A GMSK signal communication method, apparatus, device, and storage medium

Abstract

The present application discloses a GMSK signal communication method, apparatus, device, and storage medium, relating to the technical field of data transmission, including: generating continuous additional phases for respective transmission sequences of an original GMSK signal, combining information sequences of adjacent code elements of respective obtained state sequences with the state sequences, and mapping the respective obtained iterative sequences, generating an absolute phase vector group based on respective obtained first to-be-processed spreading sequences, and performing likelihood summation on each absolute phase vector group and a phase vector of a sequence obtained by processing the first to-be-processed spreading sequence using a preset front-end filter to obtain a branch path metric value; forward-state transferring each branch path metric value, and setting a path corresponding to the path metric value with the largest value among respective obtained cumulative path metric values as the maximum likelihood path, backward-tracing the maximum likelihood path to determine a target signal sequence based on the obtained target spreading sequence. This can improve the speed and quality of signal transmission.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and in particular to a GMSK signal communication method, device, equipment and storage medium. Background Art

[0002] As human beings continue to explore space, fields such as deep space exploration and manned spaceflight have gradually become hot spots in space activities. Among them, deep space tracking and control scenarios have the characteristics of scarce spectrum resources, long communication distances, weak received signals, and complex environments, which put forward more stringent requirements on the modulation waveform and the receiving performance of the receiver under extremely low signal-to-noise ratio conditions. Therefore, studying the reliable reception of efficient waveforms under extremely low signal-to-noise ratio conditions is a practical need to complete major tasks, and it is also one of the problems that need to be solved urgently in this field.

[0003] Gaussian Minimum-Shift Keying (GMSK) has the characteristics of constant envelope, continuous phase, fast out-of-band spectrum attenuation, high spectrum utilization and power utilization, and is widely used in deep space tracking and control and satellite communication scenarios. Among them, the GMSK system has two types of demodulation methods: coherent and incoherent. Among them, coherent demodulation can improve sensitivity and provide higher mutual information for the external decoder. In addition, the deep space communication link has a long communication distance and large transmission loss, and higher sensitivity is required to achieve correct demodulation and reception operations. Spread spectrum technology can effectively improve the demodulation threshold and improve bit error performance.

[0004] The basic idea of ​​spread spectrum technology is to use a high-code-rate spread spectrum sequence to expand the spectrum of the signal at the transmitter, and then use the same spread spectrum sequence to restore the original signal and obtain the spread spectrum gain based on the time-frequency synchronization of the receiver. However, the spread spectrum system can only fully obtain the spread spectrum gain by despreading and then demodulating the received signal at the receiving end, and the continuous phase characteristics of GMSK make it impossible to obtain the correlation peak when correlating the local pseudo code with the received signal, so that pseudo code capture and signal despreading cannot be completed. Therefore, it is necessary to explore the GMSK spread spectrum system that can fully utilize the gain and the corresponding coherent reception processing method to achieve reliable information transmission under extremely low signal-to-noise ratio conditions.

[0005] The currently adopted spread spectrum methods are as follows: The first method: Improve the sub-optimal coherent detection technology for GMSK signals based on Laurent decomposition, adjust the calculation method of the Viterbi (i.e., a shortest path search algorithm) detection branch metric, improve the bit error rate at the cost of a small amount of complexity, but there is still room for improvement. The second method: Use cyclic shift keying to improve MSK (Minimum Shift Keying), reduce the system complexity, and make the system performance better than the traditional MSK direct spread system, but it is more sensitive to frequency offset. The third method: Use Weil code (i.e., a coding method) to spread spectrum the spatial environment of the payload, reduce the resource usage, and improve the reliability, but the spread spectrum gain cannot be fully utilized. That is, the above existing spread spectrum methods have high implementation complexity or limited bit error rate in a low signal-to-noise ratio environment, and lack practicality in a low signal-to-noise ratio and long-distance transmission environment.

[0006] As can be seen from the above, how to improve the signal transmission speed and signal transmission quality during the GMSK signal communication process is an urgent problem to be solved at present. Summary of the Invention

[0007] In view of this, the purpose of the present invention is to provide a GMSK signal communication method, device, equipment and storage medium, which can reduce the complexity of implementing the spread spectrum method, thereby improving the signal transmission speed and signal transmission quality. The specific solutions are as follows:

[0008] In a first aspect, the present application provides a GMSK signal communication method, including:

[0009] Generate continuous additional phases for each transmission sequence corresponding to the original GMSK signal based on the phase information of the original GMSK signal to obtain a number of state sequences;

[0010] Combine the information sequences of adjacent code elements corresponding to each of the state sequences with the state sequences respectively to obtain each iterative sequence, and use a preset mapping spread spectrum rule to map each of the iterative sequences respectively to obtain corresponding first to-be-processed spread spectrum sequences;

[0011] Generate corresponding absolute phase vector groups based on each of the first to-be-processed spread spectrum sequences respectively, and perform likelihood summation on each of the absolute phase vector groups and the phase vectors corresponding to the second to-be-processed spread spectrum sequences respectively to obtain corresponding branch path metric values; the second to-be-processed spread spectrum sequence is a spread spectrum sequence obtained by processing the first to-be-processed spread spectrum sequence using a preset front-end filter;

[0012] Use the Viterbi algorithm to perform forward state transitions on the branch path metric values of each of the above, and set the path corresponding to the path metric value with the largest value among the obtained cumulative path metric values as the maximum likelihood path. Then, perform backward traceback on the maximum likelihood path to obtain the target spreading sequence, so as to determine the target signal sequence by using the preset mapping spreading rule and based on the target spreading sequence.

[0013] Optionally, generating continuous additional phases for each transmission sequence corresponding to the original GMSK signal based on the phase information of the original GMSK signal to obtain a plurality of state sequences, including:

[0014] Generating continuous additional phases by using a preset phase addition technique and based on the phase information, signal power, carrier frequency, symbol period, and baseband frequency pulse corresponding to the original GMSK signal; the continuous additional phase is a phase generated by jointly performing phase modulation on a plurality of symbols;

[0015] Adding the continuous additional phase to each transmission sequence corresponding to the original GMSK signal to obtain a plurality of state sequences; the baseband frequency pulse is an impulse response obtained by processing the original GMSK signal with a preset Gaussian filter.

