A digital demodulation method, apparatus, device, and storage medium

Abstract

This application discloses a digital demodulation method, apparatus, device, and storage medium, relating to the field of digital communication. The method includes: acquiring a filtered signal of a transmitted signal after passing through a filter, and performing phase differential on the filtered signal; extracting the obtained differential phase and determining the signal to be demodulated based on the differential phase; determining the target differential phase of the filtered signal according to the current communication environment, and constructing a composite grid based on the target differential phase; determining sub-grids based on the composite grid, and determining the branch path metric and total path metric of the signal to be demodulated based on the sub-grids; performing Viterbi demodulation based on the total path metric, and obtaining the demodulation result by backtracking the Viterbi demodulation based on the total path metric. This application constructs a composite grid phase compensation model for GMSK and proposes a composite Viterbi demodulation algorithm for GMSK signals based on differential phase, which can overcome the influence of Doppler frequency offset on demodulation performance and maintain excellent performance even with large frequency offsets.

Description

Technical Field

[0001] This invention relates to the field of digital communications, and in particular to a digital demodulation method, apparatus, device, and storage medium. Background Technology

[0002] Modern communications place increasingly higher demands on modulation and demodulation techniques, especially given the current scarcity of spectrum resources. The importance of modulation and demodulation techniques that require minimal bandwidth and offer high performance is self-evident. Gaussian Minimum-Shift Keying (GMSK) modulation offers advantages such as constant envelope and excellent spectral efficiency, making it widely used in modern communications and suitable for communication systems with adjacent channel interference and nonlinear power amplifiers.

[0003] GMSK signal demodulation techniques can be divided into coherent demodulation and non-coherent demodulation. Coherent demodulation requires carrier recovery, compensation for carrier frequency deviation and timing errors, and carrier phase synchronization, resulting in a complex overall system implementation and weak anti-interference capability. Non-coherent demodulation, on the other hand, has a relatively simple structure and better robustness to carrier frequency and phase deviations, thus gaining wider application. For example, missile-to-missile and satellite-to-missile communication links may involve speeds up to Mach 10 and accelerations reaching 20g. This high-speed, mobile communication environment results in significant Doppler effects during signal transmission, and these application scenarios also impose stringent requirements on communication reliability. Therefore, coherent demodulation is clearly unsuitable for applications in such high-dynamic environments, necessitating the research of non-coherent demodulation algorithms that are robust to Doppler frequency deviations and possess high reliability.

[0004] While most current demodulation algorithms can improve demodulation performance, they struggle to adapt to the Doppler frequency offsets present in highly dynamic communication environments. For example, while combining machine learning with GMSK demodulation improves performance, it requires extensive data and has poor adaptability to highly dynamic communication environments. The Viterbi algorithm based on phase state trellises and the Viterbi algorithm with amplitude limiting and frequency discrimination assistance improve demodulation performance, but their adaptability to frequency offsets is weak. Furthermore, while the current Viterbi demodulation method for GMSK signals based on differential phase detection has improved performance, its resistance to frequency offsets still has room for improvement. Therefore, maintaining strong robustness to frequency offsets to adapt to highly dynamic environments while ensuring good demodulation performance is a pressing problem to be solved in this field. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide a digital demodulation method, apparatus, device, and storage medium. A composite grid phase compensation model for GMSK is constructed, and a differential phase-based composite Viterbi demodulation algorithm for GMSK signals is proposed. This algorithm can overcome the influence of Doppler frequency offset on demodulation performance and maintain excellent performance even with large frequency offsets. The specific scheme is as follows:

[0006] Firstly, this application provides a digital demodulation method, including:

[0007] The filtered signal after the transmitted signal is filtered by a Gaussian filter is obtained, and the filtered signal is phase-differentiated by a differential phase detection network.

[0008] The differential phase is obtained by extracting the filtered signal and performing differential division, and the signal to be demodulated is determined based on the differential phase.

[0009] The target differential phase corresponding to the filtered signal is determined based on the current communication environment, and a composite grid is constructed based on the target differential phase.

[0010] Subgrids are determined based on the composite grid, and the branch path metric and total path metric of the signal to be demodulated are determined based on the subgrids.

[0011] Viterbi demodulation is performed based on the total path metric, and the demodulation result is obtained by backtracking the Viterbi demodulation based on the total path metric.

[0012] Optionally, determining the signal to be demodulated based on the differential phase includes:

[0013] The normalized bandwidth of the Gaussian filter corresponding to the transmitted signal is determined, and the target number of Viterbi demodulation is determined based on the normalized bandwidth; the target number of symbols is the number of symbols that cause inter-symbol interference when performing Viterbi demodulation.

[0014] The delay timer for the filtered signal is determined based on the number of target symbols, and the demodulated signal is obtained based on the delay timer.

