculating parameters such as the normalized frequency and stopband attenuation helps determine the specific requirements of the filter design. The channel filter coefficients are determined based on the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation, resulting in a channel filter corresponding to the channel filter coefficients; by using parameters calculated based on the preset baseband factor to determine the filter coefficients, the resulting channel filter has a smoother transition band, reducing the complexity of the channel filter. By inserting a preset number of preset values ​​into the channel filter coefficients, the target channel filter coefficients are obtained, and the channel filter is updated to obtain the target channel filter. Through interpolation, the transition band of the target channel filter is reduced, making the transition band steeper again. This embodiment first designs a channel filter with a relatively gentle transition band, reducing the complexity of the filter. Then, through interpolation, the range of the filter's transition band is reduced. Utilizing the limited hardware resources required for a wide transition band filter, the design of a steep transition band channel filter is achieved, thereby reducing the structural complexity of the steep transition band channel filter. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the channel filter design method provided in an embodiment of this application;

[0021] Figure 2 This is a flowchart illustrating one implementation of calculating the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation provided in an embodiment of this application.

[0022] Figure 3 This is a flowchart illustrating one implementation of determining channel filter coefficients provided in an embodiment of this application;

[0023] Figure 4 This is a flowchart illustrating one implementation of signal filtering provided in an embodiment of this application;

[0024] Figure 5 This is a flowchart illustrating one implementation of signal resampling provided in an embodiment of this application;

[0025] Figure 6 This is a schematic diagram of the structure of the channel filter design device provided in the embodiments of this application;

[0026] Figure 7 This is a schematic diagram of the structure of the terminal device provided in the embodiments of this application. Detailed Implementation

[0027] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0028] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0029] Existing lightweight RedCap terminal systems may be deployed in complex communication environments with numerous wireless signal sources. When receiving downlink signals, the terminal is highly susceptible to interference from adjacent channel signals of high-power uplink signals from other users. Because adjacent channel interference and the desired signal are very close in frequency domain, the designed single-stage Type I Finite Impulse Response (FIR) filter requires a very steep transition band, resulting in an excessively high order for the single-stage FIR filter. This necessitates the use of numerous multipliers and shift registers in hardware implementation, leading to excessive complexity and significantly increased area, power consumption, and cost. Furthermore, channel filters operating at a single baseband sampling rate can only filter narrowband adjacent channel interference within the single baseband sampling rate range, failing to filter broadband adjacent channel interference. Broadband adjacent channel interference can alias into the desired signal during downsampling by the preceding filter, impairing the signal-to-interference-plus-noise ratio (SNR) of the desired signal. Addressing this issue would further increase the number of multipliers required by the filter, increasing the demand for hardware computing resources.

[0030] To address the problems of existing technologies, embodiments of this application provide a method, apparatus, device, and computer storage medium for designing a channel filter. First, the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, and noise power spectral density of the signal are obtained; these parameters provide the basis for filter design, ensuring that the filter design meets specific signal processing requirements. Based on the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, noise power spectral density of the signal, and a preset baseband factor, the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation are calculated; calculating parameters such as the normalized frequency and stopband attenuation helps determine the specific requirements of the filter design. The channel filter coefficients are determined based on the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation, resulting in the corresponding channel filter. By using parameters calculated based on the preset baseband factor to determine the filter coefficients, the resulting channel filter has a smoother transition band, reducing the complexity of the channel filter. By inserting a preset number of preset values ​​into the channel filter coefficients, the target channel filter coefficients are obtained, and the channel filter is updated to obtain the target channel filter. Through interpolation, the transition band of the target channel filter is reduced, making the transition band steeper again. This embodiment first designs a channel filter with a relatively gentle transition band, reducing the complexity of the filter. Then, through interpolation, the range of the filter's transition band is reduced. Utilizing the limited hardware resources required for a wide transition band filter, the design of a steep transition band channel filter is achieved, thereby reducing the structural complexity of a steep transition band.

[0031] The method for designing channel filters provided in the embodiments of this application will be described below with reference to the accompanying drawings.

[0032] Figure 1 A flowchart illustrating a method for designing a channel filter according to an embodiment of this application is shown. Figure 1 As shown, the method may include the following steps: S101 to S104.

