An interpolation shaping filter with variable interpolation factor and method

Abstract

This application provides a shaping filter and method with variable interpolation multiple, including the following steps: obtaining the filter coefficient sequence h(m) of an L max -order filter, where the filter coefficient sequence h(m) includes multiple filter coefficients; where L max = 8×f smax , and f smax is the highest interpolation multiple; obtaining the target interpolation multiple f s , calculating the ratio of the highest interpolation multiple f smax to the target interpolation multiple f s , and extracting the filter coefficient sequence h(m) at the ratio interval to obtain the filter coefficient sequence h c (n); inputting the original sampling sequence a(k), inserting f s -1 zeros after each bit of the original sampling sequence a(k) to obtain the input sequence x(k s ), convolving the obtained input sequence x(k s ) with the obtained filter coefficient sequence h c (n) to obtain the filtered output sequence y(k s ); through the above steps, the filter coefficient sequence is updated at any time according to the change of the highest interpolation multiple, and the target interpolation multiple is configured and calculated through the DAC conversion clock and the symbol rate, which is applicable to multiple interpolation multiples, has strong versatility, and is applicable to the requirements of multiple projects.

Description

Technical Field

[0001] The present disclosure generally relates to the field of communication technologies, and particularly relates to a shaping filter with variable interpolation multiple and a method therefor. Background Art

[0002] In an actual communication system, the transmission channel bandwidth is limited; in order to improve the spectrum utilization rate of the communication system, it is usually necessary to interpolate and shape-filter a square-wave modulation signal at the transmitting end to reduce the sidelobe power of the signal.

[0003] The interpolation multiple is related to the DAC conversion clock and the symbol rate, and is equal to the ratio of the DAC conversion clock to the symbol rate. Since the DAC conversion clocks and symbol rates adopted in different communication scheme designs are not the same, the interpolation multiples of the shaping filter are also not the same. Common interpolation multiples include 4, 8, 16, etc.; conventional shaping filter methods need to develop different shaping filter modules for different interpolation multiples, and the generality is not strong. Summary of the Invention

[0004] In view of the above defects or deficiencies in the prior art, it is desirable to provide a shaping filter with variable interpolation multiple and a method therefor that can solve the above technical problems.

[0005] The first aspect of the present application provides a shaping filtering method with variable interpolation multiple, including the following steps:

[0006] Obtain the filtering coefficient sequence h(m) of an L max -order filter, where the filtering coefficient sequence h(m) includes a plurality of filtering coefficients; where L max = 8×f smax , f smax is the highest interpolation multiple;

[0007] Obtain the target interpolation multiple f s ;

[0008] Calculate the ratio of the highest interpolation multiple f smax to the target interpolation multiple f s ;

[0009] Extract the filtering coefficient sequence h(m) at intervals of the ratio to obtain the filter coefficient sequence h c (n);

[0010] Input the original sampling sequence a(k), and insert f s -1 zeros after each bit of data in the original sampling sequence a(k) to obtain the input sequence x(k s );

[0011] Multiply the obtained input sequence x(k s ) by the obtained filter coefficient sequence hc (n) is convolved to obtain the filtered output sequence y(k s ).

[0012] According to the technical solution provided by the embodiment of the present application, the filter coefficient sequence h(m) of the L max -order filter is stored in the module; the filter coefficient sequence h(m) of the L max -order filter is obtained by setting the highest interpolation multiple f smax , and according to the highest interpolation multiple f smax , using the FDATOOL tool in matlab to generate the filter coefficient sequence h(m) of the L max -order filter.

[0013] According to the technical solution provided by the embodiment of the present application, the highest interpolation multiple f smax and the target interpolation multiple f s satisfy the formula f smax ≥f s ≥2.

[0014] According to the technical solution provided by the embodiment of the present application, m in the filter coefficient sequence h(m) of the L max -order filter is an integer and satisfies 0≤m≤L max -1.

[0015] According to the technical solution provided by the embodiment of the present application, n in the filter coefficient sequence h c (n) is an integer and satisfies 0≤n≤L max / (f smax / f s ), the length of the filter coefficient sequence h c (n) is L, and the L is equal to L max / (f smax / f s ).

[0016] According to the technical solution provided by the embodiment of the present application, the input sequence x(k s ) and the filter coefficient sequence h c (n) are convolved according to formula (1) to obtain the filtered output sequence y(k s ):

[0017] y(k s )=[y(0),y(1),...,y(i),...,y(k)] (1)

[0018] Wherein,

[0019]

[0020] Let \(L\) be the length of the filter coefficient sequence \(h\) c (n), and \(k = k\) s .