[0016] Optionally, generating continuous additional phases for each transmission sequence corresponding to the original GMSK signal based on the phase information of the original GMSK signal, including:

[0017] Determining the intersymbol interference degree based on the normalized bandwidth corresponding to the preset Gaussian filter and the symbol period, and determining the instantaneous phase based on the intersymbol interference degree; the instantaneous phase is used to describe the phase change within the current symbol period;

[0018] Decomposing the phase information of the original GMSK signal into a phase constant part and a phase change part, where the phase constant part is the cumulative sum of the phase changes of all symbols at the current moment;

[0019] Determining a plurality of the continuous additional phases based on the phase constant part and the instantaneous phase.

[0020] Optionally, combining the information sequences of adjacent symbols corresponding to each of the state sequences with the state sequences respectively to obtain respective iterative sequences, and performing mapping on each of the iterative sequences by using a preset mapping spreading rule to obtain corresponding first to-be-processed spreading sequences, including:

[0021] Determining the number of sequences corresponding to the state sequence based on the normalized bandwidth corresponding to the preset Gaussian filter and the symbol period;

[0022] Obtain information sequences corresponding to adjacent symbol groups corresponding to the state sequences of the number of the sequences respectively, and combine each of the state sequences with the corresponding information sequence to obtain corresponding iterative sequences; the adjacent symbol groups include a preset number of adjacent symbols;

[0023] Use a preset mapping spreading rule to map each of the iterative sequences respectively to obtain corresponding first sequences to be processed for spreading; the number of the first sequences to be processed for spreading is consistent with the preset spreading factor value; there is a mapping relationship between the iterative sequence and the unique first sequence to be processed for spreading.

[0024] Optionally, after combining the information sequences of adjacent symbols corresponding to each of the state sequences with the state sequences respectively to obtain each iterative sequence, and using a preset mapping spreading rule to map each of the iterative sequences respectively to obtain corresponding first sequences to be processed for spreading, further include:

[0025] Store the first sequences to be processed for spreading into the original GMSK signal to obtain a GMSK signal to be processed, and transmit the GMSK signal to be processed through a preset channel to a preset receiving end so that the preset receiving end samples the GMSK signal to obtain a plurality of the first sequences to be processed for spreading.

[0026] Optionally, the generating corresponding absolute phase vector groups respectively based on each of the first sequences to be processed for spreading, and performing likelihood summation on each of the absolute phase vector groups and the phase vectors corresponding to the second sequences to be processed for spreading respectively to obtain corresponding branch path metric values includes:

[0027] Use a preset in-phase component extraction technique to extract corresponding in-phase component groups from each of the first sequences to be processed for spreading, and use a preset quadrature component extraction technique to extract corresponding quadrature component groups from each of the first sequences to be processed for spreading; the absolute phase vector groups include the in-phase component groups and the quadrature component groups;

[0028] Perform likelihood summation on each of the in-phase component groups and each of the quadrature component groups and the phase vectors corresponding to the second sequences to be processed for spreading respectively to obtain corresponding branch path metric values.

[0029] Optionally, the using the Viterbi algorithm to perform forward state transition on each of the branch path metric values, and setting the path corresponding to the path metric value with the largest value among the obtained cumulative path metric values as the maximum likelihood path, and then performing backward traceback on the maximum likelihood path to obtain a target spreading sequence, so as to determine a target signal sequence by using the preset mapping spreading rule and based on the target spreading sequence includes:

[0030] Use the Viterbi algorithm to perform forward state transitions on each of the branch path metric values and the corresponding initial total path metric respectively, to obtain the corresponding cumulative path metric values;

[0031] Set the likelihood path corresponding to the path metric value with the largest value among the cumulative path metric values as the maximum likelihood path, and delete the paths corresponding to the remaining cumulative path metric values respectively;

[0032] Use the Viterbi algorithm to perform backward traceback on the maximum likelihood path, obtain the backward traceback result, and arrange each of the backward traceback results in a preset arrangement order to obtain the target spreading sequence;

[0033] Use the preset mapping spreading rule to map the target spreading sequence to obtain the target signal sequence, so as to communicate using the signal corresponding to the target signal sequence.

[0034] In a second aspect, the present application provides a GMSK signal communication device, including:

[0035] A phase generation module, configured to generate continuous additional phases for each transmission sequence corresponding to the original GMSK signal based on the phase information of the original GMSK signal, to obtain a plurality of state sequences;

[0036] A sequence mapping module, configured to combine the information sequences of adjacent code elements corresponding to each of the state sequences with the state sequences respectively to obtain respective iterative sequences, and use a preset mapping spreading rule to map each of the iterative sequences respectively to obtain corresponding first to-be-processed spreading sequences;

[0037] A vector likelihood summation module, configured to generate corresponding absolute phase vector groups based on each of the first to-be-processed spreading sequences, and perform likelihood summation on each of the absolute phase vector groups and the phase vectors corresponding to the second to-be-processed spreading sequences respectively to obtain corresponding branch path metric values; the second to-be-processed spreading sequence is a spreading sequence obtained by processing the first to-be-processed spreading sequence using a preset front-end filter;

[0038] A target signal sequence determination module, configured to use the Viterbi algorithm to perform forward state transitions on each of the branch path metric values, and set the path corresponding to the path metric value with the largest value among the obtained cumulative path metric values as the maximum likelihood path, and then perform backward traceback on the maximum likelihood path to obtain the target spreading sequence, so as to determine the target signal sequence based on the target spreading sequence using the preset mapping spreading rule.

[0039] In a third aspect, the present application provides an electronic device, including:

[0040] A memory for storing a computer program;

[0041] A processor for executing the computer program to implement the foregoing GMSK signal communication method.

[0042] In a fourth aspect, the present application provides a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the foregoing GMSK signal communication method.