[0015] Optionally, determining the target differential phase corresponding to the filtered signal based on the current communication environment includes:

[0016] Determine the differential phase of the basic grid for Viterbi demodulation, and determine the phase rotation unit degree and the first phase rotation number corresponding to the filtered signal based on the current communication environment;

[0017] The target differential phase is calculated based on the differential phase of the basic grid, the phase rotation unit degree, the number of first phase rotations, and the normalized bandwidth.

[0018] Optionally, determining the sub-mesh based on the composite mesh includes:

[0019] The second phase rotation number of the composite mesh is initialized to 1, and the target parameter is obtained by dividing the second phase rotation number by two and rounding down.

[0020] The sub-mesh is determined based on the target parameters, the differential phase of the basic mesh, and the phase rotation unit degree.

[0021] Optionally, after performing Viterbi demodulation based on the total path metric, the method further includes:

[0022] Store the initial minimum value of the total path metric in the current Viterbi demodulation process;

[0023] Increment the second phase rotation count by one, and determine whether the new second phase rotation count is greater than the first phase rotation count;

[0024] If not, proceed to the step of determining a subgrid based on the composite grid and determining the branch path metric and total path metric of the demodulated signal according to the subgrid.

[0025] Optionally, the step of obtaining the demodulation result by backtracking the Viterbi demodulation based on the total path metric includes:

[0026] If the new second phase rotation count obtained by adding one to the second phase rotation count is greater than the first phase rotation count, then the target minimum value is determined from the initial minimum value in all the total path metrics, and the demodulation result is obtained by backtracking the Viterbi demodulation based on the target minimum value.

[0027] Optionally, after obtaining the demodulation result by backtracking the Viterbi demodulation based on the total path metric, the method further includes:

[0028] Determine the data demodulation requirements of the preset backend, and convert the demodulation results into hard decision information or soft decision information and output them to the preset backend according to the data demodulation requirements.

[0029] Secondly, this application provides a digital demodulation apparatus, comprising:

[0030] The phase difference module is used to acquire the filtered signal after the transmitted signal is filtered by a Gaussian filter, and to perform phase difference on the filtered signal through a differential phase detection network.

[0031] The signal determination module is used to extract the differential phase obtained by differential division of the filtered signal, and determine the demodulated signal based on the differential phase.

[0032] A mesh construction module is used to determine the target differential phase corresponding to the filtered signal based on the current communication environment, and to construct a composite mesh based on the target differential phase.

[0033] The metric determination module is used to determine sub-grids based on the composite grid, and to determine the branch path metric and total path metric of the signal to be demodulated based on the sub-grids;

[0034] The digital demodulation module is used to perform Viterbi demodulation based on the total path metric, and to obtain the demodulation result by backtracking the Viterbi demodulation based on the total path metric.

[0035] Thirdly, this application provides an electronic device, which includes a processor and a memory; wherein the memory is used to store a computer program, which is loaded and executed by the processor to implement the aforementioned digital demodulation method.

[0036] Fourthly, this application provides a computer-readable storage medium for storing a computer program that, when executed by a processor, implements the aforementioned digital demodulation method.

[0037] In this application, the first step is to acquire the filtered signal of the transmitted signal after filtering with a Gaussian filter. The filtered signal is then phase-differentialized using a differential phase detection network. The differential phase obtained after differential phase differentiation is extracted, and the signal to be demodulated is determined based on the differential phase. The target differential phase corresponding to the filtered signal is determined according to the current communication environment. A composite grid is constructed based on the target differential phase, and sub-grids are determined based on the composite grid. The branch path metric and total path metric of the signal to be demodulated are then determined based on the sub-grids. Viterbi demodulation is then performed based on the total path metric, and the demodulation result is obtained by backtracking the Viterbi demodulation based on the total path metric. In this way, this application constructs a composite grid phase compensation model for GMSK and proposes a composite Viterbi demodulation algorithm for GMSK signals based on differential phase. This algorithm can overcome the influence of Doppler frequency offset on demodulation performance and maintain excellent performance even with large frequency offsets. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0039] Figure 1 A flowchart of a digital demodulation method provided in this application;

[0040] Figure 2 This application provides a flowchart of a composite Viterbi demodulation process based on 2-bit differential phase.

[0041] Figure 3 A flowchart of a specific digital demodulation method provided in this application;

[0042] Figure 4 This application provides a performance comparison chart of various non-coherent demodulation algorithms for GMSK;

[0043] Figure 5 This application provides a comparison chart of bit error rate performance under different frequency offsets without a composite mesh.

[0044] Figure 6 This application provides a comparison chart of bit error rate performance under different frequency offsets when there is a composite grid.

[0045] Figure 7 This application provides a schematic diagram of the structure of a digital demodulation device;

[0046] Figure 8 This application provides a structural diagram of an electronic device. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Gaussian minimum shift keying (GMS) modulation, with its advantages of constant envelope and good spectral efficiency, is widely used in modern communications, particularly in systems with adjacent channel interference and nonlinear power amplifiers. However, the current high-speed mobile communication environment exhibits a significant Doppler effect during signal transmission, placing stringent demands on communication reliability. Therefore, current demodulation algorithms struggle to meet the demands of such high-dynamic environments. This application's GMSK composite grid phase compensation model, through a differential phase-based GMSK signal composite Viterbi demodulation algorithm, overcomes the impact of large Doppler frequency offsets on demodulation performance, maintaining excellent performance even with large frequency offsets.