[0033] S101, acquire the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference and noise power spectral density of the signal.

[0034] Wherein, the signal is the signal that the terminal receives and needs to be received and processed; the signal bandwidth is the width occupied in the frequency domain of the signal; the baseband sampling rate is the sampling frequency of the signal in the baseband; the frequency of adjacent channel interference is the frequency of the interfering signal in the channel adjacent to the signal; the noise power spectral density of adjacent channel interference is the power distribution of the channel interference noise in a unit frequency band; and the noise power spectral density of the signal is the power distribution of the signal's own noise in a unit frequency band.

[0035] The signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, and noise power spectral density of the signal determine the performance requirements of the filter. For example, the signal bandwidth determines the signal processing range of the filter, the baseband sampling rate determines the rate at which the filter processes the signal, the frequency and noise power spectral density of adjacent channel interference determine the type and degree of interference that the filter needs to suppress, and the noise power spectral density of the signal is used to determine the signal-to-noise ratio requirements of the filter.

[0036] By obtaining these parameters, the performance requirements of the filter can be determined, ensuring that the filter can be designed and filtered for specific signal and interference environments.

[0037] S102, calculate the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation based on the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, noise power spectral density of the signal, and preset baseband multiple.

[0038] Among them, the preset baseband multiple is the multiple of the baseband sampling rate at which the designed channel filter operates, that is, the channel filter operates at the baseband sampling rate of the preset baseband multiple; the normalized passband cutoff frequency is the ratio of the passband cutoff frequency to the sampling frequency; the normalized stopband cutoff frequency is the ratio of the stopband cutoff frequency to the sampling frequency; and the stopband attenuation is the degree of signal attenuation within the stopband.

[0039] Because a preset baseband factor has been added, the channel filter now operates at N times the baseband sampling rate, i.e., f s =Nf0, expanding the steep transition zone by N times yields the wide transition zone B. t ′ rans :

[0040] B t ′ rans =N×B trans =N(f intern,low -B sig / 2)

[0041] Among them, B t ′ rans For wide transition bands, N is the preset baseband multiple, B trans To pre-determine a steep transition zone, f intern,low B is the lowest frequency point of adjacent channel interference. sig f is the signal bandwidth of the signal. s This represents the baseband sampling rate.

[0042] By calculating the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation, key performance indicators for filter design are calculated based on the obtained parameters, which are then used in the filter design process.

[0043] S103, determine the channel filter coefficients based on the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation, and obtain the channel filter corresponding to the channel filter coefficients.

[0044] The channel filter coefficients include at least one coefficient. When determining the channel filter coefficients, the appropriate filter type is first determined by the normalized passband cutoff frequency, normalized stopband cutoff frequency, stopband attenuation, and application requirements. Then, the order of the filter and the coefficients corresponding to the order are determined by a preset algorithm, thereby obtaining the designed filter.

[0045] In some embodiments, the filter type may include Butterworth filter, Chebyshev filter, elliptic filter, etc.

[0046] The required filter order is calculated based on the filter design formula corresponding to the filter type. The filter order refers to the highest power of the transfer function polynomial contained in the filter. The higher the order, the narrower the transition band of the filter and the higher the computational complexity.

[0047] In one example, the filter type is a Butterworth filter, and the filter calculation formula for a Butterworth filter is:

[0048]

[0049] Where Q is the filter order, A stop For stopband attenuation, ω stop ω is the normalized stopband cutoff frequency. pass This is the normalized passband cutoff frequency.

[0050] The ideal frequency response of the channel filter is calculated based on the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation.

[0051] Based on the determined order and ideal frequency response, filter coefficients are calculated using digital filter design methods. For FIR filters, the window function method can be used. First, the ideal frequency response is multiplied by a window function to determine the actual frequency response. Then, the inverse Discrete Fourier Transform (DFT) is performed to obtain the filter coefficients.

[0052] This channel filter is a wide transition band filter. Because of its wide transition band, fewer multipliers and shift registers are used in the hardware implementation, resulting in lower complexity of the channel filter.

