CN117938601A - A digital demodulation method, device, equipment and storage medium - Google Patents

Abstract

The application discloses a digital demodulation method, a device, equipment and a storage medium, which relate to the field of digital communication and comprise the following steps: acquiring a filtered signal of a transmission signal passing through a filter, and carrying out phase difference on the filtered signal; extracting the obtained differential phase, and determining a signal to be demodulated according to the differential phase; determining a target differential phase of the filtered signal according to the current communication environment, and constructing a composite grid according to the target differential phase; determining a sub-grid based on the composite grid, and determining branch path metrics and total path metrics of signals to be demodulated according to the sub-grid; and carrying out Viterbi demodulation based on the total path metric, and carrying out backtracking of Viterbi demodulation according to the total path metric to obtain a demodulation result. The application builds a GMSK composite grid phase compensation model, provides a GMSK signal composite Viterbi demodulation algorithm based on differential phase, can overcome the influence of large Doppler frequency offset on demodulation performance, and can still maintain excellent performance under large frequency offset.

Description

A digital demodulation method, device, equipment and storage medium

Technical Field

The present invention relates to the field of digital communications, and in particular to a digital demodulation method, device, equipment and storage medium.

Background technique

Modern communications have increasingly higher requirements for modulation and demodulation technology, especially as spectrum resources are becoming increasingly scarce. The importance of modulation and demodulation technology with small signal bandwidth and good performance is self-evident. Gaussian Minimum-Shift Keying (GMSK) modulation has the advantages of constant envelope and good spectrum utilization. It is widely used in modern communications and is suitable for communication systems with adjacent channel interference and nonlinear power amplifiers.

The demodulation technology of GMSK signals can be divided into coherent demodulation and incoherent demodulation. The coherent demodulation method requires carrier recovery, compensation of carrier frequency deviation and timing error, and synchronization of carrier phase. The overall system is complex to implement and has weak anti-interference ability; while the incoherent demodulation method has a relatively simple structure and good robustness to carrier frequency deviation and phase deviation, so it has been more widely used. For example, missile-to-missile and satellite-to-missile communication links may have a movement speed of up to 10 Mach and an acceleration of up to 20g. This high-speed mobile communication environment determines that there is a significant Doppler effect in the signal transmission process. At the same time, these application scenarios also put forward strict requirements on the reliability of communication. Therefore, coherent demodulation is obviously difficult to adapt to the application requirements under this high-dynamic background, and it is urgent to study incoherent demodulation algorithms that are robust to Doppler frequency deviation and have high reliability.

Although most of the current demodulation algorithms can improve demodulation performance, it is difficult to adapt to the large Doppler frequency deviation in a high-dynamic communication environment. For example, the demodulation of GMSK combined with machine learning improves performance, but requires the assistance of a large amount of data and has poor adaptability to a high-dynamic communication environment. The Viterbi algorithm based on the phase state grid diagram and the Viterbi algorithm assisted by the amplitude limiting frequency detection improve the demodulation performance, but the adaptability to frequency deviation is weak. In addition, the current GMSK signal is based on the Viterbi demodulation method of differential phase detection. Although the performance has been improved, the ability to resist frequency deviation still has room for improvement. Therefore, how to maintain strong robustness to frequency deviation to adapt to a high-dynamic environment while ensuring good demodulation performance is an urgent problem to be solved in this field.

Summary of the invention

In view of this, the purpose of the present invention is to provide a digital demodulation method, device, equipment and storage medium, construct a composite grid phase compensation model of GMSK, and propose a GMSK signal composite Viterbi demodulation algorithm based on differential phase, which can overcome the influence of large Doppler frequency deviation on demodulation performance and maintain excellent performance under large frequency deviation. The specific scheme is as follows:

In a first aspect, the present application provides a digital demodulation method, comprising:

Acquire a filtered signal after the transmission signal is filtered by a Gaussian filter, and perform phase differentiation on the filtered signal through a differential phase detection network;

Extracting a differential phase obtained by differentiating the filtered signal, and determining a signal to be demodulated according to the differential phase;

Determining a target differential phase corresponding to the filtered signal according to a current communication environment, and constructing a composite grid according to the target differential phase;

Determine a sub-grid based on the composite grid, and determine a branch path metric and a total path metric of the signal to be demodulated according to the sub-grid;

Viterbi demodulation is performed based on the total path metric, and back-tracing of the Viterbi demodulation is performed according to the total path metric to obtain a demodulation result.

