GFSK signal receiving method and apparatus, and electronic device and storage medium

Abstract

The present application belongs to the technical field of signal processing. Disclosed are a GFSK signal receiving method and apparatus, and an electronic device and a storage medium. The method comprises: in a GFSK receiver, obtaining a phase differenced frequency value according to a receiving end; performing inverse Gaussian filtering processing on a decoded frequency value by means of a preset inverse Gaussian filter, so as to obtain a filtered frequency value, wherein the inverse Gaussian filter is a filter constructed on the basis of composition information of a sent signal; and performing accumulation processing on the basis of the filtered frequency value and then performing determination, so as to obtain decoded data of a received signal. The present application can achieve the effect of improving the decoding performance of a GFSK receiver.

Description

A GFSK signal receiving method, device, electronic device and storage medium Technical Field

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

[0002] GFSK (Gaussian Frequency Shift Keying) modulation is often used in Bluetooth signal transmission technology. At the transmitting end, the use of Gaussian filtering can reduce the bandwidth occupied by the transmitted signal while effectively suppressing interference with adjacent channels. However, GFSK modulation also introduces a certain amount of inter-symbol interference (ISI). During the decoding process at the receiving end, ISI and Gaussian white noise can affect the decoded frequency word, potentially causing it to have "inverted" signs, leading to decoding errors. Therefore, the existing technology suffers from poor receiver decoding performance.

[0003] Summary of the Invention

[0004] The present application provides a GFSK signal receiving method, device, electronic device and storage medium, which can improve the decoding performance of the receiver.

[0005] In a first aspect, an embodiment of the present application provides a GFSK signal receiving method, which can be applied to a Bluetooth signal receiver. The method includes:

[0006] According to the GFSK received signal, the original frequency value after phase difference is obtained;

[0007] Performing an inverse Gaussian filtering process on the original frequency value using a preset inverse Gaussian filter to obtain a filtered frequency value, wherein the inverse Gaussian filter is a filter constructed based on composition information of a transmitted signal, and the transmitted signal is a signal corresponding to the received signal after passing through the Gaussian filter at the transmitting end;

[0008] A decision is made based on the filtered frequency value to obtain decoded data of the received signal.

[0009] In one embodiment, determining based on the filtered frequency value to obtain decoded data of the received signal includes:

[0010] Performing a cumulative sum operation on each frequency in the filtered frequency value to obtain a frequency cumulative sum value;

[0011] Symbol decision decoding is performed on the frequency cumulative sum value to obtain decoded data of the received signal.

[0012] In one embodiment, the method further comprises:

[0013] Determining inverse Gaussian filter coefficients according to the composition information of the transmitted signal;

[0014] The inverse Gaussian filter is constructed based on the inverse Gaussian filter coefficients.

[0015] In one embodiment, the composition information of the transmitted signal includes the number of related symbols N and the transmitting end Gaussian filter coefficient F, F = {f(1), f(2), ... f[(2N+1)*M]}, where M is the number of sampling points corresponding to the duration of a data symbol in the receiver, and M is a natural number; N indicates that in the Gaussian filter, the current symbol is related to the previous N symbols and the next N symbols, and N represents the number of related symbols before and after, and N is a natural number;

[0016] The inverse Gaussian filter coefficients include the intermediate vector g0, the front vector g -n and the back vector g n ;

[0017] The determining of inverse Gaussian filter coefficients according to the composition information of the transmitted signal includes:

[0018] Determine the intermediate vector g0 and the forward vector g according to the number of sampling points M, the number of related symbols N and the Gaussian filter coefficient F at the transmitting end. -n and the back vector g n ;

[0019] Where g0 = g 0,1 , g 0,2 ,…,g 0,i …, g 0,M , g -n =g -n,1 , g -n,2 ,…,g -n,i …, g -n,M , g -n,i =-f{[(N-n+1*M+2-i}*g 0,i ; g n =g n,1 , g n,2 ,…,g n,i …, g n,M , g n,i =-f{[(N+n+1*M+2-i}*g 0,i ; n=1~N, i=1~M;

[0020] When i=1 and n=N, the Gaussian filter is padded with zeros, i.e., f{[(N+N)+1]*M+1}=0;

[0021] The step of constructing the inverse Gaussian filter based on the inverse Gaussian filter coefficients includes:

[0022] According to the intermediate vector g0, the front vector g -n and the back vector g n , construct the inverse Gaussian filter G = [g -n , g -n+1 ,…,g0,g1,…,g n-1 , g0].

[0023] In one embodiment, the step of receiving the GFSK signal and obtaining the original frequency value after phase difference includes:

[0024] The GFSK received signal is subjected to radio frequency mixing and filtering, angle calculation, differentiation and scaling processing to obtain an original frequency value.