[0043] As can be seen from the above, before performing GMSK signal communication in the present application, it is necessary to generate continuous additional phases for each transmission sequence corresponding to the original GMSK signal based on the phase information of the original GMSK signal to obtain a number of state sequences; combine the information sequences of adjacent code elements corresponding to each state sequence with the state sequences respectively to obtain each iterative sequence, and use a preset mapping spreading rule to map each iterative sequence respectively to obtain corresponding first spread-spectrum sequences to be processed; generate corresponding absolute phase vector groups based on each first spread-spectrum sequence to be processed, and perform likelihood summation on each absolute phase vector group and the phase vector of the corresponding state sequence respectively to obtain corresponding branch path metric values; use the Viterbi algorithm to perform forward state transitions on each branch path metric value, and set the path corresponding to the path metric value with the largest value among the obtained cumulative path metric values as the maximum likelihood path, and then perform backward traceback on the maximum likelihood path to obtain a target spread-spectrum sequence, so as to determine a target signal sequence by using the preset mapping spreading rule and based on the target spread-spectrum sequence.

[0044] Thus, it can be seen that the present application first generates continuous additional phases for each transmission sequence corresponding to the original GMSK signal based on the phase information of the original GMSK signal to obtain a number of state sequences; combines the information sequences of adjacent code elements corresponding to each state sequence with the state sequences respectively to obtain each iterative sequence, and uses a preset mapping spreading rule to map each iterative sequence respectively to obtain corresponding first spread-spectrum sequences to be processed. Then, corresponding absolute phase vector groups are generated based on each first spread-spectrum sequence to be processed, and likelihood summation is performed on each absolute phase vector group and the phase vector of the corresponding state sequence respectively to obtain corresponding branch path metric values. Subsequently, the Viterbi algorithm is used to perform forward state transitions on each branch path metric value, and the path corresponding to the path metric value with the largest value among the obtained cumulative path metric values is set as the maximum likelihood path. Finally, backward traceback is performed on the maximum likelihood path to obtain a target spread-spectrum sequence, so as to determine a target signal sequence by using the preset mapping spreading rule and based on the target spread-spectrum sequence. In this way, the complexity of implementing the spreading method is reduced, thereby improving the signal transmission speed and the signal transmission quality. Description of the Drawings

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on the provided drawings.

[0046] Figure 1 It is a flowchart of a GMSK signal communication method disclosed in this application;

[0047] Figure 2 It is a schematic flowchart of a specific absolute phase state iterative mapping method disclosed in this application;

[0048] Figure 3 It is a schematic flowchart of a specific process of jointly demodulating and despreading using the Viterbi algorithm disclosed in this application;

[0049] Figure 4 It is a schematic flowchart of a specific process of processing signals at the receiving end disclosed in this application;

[0050] Figure 5 It is a schematic diagram of the performance comparison between this application and the traditional mode disclosed in this application;

[0051] Figure 6 It is a schematic structural diagram of a GMSK signal communication device disclosed in this application;

[0052] Figure 7 It is a structural diagram of an electronic device disclosed in this application. Specific embodiments

[0053] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0054] The currently adopted spread spectrum methods are as follows: The first method: Improve the sub-optimal coherent detection technology for GMSK signals based on Laurent decomposition, adjust the calculation method of the Viterbi detection branch metric, and improve the bit error rate at the cost of a small amount of complexity. The second method: Improve MSK by using cyclic shift keying to reduce the system complexity, but it is sensitive to frequency offset. The third method: Use Weil codes to spread spectrum the spatial environment of the payload, reduce the use of resources, and improve the reliability, but it cannot fully utilize the spread spectrum gain. That is, the above existing spread spectrum methods have a high implementation complexity, or the bit error rate is limited in a low signal-to-noise ratio environment, and they lack practicality in a low signal-to-noise ratio and long-distance transmission environment. For this reason, this application provides a GMSK signal communication method, which can reduce the complexity of implementing the spread spectrum method, thereby improving the signal transmission speed and signal transmission quality.

[0055] See Figure 1 As shown, an embodiment of the present invention discloses a GMSK signal communication method, including:

[0056] Step S11: Generate continuous additional phases for each transmission sequence corresponding to the original GMSK signal based on the phase information of the original GMSK signal to obtain a plurality of state sequences.

[0057] In this embodiment, before the original GMSK signal is sent to the receiving end, the embodiment of this application needs to generate continuous additional phases for the transmission sequences corresponding to the GMSK signal. Specifically, generating continuous additional phases for each transmission sequence corresponding to the original GMSK signal based on the phase information of the original GMSK signal to obtain a plurality of state sequences may include: using a preset phase addition technique and generating continuous additional phases based on the phase information, signal power, carrier frequency, symbol period, and baseband frequency pulse corresponding to the original GMSK signal; the continuous additional phase is the phase generated by jointly modulating a plurality of code elements; adding the continuous additional phase to each transmission sequence corresponding to the original GMSK signal to obtain a plurality of state sequences; the baseband frequency pulse is the impulse response obtained by processing the original GMSK signal with a preset Gaussian filter.

[0058] Among them, the expression of the transmission sequence corresponding to the GMSK signal is as follows:

[0059] ;

[0060] Subsequently, the expression for generating continuous additional phases based on the transmission sequence corresponding to the GMSK signal is as follows:

[0061] ;

[0062] Among them, is the nth symbol corresponding to the current moment t in the transmission sequence, is the carrier frequency; t is the current moment; is the power of the transmitted signal; is the symbol period; is the modulation index; in a specific embodiment, the value of the modulation index is 0.5; is the continuous additional phase corresponding to the transmission sequence; is the baseband frequency pulse, and for GMSK signals, is the impulse response obtained by passing the rectangular pulse through a Gaussian filter, and the expression is as follows:

[0063] ;

[0064] where c = 7.546, is the normalized bandwidth of the Gaussian filter, and the expression of is as follows:

[0065] ;

[0066] where, is the standard function.

[0067] It is worth mentioning that the Gaussian filter introduces an inherent inter-symbol interference characteristic to the original GMSK signal, making exhibit multiple phase states.