Optionally, determining the signal to be demodulated according to the differential phase includes:

Determine a normalized bandwidth of the Gaussian filter corresponding to the transmitted signal, and determine a target number of symbols for the Viterbi demodulation according to the normalized bandwidth; the target number of symbols is the number of symbols causing inter-symbol interference when performing the Viterbi demodulation;

A delay device for the filtered signal is determined based on the target symbol quantity, and the signal to be demodulated is obtained based on the delay device.

Optionally, determining a target differential phase corresponding to the filtered signal according to a current communication environment includes:

Determine the differential phase of the basic grid of the Viterbi demodulation, and determine the phase rotation unit degree and the first phase rotation number corresponding to the filtered signal according to the current communication environment;

The target differential phase is calculated according to the differential phase of the basic grid, the phase rotation unit degree, the first phase rotation number and the normalized bandwidth.

Optionally, determining a sub-grid based on the composite grid includes:

Assigning an initial value of 1 to the second phase rotation number of the composite grid, and dividing the second phase rotation number by two and rounding it down to obtain a target parameter;

The sub-grid is determined according to the target parameter, the differential phase of the basic grid and the phase rotation unit degree.

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

storing an initial minimum value of the total path metric in the Viterbi demodulation performed this time;

Increasing the second phase rotation number by one, and determining whether the new second phase rotation number is greater than the first phase rotation number;

If not, jump to the step of determining a sub-grid based on the composite grid, and determining the branch path metric and the total path metric of the signal to be demodulated according to the sub-grid.

Optionally, the backtracking of the Viterbi demodulation according to the total path metric to obtain a demodulation result includes:

If the second phase rotation number is increased by one and the new second phase rotation number is greater than the first phase rotation number, a target minimum value is determined from the initial minimum values in all the total path metrics, and the Viterbi demodulation is back-traced based on the target minimum value to obtain the demodulation result.

Optionally, after performing backtracking of the Viterbi demodulation according to the total path metric to obtain a demodulation result, the method further includes:

Determine the data demodulation requirements of the preset back end, and convert the demodulation results into hard decision information or soft decision information according to the data demodulation requirements and output them to the preset back end.

In a second aspect, the present application provides a digital demodulation device, comprising:

A phase difference module, used for obtaining a filtered signal after the transmission signal is filtered by a Gaussian filter, and performing phase difference on the filtered signal through a differential phase detection network;

A signal determination module, used to extract the differential phase obtained after differentiating the filtered signal, and determine the signal to be demodulated according to the differential phase;

A grid construction module, used to determine a target differential phase corresponding to the filtered signal according to a current communication environment, and construct a composite grid according to the target differential phase;

A metric determination module, configured to determine a sub-grid based on the composite grid, and determine a branch path metric and a total path metric of the signal to be demodulated according to the sub-grid;

The digital demodulation module is used to perform Viterbi demodulation based on the total path metric, and to perform back-tracing of the Viterbi demodulation according to the total path metric to obtain a demodulation result.

In a third aspect, the present application provides an electronic device, comprising a processor and a memory; wherein the memory is used to store a computer program, and the computer program is loaded and executed by the processor to implement the aforementioned digital demodulation method.

In a fourth aspect, the present application provides a computer-readable storage medium for storing a computer program, wherein the computer program implements the aforementioned digital demodulation method when executed by a processor.

In the present application, firstly, the filtered signal after the transmission signal is filtered by a Gaussian filter is obtained, and the filtered signal is phase-differentiated through a differential phase detection network, and then the differential phase obtained after the filtered signal is differentiated is extracted, and the signal to be demodulated is determined according to the differential phase, and the target differential phase corresponding to the filtered signal is determined according to the current communication environment, and after the composite grid is constructed according to the target differential phase, the sub-grid can be determined based on the composite grid, and the branch path metric and the total path metric of the signal to be demodulated are determined according to the sub-grid, and then Viterbi demodulation is performed based on the total path metric, and the demodulation result is obtained by back-tracing the Viterbi demodulation according to the total path metric. In this way, the present application constructs a composite grid phase compensation model of GMSK, and proposes a composite Viterbi demodulation algorithm for GMSK signals based on differential phase, which can overcome the influence of Doppler frequency deviation on demodulation performance and maintain excellent performance under large frequency deviation.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

FIG1 is a flow chart of a digital demodulation method provided by the present application;

FIG2 is a flow chart of a composite Viterbi demodulation based on 2-bit differential phase provided by the present application;

FIG3 is a flow chart of a specific digital demodulation method provided by the present application;

FIG4 is a performance comparison diagram of various GMSK non-coherent demodulation algorithms provided by the present application;

FIG5 is a comparison diagram of bit error performance under different frequency offsets when there is no composite grid provided by the present application;

FIG6 is a comparison diagram of bit error performance under different frequency offsets when a composite grid is provided in the present application;

FIG7 is a schematic diagram of the structure of a digital demodulation device provided by the present application;

FIG8 is a structural diagram of an electronic device provided in this application.