[0021] The first aspect of the present application provides a shaping filter with variable interpolation multiple, including:

[0022] An acquisition module, which is used to acquire the filter coefficient sequence \(h(m)\) of an \(L\) max -order filter and the target interpolation multiple \(f\) s ; the filter coefficient sequence \(h(m)\) contains multiple filter coefficients, where \(L\) max = 8×\(f\) smax , and \(f\) smax is the highest interpolation multiple;

[0023] An interpolation frequency division calculation module, the input end of which is connected to the output end of the acquisition module. The interpolation frequency division calculation module is used to calculate the ratio of the highest interpolation multiple \(f\) smax and the target interpolation multiple \(f\) s ;

[0024] A filter coefficient adaptation extraction module, the input end of which is connected to the output end of the filter coefficient storage module and the output end of the interpolation frequency division calculation module. The filter coefficient adaptation extraction module is used to extract the filter coefficient sequence \(h(m)\) at intervals of the ratio to obtain the filter coefficient sequence \(h\) c (n);

[0025] An interpolation module, the input end of which is connected to the output end of the acquisition module. The interpolation module is used to insert \(f\) s -1 zeros after each bit of the original sampling sequence \(a(k)\) to obtain the input sequence \(x(k\) s );

[0026] A filtering module, the input end of which is connected to the output end of the filter coefficient adaptation extraction module and the output end of the interpolation module. The filtering module is used to convolve the obtained input sequence \(x(k\) s ) with the obtained filter coefficient sequence \(h\) c (n) to obtain the filtered output sequence \(y(k\) s ).

[0027] According to the technical solution provided by the embodiment of the present application, it further includes:

[0028] A filter coefficient storage module, the output end of which is connected to the input end of the acquisition module. The filter coefficient storage module is used to store the filter coefficient sequence \(h(m)\) of an \(L\) max -order filter.

[0029] The beneficial effects of the present application are as follows: Based on the technical solution provided by the present application, by obtaining the filter coefficient sequence h(m) of the L max -order filter and the target interpolation multiple f s , where L max = 8×f smax , f smax is the highest interpolation multiple, calculate the ratio of the highest interpolation multiple f smax to the target interpolation multiple f s , and extract the filter coefficient sequence h(m) at the interval of the ratio to obtain the filter coefficient sequence h c (n); then insert f s - 1 zeros after each bit of the original sampling sequence a(k) to obtain the input sequence x(k s ), convolve the obtained input sequence x(k s ) with the obtained filter coefficient sequence h c (n) to obtain the output sequence y(k s ); enabling the filter coefficient sequence to be updated at any time according to the change of the highest interpolation multiple, and the target interpolation multiple is configured and calculated through the DAC conversion clock and the symbol rate, which is applicable to multiple interpolation multiples, has strong versatility, and is applicable to the requirements of multiple projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] By reading the following detailed description of the non-limiting embodiments with reference to the accompanying drawings, other features, objectives, and advantages of the present application will become more obvious:

[0031] Figure 1 FIG. is a schematic diagram of filter coefficient adaptation extraction of a shaping filtering method with variable interpolation multiple in the present application;

[0032] Figure 2 FIG. is a convolution formula model of a shaping filtering method with variable interpolation multiple in the present application;

[0033] Figure 3 FIG. is a schematic structural diagram of a shaping filter with variable interpolation multiple in the present application.

[0034] In the figure: 1. Filter coefficient storage module; 2. Filter coefficient adaptation extraction module; 3. Interpolation frequency division calculation module; 4. Interpolation module; 5. Filtering module; 6. Acquisition module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0035] The present application will be further described in detail below with reference to the accompanying drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the relevant invention and are not intended to limit the invention. Additionally, it should be noted that for the sake of description, only the parts related to the invention are shown in the drawings.

[0036] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The following will describe this application in detail with reference to the accompanying drawings and in combination with the embodiments.

[0037] Embodiment 1

[0038] Please refer to Figure 1 - Figure 2 which is a schematic structural diagram of a shaping filtering method with variable interpolation multiple provided by this application, including the following steps:

[0039] Obtain the filtering coefficient sequence h(m) of an L max -order filter, where the filtering coefficient sequence h(m) contains multiple filtering coefficients; where L max = 8×f smax , f smax is the highest interpolation multiple;

[0040] Obtain the target interpolation multiple f s ;

[0041] Calculate the ratio of the highest interpolation multiple f smax to the target interpolation multiple f s ;

[0042] Extract the filtering coefficient sequence h(m) at intervals of the ratio to obtain the filter coefficient sequence h c (n);

[0043] Input the original sampling sequence a(k), and insert f s -1 zeros after each bit of data in the original sampling sequence a(k) to obtain the input sequence x(k s );

[0044] Perform convolution on the obtained input sequence x(k s ) and the obtained filter coefficient sequence h c (n) to obtain the filtered output sequence y(k s ).