[0049] See Figure 1 As shown, this embodiment of the invention discloses a digital demodulation method, including:

[0050] Step S11: Obtain the filtered signal after the transmitted signal is filtered by a Gaussian filter, and perform phase difference on the filtered signal through a differential phase detection network.

[0051] In this embodiment, as Figure 2 As shown, the receiving end first needs to obtain the filtered signal after the transmitted signal has been filtered by a Gaussian filter. Specifically, let the transmitted sequence be α = ... a -1 ,a0,a1...;a i If ∈{-1,+1}, then the corresponding GMSK transmission signal can be represented as:

[0052]

[0053] In the formula, ωc is the carrier angular frequency, and P s Where is the power of the transmitted signal, T is the symbol period, g(t) is the baseband frequency pulse, and h is the modulation index, which is 0.5 in GMSK. This is the additional phase corresponding to the transmitted sequence. For the GMSK signal, g(t) is the impulse response of the rectangular pulse after passing through a Gaussian filter:

[0054] g(t) = Q(cB) t T(-t / T))-Q(cB t T(1-t / T));

[0055] Where, c = 7.546, B t T is the normalized bandwidth of the Gaussian filter, and

[0056] This is the standard Q function.

[0057] After the GMSK signal passes through the AWGN (Additive White Gaussian Noise) channel, the received signal is represented as follows:

[0058] r(t,α)=s(t,α)+n(t);

[0059] n(t) is Gaussian white noise with double-sideband power spectral density N0 / 2.

[0060] At the receiver, r(t,α) is first passed through a front-end filter to remove out-of-band noise, with its bandwidth typically set to 99% of the power bandwidth of the GMSK transmitted signal. After filtering, the phase signal used for back-end detection can be expressed as:

[0061]

[0062]

[0063] In the formula, ρ is the signal-to-noise ratio at the receiver, and n c (t) and n s (t) represents the in-phase component and the quadrature component of n(t), respectively. After obtaining the filtered signal, the filtered signal can be phase-differentiated by a differential phase detection network.

[0064] Step S12: Extract the differential phase obtained by differential division of the filtered signal, and determine the demodulated signal based on the differential phase.

[0065] like Figure 2 As shown, in this embodiment, the filtered signal can be passed through a 2-bit differential phase detection network. This network performs a 2-bit phase delay and differential on the signal, and extracts the differential phase. Then, the normalized bandwidth of the Gaussian filter corresponding to the transmitted signal is determined. Based on the normalized bandwidth, the target number of symbols for Viterbi demodulation is determined. After determining the delay timer for the filtered signal based on the target number of symbols, the demodulated signal can be obtained based on the delay timer. Here, the target number of symbols refers to the number of symbols that cause inter-symbol interference during Viterbi demodulation.

[0066] It should be noted that for the GMSK signal, the network output at the end of the k-th symbol interval (t = kT + T) can be expressed by the following formula:

[0067]

[0068]

[0069] In the formula, ζ k =η(kT+T)-η(kT-T), where L means that the main inter-symbol interference is caused by L symbols to the left and right of the current symbol, and all modulo 2π operations satisfy -π < Φ. k ≤π, different B t θ under T i The values ​​are shown in the table below:

[0070] Table 1 Different B t θ under T i Value and signal 99% power bandwidth

[0071]

[0072] θ in the above table i The value is in degrees.

[0073] In Viterbi demodulation, it is necessary to construct an ideal differential phase value and perform likelihood estimation by subtracting it from the output of the receiver's 2-bit differential phase network. During the k-th symbol interval, state S... k Transition to state S k+1The corresponding ideal differential phase value is calculated as follows:

[0074]

[0075] In the formula, d = (d k-2L'-1 ,d k-2L' ,d k-2L'+1 ,...,d k ) is state S k Transition to state S k+1 The corresponding sequence, state S k The definition of S k =(a k-2L'-1 ,a k-2L' ,a k-2L'+1 ,...,a k-1 L' is the number of symbols for inter-symbol interference considered during Viterbi demodulation, satisfying 1≤L'≤L.

[0076] The phase of the filtered signal is extracted and differentially divided into 2 bits, based on the B of the transmitted signal. t T determines L', and the differential phase is passed through an L'T delay circuit to obtain the demodulated signal Φ. k-L' The determined demodulation signal is:

[0077]

[0078] Step S13: Determine the target differential phase corresponding to the filtered signal based on the current communication environment, and construct a composite grid based on the target differential phase.