[0068] Furthermore, for , let:

[0069] ;

[0070] Then by combining and we can obtain:

[0071] ;

[0072] where d is the total number of symbols in the transmission sequence at the current moment t and before the moment t, is the instantaneous phase, which describes the phase change within the current symbol period, and this change is caused by the phase modulation of several symbols jointly; represents the degree of inter-symbol interference, which is determined by the value (i.e., the normalized bandwidth of the Gaussian filter); It represents the part with a constant phase within the current symbol period, which is the cumulative sum of the phase changes of all symbols before the current moment. Specifically, based on the phase information of the original GMSK signal, continuous additional phases can be generated for each transmission sequence corresponding to the original GMSK signal, including: determining the degree of inter-symbol interference based on the normalized bandwidth corresponding to the preset Gaussian filter and the symbol period, and determining the instantaneous phase based on the degree of inter-symbol interference; the instantaneous phase is used to describe the phase change within the current symbol period; decomposing the phase information of the original GMSK signal into a constant-phase part and a phase-change part, where the constant-phase part is the cumulative sum of the phase changes of all symbols at the current moment; determining a number of continuous additional phases based on the constant-phase part and the instantaneous phase.

[0073] Furthermore, There are a total of 4 possible values, and the possible values are shown as follows:

[0074] .

[0075] Thus, it can be seen that and jointly determine the phase state of the GMSK signal , that is, the value of determines the number of phases

[0076] In a specific embodiment, assuming that the number of is m, the absolute phase state is defined as ; meanwhile, regardless of the value taken by , the inter-symbol interference caused by the symbols outside 2 bits can be ignored. Therefore, in the embodiments of the present application, only the influence of the inter-symbol interference between adjacent 3 bits needs to be considered. For a certain absolute phase state, there are at most 8 possible transition paths. In addition, the state is jointly determined by the state

[0077] Step S12: Combine the information sequences of the adjacent symbols corresponding to each of the state sequences with the state sequences respectively to obtain each iteration sequence, and map each of the iteration sequences respectively using a preset mapping and spreading rule to obtain the corresponding first to-be-processed spreading sequence.

[0078] In this embodiment, the state sequence of is used to represent m states of where represents rounding up. In a specific embodiment, the 3-bit information sequence represents a group of adjacent symbols The iterative sequence. Among them, the above iterative sequence covers all state transition possibilities of the signal. In addition, The expression of the state sequence at the

[0079] ;

[0080] And the expression of the information sequence corresponding to the above state sequence is as follows:

[0081] ;

[0082] It is worth mentioning that for each set of iterative sequences formed by the above state sequence and the corresponding information sequence, there is a unique spreading sequence that forms a mapping relationship with it, and according to the new absolute phase state Update the state sequence to perform mapping operations and spreading operations on the data information in sequence. Specifically, combine the information sequences and state sequences of adjacent code elements corresponding to each state sequence respectively to obtain each iterative sequence, and use the preset mapping and spreading rules to map each iterative sequence respectively to obtain the corresponding first spreading sequence to be processed, which may include: determining the number of sequences corresponding to the state sequence based on the normalized bandwidth and symbol period corresponding to the preset Gaussian filter; obtaining the information sequences corresponding to the adjacent code element groups corresponding to the number of sequences of state sequences respectively, and combining each state sequence with the corresponding information sequence to obtain the corresponding iterative sequence; the adjacent code element group includes a preset number of adjacent code elements; using the preset mapping and spreading rules to map each iterative sequence respectively to obtain the corresponding first spreading sequence to be processed; the number of the first spreading sequences to be processed is consistent with the preset spreading factor value; the iterative sequence and the unique first spreading sequence to be processed are in a mapping relationship.

[0083] In a specific embodiment, let the spreading factor be N, and the expression of the spreading mapping relationship of the state sequence is as follows:

[0084] ;

[0085] Among them, Is a spreading sequence of length N. In a specific embodiment, if , then at this time the number of absolute phase states m = 12, the number of bits corresponding to the state sequence and the iterative sequence are 4 and 7 respectively, and the absolute phase state iterative mapping method is as Figure 2 Shown: The sequence in the blue box is the iterative sequence, the sequence in the red box is the spreading sequence, and the sequence between the blue box and the red box is the information sequence, where t1 represents the time corresponding to the first code element, t2 represents the time corresponding to the second code element, t3 represents the time corresponding to the third code element, t4 represents the time corresponding to the fourth code element, and t5 represents the time corresponding to the fifth code element.

[0086] In this embodiment, after the GMSK signal passes through the AWGN channel, the expression of the signal received by the receiving end is as follows:

[0087] ;

[0088] Wherein, is the expression of the signal received by the receiving end, is the spreading sequence corresponding to the signal, is the double-sided power spectrum, and the Gaussian white noise with a density of .

[0089] Specifically, after combining the information sequences of adjacent code elements corresponding to each state sequence with the state sequences respectively to obtain each iteration sequence, and using the preset mapping spreading rule to map each iteration sequence respectively to obtain the corresponding first spreading sequence to be processed, it may further include: storing the first spreading sequence to be processed into the original GMSK signal to obtain the GMSK signal to be processed, and transmitting the GMSK signal to be processed through a preset channel to a preset receiving end, so that the preset receiving end samples the GMSK signal to be processed to obtain a plurality of first spreading sequences to be processed.

[0090] Step S13: Generate corresponding absolute phase vector groups based on each of the first spreading sequences to be processed, and perform likelihood summation on each of the absolute phase vector groups and the phase vectors corresponding to the second spreading sequence to be processed respectively to obtain corresponding branch path metric values; the second spreading sequence to be processed is the spreading sequence obtained by processing the first spreading sequence to be processed using a preset front-end filter.

[0091] In this embodiment, after the receiving end obtains , the embodiment of the present application needs to process using a front-end filter to obtain a phase signal for backend detection, wherein the expression of the phase signal for backend detection is as follows:

[0092] ;

[0093] Furthermore, in the state iteration mapping spreading system, each state transition can be mapped to a spreading sequence of length N , and then, a phase vector group is generated based on the spreading sequence, that is, the corresponding ideal absolute phase state is changed from a single value to a group of absolute phase vectors Specifically, corresponding absolute phase vector groups are generated based on each first spread spectrum sequence to be processed, and likelihood summation is respectively performed on each absolute phase vector group and the phase vector corresponding to the second spread spectrum sequence to be processed to obtain corresponding branch path metric values, which may include: extracting corresponding in-phase component groups from each first spread spectrum sequence to be processed by using a preset in-phase component extraction technique, and extracting corresponding quadrature component groups from each first spread spectrum sequence to be processed by using a preset quadrature component extraction technique; the absolute phase vector group includes the in-phase component group and the quadrature component group; likelihood summation is respectively performed on each in-phase component group and each quadrature component group and the phase vector of the corresponding second spread spectrum sequence to be processed to obtain corresponding branch path metric values.