[0025] In one embodiment, performing inverse Gaussian filtering on the original frequency value using a preset inverse Gaussian filter includes:

[0026] The original frequency value is input into a preset inverse Gaussian filter, which performs inverse Gaussian filtering on the original frequency value according to the following formula:

[0027] Where k is the kth symbol, i is the serial number of the sampling point within the k symbol, i∈[1,M]; sign is the sign-taking operation;

[0028] x(k,1, x(k,2, … x(k,M) are the values ​​of the sampling points of the k-th symbol in the original frequency, x(kn,B) and x(k+n,B) are the values ​​of the corresponding optimal sampling points within the n symbols before the k-th symbol and the values ​​of the corresponding optimal sampling points within the n symbols after the k-th symbol, respectively.

[0029] In a second aspect, an embodiment of the present application provides a GFSK signal receiving device, the device comprising:

[0030] The frequency value acquisition module is used to obtain the original frequency value after phase difference according to the GFSK received signal;

[0031] an inverse Gaussian filtering module, configured to perform inverse Gaussian filtering on the original frequency value using a preset inverse Gaussian filter to obtain a filtered frequency value, wherein the inverse Gaussian filter is a filter constructed based on the composition information of the transmitted signal, and the transmitted signal is a signal corresponding to the received signal after passing through the Gaussian filter at the transmitting end;

[0032] A decision decoding module is used to make a decision based on the filtered frequency value to obtain decoded data of the received signal.

[0033] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the GFSK signal receiving method of any of the above embodiments are performed.

[0034] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the GFSK signal receiving method as described in any of the above embodiments are implemented.

[0035] In summary, compared with the prior art, the technical solutions provided by the embodiments of the present application have at least the following beneficial effects:

[0036] An embodiment of the present application provides a GFSK signal receiving method. The method obtains an original frequency value based on a GFSK received signal, then performs inverse Gaussian filtering on the original frequency value using a preset inverse Gaussian filter to obtain a filtered frequency value. The inverse Gaussian filter is constructed based on information about the composition of the transmitted signal and can specifically eliminate intersymbol interference (ISI) present in the original frequency value. A decision is then made based on the filtered frequency value to obtain decoded data of the received signal. This method can perform inverse Gaussian filtering on the original frequency value using a preset inverse Gaussian filter, thereby specifically eliminating ISI introduced by the Gaussian filter at the signal transmitting end. This method can improve the decoding accuracy of the received signal, thereby enhancing the decoding performance of the receiver. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] FIG1 is a flowchart of a signal receiving method provided by an exemplary embodiment of the present application.

[0038] FIG2 is a flowchart of a signal receiving method provided by yet another exemplary embodiment of the present application.

[0039] FIG3 is a schematic diagram of capturing transmitted symbol information provided by an exemplary embodiment of the present application.

[0040] FIG4 is a diagram comparing the effects of a solution provided by an exemplary embodiment of the present application.

[0041] FIG5 is a schematic diagram of Gaussian filtering at the transmitting end provided by an exemplary embodiment of the present application.

[0042] FIG6 is a time-domain diagram of inverse Gaussian filter coefficients provided by an exemplary embodiment of the present application (with 16 sampling points).

[0043] FIG7 is a schematic diagram of a frequency spectrum of an inverse Gaussian filter provided by an exemplary embodiment of the present application.

[0044] FIG8 is a time domain diagram of the inverse Gaussian filter coefficients provided by an exemplary embodiment of the present application (sampling point is 8)

[0045] FIG9 is a waveform diagram of a Gaussian filter and an inverse Gaussian filter acting simultaneously according to an exemplary embodiment of the present application.

[0046] FIG10 is a structural diagram of a signal receiving device provided by an exemplary embodiment of the present application.

[0047] FIG11 is a structural diagram of a signal receiving device provided by yet another exemplary embodiment of the present application. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0049] Referring to FIG. 1 , an embodiment of the present application provides a GFSK signal receiving method, which is described using a signal receiver as an example. The method may include the following steps:

[0050] Step S1: Obtain the original frequency value after phase difference according to the GFSK received signal.

[0051] The received signal is the original signal received by the receiver, which is sent to the receiver by a transmitter using GFSK modulation. The received signal typically includes multiple symbols, each of which can correspond to multiple frequency values, but a frequency value can only correspond to one symbol. Each frequency value is a sample point value within its corresponding symbol. The original frequency value includes the frequency value corresponding to each symbol. In this case, inter-symbol crosstalk (ISC) may exist between the frequencies corresponding to different symbols. ISI refers to waveform distortion and broadening of preceding and following symbols due to suboptimal overall system transmission characteristics. This causes a long tail in the preceding waveform, which extends to the sampling instant of the current symbol and interferes with the decision of the current symbol.

[0052] Specifically, the signal receiver processes the received signal to obtain the original frequency value.