[0053] S104, insert a preset number of preset values ​​into the channel filter coefficients to obtain the target channel filter coefficients and update the channel filter to obtain the target channel filter.

[0054] Because a preset baseband factor is incorporated into the calculation, the channel filter operates at N times the baseband sampling rate. The passband and transition band of this channel filter are simultaneously expanded by N times, making it a low-complexity wide transition band filter. It cannot directly filter the signal, so the filter coefficients need to be interpolated.

[0055] In some embodiments, when inserting a preset number of preset values ​​into the channel filter coefficients, N-1 zero values ​​can be inserted after each coefficient to perform N-fold interpolation on the coefficients.

[0056] In one example, the channel filter coefficients are b1, b2, b3, ... b k Let k be the filter order. After N times the difference, the target channel filter coefficients are obtained. The target filter coefficients B can be expressed as B = {b1,0,…,0,b2,0,…,0,b} k ,0,…,0}.

[0057] After interpolating the coefficients by a factor of N, both the passband and transition band of the filter will be reduced by a factor of N. The transition band of the filter after N-fold interpolation satisfies:

[0058]

[0059] Among them, B t ″ rans For the transition band after N times interpolation, B t ′ rans For wide transition bands, N is the preset baseband multiple, B trans A steep transition zone is pre-designed.

[0060] After interpolation, the transition band of the filter becomes steep again. Since the coefficients are interpolated to zero, no new multipliers are needed in the hardware implementation. In other words, this proposal achieves the design of a steep transition band channel filter using the small amount of hardware resources required for a wide transition band filter.

[0061] First, obtain the parameters required for the filter design to ensure it meets specific signal processing needs. Calculating parameters such as normalized frequency and stopband attenuation helps determine the specific requirements of the filter design. By determining the filter coefficients using parameters calculated based on a preset baseband factor, the resulting channel filter has a relatively smooth transition band, reducing its complexity. Through interpolation, the transition band of the target channel filter is narrowed, making it steep again. By designing a channel filter with a relatively smooth transition band, reducing its complexity, and then narrowing the range of the filter's transition band through interpolation, a steep transition band channel filter design is achieved using the limited hardware resources required for a wide transition band filter, thereby reducing the structural complexity of a steep transition band.

[0062] In some embodiments, such as Figure 2 As shown, the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation are calculated based on the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, noise power spectral density of the signal, and preset baseband multiple. This can include steps S201 to S203.

[0063] S201, calculate the normalized passband cutoff frequency based on the preset baseband multiple, signal bandwidth and baseband sampling rate;

[0064] S202, calculate the normalized stopband cutoff frequency based on the preset baseband multiple, the frequency of adjacent channel interference, and the baseband sampling rate;

[0065] S203, calculate the stopband attenuation based on the noise power spectral density of the adjacent channel interference and the noise power spectral density of the signal.

[0066] By calculating the normalized passband cutoff frequency and the normalized stopband cutoff frequency, it is ensured that the channel filter can accurately pass signals within the useful signal band, while effectively suppressing adjacent channel interference, thereby helping to reduce signal distortion; by calculating the stopband attenuation, it is ensured that the channel filter can provide sufficient attenuation within the stopband.

[0067] In some embodiments, the normalized passband cutoff frequency is calculated based on a preset baseband multiple, signal bandwidth, and baseband sampling rate. The calculation formula can be:

[0068]

[0069] Where, ω passThe normalized passband cutoff frequency is N, where N is the preset baseband multiple, and B is the baseband multiple. sig f is the signal bandwidth of the signal. s This represents the baseband sampling rate.

[0070] The normalized stopband cutoff frequency is calculated based on the preset baseband multiplier, the frequency of adjacent channel interference, and the baseband sampling rate. The calculation formula is as follows:

[0071]

[0072] Where, ω stop The normalized stopband cutoff frequency is given by N, where N is a preset baseband multiple, and f is the baseband multiple. intern,low f is the lowest frequency point of adjacent channel interference. s This represents the baseband sampling rate.