[0094] In a specific embodiment, maximum likelihood summation is performed on the state phase vector of the received signal and the ideal absolute phase vector of the corresponding spread spectrum sequence to obtain the corresponding branch path metric value. Among them, the determination formula of the branch path metric value is as follows:

[0095] ;

[0096] Among them, is the branch path metric value, N represents the spreading factor, that is, the spreading multiple. represents the in-phase component of the second spread spectrum sequence to be processed during the k-th state transition of the th element value; represents the quadrature component of the second spread spectrum sequence to be processed during the k-th state transition of the th element value; represents the corresponding element in the in-phase component group; represents the corresponding element in the quadrature component group.

[0097] Furthermore, after obtaining each branch path metric value, the total path metric value can be determined based on each branch path metric value. Among them, the determination formula of the total path metric value is as follows:

[0098] ;

[0099] Among them, is the total path metric value, is the initial total path metric value.

[0100] Step S14: Use the Viterbi algorithm to perform forward state transitions on the branch path metric values, and set the path corresponding to the path metric value with the largest value among the obtained cumulative path metric values as the maximum likelihood path. Then, perform backward traceback on the maximum likelihood path to obtain the target spreading sequence, so as to determine the target signal sequence by using the preset mapping spreading rule and based on the target spreading sequence.

[0101] In this embodiment, after obtaining the total path metric values of each branch, the embodiments of the present application need to perform forward state transitions according to the path metric and save the maximum value of each total path metric value. Further, after completing the forward state transitions, the embodiments of the present application need to determine the numerical magnitudes of the obtained total path metric values, and determine the maximum value of the total path metric value as the target total path metric value. Subsequently, perform backward traceback on the selected target total path metric value to obtain the maximum likelihood path, and map it to the original information sequence according to its state transition situation by using the corresponding ideal absolute phase vector to complete joint demodulation and despreading.

[0102] Specifically, using the Viterbi algorithm to perform forward state transitions on the branch path metric values, and setting the path corresponding to the path metric value with the largest value among the obtained cumulative path metric values as the maximum likelihood path, and then performing backward traceback on the maximum likelihood path to obtain the target spreading sequence, so as to determine the target signal sequence by using the preset mapping spreading rule and based on the target spreading sequence may include: using the Viterbi algorithm to perform forward state transitions on each branch path metric value and the corresponding initial total path metric respectively to obtain the corresponding cumulative path metric values; setting the likelihood path corresponding to the path metric value with the largest value among the cumulative path metric values as the maximum likelihood path, and deleting the paths corresponding to the remaining cumulative path metric values respectively; using the Viterbi algorithm to perform backward traceback on the maximum likelihood path to obtain the backward traceback result, and arranging the backward traceback results in a preset arrangement order to obtain the target spreading sequence; using the preset mapping spreading rule to map the target spreading sequence to obtain the target signal sequence, so as to communicate by using the signal corresponding to the target signal sequence.

[0103] In a specific embodiment, when ..., the schematic diagram of joint demodulation and despreading using the Viterbi algorithm is as Figure 3 shown: Among them, the red arrow is the maximum likelihood path, the black arrows are the branch paths, and I is the in-phase component corresponding to the second spreading sequence to be processed, and Q is the quadrature component corresponding to the second spreading sequence to be processed. t1, t2, and t k respectively represent the decision moment corresponding to the first symbol, the decision moment corresponding to the second symbol, and the decision moment corresponding to the kth symbol.

[0104] It can be seen that, in the embodiments of the present application, first, continuous additional phases need to be generated for each transmission sequence corresponding to the original GMSK signal based on the phase information of the original GMSK signal to obtain a plurality of state sequences; the information sequences of adjacent symbols corresponding to each state sequence are respectively combined with the state sequences to obtain each iterative sequence, and each iterative sequence is respectively mapped by using a preset mapping spreading rule to obtain a corresponding first to-be-processed spreading sequence. Then, corresponding absolute phase vector groups are respectively generated based on each first to-be-processed spreading sequence, and the absolute phase vector groups and the phase vectors of the corresponding state sequences are respectively subjected to likelihood summation to obtain corresponding branch path metric values. Subsequently, the Viterbi algorithm is used to perform forward state transition on each branch path metric value, and the path corresponding to the path metric value with the largest value among the obtained cumulative path metric values is set as the maximum likelihood path. Finally, backward traceback is performed on the maximum likelihood path to obtain a target spreading sequence, so as to determine a target signal sequence by using the preset mapping spreading rule and based on the target spreading sequence. In this way, the complexity of implementing the spreading method is reduced, thereby improving the signal transmission speed and the signal transmission quality.

[0105] Further, as shown in Figure 4 , the embodiments of the present invention disclose a process for processing signals at a receiving end, including:

[0106] First, the signal is sampled by using a front-end filter to obtain a phase signal for backend detection. Then, the Viterbi algorithm is used and based on the spreading sequence to generate an ideal absolute phase vector group ; then, the length of the transmission sequence is determined , and an initial value is assigned .

[0107] Subsequently, the branch path metric and the total path metric of the state transition process are calculated, and the path corresponding to the maximum value in the total path metric is retained as the maximum likelihood path, and the remaining paths are deleted.

[0108] Then, an increment operation is performed on k, that is, . Subsequently, k is judged. If it satisfies , then it jumps to the process of calculating the branch path metric and the total path metric of the state transition process. If it does not satisfy , then it jumps to select the path corresponding to the path metric value with the largest value in the total path metric values, and determines it as the maximum likelihood path, and backward traceback is performed according to the Viterbi demodulation process corresponding to the maximum likelihood path.

[0109] Finally, the target sequence is determined according to the state transition situation of the maximum likelihood path to complete the entire demodulation process.