[0045] Specifically, the target interpolation multiple f s is calculated according to the DAC conversion clock and symbol rate adopted in the designed communication scheme, and the target interpolation multiple f s is equal to the ratio of the DAC conversion clock to the symbol rate;

[0046] Specifically, the highest interpolation multiple f smax is designed according to the maximum value in the current actual application and can be replaced according to the actual situation;

[0047] Specifically, both k and ks are integers greater than 1;

[0048] Specifically, since 1 byte is equal to 8 bits, interpolation is performed after each bit of data. For example, originally one bit is one sampling point, and after interpolation, one bit becomes f smax sampling points. Therefore, L max = 8 × f smax ;

[0049] In some embodiments, the original sampling sequence a(k) is a modulation signal in the form of a square wave, and the time interval between two adjacent data of the original sampling sequence a(k) is the bit width denoted as T b , and the time interval between two adjacent data of the input sequence x(k s ) is the sampling point width denoted as T S , satisfying T S = T b / f s ;

[0050] Working principle: By obtaining the filter coefficient sequence h(m) of the L max -order filter and the target interpolation multiple f s , where L max = 8 × f smax , and f smax is the highest interpolation multiple, calculate the ratio of the highest interpolation multiple f smax to the target interpolation multiple f s , and extract the filter coefficient sequence h(m) at this ratio interval to obtain the filter coefficient sequence h c (n); then insert f s -1 zeros after each bit of the original sampling sequence a(k) to obtain the input sequence x(k s ), and convolve the obtained input sequence x(k s ) with the obtained filter coefficient sequence h c (n) to obtain the output sequence y(k s ); enabling the filter coefficient sequence to be updated at any time according to the change of the highest interpolation multiple, and the target interpolation multiple is configured and calculated through the DAC conversion clock and the symbol rate, which is applicable to various interpolation multiples, has strong versatility, and is applicable to the requirements of multiple projects.

[0051] In some embodiments, the filter coefficient sequence h(m) of the L max -order filter is stored in the module; the filter coefficient sequence h(m) of the L max -order filter is generated by setting the highest interpolation multiple f smax , and according to the highest interpolation multiple f smax , using the FDATOOL tool in matlab to generate the filter coefficient sequence h(m) of the L max -order filter.

[0052] Specifically, the maximum interpolation multiple f is set according to common application scenarios. smax , and according to the maximum interpolation multiple f smax The filtering coefficient sequence h(m) of the L-th order filter is generated by using the FDATOOL tool in Matlab and stored in the module. The filtering coefficient sequence h(m) is updated at any time according to the maximum interpolation multiple f max . smax changes.

[0053] In some embodiments, the maximum interpolation multiple f smax and the target interpolation multiple f s satisfy the formula f smax ≥ f s ≥ 2.

[0054] Specifically, according to the Shannon sampling theorem, the sampling frequency should be greater than or equal to 2 times the highest frequency in the analog signal spectrum. Therefore, both the maximum interpolation multiple f smax and the target interpolation multiple f s are even numbers; at the same time, the maximum interpolation multiple f smax is the maximum value in practical applications. Therefore, the maximum interpolation multiple f smax and the target interpolation multiple f s satisfy the formula f smax ≥ f s ≥ 2.

[0055] In some embodiments, m in the filtering coefficient sequence h(m) of the L-th order filter is an integer and satisfies 0 ≤ m ≤ L max - 1. max

[0056] Specifically, m is the number of filtering coefficients in the filtering coefficient sequence h(m) of the L-th order filter, denoted as h(0) to h(L max - 1). max

[0057] In some embodiments, n in the filter coefficient sequence h c (n) is an integer and satisfies 0 ≤ n ≤ L max / (f smax / f s ) - 1. The length of the filter coefficient sequence h c (n) is L, and the L is equal to L max / (f smax / f s ).