[0073] The stopband attenuation can be calculated based on the noise power spectral density of adjacent channel interference and the noise power spectral density of the signal. The calculation formula is as follows:

[0074] A stop =psd inter -psd sig +α

[0075] Among them, A stop For stopband attenuation, PSD inter The noise power spectral density of adjacent channel interference, psd sig Let denot be the noise power spectral density of the signal, and α be the preset signal-to-interference-plus-noise ratio demodulation threshold factor.

[0076] When the modulation signal is a low-order modulation signal such as Quadrature Phase Shift Keying (QPSK), the α value can be appropriately reduced to lower the implementation complexity; when the modulation signal is a high-order modulation signal such as 256QAM, the α value can be appropriately increased to minimize the residual interference aliased into the useful signal bandwidth.

[0077] In some embodiments, the formula for calculating the signal bandwidth can be:

[0078] B sig =N RE ×SCS

[0079] Among them, B sig N is the signal bandwidth. RE The minimum time-frequency resource unit (RE) for the signal is denoted by , and SCS is the subcarrier spacing.

[0080] In some embodiments, such as Figure 3 As shown, the channel filter coefficients are determined based on the normalized passband cutoff frequency, the normalized stopband cutoff frequency, and the stopband attenuation, which may include S301 to S303.

[0081] S301, calculate the ideal frequency response of the channel filter based on the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation;

[0082] S302, Determine the target's actual frequency response based on the relationship between the ideal frequency response and the actual frequency response;

[0083] S303 converts the target's actual frequency response into a time-domain response to obtain the channel filter coefficients.

[0084] By calculating the ideal frequency response and converting it to the actual frequency response, the filter parameters can be adjusted according to actual needs, thus achieving a filtering effect closer to the ideal.

[0085] In some embodiments, after obtaining the target channel filter, the method may further include:

[0086] Calculate the image normalized stopband cutoff frequency based on the normalized stopband cutoff frequency and the preset baseband multiple;

[0087] The anti-mirror filter coefficients are determined based on the normalized passband cutoff frequency, the mirrored normalized stopband cutoff frequency, and the stopband attenuation, thus obtaining the corresponding anti-mirror filter.

[0088] The first channel filter is obtained by combining the target channel filter and the anti-mirror filter.

[0089] In some embodiments, the image normalized stopband cutoff frequency is calculated based on the normalized stopband cutoff frequency and a preset baseband factor. The calculation formula can be:

[0090]

[0091] Where, ω mirror,stop The normalized stopband cutoff frequency is the image-defined frequency, where N is the preset baseband multiple, and ω is the normalized stopband cutoff frequency. stop f is the normalized stopband cutoff frequency. intern,low f is the lowest frequency point of adjacent channel interference. s This represents the baseband sampling rate.

[0092] In some embodiments, the specific steps for determining the anti-mirror filter are the same as those for the channel filter, requiring the design of a normalized passband cutoff frequency of ω. pass The normalized stopband and passband cutoff frequencies are ω mirror,stop The stopband attenuation is A stop Anti-mirror filter.

[0093] Because the image and the signal are far apart, the transition band of this filter is relatively smooth, the order is low, and only a small number of multiplier resources are used.

[0094] By calculating the image-normalized stopband cutoff frequency and designing an anti-image filter, the image frequency components generated by the filter can be suppressed, effectively reducing the interference of image frequencies.

[0095] In some embodiments, such as Figure 4 As shown, after obtaining the target channel filter, the method further includes steps S401 to S403.

[0096] S401, acquire the signal to be filtered;

[0097] S402, Filter the signal to be filtered according to the target channel filter coefficients of the target channel filter to obtain the first filtered signal;

[0098] S403, the first filtered signal is filtered according to the anti-mirror filter coefficients of the anti-mirror filter to obtain the target filtered signal.

[0099] By sequentially filtering through the target channel filter and the anti-mirror filter, the channel filter can effectively remove adjacent channel interference at N times the baseband sampling rate, significantly eliminating noise interference and image frequency interference in the filtered signal.

[0100] In some embodiments, such as Figure 5 As shown, the anti-mirror filter includes multiple anti-mirror filter coefficients. Before filtering the signal to be filtered according to the anti-mirror filter coefficients of the anti-mirror filter, the method may further include: S501 to S503.