[0079] It should be noted that, considering the frequency offset effect in 2-bit differential Viterbi demodulation, if the Doppler effect exists in the AWGN channel, the received signal can be expressed as:

[0080]

[0081] In the formula, Δf(t) is the Doppler frequency offset. After front-end filtering and a 2-bit differential phase network, the output at the end of the k-th symbol interval (t = kT + T) is expressed as:

[0082]

[0083] In the formula Φ k The output of the 2-bit differential phase network without frequency offset, Δθ d This is the cumulative phase shift caused by the frequency shift due to the Doppler effect over a time interval of 2T.

[0084]

[0085] Then, in the backend Viterbi demodulation, the formula for calculating the branch path metric becomes:

[0086] B M (S k ,S k+1 )={mod[(Φ k-L' +Δθ d,k-L' -P(S k ,S k+1 )),2π]} 2 ;

[0087] As can be seen from the above formula, when there is a frequency offset, the calculation of the branch path metric and the total path metric introduces an error. The larger the cumulative phase offset caused by the Doppler effect, the larger the calculation error of the path metric, and the more severe the degradation of demodulation performance.

[0088] Therefore, this embodiment addresses the impact of frequency offset on the output of a 2-bit differential phase network. Based on Viterbi demodulation, a composite grid is constructed to compensate for accumulated phase errors. A composite Viterbi algorithm is proposed for the receiver backend to improve adaptability to frequency offset. First, the differential phase of the basic grid for Viterbi demodulation is determined. Then, based on the current communication environment, the phase rotation unit degree and the number of first phase rotations corresponding to the filtered signal are determined. Finally, the target differential phase is calculated based on the differential phase of the basic grid, the phase rotation unit degree, the number of first phase rotations, and the normalized bandwidth. A composite grid is then constructed based on the target differential phase. It is understood that in specific engineering applications, considering the specific communication system and environment, when parameters such as carrier frequency and frame structure are determined, the range of Doppler frequency offset and its caused accumulated phase error can be analyzed. Based on this, selecting appropriate values ​​for the number of first phase rotations M and the phase rotation unit degree Δθ allows for more accurate compensation of the phase error, resulting in a more precise decision.

[0089] Step S14: Determine subgrids based on the composite grid, and determine the branch path metric and total path metric of the signal to be demodulated based on the subgrids.

[0090] In this embodiment, appropriate values ​​of M and Δθ are selected, based on B. t T calculates P(S) k ,S k+1 Given the values ​​of ), construct a composite mesh, initially assigning j = 1. Let The subgrid P = {P1 + xΔθ, P2 + xΔθ, ..., P} can then be selected. N +xΔθ}, according to M(S k+1 )=M(S k )+B M (S k ,S k+1 ) and BM (S k ,S k+1 )={mod[(Φ k-L' +Δθ d,k-L' -P(S k ,S k+1 )-xΔθ),2π]} 2 This allows us to calculate the branch path metric and total path metric for each symbol during state transitions, and then perform Viterbi demodulation (without backtracking).

[0091] Step S15: Perform Viterbi demodulation based on the total path metric, and obtain the demodulation result by backtracking the Viterbi demodulation based on the total path metric.

[0092] In this embodiment, Viterbi demodulation can be performed based on the total path metric obtained in the previous step, and the demodulation result is obtained by backtracking the Viterbi demodulation based on the total path metric. After obtaining the demodulation result, the data demodulation requirements of the preset backend are determined, and the demodulation result is converted into hard decision information or soft decision information and output to the preset system backend according to the data demodulation requirements, thus completing the entire demodulation process.

[0093] This embodiment first acquires the filtered signal after the transmitted signal is filtered by a Gaussian filter, and then performs phase difference detection on the filtered signal through a differential phase detection network. The differential phase obtained after differential detection is then extracted, and the signal to be demodulated is determined based on the differential phase. The target differential phase corresponding to the filtered signal is determined based on the current communication environment. After constructing a composite grid based on the target differential phase, sub-grids can be determined based on the composite grid. The branch path metric and total path metric of the signal to be demodulated are then determined based on the sub-grids. Viterbi demodulation is then performed based on the total path metric, and the demodulation result is obtained by backtracking the Viterbi demodulation based on the total path metric. Through the above technical solution, this embodiment addresses the challenge of existing GMSK demodulation methods being unable to adapt to the challenges of Doppler frequency offset in high-dynamic communication environments. It analyzes the impact of cumulative phase error caused by Doppler frequency offset on existing 2-bit differential phase Viterbi demodulation algorithms, constructs a composite grid phase compensation model for GMSK, and proposes a novel 2-bit differential phase composite Viterbi demodulation algorithm. This algorithm overcomes the impact of Doppler frequency offset on demodulation performance at the cost of a small increase in complexity.

[0094] Based on the previous embodiment, this application constructs a composite mesh phase compensation model for GMSK and proposes a novel 2-bit differential phase composite Viterbi demodulation algorithm. Next, this embodiment will describe in detail the demodulation process based on the composite mesh. See [link to previous embodiment]. Figure 3 As shown, this embodiment of the invention discloses a specific digital demodulation method, including:

[0095] Step S21: Determine the target differential phase corresponding to the filtered signal based on the current communication environment, and construct a composite grid based on the target differential phase.