[0058] Specifically, it is known that the L max is equal to 8 × fsmax , so the said L is equal to 8×f s , from which it is deduced that L is equal to L max / (f smax / f s );

[0059] Specifically, the said n is the number of filter coefficients in the filter coefficient sequence h c (n), denoted as h c (0) to h c (L max / (f smax / f s ) - 1);

[0060] In some embodiments, as Figure 1 shown, the ratio of the highest interpolation multiple to the target interpolation multiple is 2. Taking 2 as the interval, the stored filter coefficient sequence h(m) is decimated to obtain h c (0) = h(0), h c (1) = h(2), h c (2) = h(4), h c (3) = h(6), h c (4) = h(8)......, h c (L max / (f smax / f s ) - 1) = h(L max - 1).

[0061] In certain embodiments, according to formula (1), the input sequence x(k s ) is convolved with the filter coefficient sequence h c (n) to obtain the filtered output sequence y(k s ):

[0062] y(k s ) = [y(0), y(1),..., y(i),..., y(k)] (1)

[0063] Wherein,

[0064]

[0065] L is the length of the filter coefficient sequence h c (n) and k = k s .

[0066] In some embodiments, the said L is equal to 4, the ks is equal to 5, then n = L - 1 = 3;

[0067] One - time convolution:

[0068] Second convolution:

[0069] Third convolution:

[0070] Fourth convolution:

[0071] Fifth convolution:

[0072] Sixth convolution:

[0073] The output sequence y(k s ) = [y(0), y(1), y(2), y(3), y(4), y(5)].

[0074] Embodiment 2

[0075] Please refer to Figure 3 which is a schematic structural diagram of a shaping filter with variable interpolation multiple provided by this application, including:

[0076] An acquisition module 6, which is used to acquire the filter coefficient sequence h(m) of an L max -order filter and the target interpolation multiple f s ; the filter coefficient sequence h(m) contains multiple filter coefficients, where L max = 8×f smax , f smax is the highest interpolation multiple;

[0077] An interpolation frequency division calculation module 3, the input end of the interpolation frequency division calculation module 3 is connected to the output end of the acquisition module 6, and the interpolation frequency division calculation module 3 is used to calculate the ratio of the highest interpolation multiple f smax and the target interpolation multiple f s ;

[0078] A filter coefficient adaptation extraction module 2, the input end of the filter coefficient adaptation extraction module 2 is connected to the output end of the acquisition module 6 and the output end of the interpolation frequency division calculation module 3, and the filter coefficient adaptation extraction module 2 is used to extract the filter coefficient sequence h(m) at intervals of the ratio to obtain a filter coefficient sequence h c (n);

[0079] An interpolation module 4, the input end of the interpolation module 4 is connected to the output end of the acquisition module 6, and the interpolation module 4 is used to insert f s - 1 zeros after each bit of the original sampling sequence a(k) to obtain an input sequence x(k s );

[0080] Filtering module 5, the input end of the filtering module 5 is connected to the output end of the filtering coefficient adaptation extraction module 2 and the output end of the interpolation module 4, and the filtering module 5 is used to obtain the input sequence x(k s ) and the obtained filter coefficient sequence h c (n) are convolved to obtain the filtered output sequence y(k s ).

[0081] Furthermore, as Figure 3 shown, the filtering coefficient sequence h(m) of the L max -order filter and the target interpolation multiple f s are obtained through the obtaining module, and the filtering coefficient sequence h(m) includes a plurality of filtering coefficients, where L max = 8×f smax , f smax is the highest interpolation multiple; at the same time, the highest interpolation multiple f smax and the target interpolation multiple f s are input into the interpolation frequency division calculation module 3, and the ratio of the highest interpolation multiple f smax to the target interpolation multiple f s is calculated, and the calculation result is sent to the filtering coefficient adaptation extraction module 2, and the filtering coefficient sequence h(m) is extracted at intervals of the ratio in the filtering coefficient adaptation extraction module 2 to obtain the filter coefficient sequence h c (n);

[0082] At the same time, the original sampling sequence a(k) is input into the interpolation module 4, and the interpolation rule of the interpolation module 4 is to interpolate f s - 1 zeros after each bit of data of the original sampling sequence a(k) to obtain the input sequence x(k s ), and then the obtained filter coefficient sequence h c (n) and the obtained input sequence x(k s ) are input into the filtering module 5 for convolution to obtain the filtered output sequence y(k s ).

[0083] In some embodiments, it further includes:

[0084] Filtering coefficient storage module 1, the output end of the filtering coefficient storage module 1 is connected to the input end of the obtaining module 6, and the filtering coefficient storage module 1 is used to store the filtering coefficient sequence h(m) of the L max -order filter.