[0053] In some implementations, step S1 may include the following steps: performing radio frequency mixing and filtering, angle calculation, differentiation, and scaling processing on the GFSK received signal to obtain an original frequency value.

[0054] Step S2, performing inverse Gaussian filtering on the original frequency value through a preset inverse Gaussian filter to obtain a filtered frequency value, wherein the inverse Gaussian filter is a filter constructed based on the composition information of the transmitted signal, and the transmitted signal is a signal corresponding to the received signal after passing through the Gaussian filter at the transmitting end.

[0055] Among them, the inverse Gaussian filter is a filter constructed based on the composition information of the transmitted signal. The transmitted signal is a signal corresponding to the received signal after passing through the Gaussian filter at the transmitting end. Therefore, the original frequency value can be filtered according to the Gaussian filter characteristics of the signal transmitting end, so as to better eliminate interference, so that each frequency value in the filtered frequency value only carries the symbol information of its corresponding single symbol.

[0056] Step S3: Making a decision based on the filtered frequency value to obtain decoded data of the received signal.

[0057] The decision may refer to symbol decision decoding, and the decoded data may be a decoded sequence of a received signal, that is, data originally sent by the signal transmitter.

[0058] Specifically, the signal receiver can make a decision based on the filtered frequency value to obtain decoded data of the received signal.

[0059] In the above embodiment, after removing the inter-symbol interference, the method can directly perform symbol decision decoding on the filtered frequency value to obtain the originally transmitted data, thereby achieving the effect of removing the inter-symbol interference caused by the Gaussian filter at the signal transmitting end.

[0060] In the above steps, the signal receiver processes the received signal to obtain the original frequency value and the signal receiver judges the frequency value to obtain decoded data, which are mature technologies in the existing technology. At the same time, the contents not described in detail in this specification belong to the existing technology known to those skilled in the art.

[0061] In the above embodiment, the signal receiving method can obtain an original frequency value based on the received signal; then, the original frequency value is subjected to inverse Gaussian filtering using a preset inverse Gaussian filter to obtain a filtered frequency value, wherein the inverse Gaussian filter is a filter constructed based on the composition information of the transmitted signal and can specifically eliminate inter-symbol interference present in the original frequency value; a judgment is made based on the filtered frequency value to obtain decoded data of the received signal. The above method can perform inverse Gaussian filtering on the original frequency value using a preset inverse Gaussian filter, thereby specifically eliminating inter-symbol interference caused by the Gaussian filter at the signal transmitting end, thereby improving the decoding accuracy of the received signal and thereby enhancing the decoding performance of the receiver.

[0062] After removing the inter-symbol interference, each sample point value in the symbol only carries the symbol information of the symbol. However, at this time, each sampling point may still be affected by Gaussian white noise, which may lead to decoding errors.

[0063] In other embodiments, in order to solve the problem that the GFSK receiver is affected by Gaussian white noise, resulting in degradation of demodulation performance, referring to FIG. 2 , step S3 may include the following steps:

[0064] Step S31, performing a cumulative sum operation on each frequency in the filtered frequency value to obtain a frequency cumulative sum value;

[0065] Step S32: performing symbol decision decoding on the frequency cumulative sum value to obtain decoded data of the received signal.

[0066] Specifically, in order to capture the original transmitted symbol information to the greatest extent possible, the cumulative sum of multiple sample values ​​within the symbol can be calculated, as shown in the schematic diagram of transmitted symbol information capture in Figure 3, further reducing the impact of Gaussian white noise on the receiver. The cumulative sum calculation formula is as follows: Y(k) = y(k,1) + ...y(k,j), ...y(k,M);

[0067] Y(k) is the frequency cumulative sum value, k is the current symbol index, j is the corresponding sampling point index within the symbol, and can range from [1 to M]. M is the maximum number of samples within the symbol. For example, when the sampling rate is 16 times the data symbol rate, M = 16. Y(k) is obtained by maximally capturing the transmitted symbol information. The receiver determines Y(k) to obtain the decoded sequence.

[0068] In the above embodiment, in addition to eliminating inter-symbol interference through an inverse Gaussian filter, the method can also capture the information of the transmitted symbols to the greatest extent through cumulative sum operations, thereby further suppressing Gaussian white noise interference, reducing the random influence of white noise on the frequency, and further improving the receiver decoding performance.

[0069] Based on the above embodiments, the technical solutions in this application can be verified through simulation. For example, the GFSK transmission symbol rate is set to 1Msps, the modulation index h = 0.32, and the receiver sampling rate is 16Mbps. To reflect the effect and gain of this application, the RF modulation / demodulation / filtering steps are not added here, and the optimal sampling point is the ideal sampling point. Three solutions are used for comparison;

[0070] Solution (1) Directly determine and demodulate the received frequency;

[0071] Solution (2) adopts the signal receiving method proposed in this application;

[0072] Solution (3) adopts the signal receiving method proposed in this application. When using the previous and next symbols, the same symbols as those of the transmitting end are used. This solution is called "theoretical value".