[0096] Step S22: Determine subgrids based on the composite grid, and determine the branch path metric and total path metric of the signal to be demodulated based on the subgrids.

[0097] When determining subgrids based on a composite mesh, the second phase rotation number j of the composite mesh is first assigned an initial value of 1. The target parameter is then obtained by dividing the second phase rotation number by two and rounding down. The subgrid is then determined based on the target parameter, the differential phase of the basic mesh, and the phase rotation unit degree. After constructing the composite mesh, the initial value j is assigned as 1, and then... The subgrid P = {P1 + xΔθ, P2 + xΔθ, ..., P} can then be selected. N +xΔθ}.

[0098] Then according to M(S) k+1 )=M(S k )+B M (S k ,S k+1 ) and B M (S k ,S k+1 )={mod[(Φ k-L' +Δθ d,k-L' -P(S k ,S k+1 )-xΔθ),2π]} 2 This allows us to calculate the branch path metric and the total path metric for each symbol during state transitions.

[0099] In this embodiment, when performing composite Viterbi demodulation, when the B signal at the transmitting end... t When T is determined, and the Viterbi detector at the receiving end determines the selected L', all P(S) k ,S k+1 The values ​​of all possible sequences of length 2L'+2 can be determined. Let P(S) be the sum of all possible sequences of length 2L'+2. k ,S k+1 There are N possible values, denoted as P = {P1, P2, ..., P...} N Let be the differential phase of the basic mesh. Then, by rotating the differential phase of the basic mesh by Δθ, we obtain the composite mesh, which is expressed as:

[0100] P = {P ix}={P i +xΔθ},x=0,±1,...,i=1,2,...,N;

[0101] If there are M possible values ​​for x, then x can take values ​​from 0 to... This indicates rounding down to the nearest integer.

[0102] After the composite mesh is constructed, the values ​​of x and Δθ are selected, that is, a set of sub-mesh P = {P1 + xΔθ, P2 + xΔθ, ..., P} is selected. N +xΔθ}. The corrected formula for calculating the branch path metric then becomes:

[0103] B M (S k ,S k+1 )={mod[(Φ k-L' +Δθ d,k-L' -P(S k ,S k+1 )-xΔθ),2π]} 2 ;

[0104] In this way, the cumulative phase error Δθ caused by the phase rotation xΔθ in the composite mesh due to the Doppler frequency offset d Compensation has been made if there exists a value of x that satisfies |xΔθ|≥|Δθ. d If, in a composite mesh, there exists a sub-mesh such that the phase rotation along a certain path is greater than the cumulative phase error caused by the Doppler effect, then there must exist a sub-mesh in the composite mesh whose cumulative phase error after compensating for the 2-bit differential phase is less than Δθ / 2. That is, there exists an x ​​value that satisfies |Δθ / 2. d +xΔθ|≤Δθ / 2 makes the calculation error of branch path metric and total path metric smaller after using composite mesh compensation.

[0105] In practical differential demodulation systems, if there is jitter or interference Δθ in the differential phase... e When Δθ is satisfied e ≤0.03π, the bit error rate curve at this point is similar to Δθ e When Δθ = 0, the bit error curves almost coincide, and the system's bit error rate is unaffected by the phase error. Therefore, if Δθ ≤ 0.06π is chosen, by selecting the value of M, there exists a value of x such that |Δθ| = 0.06π. d If +xΔθ|≤0.03π, then the demodulation performance of the corresponding path is almost unaffected by the Doppler frequency offset. If at symbol rate R... s Considering a static Doppler frequency offset of 32kHz at 500kHz, the calculated value of Δθ is... d =0.256π, choose Δθ = 0.06π, M = 9, then there exists x = -4 satisfying |Δθ d +xΔθ|=0.016π≤0.03π indicates that the calculation errors of the branch path metric and the total path metric are very small under the corresponding path, and demodulation can be performed correctly.

[0106] Step S23: Perform Viterbi demodulation based on the total path metric, and obtain the demodulation result by backtracking the Viterbi demodulation based on the total path metric.

[0107] It should be noted that in the current traditional Viterbi demodulation based on 2-bit differential, the formula for calculating the branch path metric during state transition is:

[0108] B M (S k ,S k+1 )={mod[(Φ k-L' -P(S k ,S k+1 )),2π]} 2 ;

[0109] The total path metric at the end of the k-th symbol interval is:

[0110] M(S k+1 )=M(S k )+B M (S k ,S k+1 );

[0111] During demodulation, the branch path metric and total path metric are calculated according to the above formula. A forward state transition is then performed. Using the maximum likelihood approach, when multiple branch paths reach the same state node, the path with the smallest total path metric is retained as the surviving path, while the remaining paths are considered contentious and are deleted, thus simplifying the complexity. When the Viterbi demodulation length reaches the backtracking length, a backward backtracking decision is made. The minimum value in the final total path metric is selected, and the state corresponding to that value is backtracked to obtain the maximum likelihood path. Based on the state transitions in the maximum likelihood path, the corresponding transmission sequence is determined, thus completing the demodulation.