Detailed ways

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

The Gaussian minimum shift keying modulation method in modern communications has the advantages of constant envelope and good spectrum utilization, and is widely used in modern communications, and is suitable for communication systems with adjacent channel interference and nonlinear power amplifiers. However, the current high-speed mobile communication environment has a significant Doppler effect during signal transmission, and also puts forward strict requirements on the reliability of communication. Therefore, the current demodulation algorithm is difficult to adapt to the application requirements under such a high dynamic background. The composite grid phase compensation model of GMSK constructed in this application can overcome the influence of large Doppler frequency deviation on demodulation performance through the composite Viterbi demodulation algorithm of GMSK signal based on differential phase, and can still maintain excellent performance under large frequency deviation.

As shown in FIG1 , an embodiment of the present invention discloses a digital demodulation method, including:

Step S11, obtaining a filtered signal after the transmission signal is filtered by a Gaussian filter, and performing phase differentiation on the filtered signal through a differential phase detection network.

In this embodiment, as shown in FIG2 , the receiving end first needs to obtain the filtered signal after the transmission signal is filtered by a Gaussian filter. Specifically, assuming that the transmission sequence is α=...a _-1 ,a ₀ ,a ₁ ...; a _i ∈{-1,+1}, the corresponding GMSK transmission signal can be expressed as:

Where ωc is the carrier angular frequency, _Ps 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. is the additional phase corresponding to the transmitted sequence. For GMSK signals, g(t) is the impulse response of a rectangular pulse after passing through a Gaussian filter:

g(t)=Q(cB _t T(-t/T))-Q(cB _t T(1-t/T));

Where c = 7.546, _BtT is the normalized bandwidth of the Gaussian filter, and

is the standard Q function.

After the GMSK signal passes through the AWGN (Additive White Gaussian Noise) channel, the received signal is expressed as:

r(t,α)＝s(t,α)+n(t);

n(t) is a Gaussian white noise with a double-sideband power spectral density of N ₀ /2.

At the receiving end, r(t,α) is first filtered out of the out-of-band noise by a front-end filter, whose bandwidth is usually set to 99% of the power bandwidth of the GMSK transmission signal. After passing through the filter, the phase signal used for back-end detection can be expressed as:

Where ρ is the signal-to-noise ratio at the receiving end, and n _c (t) and _ns (t) are the in-phase component and quadrature component of n(t), respectively. After obtaining the filtered signal, the filtered signal can be phase-differentiated through a differential phase detection network.

Step S12: extracting the differential phase obtained by differentiating the filtered signal, and determining the signal to be demodulated according to the differential phase.

As shown in FIG2 , in this embodiment, the filtered signal can be passed through a 2-bit differential phase detection network, which performs 2-bit delay and differentiation on the phase of the signal, and extracts the differential phase. Then, the normalized bandwidth of the Gaussian filter corresponding to the transmitted signal is determined, and the target number of symbols for Viterbi demodulation is determined according to the normalized bandwidth. After the delay device of the filtered signal is determined based on the target number of symbols, the signal to be demodulated can be obtained based on the delay device. Among them, the above-mentioned target number of symbols is the number of symbols that cause inter-code interference when performing Viterbi demodulation.

It should be noted that for GMSK signals, the network output at the end of the kth symbol interval (t=kT+T) can be expressed as follows:

Wherein, ζ _k =η(kT+T)-η(kT-T), L means that the main inter-symbol interference is caused by the L symbols to the left and right of the current symbol, wherein all operations modulo 2π satisfy -π＜Φ _k ≤π, and the values of θ _i under different B _t T are shown in the following table:

Table 1 θ _i values and 99% power bandwidth of signal under different B _t T

The unit of θ _i values in the above table is degree.

In Viterbi demodulation, it is necessary to construct the likelihood of the difference between the ideal differential phase value and the output of the 2-bit differential phase network at the receiving end. The ideal differential phase value corresponding to the transition from state _Sk to state Sk ₊₁ in the kth symbol interval is calculated as follows:

In the formula, d = (d _k-2L'-1 , d _k-2L' , d _k-2L'+1 , ..., d _k ) is the sequence corresponding to the transition from state _Sk to state _Sk+1 , state _Sk is defined as _Sk = ( _ak-2L'-1 , a _k-2L' , a _k-2L'+1 , ..., a _k-1 ), L' is the number of symbols of inter-code interference on both sides considered in Viterbi demodulation, satisfying 1≤L'≤L.