[0073] As shown in the scheme effect comparison diagram in Figure 4, by comparing the three schemes, the signal receiving method proposed in this application can improve the receiver decoding performance by 4dB (BER=10 -3 ), this solution is about 1dB different from the theoretical value.

[0074] In some embodiments, the method may further include the following steps: determining inverse Gaussian filter coefficients according to composition information of the transmitted signal; and constructing an inverse Gaussian filter based on the inverse Gaussian filter coefficients.

[0075] Specifically, in the signal receiver, an inverse Gaussian filter is constructed according to the composition information of the transmitted signal. The inverse Gaussian filter may be a one-dimensional vector, and the coefficients of the inverse Gaussian filter are stored in a read-only memory (ROM) of the receiver.

[0076] In one implementation of the above embodiment, it is assumed that the GFSK transmitter transmission symbol rate is R1 symbol per second (sps); the GFSK receiver sampling rate is R2 bits per second (bps), and the number of sampling points M = R2 / R1; the length of the Gaussian filter coefficient F at the transmitter is (2N+1)*M, where M is the number of sampling points corresponding to the duration of a data symbol in the receiver, M is a natural number, N indicates that in the Gaussian filter, the current symbol is related to the previous N symbols and the next N symbols, and N represents the number of related symbols before and after, N is a natural number, and is generally 1 in the GFSK receiver. Therefore, the composition information of the transmitted signal includes the number of related symbols N and the transmitter Gaussian filter coefficient F, and F can be expressed as: F = {f(1), f(2), ... f[(2N+1)*M]}, where F can be a one-dimensional row vector with a dimension of 1×(2N+1)*M, or a one-dimensional column vector with a dimension of (2N+1)*M×1.

[0077] The inverse Gaussian filter coefficients include the intermediate vector g0, the front vector g -n and the back vector g n ;

[0078] Determine the inverse Gaussian filter coefficients based on the composition information of the transmitted signal, including:

[0079] According to the number of sampling points M, the number of related symbols N and the Gaussian filter coefficient F at the transmitter, the intermediate vector g0 and the forward vector g are determined. -n and the back vector g n ;

[0080] Where g0=[g 0,1 , g 0,2 ,…,g 0,i …, g 0,M ], g -n =[g -n,1 , g -n,2 ,…,g -n,i …, g -n,M ], g -n,i =-f{[(Nn)+1]*M+2-i}*g 0,i ; g n =[g n,1 , g n,2 ,…,g n,i …, g n,M ], g n,i =-f{[(N+n)+1]*M+2-i}*g 0,i ;

[0081] Wherein, n=1~N, i=1~M;

[0082] When i=1 and n=N, a zero-padding operation is performed on the Gaussian filter, that is, f{[(N+N)+1]*M+1}=0.

[0083] Based on the inverse Gaussian filter coefficients, an inverse Gaussian filter is constructed, including:

[0084] According to the intermediate vector g0, the front vector g -n and the back vector g n , construct the inverse Gaussian filter G = [g -n , g -n+1 ,…,g0,g1,…,g n-1 , g0], G is a one-dimensional vector, the dimension of the vector can be 1×(2N+1)*M, corresponding to the dimension of F; the subvector g of G is a one-dimensional vector with a dimension of 1×M.

[0085] In the specific implementation process, the values ​​of the sampling points corresponding to the symbol k in the original frequency are x(k,1), x(k,2), ..., x(k,M), and the inverse Gaussian filtering is performed on them, which can be expressed as follows:

[0086] Among them, k is the kth symbol, i is the serial number of the sampling point within the k symbol, i∈[1,M], sign is the sign operation,

[0087] Where "B" represents the best position, that is, the best sampling point, x(kn,B) and x(k+n,B) are the values ​​of the best sampling point within the first n symbols of the k-th symbol and the values ​​of the best sampling point within the last n symbols of the k-th symbol, respectively.

[0088] After removing the inter-symbol interference, y(k) can be directly decoded for symbol decision. Alternatively, a cumulative sum operation can be performed to maximize the information captured by the transmitted symbols and further eliminate the influence of Gaussian white noise. The cumulative sum process can be as follows:

[0089] Then, by performing symbol decision on Y(k), the originally transmitted data, ie, the decoded data of the received signal, can be obtained.

[0090] In the above embodiment, the method can remove the inter-symbol interference caused by the Gaussian filter by constructing an inverse Gaussian filter in the receiver. Since the inverse Gaussian filter is calculated based on the received transmission signal, it is more suitable for removing the inter-symbol interference in the transmission signal.