[0101] S501, sample the first filtered signal according to the preset interval to obtain the target first filtered signal;

[0102] S502, based on the preset relationship between the anti-mirror filter coefficients and the first filtered signal, multiple anti-mirror filter coefficients are filtered to obtain the target anti-mirror filter coefficients corresponding to the target first filtered signal;

[0103] S503, filtering the signal to be filtered according to the anti-mirror filter coefficients of the anti-mirror filter, including:

[0104] The target first filter signal is filtered according to the target anti-mirror filter parameters.

[0105] First, the first filtered signal and the anti-mirror filter coefficients are resampled N times. This places the convolution operation on the side with the low sampling rate, reducing the number of multiplications per unit time and saving power.

[0106] In some embodiments, the first filtered signal before sampling can be represented as:

[0107] X = {x1, x2, x3, ..., x}n}

[0108] Where X is the first filtered signal, x n Let n be the nth element.

[0109] The first filtered signal is sampled multiple times according to a preset interval, and the target first filtered signal after sampling is:

[0110] X1={x1,x N+1 ,x 2N+1 ,…,x n′N+1}

[0111] X2={x2,x N+2 ,x 2N+2 ,…,x n′N+2}

[0112] ...

[0113] X N ={x N ,x 2N ,x 3N ,…,x (n′+1)N}

[0114] Among them, X N For a subsequence of the first filtered signal sampled at intervals N, n ′ n represents the length of each subsequence of the first filtered signal after sampling. ′ =ceil(n / N), where ceil means rounding up.

[0115] The anti-mirror filter coefficients can be expressed as:

[0116] C = {c1, c2, c3, ..., c} s}

[0117] Where C is the first filtered signal, c s Let be the s-th element.

[0118] The target anti-mirror filter coefficients corresponding to the first filtered signal of the target are:

[0119] C1 = {c1, c N+1 ,c 2N+1 ,…,c s′N+1}

[0120] C2 = {c2,c N+2 ,c 2N+2 ,…,c s′N+2}

[0121] ...

[0122] C N ={cN ,c 2N ,c 3N ,…,c (s′+1)N}

[0123] Among them, C N For a subsequence of anti-mirror filter coefficients sampled at interval N, s ′ s represents the length of the subsequence of each anti-mirror filter coefficient after sampling. ′ =ceil(s / N), where ceil means rounding up.

[0124] Filtering the target first filter signal according to the target anti-mirror filter parameters can include:

[0125] For X1,…,X N and C1,…,C N The phases are convolved, and the result after convolution is Y1,…,Y. N .

[0126] Y1 = conv(X1, C1)

[0127] Y2 = conv(X2, C2)

[0128] ...

[0129] Y N =conv(X) N C N )

[0130] Then, summing all the convolution results yields the target filtered signal Y:

[0131] Y = Y1 + Y2 + ... + Y N

[0132] Since both the first filtered signal and the target anti-mirror filter coefficients have been resampled N times, the filtered signal has also been resampled N times. The anti-mirror filter not only removes the mirror image but also performs N-fold resampling of the time-domain signal. Furthermore, by swapping the order of convolution and resampling, the convolution operation is performed on the low sampling rate side, reducing the number of multiplication operations per unit time and lowering the overall power consumption.

[0133] Figure 6 An apparatus 600 for designing a channel filter according to an embodiment of this application is shown. The apparatus may include:

[0134] The acquisition module 601 is used to acquire the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, and noise power spectral density of the signal.

[0135] The calculation module 602 is used to calculate the normalized passband cutoff frequency, normalized stopband cutoff frequency and stopband attenuation based on the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, noise power spectral density of the signal and preset baseband multiple.

[0136] The determination module 603 is used to determine the channel filter coefficients based on the normalized passband cutoff frequency, the normalized stopband cutoff frequency, and the stopband attenuation, and to obtain the channel filter corresponding to the channel filter coefficients.

[0137] The update module 604 is used to insert a preset number of preset values ​​into the channel filter coefficients to obtain the target channel filter coefficients and update the channel filter to obtain the target channel filter.