Extract the phase of the filtered signal and perform 2-bit differential, determine L' according to the B _t T of the transmitted signal, and pass the differential phase through the L'T delay device to obtain the signal Φ _k-L' for demodulation. The signal to be demodulated is determined as:

Step S13: determining a target differential phase corresponding to the filtered signal according to the current communication environment, and constructing a composite grid according to the target differential phase.

It should be pointed out that the frequency offset effect is considered in 2-bit differential Viterbi demodulation. If the Doppler effect exists in the AWGN channel, the received signal can be expressed as:

Where Δf(t) is the Doppler frequency deviation. After front-end filtering and a 2-bit differential phase network, the output at the end of the kth symbol interval (t = kT + T) is expressed as:

Where _Φk is the output of the 2-bit differential phase network when there is no frequency offset, and _Δθd is the cumulative phase deviation caused by the frequency offset caused by the Doppler effect within 2T time.

Then in the back-end Viterbi demodulation, the calculation formula of the branch path metric becomes:

_BM (S _k ,S _k+1 )＝{mod[(Φ _k-L′ +Δθ _d,k-L′- P(S _k ,S _k+1 )),2π]} ² ;

It can be seen from the above formula that when there is frequency deviation, the calculation of the branch path metric value and the total path metric value introduces errors. The greater the cumulative phase deviation caused by the Doppler effect, the greater the calculation error of the path metric, and the more serious the degradation of the demodulation performance.

Therefore, in this embodiment, in view of the influence of frequency offset on the output of the 2-bit differential phase network, a composite grid is constructed on the basis of Viterbi demodulation to compensate for the cumulative phase error, and a composite Viterbi algorithm is proposed to be applied to the receiver backend to improve the adaptability to frequency offset. First, the differential phase of the basic grid of Viterbi demodulation is determined, and the phase rotation unit degree and the first phase rotation number corresponding to the filtered signal are determined according to the current communication environment, and the target differential phase is calculated according to the differential phase, the phase rotation unit degree, the first phase rotation number and the normalized bandwidth of the basic grid, and then the composite grid is constructed according to the target differential phase. It can be understood that in specific engineering applications, combined with specific communication systems and communication environments, when parameters such as carrier frequency and frame structure are determined, the Doppler frequency offset and the cumulative phase error range caused by it can be analyzed, and the appropriate first phase rotation number M and the phase rotation unit degree Δθ value are selected accordingly, so that the phase error can be compensated more accurately and a more accurate judgment result can be obtained.

Step S14, determining a sub-grid based on the composite grid, and determining a branch path metric and a total path metric of the signal to be demodulated according to the sub-grid.

In this embodiment, appropriate values of M and Δθ are selected, and the values of P(S _k ,S _k+1 ) are calculated according to B _t T, a composite grid is constructed, and the initial value j=1 is assigned. The subgrid P = {P ₁ +xΔθ, P ₂ +xΔθ, ..., _PN +xΔθ} can be selected, and according to M(S _k+1 ) = _M (S _k ) + BM (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 , the branch path metric and the total path metric at the state transition corresponding to each symbol can be calculated to perform Viterbi demodulation (backtracking is not performed at this time).

Step S15: Perform Viterbi demodulation based on the total path metric, and perform back-tracing of the Viterbi demodulation according to the total path metric to obtain a demodulation result.

In this embodiment, Viterbi demodulation can be performed based on the total path metric obtained in the previous step, and the demodulation result can be obtained by back-tracing the Viterbi demodulation according to 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 according to the data demodulation requirements and output to the preset system backend to complete the entire demodulation process.

This embodiment first obtains the filtered signal after the transmission signal is filtered by a Gaussian filter, and performs phase differentiation on the filtered signal through a differential phase detection network, then extracts the differential phase obtained after the filtered signal is differentiated, and determines the signal to be demodulated according to the differential phase, determines the target differential phase corresponding to the filtered signal according to the current communication environment, and constructs a composite grid according to the target differential phase. The subgrid can be determined based on the composite grid, and the branch path metric and the total path metric of the signal to be demodulated are determined according to the subgrid, and then Viterbi demodulation is performed based on the total path metric, and the demodulation result is obtained by backtracking the Viterbi demodulation according to the total path metric. Through the above technical solution, this embodiment analyzes the impact of the cumulative phase error caused by the Doppler frequency offset on the existing 2-bit differential phase Viterbi demodulation algorithm for the existing GMSK demodulation method that is difficult to adapt to the challenge of large Doppler frequency offset in a high dynamic communication environment, constructs a composite grid phase compensation model for GMSK, and proposes a new 2-bit differential phase composite Viterbi demodulation algorithm, which overcomes the impact of large Doppler frequency offset on demodulation performance at the cost of increasing a small complexity.