[0112] In this embodiment, after constructing the composite mesh in the composite Viterbi demodulation, for each group of sub-mesh, a forward state transition is performed based on the modified branch path metric calculation formula and the total path metric calculation formula. Simultaneously, the absolute value of the difference between the surviving path metric and the contention path metric is calculated and saved. When channel coding exists in the system, this can serve as a reliability measure for soft information; the larger the value, the more reliable the bit correctness determined by the surviving path. When the demodulation length of the Viterbi for this group of sub-mesh reaches the backtracking length, the minimum value in the final total path metric is selected and saved. After all sub-mesh has completed the forward calculation, the saved calculation results are compared, the minimum value is selected, and the sub-mesh corresponding to that value is backtracked to obtain the demodulation result. Therefore, after Viterbi demodulation based on the total path metric, the initial minimum value of the final total path metric in this Viterbi demodulation is stored, the second phase rotation count is incremented by one, and it is determined whether the new second phase rotation count is greater than the first phase rotation count, i.e., j = j + 1. If j ≤ M, the process jumps to the step of determining the subgrid based on the composite grid and determining the branch path metric and total path metric of the signal to be demodulated based on the subgrid. Otherwise, the minimum values ​​of the total path metric stored in M ​​Viterbi demodulations are compared, the minimum value is selected, and the Viterbi demodulation process corresponding to this value is backtracked. That is, if the new second phase rotation count obtained after incrementing the second phase rotation count is greater than the first phase rotation count, the target minimum value is determined from the initial minimum values ​​of all total path metrics, and the Viterbi demodulation backtracking is performed based on the target minimum value to obtain the demodulation result.

[0113] For a more detailed description of the process of step S21, please refer to the relevant content disclosed in the foregoing embodiments, which will not be repeated here.

[0114] In this embodiment, it is assumed that the data length of one frame is K. According to the Viterbi algorithm, each state transition calculation requires 1 multiplication and 2 additions. There are a total of 2 additions at the end of each symbol interval. 2L’+1 There are several states, and each state node has two branches for state transition. Without a composite mesh, the computational complexity is O(3K·2). 2L'+2 When composite meshes exist, the increased complexity depends on the number of additional sub-meshes, i.e., the value of M, resulting in a final algorithm complexity of O(3MK·2). 2L'+2 It is worth noting that the forward computation process of each subgrid is independent, so the composite Viterbi detection can be processed in parallel, without performance degradation in processing latency compared with traditional algorithms.

[0115] Based on the above steps, this embodiment conducted a simulation experiment based on the disclosed algorithm process and the previous embodiment, and the results are as follows:

[0116] A modulation and demodulation system model of GMSK was established using Matlab, and the bit error rate performance and adaptability to frequency offset of the algorithm proposed in this embodiment were simulated. The transmitting end uses B... t The GMSK modulation scheme with a T value of 0.5, based on the frame structure set at the transmitting end, uses the following parameters at the receiving end: L' = 1, M = 9, Δθ = 0.06π, 16-point sampling, and an additive white Gaussian noise channel. The received signal is sequentially subjected to 99% bandwidth filtering, 2-bit differential phase detection, L'T delay, and composite Viterbi demodulation. Turbo encoding and decoding with parameters (2,1,3) are added at both ends of the system to utilize the soft information constructed during composite Viterbi demodulation.

[0117] First, the demodulation performance of the proposed algorithm and the traditional classical algorithm were simulated and compared. Then, the performance of the algorithm against the Doppler effect was analyzed for both cases with and without composite mesh.

[0118] Figure 4 The bit error rate (BER) performance of "2-bit differential demodulation", "2-bit differential + Viterbi demodulation", and "2-bit differential + composite Viterbi demodulation" was compared under no frequency offset. It is evident that "2-bit differential + Viterbi demodulation" outperforms "2-bit differential demodulation". The former shows a significant decrease in BER with increasing signal-to-noise ratio (SNR), and can rapidly decrease by an order of magnitude at high SNRs, reaching 1 × 10⁻⁶ at 7 dB. -5 The performance of "2-bit differential + composite Viterbi demodulation" is basically the same as that of "2-bit differential + Viterbi demodulation", indicating that the construction of the composite grid did not lead to a decrease in bit error rate performance and still maintained good performance.

[0119] Considering Doppler frequency offset, the system bit error rate curves were simulated and analyzed under the following conditions: no frequency offset, frequency offset of 16 kHz, and frequency offset of 32 kHz, with and without a composite grid. The simulation results are as follows: Figure 5 and Figure 6 As shown in the figure, the comparison reveals that without a composite mesh, the algorithm's ability to resist Doppler frequency shift is limited, exhibiting a significant performance drop at a frequency offset of 16 kHz, and losing its demodulation function at a frequency offset of 32 kHz. With a composite mesh, however, the algorithm demonstrates strong adaptability to Doppler frequency shift, maintaining essentially the same demodulation performance as without a frequency offset, even at a frequency offset of 32 kHz. Therefore, the algorithm proposed in this embodiment possesses both good performance and strong resistance to Doppler frequency shift.