[0138] In some embodiments, the calculation module 602 is further configured to calculate the normalized passband cutoff frequency based on a preset baseband multiple, signal bandwidth, and baseband sampling rate;

[0139] The calculation module 602 is also used to calculate the normalized stopband cutoff frequency based on the preset baseband multiple, the frequency of adjacent channel interference and the baseband sampling rate;

[0140] The calculation module 602 is also used to calculate the stopband attenuation based on the noise power spectral density of the adjacent channel interference and the noise power spectral density of the signal.

[0141] In some embodiments, the channel filter design apparatus 600 may further include:

[0142] The calculation module 602 is also used to calculate the ideal frequency response of the channel filter based on the normalized passband cutoff frequency, the normalized stopband cutoff frequency, and the stopband attenuation.

[0143] The determination module 603 is also used to determine the target actual frequency response based on the relationship between the ideal frequency response and the actual frequency response;

[0144] The conversion module is used to convert the actual frequency response of the target into a time-domain response to obtain the channel filter coefficients.

[0145] In some embodiments, the channel filter design apparatus 600 may further include:

[0146] The calculation module 602 is also used to calculate the image normalized stopband cutoff frequency based on the normalized stopband cutoff frequency and the preset baseband multiple.

[0147] The determination module 603 is also used to determine the anti-mirror filter coefficients based on the normalized passband cutoff frequency, the mirrored normalized stopband cutoff frequency and the stopband attenuation, so as to obtain the corresponding anti-mirror filter.

[0148] The combination module is used to combine the target channel filter and the anti-mirror filter to obtain the first channel filter.

[0149] In some embodiments, the channel filter design apparatus 600 may further include:

[0150] The acquisition module 601 is also used to acquire the signal to be filtered;

[0151] The filtering module is used to filter the signal to be filtered according to the target channel filter coefficients of the target channel filter to obtain the first filtered signal.

[0152] The filtering module is also used to filter the first filtered signal according to the anti-mirror filter coefficients of the anti-mirror filter to obtain the target filtered signal.

[0153] In some embodiments, the channel filter design apparatus 600 may further include:

[0154] The sampling module is used to sample the first filtered signal according to a preset interval to obtain the target first filtered signal;

[0155] The filtering module is used to filter multiple anti-mirror filter coefficients according to a preset relationship between the anti-mirror filter coefficients and the first filtered signal, so as to obtain the target anti-mirror filter coefficients corresponding to the target first filtered signal.

[0156] The filtering module is also used to filter the target first filtered signal according to the target anti-mirror filter parameters.

[0157] Figure 6 The various modules in the device shown can achieve Figure 1 The various steps involved, and the corresponding technical effects achieved, will not be elaborated upon here for the sake of brevity.

[0158] Figure 7 A schematic diagram of the hardware structure of the terminal device provided in an embodiment of this application is shown.

[0159] The terminal device may include a processor 701 and a memory 702 storing computer program instructions.

[0160] Specifically, the processor 701 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0161] Memory 702 may include mass storage for data or instructions. For example, and not limitingly, memory 702 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. In one instance, memory 702 may include removable or non-removable (or fixed) media, or memory 702 may be non-volatile solid-state memory. Memory 702 may be internal or external to the integrated gateway disaster recovery device.

[0162] In one example, memory 702 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method of channel filter design according to this disclosure.

[0163] The processor 701 reads and executes computer program instructions stored in the memory 702 to achieve... Figure 1 The method for designing a channel filter in the illustrated embodiment.

[0164] In one example, the terminal device may also include a communication interface 703 and a bus 704. Wherein, for example... Figure 7 As shown, the processor 701, memory 702, and communication interface 703 are connected through bus 704 and complete communication with each other.

[0165] The communication interface 703 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0166] Bus 704 includes hardware, software, or both, that couples components of an end device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 704 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0167] Furthermore, in conjunction with the channel filter design methods in the above embodiments, this application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the channel filter design methods in the above embodiments.

[0168] This application also provides a computer program product, including a computer program that, when executed, implements any of the channel filter design methods described in the above embodiments.