Based on the previous embodiment, the present application constructs a composite grid phase compensation model for GMSK and proposes a new 2-bit differential phase composite Viterbi demodulation algorithm. Next, the demodulation process according to the composite grid is described in detail in this embodiment. Referring to FIG3 , an embodiment of the present invention discloses a specific digital demodulation method, including:

Step S21, determining a target differential phase corresponding to the filtered signal according to the current communication environment, and constructing a composite grid according to the target differential phase.

Step S22: determining a sub-grid based on the composite grid, and determining a branch path metric and a total path metric of the signal to be demodulated according to the sub-grid.

When determining a subgrid based on a composite grid, firstly, the second phase rotation times j of the composite grid is assigned an initial value of 1, and the second phase rotation times is divided by two and rounded down to obtain the target parameter, and then the subgrid is determined based on the target parameter, the differential phase of the basic grid, and the phase rotation unit degree. After constructing the composite grid, the initial value j = 1 is assigned, and That is, the sub-grid P = {P ₁ +xΔθ, P ₂ +xΔθ, ..., P _N +xΔθ} can be selected.

Then, according to M(S _k+1 )=M(S _k )+ _BM (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 , the branch path metric and the total path metric for the state transition corresponding to each symbol can be calculated.

In this embodiment, when composite Viterbi demodulation is performed, when _BtT of the transmitting end is determined and the selected L' is determined by the Viterbi detection of the receiving end, all P( _Sk , Sk ₊₁ ) values can be determined. Assuming that there are N P( _Sk , Sk+ ₁ ) values corresponding to all possible sequences of length 2L'+2, P={ _P1 , _P2 , ..., _PN } is the differential phase of the basic grid. Then, by rotating the differential phase of the basic grid by Δθ, a composite grid is obtained, which is expressed as:

P＝{P _ix }＝{P _i +xΔθ},x＝0,±1,...,i＝1,2,...,N；

If there are M possible values of x, then x ranges from 0 to Indicates rounding down.

After the composite grid is constructed, the values of x and Δθ are selected, that is, a group of subgrids P = {P ₁ +xΔθ, P ₂ +xΔθ, ..., P _N +xΔθ} is selected. At this time, the calculation formula of the modified branch path metric value becomes:

_BM (S _k ,S _k+1 )＝{mod[(Φ _k-L′ +Δθ _d,k-L′- P(S _k ,S _k+1 )-xΔθ),2π]} ² ;

In this way, the phase rotation xΔθ in the composite grid compensates for the cumulative phase error Δθ _d caused by the Doppler frequency offset. If there is an x value satisfying |xΔθ|≥|Δθ _d |, that is, there is a sub-grid in the composite grid that makes the phase rotation of a certain path greater than the cumulative phase error caused by the Doppler effect, then at this time there must be a sub-grid in the composite grid whose cumulative phase error after compensating the 2-bit differential phase must be less than Δθ/2, that is, there is an x value satisfying |Δθ _d +xΔθ|≤Δθ/2, so that the calculation errors of the branch path metric and the total path metric after the composite grid compensation are reduced.

In an actual differential demodulation system, if there is jitter or interference Δθ _e in the differential phase, when Δθ _e ≤0.03π is satisfied, the bit error curve at this time is almost the same as the bit error curve when Δθ _e =0, and the bit error rate of the system is not affected by the phase error. Therefore, if Δθ ≤0.06π is selected, by selecting the M value, there can be an x value such that |Δθ _d +xΔθ|≤0.03π, and the demodulation performance of the corresponding path is almost unaffected by the Doppler frequency deviation. If the static Doppler frequency deviation of 32KHz is considered at the symbol rate R _s =500KHz, it can be calculated that Δθ _d =0.256π at this time, and Δθ =0.06π is selected, M =9, then there is x =-4 to satisfy |Δθ _d +xΔθ| =0.016π≤0.03π, and the calculation error of the branch path metric and the total path metric under the corresponding path is very small, and demodulation can be performed correctly.

Step S23: Perform Viterbi demodulation based on the total path metric, and perform back-tracing of the Viterbi demodulation according to the total path metric to obtain a demodulation result.