[0091] As shown in Figure 5, a Gaussian filter is used on the GFSK signal transmitter to reduce the signal bandwidth and minimize interference with adjacent channels. However, on the GFSK receiver, the resulting signal is subject to interference from adjacent symbols, known as intersymbol interference (ISI). To address this issue, an inverse Gaussian filter must be designed. The following example illustrates the construction of this inverse filter.

[0092] Assume that the signal symbol rate is 1 Msps, the number of sampling points M is 16, and the symbols S(1), S(2), S(3), ..., S(n) are transmitted. After interpolation, the array S'(n) = [S(1), 0, ..., S(2), 0, ...] is obtained, where the number of "0"s is 15; the Gaussian filter coefficients are f(1), f(2), f(48). After passing through the Gaussian filter, the transmitted signal is [x(1,1), x(1,2) ... x(1,16), x(2,1), x(2,2), ... x(2,16), x(k,i), where k is the symbol number and i is the sampling point number within a symbol. The two-dimensional vector x(k,i) can also be converted into the corresponding one-dimensional vector: X(k*M+i) = x(k,i).

[0093] In order to design the inverse Gaussian filter, the coefficients of the inverse Gaussian filter are obtained according to the composition of the transmitted signal. For the convenience of derivation, it is assumed that the first symbol S(1) corresponds to the maximum sampling point (optimal sampling point) with a sequence number of 1. Then, according to the characteristics of the Gaussian filter, the maximum sampling point of the second symbol S(2) is determined to be 1+16=17. According to the convolution law X(n)=S'(n)*f(n), the calculation formula of X(17) is: X(17)=f(25)*S(2)+f(9)*S(1)+f(41)*S(3);

[0094] Therefore, S(2)=X(17) / f(25)-f(9) / f(25)*S(1)-f(41) / f(25)S(3);

[0095] Similarly, for X(18), X(18) = f(24)*S(2) + f(8)*S(1) + f(40)*S(3); S(2) = X(18) / f(24) - f(8) / f(24)*S(1) - f(40) / f(24)S(3);

[0096] According to this method, the calculation method for any k symbols can be derived: X(k*16+i-8)=f(34-i)*S(k)+f(18-i)*S(k-1)+f(50-i)*S(k+1);

[0097] Where k is the symbol sequence number sent, i is the sample point sequence number within the symbol, and the value range of i is 1 to 16. Since the number of Gaussian filter coefficients is an even number, in order to facilitate derivation and calculation, the filter coefficient is an odd number and does not overflow. The end of the filter coefficient f can be padded with "0", that is, f(49) = 0.

[0098] Therefore, an inverse Gaussian filter G can be constructed, where G is a one-dimensional vector with a dimension of 1*48 (row vector), G=[g1; g2; g3].

[0099] Among them, the dimensions of g1, g2, and g3 are all 1*16, g1 represents the coefficient of the first symbol, g2 represents the coefficient of the second symbol, and g3 represents the coefficient of the third symbol. g1, g2, and g3 can be calculated based on the above coefficients. g1 = -[f(17) / f(33), f(16) / f(32)…, f(3) / f(19), f(2) / f(18)]; g2 = [1 / f(33), …, 1 / f(19), 1 / f(18)]; g3 = -[f(49) / f(33), f(48) / f(32), …, f(34) / f(18)].

[0100] Through the above analysis, the time domain diagram of the coefficients of the inverse Gaussian filter (with 16 sampling points) is shown in FIG6 , and FIG7 is a schematic diagram of the spectrum of the inverse Gaussian filter.

[0101] When the number of sampling points is 8, a similar inverse Gaussian filter G1 can be obtained by using the above method. The time domain diagram of the coefficient of the inverse Gaussian filter G1 (with 8 sampling points) is shown in Figure 8. The dimension of the one-dimensional vector G1 is 1*24, where the dimensions of g4, g5, and g6 are all 1*8; G1 = [g4; g5; g6]; g4 = -[f(9) / f(17), f(8) / f(16)…, f(2) / f(10)]; g5 = [1 / f(17),…, 1 / f(11), 1 / f(10)]; g6 = -[f(25) / f(17), f(24) / f(16),…f(18) / f(10)].

[0102] When the inverse Gaussian filter and the Gaussian filter are applied simultaneously, the waveform shown in Figure 10 is obtained. Therefore, at the receiving end, the inverse Gaussian filter can obtain "the entire energy within the symbol." That is, when demodulating symbol m, no other symbols within the range of m sampling points (1 to 16) interfere with it, theoretically eliminating intersymbol interference.