[0085] Specifically, determine the highest interpolation multiple f smaxAfter that, use the FDATOOL tool in Matlab to generate the filter coefficient sequence h(m) of the L max -order filter, and store the generated filter coefficient sequence h(m) in the filter coefficient storage module 1. When in use, the acquisition module 6 acquires it in the filter coefficient storage module 1; the data in the filter coefficient storage module 1 changes according to the highest interpolation multiple f smax .

[0086] The above description is only the preferred embodiment of the present application and the explanation of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions disclosed in the present application.

Claims

1. A shaping filtering method with variable interpolation multiple, characterized in that including the following steps: Obtain L max The filter coefficient sequence h(m) of an L max -order filter, where the filter coefficient sequence h(m) includes a plurality of filter coefficients; where L smax = 8 × f smax , and f is the highest interpolation multiple; Obtain the target interpolation multiple f s ; Calculate the highest interpolation multiple f smax and the target interpolation multiple f s ratio; Extract the filter coefficient sequence h(m) at intervals of the ratio to obtain the filter coefficient sequence h c (n); Input the original sampling sequence a(k), and insert f s s -1 zeros after each bit of the original sampling sequence a(k) to obtain the input sequence x(k s s ); The obtained input sequence x(k s ) is convolved with the obtained filter coefficient sequence h c (n) to obtain the filtered output sequence y(k s ).

2. The shaping filtering method with variable interpolation multiple according to claim 1, wherein L max The filter coefficient sequence h(m) of the L max -order filter is stored in the module; the L smax -order filter coefficient sequence h(m) is obtained by setting the highest interpolation multiple f smax and using the FDATOOL tool in matlab to generate the filter coefficient sequence h(m) of the L max -order filter.

3. A shaping filter method with variable interpolation multiple according to claim 1, characterized in that The highest interpolation multiple f smax and the target interpolation multiple f s satisfy the formula f smax ≥ f s ≥ 2 4. A shaping filtering method with variable interpolation multiple according to claim 1, characterized in that, The said L max In the filter coefficient sequence h(m) of the L-order filter, m is an integer and satisfies 0 ≤ m ≤ L max -1.

5. A shaping filtering method with variable interpolation multiple according to claim 1, characterized in that, The filter coefficient sequence h c (n) where n is an integer and satisfies 0 ≤ n ≤ L max / (f smax / f s ) - 1, the length of the filter coefficient sequence h c (n) is L, where L = L max / (f smax / f s ).

6. A shaping filtering method with variable interpolation multiple according to claim 5, characterized in that, Convolve the input sequence x(k s ) with the filter coefficient sequence h c (n) according to formula (1) to obtain the filtered output sequence y(k s ): y(k s ) = [y(0), y(1),..., y(i),..., y(k)] (1) wherein, L is the length of the filter coefficient sequence h c (n), and k = k s .

7. A shaping filter with variable interpolation multiple, characterized in that, including: An acquisition module (6) for acquiring the filtering coefficient sequence h(m) of an L max -order filter and the target interpolation multiple f s ; the filtering coefficient sequence h(m) includes a plurality of filtering coefficients, where L max = 8 × f smax , and f smax is the highest interpolation multiple; Interpolation frequency division calculation module (3), the input end of the interpolation frequency division calculation module (3) is connected to the output end of the acquisition module (6), and the interpolation frequency division calculation module (3) is used to calculate the ratio of the highest interpolation multiple f smax and the target interpolation multiple f s of; Filter coefficient adaptation extraction module (2), the input end of the filter coefficient adaptation extraction module (2) is connected to the output end of the filter coefficient storage module (1) and the output end of the interpolation frequency division calculation module (3), and the filter coefficient adaptation extraction module (2) is used to extract the filter coefficient sequence h(m) at intervals of the ratio to obtain the filter coefficient sequence h c (n); Interpolation module (4), the input end of the interpolation module (4) is connected to the output end of the acquisition module (6), and the interpolation module (4) is used to insert f s -1 zeros after each bit of the original sampling sequence a(k) to obtain the input sequence x(k s ); Filtering module (5), the input end of the filtering module (5) is connected to the output end of the filtering coefficient adaptation extraction module (2) and the output end of the interpolation module (4), and the filtering module (5) is used to perform convolution on the obtained input sequence x(k s ) and the obtained filter coefficient sequence h c (n) to obtain the filtered output sequence y(k s ).

8. A shaping filter with variable interpolation multiple according to claim 7, characterized in that further including: Filter coefficient storage module (1), the output end of the filter coefficient storage module (1) is connected to the input end of the acquisition module (6), and the filter coefficient storage module (1) is used to store the filter coefficient sequence h(m) of an L max -order filter.

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