[0110] It is worth mentioning that in the embodiments of the present application, the bit error performance of the Viterbi algorithm under different spreading factors is verified. In a specific embodiment, let , the symbol rate is 20 MHz (Mega Hertz), the spreading factors are 1, 32, 128, and 1024, the channel is an additive white Gaussian noise channel, and CRC (Cyclic Redundancy Check) check, de-scrambling, and 1 / 2 code Turbo (a channel coding technology) coding are added at both ends of the system to construct a complete communication system. Then, the constructed communication system is used for simulation to obtain simulation results, and the bit error performance of the embodiments of the present application and the traditional coherent demodulation and despreading processing mode under different spreading factors is compared and analyzed. The results are as Figure 5 shown:

[0111] Among them, the dotted line with circles in red (proposed) is the curve corresponding to the spreading factor of 1 in the present application, the dotted line with triangles in red (conventional) is the curve corresponding to the spreading factor of 1 in the traditional scheme, the dotted line with circles in light blue is the curve corresponding to the spreading factor of 32 in the present application, the dotted line with triangles in light blue is the curve corresponding to the spreading factor of 32 in the traditional scheme, the dotted line with circles in dark blue is the curve corresponding to the spreading factor of 128 in the present application, the dotted line with triangles in dark blue is the curve corresponding to the spreading factor of 128 in the traditional scheme, the dotted line with circles in green is the curve corresponding to the spreading factor of 1024 in the present application, and the dotted line with triangles in green is the curve corresponding to the spreading factor of 1024 in the traditional scheme. It is easy to obtain that when the spreading factor in the embodiments of the present application is doubled each time, the bit error performance is improved by about 3 dB (Decibel), realizing ideal spreading and breaking through the limitations of continuous phase modulation in the spreading system. It can be seen that the method adopted in the present application has good performance while being able to make full use of the spreading gain and can be used for reliable communication in long-distance and extremely low signal-to-noise ratio environments.

[0112] Thus, it can be seen that in the embodiments of the present application, first, the Viterbi algorithm is used to perform forward state transition on the metric values of each branch path, and the path corresponding to the maximum path metric value among the obtained cumulative path metric values is set as the maximum likelihood path. Finally, backward traceback is performed on the maximum likelihood path to obtain the target spreading sequence, so as to determine the target signal sequence by using the preset mapping spreading rule and based on the target spreading sequence. In this way, the complexity of implementing the spreading method is reduced, thereby improving the signal transmission speed and the signal transmission quality, and enhancing the user experience.

[0113] Correspondingly, see Figure 6As shown in the figure, the present application also provides a GMSK signal communication device, including:

[0114] A phase generation module 11, configured to generate continuous additional phases for each transmission sequence corresponding to the original GMSK signal based on the phase information of the original GMSK signal, so as to obtain a plurality of state sequences;

[0115] A sequence mapping module 12, configured to combine the information sequences of adjacent code elements respectively corresponding to each state sequence with the state sequences respectively to obtain respective iterative sequences, and map each iterative sequence respectively by using a preset mapping and spreading rule to obtain corresponding first to-be-processed spreading sequences;

[0116] A vector likelihood summation module 13, configured to generate corresponding absolute phase vector groups respectively based on each first to-be-processed spreading sequence, and perform likelihood summation on each absolute phase vector group and the phase vectors corresponding to the second to-be-processed spreading sequence respectively to obtain corresponding branch path metric values; the second to-be-processed spreading sequence is a spreading sequence obtained by processing the first to-be-processed spreading sequence by using a preset front-end filter;

[0117] A target signal sequence determination module 14, configured to perform forward state transition on each branch path metric value by using the Viterbi algorithm, set the path corresponding to the path metric value with the largest value among the obtained cumulative path metric values as the maximum likelihood path, and then perform backward traceback on the maximum likelihood path to obtain a target spreading sequence, so as to determine a target signal sequence by using the preset mapping and spreading rule and based on the target spreading sequence.

[0118] As can be seen from the above, before the GMSK signal communication is performed in the embodiment of the present application, it is first necessary to generate continuous additional phases for each transmission sequence corresponding to the original GMSK signal based on the phase information of the original GMSK signal to obtain a plurality of state sequences; combine the information sequences of adjacent symbols corresponding to each state sequence with the state sequences respectively to obtain each iterative sequence, and use a preset mapping spreading rule to map each iterative sequence respectively to obtain a corresponding first spreading sequence to be processed. Then, generate corresponding absolute phase vector groups based on each first spreading sequence to be processed respectively, and perform likelihood summation on each absolute phase vector group and the phase vector of the corresponding state sequence respectively to obtain corresponding branch path metric values. Subsequently, use the Viterbi algorithm to perform forward state transition on each branch path metric value, and set the path corresponding to the path metric value with the largest value among the obtained cumulative path metric values as the maximum likelihood path. Finally, perform backward traceback on the maximum likelihood path to obtain a target spreading sequence, so as to determine a target signal sequence by using the preset mapping spreading rule and based on the target spreading sequence. In this way, the complexity of implementing the spreading method is reduced, thereby improving the signal transmission speed and the signal transmission quality, and enhancing the user experience.

[0119] In some specific embodiments, the phase generation module 11 may specifically include:

[0120] A phase generation subunit, configured to generate continuous additional phases by using a preset phase addition technique and based on the phase information, signal power, carrier frequency, symbol period, and baseband frequency pulse corresponding to the original GMSK signal; the continuous additional phases are phases generated by jointly performing phase modulation on a plurality of symbols;

[0121] A state sequence determination unit, configured to add the continuous additional phases to each transmission sequence corresponding to the original GMSK signal to obtain a plurality of state sequences; the baseband frequency pulse is an impulse response obtained by processing the original GMSK signal with a preset Gaussian filter.

[0122] In some specific embodiments, the phase generation module 11 may specifically include:

[0123] An instantaneous phase determination unit, configured to determine the intersymbol interference degree based on the normalized bandwidth and symbol period corresponding to the preset Gaussian filter, and determine the instantaneous phase based on the intersymbol interference degree; the instantaneous phase is used to describe the phase change within the current symbol period;

[0124] A phase information decomposition unit, configured to decompose the phase information of the original GMSK signal into a phase constant part and a phase change part, where the phase constant part is the cumulative sum of the phase changes of all symbols at the current moment;

[0125] An additional phase determination unit for determining a plurality of the consecutive additional phases based on the phase constant part and the instantaneous phase.