[0103] In the specific implementation process, the specific method of inverse Gaussian filtering is:

[0104] x(k-1,1) to x(k-1,16) are the sample values ​​corresponding to the previous symbol; x(k,1) to x(k,16) are the sample values ​​corresponding to the current symbol; x(k+1,1) to x(k+1,16) are the sample values ​​corresponding to the next symbol;

[0105] Therefore, after the current symbols x(k,1)~x(k,16) eliminate the inter-symbol interference, they are y(k,1)~y(k,16). The calculation method can be: y(k,1)=G(16+1)*x(k,1)+sign(x(k-1,B))*G(1)+sign(x(k+1,B))*G(32+1); y(k,i)=G(16+i)*x(k,i)+sign(x(k-1,B))*G(i)+sign(x(k+1,B))*G(32+i); … y(k,16)=G(16+16)*x(k,16)+sign(x(k-1,B))*G(16)+sign(x(k+1,B))*G(48).

[0106] Here, i is within the range of sample points, and sign(x) represents the sign of x (i.e., when x is negative, the value is "-1"; when x is non-negative, the value is "+1"). x(k-1, B) can be the value corresponding to the best sampling point in the previous symbol; similarly, x(k+1, B) can be the value corresponding to the best sampling point in the next symbol.

[0107] Taking the receiver sampling points X(1) to X(48) as an example, let the optimal sampling point be the intermediate value. X(1) to X(16) are the sampling points of the first symbol, which can also be represented by x(1,1) to x(1,16); X(17) to X(32) are the sampling points of the second symbol, which can also be represented by x(2,1) to x(2,16); X(33) to X(48) are the sampling points of the third symbol, which can also be represented by x(3,1) to x(3,16); suppose that x(1,B) and x(2,B) are the optimal sampling points of the previous symbol and the next symbol, respectively. Therefore, the sampling point sequence corresponding to the second symbol is x(2,1) to x(2,16). The values ​​y(2,1) to y(2,16) after inverse Gaussian filtering can be calculated as follows: y(2,1) = x(2,1)*G(17)+sign(x(1,B))*G(1)+sign(x(2,B))*G(33); y(2,2) = x(2,2)*G(18)+sign(x(1,B))*G(2)+sign(x(2,B))*G(34); … y(2,16) = x(2,16)*G(24)+sign(x(1,B))*G(16)+sign(x(2,B))*G(48).

[0108] Please refer to FIG. 11 . Another embodiment of the present application provides a GFSK signal receiving device, which may include a frequency value acquisition module 101 , an inverse Gaussian filtering module 102 , and a decision decoding module 103 .

[0109] The frequency value acquisition module 101 is configured to obtain the original frequency value after phase difference according to the GFSK received signal.

[0110] The inverse Gaussian filtering module 102 is used to perform inverse Gaussian filtering on the original frequency value through a preset inverse Gaussian filter to obtain a filtered frequency value. The inverse Gaussian filter is a filter constructed based on the composition information of the transmitted signal, and the transmitted signal is a signal corresponding to the received signal after passing through the Gaussian filter at the transmitting end.

[0111] The decision decoding module 103 is configured to make a decision based on the filtered frequency value to obtain decoded data of the received signal.

[0112] In specific implementation, the above-mentioned signal receiving device can be a Bluetooth signal receiver, and the original frequency value acquisition module 101, inverse Gaussian filtering module 102 and decision decoding module 103 included therein can all be implemented in whole or in part through software, hardware or a combination thereof.

[0113] In some embodiments, the decision decoding module 103 is specifically used to: perform accumulation and sum operations on each frequency in the filtered frequency value to obtain a frequency accumulation and sum value; perform symbol decision decoding on the frequency accumulation and sum value to obtain decoded data of the received signal.

[0114] In some embodiments, referring to FIG11 , the apparatus further includes:

[0115] The inverse Gaussian filter construction module 100 is used to determine the inverse Gaussian filter coefficients according to the composition information of the transmitted signal, and to construct the inverse Gaussian filter based on the inverse Gaussian filter coefficients.

[0116] Furthermore, the composition information of the transmitted signal includes the number of related symbols N and the transmitting end Gaussian filter coefficient F, F = {f(1), f(2), ... f[(2N+1)*M]}, M is the number of sampling points corresponding to the duration of a data symbol in the receiver, and M is a natural number; wherein N represents the correlation between the current symbol and the previous N symbols and the next N symbols in the Gaussian filter, and N represents the number of related symbols before and after, and N is a natural number;

[0117] The inverse Gaussian filter coefficients include the intermediate vector g0, the front vector g -n and the back vector g n ;

[0118] The inverse Gaussian filter building module 100 is specifically used for:

[0119] According to the number of sampling points M, the number of related symbols N and the Gaussian filter coefficient F at the transmitter, the intermediate vector g0 and the forward vector g are determined. -n and the back vector g n , and according to the intermediate vector g0, the front vector g -n and the back vector g n , construct the inverse Gaussian filter G = [g -n , g -n+1 ,…,g0,g1,…,g n-1 ,g0];

[0120] Where g0=[g 0,1 , g 0,2 ,…,g 0,i …, g 0,M ], g -n =[g -n,1 , g-n,2 ,…,g -n,i …, g -n,M ], g -n,i =-f{[(Nn)+1]*M+2-i}*g 0,i ; g n =[g n,1 , g n,2 ,…,g n,i …, g n,M ], g n,i =-f{[(N+n)+1]*M+2-i}*g 0,i ; n=1~N, i=1~M.