It should be pointed out that in the current traditional Viterbi demodulation based on 2-bit differential, the calculation formula of the branch path metric value during state transition is:

_BM (S _k ,S _k+1 )={mod[(Φ _k-L'- P(S _k ,S _k+1 )),2π]} ² ;

Then the total path metric corresponding to the end of the kth code element interval is:

M(S _k+1 )=M(S _k )+ _BM (S _k ,S _k+1 );

During demodulation, the branch path metric and the total path metric are calculated according to the above formula, and the forward state transfer is performed. According to the maximum likelihood idea, when multiple branch paths reach the same state node, the path with the smallest total path metric is retained as the surviving path, and the remaining paths are deleted as competitive paths, thereby simplifying the complexity. When the demodulation length of Viterbi 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 the value is backtracked to obtain the maximum likelihood path. The corresponding transmission sequence is determined according to the state transition in the maximum likelihood path, thereby completing the demodulation.

In the composite Viterbi demodulation of this embodiment, after the construction of the composite grid is completed, for each group of sub-grids, the forward state transfer is performed according to the modified branch path metric calculation formula and the total path metric calculation formula. At the same time, the absolute value of the difference between the surviving path metric value and the competing path metric value is calculated and saved. When the system has channel coding, it can be used as a reliability measure of soft information. The larger the value, the more reliable the bit correctness determined by the surviving path. When the demodulation length of the Viterbi of this group of sub-grids reaches the backtracking length, the minimum value in the final total path metric is selected and saved. When all sub-grids complete the forward calculation, the saved calculation results are compared and the minimum value is selected, and the sub-grid corresponding to the value is backtracked to obtain the demodulation result. Therefore, after Viterbi demodulation is performed based on the total path metric, the initial minimum value in the final total path metric in this Viterbi demodulation is stored, and the second phase rotation number is increased by one, and it is determined whether the new second phase rotation number is greater than the first phase rotation number, that is, j=j+1. If j≤M is satisfied, jump to the step of determining the subgrid based on the composite grid, and determining the branch path metric and the total path metric of the signal to be demodulated according to the subgrid. Otherwise, the total path metric minimum values stored in the M-time Viterbi demodulation are compared, the minimum value is selected, and the Viterbi demodulation process corresponding to the value is backtracked, that is, if the new second phase rotation number obtained after the second phase rotation number is increased by one is greater than the first phase rotation number, the target minimum value is determined from the initial minimum values in all total path metrics, and the Viterbi demodulation is backtracked according to the target minimum value to obtain the demodulation result.

For a more specific processing procedure of the above step S21, reference may be made to the corresponding contents disclosed in the above embodiments, which will not be described in detail here.

In this embodiment, it is assumed that the data length of a frame is K. According to the Viterbi algorithm, the calculation of each state transition requires 1 multiplication and 2 additions. There are 2 ^2L'+1 states at the end of each code element interval, and each state node has two branches for state transition. When there is no composite grid, the calculation complexity is O(3K·2 ^2L'+2 ). When there is a composite grid, the increased complexity depends on the number of increased sub-grids, that is, the value of M, and the final algorithm complexity is O(3MK·2 ^2L'+2 ). It is worth noting that the forward calculation process of each sub-grid is independent, so the composite Viterbi detection can be processed in parallel, and there is no performance degradation in processing delay compared with the traditional algorithm.

According to the above steps, this embodiment performs a simulation experiment based on the above disclosed algorithm process combined with the previous embodiment, and the results are as follows:

The modulation and demodulation system model of GMSK is established by using Matlab, and the error performance and adaptability to frequency deviation of the algorithm proposed in this embodiment are simulated. The transmitting end adopts the GMSK modulation mode with a _BtT value of 0.5. According to the frame structure set by the transmitting end, the parameters selected by the receiving end are L'＝1, M＝9, Δθ＝0.06π, 16-point sampling, and the channel is set as an additive white Gaussian noise channel. The received signal is subjected to 99% signal bandwidth filtering, 2bit differential phase detection, L'T delay, and composite Viterbi demodulation in sequence, and Turbo encoding and decoding with parameters of (2,1,3) are added at both ends of the system to utilize the soft information constructed during composite Viterbi demodulation.

Firstly, the demodulation performance of the algorithm proposed in this paper and the traditional classical algorithm are simulated and compared, and then the anti-Doppler effect performance is analyzed for the cases with and without composite grids.