[0126] In some specific embodiments, the sequence mapping module 12 may specifically include:

[0127] A sequence number determination unit for determining the number of sequences corresponding to the state sequence based on the normalized bandwidth corresponding to the preset Gaussian filter and the symbol period;

[0128] An iterative sequence determination unit for obtaining information sequences corresponding to adjacent symbol groups corresponding to the number of state sequences, and combining each state sequence with the corresponding information sequence to obtain a corresponding iterative sequence; the adjacent symbol group includes a preset number of adjacent symbols;

[0129] A first spreading sequence determination unit for respectively mapping each iterative sequence by using a preset mapping spreading rule to obtain corresponding first to-be-processed spreading sequences; the number of the first to-be-processed spreading sequences is consistent with the preset spreading factor value; there is a mapping relationship between the iterative sequence and the unique first to-be-processed spreading sequence.

[0130] In some specific embodiments, the GMSK signal communication device may further include:

[0131] A second spreading sequence determination unit for storing the first to-be-processed spreading sequence into the original GMSK signal to obtain a to-be-processed GMSK signal, and transmitting the to-be-processed GMSK signal through a preset channel to a preset receiving end so that the preset receiving end samples the to-be-processed GMSK signal to obtain a plurality of the first to-be-processed spreading sequences.

[0132] In some specific embodiments, the vector likelihood summation module 13 may specifically include:

[0133] A component group extraction unit for extracting a corresponding in-phase component group from each first to-be-processed spreading sequence by using a preset in-phase component extraction technique, and extracting a corresponding quadrature component group from each first to-be-processed spreading sequence by using a preset quadrature component extraction technique; the absolute phase vector group includes the in-phase component group and the quadrature component group;

[0134] A branch path metric value determination unit for respectively performing likelihood summation on each in-phase component group and each quadrature component group with the phase vectors of the corresponding second to-be-processed spreading sequences to obtain corresponding branch path metric values.

[0135] In some specific embodiments, the target signal sequence determination module 14 may specifically include:

[0136] An accumulated path metric value unit, configured to perform forward state transitions on each of the branch path metric values and the corresponding initial total path metric using the Viterbi algorithm to obtain the corresponding accumulated path metric values;

[0137] A maximum likelihood path determination unit, configured to set the likelihood path corresponding to the path metric value with the largest value among the accumulated path metric values as the maximum likelihood path, and delete the paths corresponding to the remaining accumulated path metric values respectively;

[0138] A path backward traceback unit, configured to perform backward traceback on the maximum likelihood path using the Viterbi algorithm to obtain a backward traceback result, and arrange the backward traceback results in a preset arrangement order to obtain a target spreading sequence;

[0139] A spreading sequence mapping unit, configured to map the target spreading sequence using the preset mapping spreading rule to obtain a target signal sequence for communicating using the signal corresponding to the target signal sequence.

[0140] Furthermore, an embodiment of the present application also discloses an electronic device. Figure 7 It is a structural diagram of an electronic device 20 shown according to an exemplary embodiment, and the content in the figure should not be considered as any limitation to the scope of use of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. Among them, the memory 22 is used to store a computer program, and the computer program is loaded and executed by the processor 21 to implement the relevant steps in the GMSK signal communication method disclosed in any of the foregoing embodiments. Additionally, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0141] In this embodiment, the power supply 23 is used to provide operating voltages for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows is any communication protocol applicable to the technical solution of the present application, and no specific limitation is imposed on it here; the input / output interface 25 is used to obtain external input data or output data to the outside, and the specific interface type can be selected according to specific application requirements, and no specific limitation is made here.

[0142] In addition, as a carrier for storing resources, the memory 22 can be a read-only memory, a random access memory, a magnetic disk, an optical disc, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0143] Among them, the operating system 221 is used to manage and control each hardware device and the computer program 222 on the electronic device 20, and it can be Windows Server, Netware, Unix, Linux, etc. In addition to the computer program that can be used to complete the GMSK signal communication method executed by the electronic device 20 disclosed in any of the foregoing embodiments, the computer program 222 can further include computer programs that can be used to complete other specific tasks.

[0144] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the foregoing disclosed GMSK signal communication method is implemented. For the specific steps of this method, reference can be made to the corresponding content disclosed in the foregoing embodiments, and details will not be repeated here.

[0145] In this specification, the various embodiments are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The same or similar parts among the various embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0146] Those skilled in the art can further realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the components and steps of the examples have been generally described according to their functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0147] The steps of the method or algorithm described in combination with the embodiments disclosed herein can be directly implemented by hardware, a software module executed by a processor, or a combination of the two. The software module can be placed in a random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium well-known in the technical field.

[0148] Finally, it should also be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising said element.

[0149] The technical solutions provided in this application have been introduced in detail above. Specific examples are used in this text to elaborate on the principle and implementation manner of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A GMSK signal communication method, characterized in that: include: Based on the phase information of the original GMSK signal, a continuous additional phase is generated for each transmission sequence corresponding to the original GMSK signal to obtain a plurality of state sequences; Combining information sequences of adjacent symbols corresponding to each state sequence with the state sequence to obtain each iterative sequence, and mapping each iterative sequence using a preset mapping spread spectrum rule to obtain a corresponding first spread spectrum sequence to be processed; Generate corresponding absolute phase vector groups based on each of the first spread spectrum sequences to be processed, and perform likelihood summation on each of the absolute phase vector groups and the phase vector corresponding to the second spread spectrum sequence to be processed, to obtain corresponding branch path metric values; The second spread spectrum sequence to be processed is a spread spectrum sequence obtained by processing the first spread spectrum sequence to be processed by using a preset front-end filter; The Viterbi algorithm is used to perform a forward state transfer on the metric values ​​of each branch path, and the path corresponding to the path metric value with the largest value among the accumulated path metric values ​​is set as the maximum likelihood path. The maximum likelihood path is then traced back backward to obtain a target spread spectrum sequence, so as to determine a target signal sequence based on the target spread spectrum sequence using the preset mapping spread spectrum rule.