[0121] In some embodiments, the frequency value acquisition module 101 is specifically configured to perform radio frequency mixing and filtering, angle calculation, differentiation, and scaling on the GFSK received signal to obtain an original frequency value.

[0122] For the specific limitations of the signal receiving device provided in this embodiment, please refer to the embodiment of the signal receiving method above and will not be repeated here. Each module in the above-mentioned signal receiving device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the electronic device in the form of hardware, or can be stored in the memory of the electronic device in the form of software so that the processor can call and execute the operations corresponding to each of the above modules.

[0123] An embodiment of the present application provides an electronic device, which may include a processor, a memory, a network interface, and a database connected via a system bus. The processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the electronic device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the processor executes the steps of the signal receiving method as described in any of the above embodiments.

[0124] The working process, working details and technical effects of the electronic device provided in this embodiment can be found in the above embodiments of the signal receiving method, which will not be described in detail here.

[0125] The present application provides a computer-readable storage medium having a computer program stored thereon. When executed by a processor, the computer program implements the steps of the signal receiving method described in any of the above embodiments. The computer-readable storage medium refers to a medium for storing data, and may include, but is not limited to, a floppy disk, an optical disk, a hard disk, a flash memory, a USB flash drive, and / or a memory stick. The computer may be a general-purpose computer, a dedicated computer, a computer network, or other programmable device.

[0126] The working process, working details and technical effects of the computer-readable storage medium provided in this embodiment can be found in the above embodiments of the signal receiving method, and will not be described in detail here.

[0127] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0128] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0129] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for receiving GFSK signals, characterized in that, The method includes: Obtaining the original frequency value after phase difference based on the GFSK received signal; Performing inverse Gaussian filtering on the original frequency value through a preset inverse Gaussian filter to obtain the filtered frequency value, where the inverse Gaussian filter is a filter constructed based on the composition information of the transmitted signal, and the transmitted signal is the signal that has passed through a Gaussian filter at the transmitting end corresponding to the received signal; Making a decision based on the filtered frequency value to obtain the decoded data of the received signal.

2. The method according to claim 1, characterized in that The making a decision based on the filtered frequency value to obtain the decoded data of the received signal includes: Performing a cumulative sum operation on each frequency in the filtered frequency value to obtain a frequency cumulative sum value; Performing symbol decision decoding on the frequency cumulative sum value to obtain the decoded data of the received signal.

3. The method according to any one of claims 1 to 2, characterized in that, The method further includes: Determining the inverse Gaussian filter coefficients according to the composition information of the transmitted signal; Constructing the inverse Gaussian filter based on the inverse Gaussian filter coefficients.

4. The method according to claim 3, characterized in that, The composition information of the transmitted signal includes the number of relevant symbols N and the Gaussian filter coefficients F at the transmitting end, F = {f(1), f(2),..., f[(2N + 1)*M]}, where M is the number of sampling points corresponding to one data symbol duration in the receiver, and M is a natural number; N indicates that in the Gaussian filter, the current symbol is related to the previous N symbols and the next N symbols, and N represents the number of forward and backward related symbols, and N is a natural number; The reverse Gaussian filter coefficients include an intermediate vector g0, a front vector g -n and a rear vector g n ; The determining the inverse Gaussian filter coefficients according to the composition information of the transmitted signal includes: Determine the intermediate vector g0, the front vector g, and the back vector g according to the number of sampling points M, the number of correlation symbols N, and the Gaussian filter coefficients F of the transmitter -n and the back vector g n ; Among them, g0 = [g 0,1 , g 0,2 , …, g 0,i …, g 0,M , g -n = [g -n,1 , g -n,2 , …, g -n,i …, g -n,M , g -n,i = -f{[(N - n)+1]*M + 2 - i}*g 0,i ; g n = [g n,1 , g n,2 , …, g n,i …, g n,M , g n,i = -f{[(N + n)+1]*M + 2 - i}*g 0,i ; n = 1 to N, i = 1 to M; When i = 1 and n = N, performing a zero-padding operation on the Gaussian filter, that is, f{[(N + N) + 1]*M + 1} = 0; The constructing the inverse Gaussian filter based on the inverse Gaussian filter coefficients includes: According to the intermediate vector g0, the front vector g -n and the rear vector g n , construct the inverse Gaussian filter G = [g -n , g -n+1 , ……, g0, g1, ……, g n-1 , g0].