[0120] Based on the above technical solution, this embodiment proposes a Viterbi demodulation algorithm for GMSK signals based on 2-bit differential phase. The mechanism of Viterbi demodulation using 2-bit differential phase and composite grid is analyzed, and its ability to resist Doppler frequency offset is theoretically derived. A Matlab system simulation model is established, and simulation results verify the feasibility and stability of the algorithm. The algorithm's bit error rate can reach 10 at 7dB. -5 The algorithm exhibits excellent performance with no degradation under Doppler frequency offset conditions not exceeding 32 kHz. It demonstrates good performance, moderate implementation complexity, and robustness to carrier frequency offset and phase error, making it suitable for high-dynamic communication environments and promising for future applications.

[0121] See Figure 7 As shown in the embodiments, this application also discloses a digital demodulation device, including:

[0122] Phase difference module 11 is used to acquire the filtered signal after the transmitted signal is filtered by a Gaussian filter, and to perform phase difference on the filtered signal through a differential phase detection network.

[0123] The signal determination module 12 is used to extract the differential phase obtained by differential analysis of the filtered signal, and determine the demodulated signal based on the differential phase.

[0124] The mesh construction module 13 is used to determine the target differential phase corresponding to the filtered signal according to the current communication environment, and construct a composite mesh according to the target differential phase;

[0125] The metric determination module 14 is used to determine sub-grids based on the composite grid, and to determine the branch path metric and total path metric of the signal to be demodulated based on the sub-grids;

[0126] The digital demodulation module 15 is used to perform Viterbi demodulation based on the total path metric, and to obtain the demodulation result by backtracking the Viterbi demodulation based on the total path metric.

[0127] This embodiment first acquires the filtered signal after the transmitted signal is filtered by a Gaussian filter, and then performs phase difference detection on the filtered signal through a differential phase detection network. The differential phase obtained after differential detection is then extracted, and the signal to be demodulated is determined based on the differential phase. The target differential phase corresponding to the filtered signal is determined according to the current communication environment. After constructing a composite grid based on the target differential phase, sub-grids can be determined based on the composite grid. The branch path metric and total path metric of the signal to be demodulated are then determined based on the sub-grids. Viterbi demodulation is then performed based on the total path metric, and the demodulation result is obtained by backtracking the Viterbi demodulation based on the total path metric. In this way, by constructing a composite grid phase compensation model for GMSK, this embodiment proposes a differential phase-based composite Viterbi demodulation algorithm for GMSK signals, which can overcome the influence of Doppler frequency offset on demodulation performance and maintain excellent performance even with large frequency offsets.

[0128] In some specific embodiments, the signal determination module 12 specifically includes:

[0129] The symbol determination unit is used to determine the normalized bandwidth of the Gaussian filter corresponding to the transmitted signal, and to determine the target number of Viterbi demodulation based on the normalized bandwidth; the target number of symbols is the number of symbols that cause inter-symbol interference when performing Viterbi demodulation.

[0130] A signal delay unit is used to determine the delay unit of the filtered signal based on the number of target symbols, and to obtain the demodulated signal based on the delay unit.

[0131] In some specific embodiments, the mesh construction module 13 specifically includes:

[0132] A phase determination unit is used to determine the differential phase of the basic grid of the Viterbi demodulation, and to determine the phase rotation unit degree and the first phase rotation number corresponding to the filtered signal according to the current communication environment.

[0133] The phase calculation unit is used to calculate the target differential phase based on the differential phase of the basic grid, the phase rotation unit degree, the first phase rotation number, and the normalized bandwidth.

[0134] In some specific embodiments, the measurement determination module 14 specifically includes:

[0135] The parameter determination unit is used to assign an initial value of 1 to the number of second phase rotations of the composite mesh, and then divide the number of second phase rotations by two and round down to obtain the target parameter.

[0136] A sub-mesh determination unit is used to determine the sub-mesh based on the target parameters, the differential phase of the basic mesh, and the phase rotation unit degree.

[0137] In some specific embodiments, the digital demodulation module 15 further includes:

[0138] A metric storage unit is used to store the initial minimum value of the total path metric in the current Viterbi demodulation process.

[0139] The count determination unit is used to increment the second phase rotation count by one and determine whether the new second phase rotation count is greater than the first phase rotation count; if not, it jumps to the step of determining the subgrid based on the composite grid and determining the branch path metric and total path metric of the demodulated signal according to the subgrid.

[0140] In some specific embodiments, the digital demodulation module 15 specifically includes:

[0141] The signal demodulation unit is configured to determine a target minimum value from the initial minimum values ​​of all total path metrics if the new second phase rotation number obtained after adding one to the second phase rotation number is greater than the first phase rotation number, and to obtain the demodulation result by backtracking the Viterbi demodulation based on the target minimum value.