[0169] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0170] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or text segments used to perform the required tasks. Programs or text segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memory (ROM), flash memory, erasable read-only memory (EROM), floppy disks, compact disc read-only memory (CD-ROM), optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Text segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0171] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0172] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0173] The above are merely specific embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for designing a channel filter, characterized in that, include: Acquire the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, and noise power spectral density of the signal; Based on the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, noise power spectral density of the signal, and preset baseband multiple, calculate the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation. The channel filter coefficients are determined based on the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation, and the channel filter corresponding to the channel filter coefficients is obtained. A preset number of preset values ​​are inserted into the channel filter coefficients to obtain the target channel filter coefficients and update the channel filter to obtain the target channel filter.

2. The method for designing a channel filter according to claim 1, characterized in that, The step of calculating the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation based on the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, noise power spectral density of the signal, and a preset baseband factor includes: Calculate the normalized passband cutoff frequency based on the preset baseband multiple, signal bandwidth, and baseband sampling rate; The normalized stopband cutoff frequency is calculated based on the preset baseband multiple, the frequency of adjacent channel interference, and the baseband sampling rate. The stopband attenuation is calculated based on the noise power spectral density of the adjacent channel interference and the noise power spectral density of the signal.

3. The method for designing a channel filter according to claim 1, characterized in that, The step of determining the channel filter coefficients based on the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation includes: The ideal frequency response of the channel filter is calculated based on the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation. The target actual frequency response is determined based on the relationship between the ideal frequency response and the actual frequency response. The actual frequency response of the target is converted into a time-domain response to obtain the channel filter coefficients.

4. The method for designing a channel filter according to claim 1, characterized in that, After obtaining the target channel filter, the method also includes: Calculate the image normalized stopband cutoff frequency based on the normalized stopband cutoff frequency and the preset baseband multiple; The anti-mirror filter coefficients are determined based on the normalized passband cutoff frequency, the mirrored normalized stopband cutoff frequency, and the stopband attenuation, thus obtaining the corresponding anti-mirror filter. The target channel filter and the anti-mirror filter are combined to obtain the first channel filter.

5. The method for designing a channel filter according to claim 4, characterized in that, After obtaining the target channel filter, the method also includes: Obtain the signal to be filtered; The signal to be filtered is filtered according to the target channel filter coefficients of the target channel filter to obtain a first filtered signal; The first filtered signal is filtered according to the anti-mirror filter coefficients of the anti-mirror filter to obtain the target filtered signal.

6. The method for designing a channel filter according to claim 5, characterized in that, The anti-mirror filter includes multiple anti-mirror filter coefficients. Before filtering the signal to be filtered according to the anti-mirror filter coefficients, the method further includes: The first filtered signal is sampled according to a preset interval to obtain the target first filtered signal; Based on the preset relationship between the anti-mirror filter coefficients and the first filtered signal, multiple anti-mirror filter coefficients are filtered to obtain the target anti-mirror filter coefficients corresponding to the target first filtered signal; The signal to be filtered is filtered according to the anti-mirror filter coefficients of the anti-mirror filter, including: The target first filtered signal is filtered according to the target anti-mirror filter coefficients.

7. An apparatus for designing a channel filter, characterized in that, The device includes: The acquisition module is used to acquire the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, and noise power spectral density of the signal. The calculation module is used to calculate the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation based on the signal bandwidth, baseband sampling rate, frequency of adjacent channel interference, noise power spectral density of adjacent channel interference, noise power spectral density of the signal, and preset baseband multiple. The determination module is used to determine the channel filter coefficients based on the normalized passband cutoff frequency, normalized stopband cutoff frequency, and stopband attenuation, and to obtain the channel filter corresponding to the channel filter coefficients. The update module is used to insert a preset number of preset values ​​into the channel filter coefficients to obtain the target channel filter coefficients and update the channel filter to obtain the target channel filter.

8. A terminal device, characterized in that, The equipment includes: Processor and memory storing computer program instructions; A method for designing a channel filter as described in any one of claims 1-6 when the processor executes computer program instructions.

9. A computer-readable storage medium, characterized in that, A computer-readable storage medium stores computer program instructions that, when executed by a processor, implement the method for designing a channel filter as described in any one of claims 1-6.

10. A computer program product, characterized in that, When the instructions in a computer program product are executed by the processor of an electronic device, the electronic device causes the electronic device to perform the method of channel filter design as described in any one of claims 1-6.

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