Figure 4 compares the bit error performance of "2-bit differential demodulation", "2-bit differential + Viterbi demodulation" and "2-bit differential + composite Viterbi demodulation" when there is no frequency offset. It can be seen that the performance of "2-bit differential + Viterbi demodulation" is better than that of "2-bit differential demodulation". The bit error rate of the former decreases significantly with the increase of the signal-to-noise ratio, and can quickly decrease by an order of magnitude under high signal-to-noise ratio, reaching the order of 1× ^10-5 at 7dB; while 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 does not lead to a decrease in the bit error performance and still maintains good performance.

Considering the Doppler frequency deviation, the system error curves without composite grid and with composite grid were simulated and analyzed respectively under no frequency deviation, frequency deviation of 16KHz, and frequency deviation of 32KHz, and the simulation results are shown in Figures 5 and 6. By comparison, it can be seen that when there is no composite grid, the algorithm has limited ability to resist Doppler frequency shift, and the performance shows a more obvious decline under the frequency deviation of 16KHz, and the algorithm has lost its demodulation function under the frequency deviation of 32KHz; while when there is a composite grid, the algorithm has a strong adaptability to Doppler frequency shift, and even under the frequency deviation of 32KHz, the algorithm can still maintain a demodulation performance that is basically consistent with that when there is no frequency deviation. It can be seen that the algorithm proposed in this embodiment has a strong ability to resist Doppler frequency shift while having good performance.

Through the above technical solution, this embodiment proposes a GMSK signal composite Viterbi demodulation algorithm based on 2-bit differential phase, analyzes the mechanism of Viterbi demodulation using 2-bit differential phase and composite grid, and theoretically derives its ability to resist Doppler frequency deviation; a Matlab system simulation model is established, and the simulation results verify the feasibility and stability of the algorithm. The bit error rate of the algorithm can reach ^10-5 at 7dB, and the performance does not degrade under the condition of Doppler frequency deviation not exceeding 32KHz, and can maintain excellent performance. The algorithm has good performance, moderate implementation complexity, good robustness to carrier frequency deviation and phase error, and has good applicability and application prospects in high dynamic communication environments.

As shown in FIG. 7 , the embodiment of the present application further discloses a digital demodulation device, including:

The phase difference module 11 is used to obtain a filtered signal after the transmission signal is filtered by a Gaussian filter, and perform phase difference on the filtered signal through a differential phase detection network;

A signal determination module 12, configured to extract a differential phase obtained by differentiating the filtered signal, and determine a signal to be demodulated according to the differential phase;

A grid construction module 13, used to determine a target differential phase corresponding to the filtered signal according to the current communication environment, and construct a composite grid according to the target differential phase;

A metric determination module 14, configured to determine a sub-grid based on the composite grid, and determine a branch path metric and a total path metric of the signal to be demodulated according to the sub-grid;

The digital demodulation module 15 is used to perform Viterbi demodulation based on the total path metric, and to perform back-tracing of the Viterbi demodulation according to the total path metric to obtain a demodulation result.

This embodiment first obtains the filtered signal after the transmission signal is filtered by a Gaussian filter, and performs phase differentiation on the filtered signal through a differential phase detection network, and then extracts the differential phase obtained after the filtered signal is differentiated, and determines the signal to be demodulated according to the differential phase, determines the target differential phase corresponding to the filtered signal according to the current communication environment, and after constructing a composite grid according to the target differential phase, a sub-grid can be determined based on the composite grid, and the branch path metric and the total path metric of the signal to be demodulated can be determined according to the sub-grid, and then Viterbi demodulation is performed based on the total path metric, and the demodulation result is obtained by back-tracing the Viterbi demodulation according to the total path metric. In this way, by constructing a composite grid phase compensation model of GMSK, this embodiment proposes a GMSK signal composite Viterbi demodulation algorithm based on differential phase, which can overcome the influence of Doppler frequency deviation on demodulation performance and maintain excellent performance under large frequency deviation.

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

A symbol determination unit, configured to determine a normalized bandwidth of the Gaussian filter corresponding to the transmitted signal, and determine a target number of symbols for the Viterbi demodulation according to the normalized bandwidth; the target number of symbols is the number of symbols causing inter-symbol interference when performing the Viterbi demodulation;

A signal delay unit is used to determine a delay device of the filtered signal based on the target symbol quantity, and obtain the signal to be demodulated based on the delay device.

In some specific embodiments, the grid construction module 13 specifically includes:

A phase determination unit, configured to determine a differential phase of a basic grid of the Viterbi demodulation, and determine a phase rotation unit degree and a first phase rotation number corresponding to the filtered signal according to the current communication environment;

A phase calculation unit is used to calculate the target differential phase according to the differential phase of the basic grid, the phase rotation unit degree, the first phase rotation number and the normalized bandwidth.