[0142] In some specific embodiments, the digital demodulation module 15 further includes:

[0143] The result output unit is used to determine the data demodulation requirements of the preset backend, and convert the demodulation result into hard decision information or soft decision information according to the data demodulation requirements and output it to the preset backend.

[0144] Furthermore, embodiments of this application also disclose an electronic device, Figure 8 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.

[0145] Figure 8 This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may 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. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the digital demodulation method disclosed in any of the foregoing embodiments. Furthermore, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0146] In this embodiment, the power supply 23 is used to provide operating voltage 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 can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0147] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0148] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the digital demodulation method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include a computer program capable of performing other specific tasks.

[0149] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned disclosed digital demodulation method. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0150] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0151] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software 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 beyond the scope of this application.

[0152] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main 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 known in the art.

[0153] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0154] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A digital demodulation method, characterized in that, include: The filtered signal after the transmitted signal is filtered by a Gaussian filter is obtained, and the filtered signal is phase-differentiated by a differential phase detection network. The differential phase is obtained by extracting the filtered signal and performing differential division, and the signal to be demodulated is determined based on the differential phase. The target differential phase corresponding to the filtered signal is determined based on the current communication environment, and a composite grid is constructed based on the target differential phase. Subgrids are determined based on the composite grid, and the branch path metric and total path metric of the signal to be demodulated are determined based on the subgrids. Viterbi demodulation is performed based on the total path metric, and the demodulation result is obtained by backtracking the Viterbi demodulation based on the total path metric.

2. The digital demodulation method according to claim 1, characterized in that, The step of determining the signal to be demodulated based on the differential phase includes: The normalized bandwidth of the Gaussian filter corresponding to the transmitted signal is determined, and the target number of Viterbi demodulation is determined based on the normalized bandwidth; the target number of symbols is the number of symbols that cause inter-symbol interference when performing Viterbi demodulation. The delay timer for the filtered signal is determined based on the number of target symbols, and the demodulated signal is obtained based on the delay timer.

3. The digital demodulation method according to claim 2, characterized in that, Determining the target differential phase corresponding to the filtered signal based on the current communication environment includes: Determine the differential phase of the basic grid for Viterbi demodulation, and determine the phase rotation unit degree and the first phase rotation number corresponding to the filtered signal based on the current communication environment; The target differential phase is calculated based on the differential phase of the basic grid, the phase rotation unit degree, the number of first phase rotations, and the normalized bandwidth.

4. The digital demodulation method according to claim 3, characterized in that, The process of determining sub-grids based on the composite grid includes: The second phase rotation number of the composite mesh is initialized to 1, and the target parameter is obtained by dividing the second phase rotation number by two and rounding down. The sub-mesh is determined based on the target parameters, the differential phase of the basic mesh, and the phase rotation unit degree.

5. The digital demodulation method according to claim 4, characterized in that, After performing Viterbi demodulation based on the total path metric, the process further includes: Store the initial minimum value of the total path metric in the current Viterbi demodulation process; Increment the second phase rotation count by one, and determine whether the new second phase rotation count is greater than the first phase rotation count; If not, proceed to the step of determining a subgrid based on the composite grid and determining the branch path metric and total path metric of the demodulated signal according to the subgrid.

6. The digital demodulation method according to claim 5, characterized in that, The backtracking process for obtaining the demodulation result based on the Viterbi demodulation using the total path metric includes: If the new second phase rotation count obtained by adding one to the second phase rotation count is greater than the first phase rotation count, then the target minimum value is determined from the initial minimum value in all the total path metrics, and the demodulation result is obtained by backtracking the Viterbi demodulation based on the target minimum value.

7. The digital demodulation method according to any one of claims 1 to 6, characterized in that, After obtaining the demodulation result by backtracking the Viterbi demodulation based on the total path metric, the method further includes: Determine the data demodulation requirements of the preset backend, and convert the demodulation results into hard decision information or soft decision information and output them to the preset backend according to the data demodulation requirements.

8. A digital demodulation device, characterized in that, include: The phase difference module is used to acquire the filtered signal after the transmitted signal is filtered by a Gaussian filter, and to perform phase difference on the filtered signal through a differential phase detection network. The signal determination module is used to extract the differential phase obtained by differential division of the filtered signal, and determine the demodulated signal based on the differential phase. A mesh construction module is used to determine the target differential phase corresponding to the filtered signal based on the current communication environment, and to construct a composite mesh based on the target differential phase. The metric determination module is used to determine sub-grids based on the composite grid, and to determine the branch path metric and total path metric of the signal to be demodulated based on the sub-grids; The digital demodulation module is used to perform Viterbi demodulation based on the total path metric, and to obtain the demodulation result by backtracking the Viterbi demodulation based on the total path metric.

9. An electronic device, characterized in that, The electronic device includes a processor and a memory; wherein the memory is used to store a computer program, which is loaded and executed by the processor to implement the digital demodulation method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store a computer program, which, when executed by a processor, implements the digital demodulation method as described in any one of claims 1 to 7.

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