2. The GMSK signal communication method according to claim 1, characterized in that: The phase information of the original GMSK signal is used to generate a continuous additional phase for each transmission sequence corresponding to the original GMSK signal, and a plurality of state sequences are obtained, including: Generate a continuous additional phase by using a preset phase addition technology and based on phase information, signal power, carrier frequency, symbol period and baseband frequency pulse corresponding to the original GMSK signal; the continuous additional phase is a phase generated by phase modulation of a plurality of code elements; The continuous additional phase is added to each transmission sequence corresponding to the original GMSK signal to obtain a plurality of state sequences; the baseband frequency pulse is an impulse response obtained after the original GMSK signal is processed by a preset Gaussian filter.

3. The GMSK signal communication method according to claim 2, characterized in that: The step of generating a continuous additional phase for each transmission sequence corresponding to the original GMSK signal based on the phase information of the original GMSK signal includes: Determine the inter-symbol crosstalk degree based on the normalized bandwidth and symbol period corresponding to the preset Gaussian filter, and determine the instantaneous phase based on the inter-symbol crosstalk degree; the instantaneous phase is used to describe the phase change in the current symbol period; Decomposing the phase information of the original GMSK signal into a constant phase part and a phase change part, wherein the constant phase part is the accumulated sum of phase changes of all symbols at the current moment; A number of the consecutive additional phases are determined based on the phase constant portion and the instantaneous phase.

4. The GMSK signal communication method according to claim 2, characterized in that: The step of combining the information sequences of adjacent symbols corresponding to the state sequences with the state sequences to obtain the iterative sequences, and mapping the iterative sequences using a preset mapping spread spectrum rule to obtain the corresponding first spread spectrum sequence to be processed includes: Determining the number of sequences corresponding to the state sequence based on the normalized bandwidth corresponding to the preset Gaussian filter and the symbol period; Acquire information sequences corresponding to adjacent codeword groups corresponding to the number of state sequences respectively, and combine each state sequence with the corresponding information sequence to obtain a corresponding iterative sequence; the adjacent codeword group includes a preset number of adjacent codewords; Each of the iterative sequences is mapped using a preset mapping spread spectrum rule to obtain a corresponding first spread spectrum sequence to be processed; the number of the first spread spectrum sequences to be processed is consistent with a preset spread spectrum factor value; the iterative sequence is in a mapping relationship with the only first spread spectrum sequence to be processed.

5. The GMSK signal communication method according to claim 1, characterized in that: After combining the information sequences of adjacent symbols corresponding to the state sequences respectively with the state sequences to obtain the iterative sequences, and mapping the iterative sequences respectively using a preset mapping spread spectrum rule to obtain the corresponding first spread spectrum sequence to be processed, the method further includes: The first spread spectrum sequence to be processed is stored in the original GMSK signal to obtain a GMSK signal to be processed, and the GMSK signal to be processed is transmitted to a preset receiving end through a preset channel so that the preset receiving end samples the GMSK signal to be processed to obtain a plurality of the first spread spectrum sequences to be processed.

6. The GMSK signal communication method according to claim 1, characterized in that: The generating corresponding absolute phase vector groups based on each of the first spread spectrum sequences to be processed respectively, and performing likelihood summation on each of the absolute phase vector groups and the phase vector corresponding to the second spread spectrum sequence to be processed respectively to obtain a corresponding branch path metric value, includes: Extracting a corresponding in-phase component group from each of the first spread spectrum sequences to be processed using a preset in-phase component extraction technology, and extracting a corresponding orthogonal component group from each of the first spread spectrum sequences to be processed using a preset orthogonal component extraction technology; the absolute phase vector group includes the in-phase component group and the orthogonal component group; Likelihood summation is performed on each of the in-phase component groups and each of the orthogonal component groups and the corresponding phase vector of the second spread spectrum sequence to be processed to obtain a corresponding branch path metric value.

7. The GMSK signal communication method according to any one of claims 1 to 6, characterized in that: The method uses the Viterbi algorithm to perform a forward state transfer on the metric values ​​of each branch path, sets the path corresponding to the path metric value with the largest value among the accumulated path metric values ​​as the maximum likelihood path, and then performs backward tracing on the maximum likelihood path to obtain a target spread spectrum sequence, so as to determine a target signal sequence based on the target spread spectrum sequence by using the preset mapping spread spectrum rule, including: Using the Viterbi algorithm, forward state transfer is performed on each of the branch path metrics and the corresponding initial total path metrics to obtain the corresponding cumulative path metric value; The likelihood path corresponding to the path metric value with the largest value among the accumulated path metric values ​​is set as the maximum likelihood path, and the paths corresponding to the remaining accumulated path metric values ​​are deleted; Performing backward tracing of the maximum likelihood path using the Viterbi algorithm to obtain a backward tracing result, and arranging each of the backward tracing results in a preset arrangement order to obtain a target spread spectrum sequence; The target spread spectrum sequence is mapped using the preset mapping spread spectrum rule to obtain a target signal sequence, so as to communicate using a signal corresponding to the target signal sequence.

8. A GMSK signal communication device, characterized in that: include: A phase generation module, used for generating continuous additional phases for each transmission sequence corresponding to the original GMSK signal based on the phase information of the original GMSK signal, to obtain a plurality of state sequences; A sequence mapping module, used to combine information sequences of adjacent code elements corresponding to each state sequence with the state sequence to obtain each iterative sequence, and map each iterative sequence using a preset mapping spread spectrum rule to obtain a corresponding first spread spectrum sequence to be processed; A vector likelihood summing module, configured to generate corresponding absolute phase vector groups based on each of the first spread spectrum sequences to be processed, and perform likelihood summation on each of the absolute phase vector groups and the phase vector corresponding to the second spread spectrum sequence to be processed, to obtain a corresponding branch path metric value; The second spread spectrum sequence to be processed is a spread spectrum sequence obtained by processing the first spread spectrum sequence to be processed by using a preset front-end filter; The target signal sequence determination module is used to use the Viterbi algorithm to perform forward state transfer on the metric values ​​of each branch path, and set the path corresponding to the path metric value with the largest value among the accumulated path metric values ​​as the maximum likelihood path, and then trace back the maximum likelihood path to obtain the target spread spectrum sequence, so as to determine the target signal sequence based on the target spread spectrum sequence using the preset mapping spread spectrum rule.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the steps of the GMSK signal communication method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store a computer program, wherein when the computer program is executed by a processor, the steps of the GMSK signal communication method according to any one of claims 1 to 7 are implemented.

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