5. The method according to claim 4, wherein The obtaining the original frequency value after phase difference based on the GFSK received signal includes: Performing radio frequency mixing filtering, angle calculation, differentiation, and scaling processing on the GFSK received signal to obtain the original frequency value.

6. The method according to claim 5, characterized in that, The performing inverse Gaussian filtering on the original frequency value through a preset inverse Gaussian filter includes: Input the original frequency value into a preset inverse Gaussian filter, and the inverse Gaussian filter performs inverse Gaussian filtering on the original frequency value according to the following formula: Among them, k is the k-th symbol, i is the serial number of the sampling point within the k symbols, i ∈ [1, M]; sign is the symbol-taking operation; x(k, 1), x(k, 2),... x(k, M) are the values of the sampling points of the k-th symbol in the original frequency, and x(k - n, B), x(k + n, B) are the values of the corresponding optimal sampling points within the first n symbols before the k-th symbol and the values of the corresponding optimal sampling points within the last n symbols after the k-th symbol, respectively.

7. A GFSK signal receiving device, characterized in that, The device includes: A frequency value acquisition module for obtaining the original frequency value after phase difference based on the GFSK received signal; An inverse Gaussian filtering module for performing inverse Gaussian filtering on the original frequency value through a preset inverse Gaussian filter to obtain the filtered frequency value, where the inverse Gaussian filter is a filter constructed based on the composition information of the transmitted signal, and the transmitted signal is the signal that has passed through a Gaussian filter at the transmitting end corresponding to the received signal; A decision decoding module for making a decision based on the filtered frequency value to obtain the decoded data of the received signal.

8. The device according to claim 7, characterized in that The decision decoding module is used for: Perform a cumulative sum operation on each frequency in the filtered frequency values to obtain a cumulative sum value of the frequencies; Perform symbol decision decoding on the cumulative sum value of the frequencies to obtain the decoded data of the received signal.

9. The device according to any one of claims 7 to 8, characterized in that The device further includes: An inverse Gaussian filter construction module, configured to determine inverse Gaussian filter coefficients according to the composition information of the transmitted signal, and construct the inverse Gaussian filter based on the inverse Gaussian filter coefficients.

10. The device according to claim 9, characterized in that The composition information of the transmitted signal includes the number of relevant symbols N and the Gaussian filter coefficients F at the transmitter, F = {f(1), f(2), …… f[(2N + 1)*M]}, where M is the number of sampling points corresponding to one data symbol duration in the receiver, and M is a natural number; N represents that in the Gaussian filter, the current symbol is related to the previous N symbols and the next N symbols, and N represents the number of symbols related before and after, and N is a natural number; The reverse Gaussian filter coefficients include an intermediate vector g0, a front vector g -n and a rear vector g n ; The inverse Gaussian filter construction module is used for: Determine the intermediate vector g0, the front vector g, and the rear vector g according to the number M of the sampling points, the number N of the correlation symbols, and the Gaussian filter coefficients F of the transmitter -n and the rear vector g n ; where g0 = [g 0,1 , g 0,2 , …, g 0,i …, g 0,M , g -n = [g -n,1 , g -n,2 , …, g -n,i …, g -n,M , g -n,i = -f{[(N - n)+1]*M + 2 - i}*g 0,i ; g n = [g n,1 , g n,2 , …, g n,i …, g n,M , g n,i = -f{[(N + n)+1]*M + 2 - i}*g 0,i ; n = 1 to N, i = 1 to M; When i = 1 and n = N, perform zero-padding operation on the Gaussian filter, that is, f{[(N + N) + 1]*M + 1} = 0; According to the intermediate vector g0, the front vector g -n and the rear vector g n , construct the inverse Gaussian filter G = [g -n , g -n+1 , ……, g0, g1, ……, g n-1 , g0].

11. The device according to claim 7, characterized in that, The frequency value acquisition module is used for: Perform radio frequency mixing filtering, angle calculation, differentiation, and scaling processing on the GFSK received signal to obtain the original frequency values.

12. The device according to claim 11, characterized in that, The inverse Gaussian filtering module is used for: Input the original frequency value into a preset inverse Gaussian filter, and the inverse Gaussian filter performs inverse Gaussian filtering on the original frequency value according to the following formula: Among them, k is the k-th symbol, i is the serial number of the sampling point within the k symbols, i ∈ [1, M]; sign is the symbol-taking operation; x(k, 1), x(k, 2), … x(k, M) are the values of the sampling points of the k-th symbol in the original frequency, x(k - n, B) and x(k + n, B) are the values of the corresponding best sampling points within the previous n symbols of the k-th symbol and the values of the corresponding best sampling points within the next n symbols of the k-th symbol, respectively.

13. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 6.

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