In some specific embodiments, the metric determination module 14 specifically includes:

a parameter determination unit, configured to assign an initial value of 1 to the second phase rotation number of the composite grid, and to divide the second phase rotation number by two and then round it down to obtain a target parameter;

A subgrid determining unit is used to determine the subgrid according to the target parameter, the differential phase of the basic grid and the phase rotation unit degree.

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

A metric value storage unit, used to store the initial minimum value of the total path metric in the Viterbi demodulation performed this time;

A number judgment unit is used to increase the second phase rotation number by one and judge whether the new second phase rotation number is greater than the first phase rotation number; if not, jump to the step of determining the sub-grid based on the composite grid, and determining the branch path measurement and total path measurement of the signal to be demodulated according to the sub-grid.

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

A signal demodulation unit is used to determine a target minimum value from the initial minimum values in all the total path metrics if the new second phase rotation number obtained by adding one to the second phase rotation number is greater than the first phase rotation number, and to perform backtracking of the Viterbi demodulation based on the target minimum value to obtain the demodulation result.

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

The result output unit is used to determine the data demodulation requirements of the preset back end, 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 back end.

Furthermore, an embodiment of the present application also discloses an electronic device. FIG8 is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram cannot be regarded as any limitation on the scope of use of the present application.

FIG8 is a schematic diagram of the structure of an electronic device 20 provided in an embodiment 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. The memory 22 is used to store 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 above embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

In this embodiment, the power supply 23 is used to provide working 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 the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain 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.

In addition, the memory 22, as a carrier for storing resources, can be a read-only memory, a random access memory, a disk or an optical disk, 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.

The operating system 221 is used to manage and control the hardware devices and computer program 222 on the electronic device 20, and can be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program that can be used to complete the digital demodulation method performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 can further include a computer program that can be used to complete other specific tasks.

Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein the computer program, when executed by a processor, implements the digital demodulation method disclosed above. For the specific steps of the method, reference may be made to the corresponding contents disclosed in the above embodiments, and no further description will be given here.

In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the 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 method part.

Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

The technical solution provided by the present application is introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for general technicians in this field, according to the idea of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims (10)

1. A digital demodulation method, comprising:

acquiring a filtered signal of a transmission signal after being filtered by a Gaussian filter, and carrying out phase difference on the filtered signal by a differential phase detection network;

extracting a differential phase obtained after the filtered signals are subjected to differential, and determining a signal to be demodulated according to the differential phase;

determining a target differential phase corresponding to the filtered signal according to the current communication environment, and constructing a composite grid according to the target differential phase;

determining a sub-grid based on the composite grid, and determining branch path metrics and total path metrics of the signals to be demodulated according to the sub-grid;

and carrying out Viterbi demodulation based on the total path metric, and carrying out backtracking of the Viterbi demodulation according to the total path metric to obtain a demodulation result.

2. The digital demodulation method according to claim 1, wherein said determining a signal to be demodulated from said differential phase comprises:

Determining a normalized bandwidth of the Gaussian filter corresponding to the transmission signal, and determining the target symbol number of the Viterbi demodulation according to the normalized bandwidth; the target symbol number is the symbol number which causes at least inter-symbol interference when the Viterbi demodulation is performed;

and determining a delayer of the filtered signal based on the target symbol number, and obtaining the signal to be demodulated based on the delayer.

3. The digital demodulation method according to claim 2, wherein the determining the target differential phase corresponding to the filtered signal according to the current communication environment includes:

determining the differential phase of the basic grid of the Viterbi demodulation, and determining the corresponding phase rotation unit degree and first phase rotation times of the filtered signal according to the current communication environment;

And calculating the target differential phase according to the differential phase of the basic grid, the phase rotation unit degree, the first phase rotation times and the normalized bandwidth.

4. The digital demodulation method according to claim 3, wherein said determining a sub-grid based on said composite grid comprises:

Giving an initial value of 1 to the second phase rotation times of the composite grid, dividing the second phase rotation times by two, and then rounding downwards to obtain a target parameter;

And determining the sub-grid according to the target parameter, the differential phase of the basic grid and the phase rotation unit degree.

5. The digital demodulation method according to claim 4, wherein after said viterbi demodulation based on said total path metric, further comprising:

Storing an initial minimum value in the total path metric in the Viterbi demodulation at this time;

Adding one to the second phase rotation times, and judging whether the new second phase rotation times are larger than the first phase rotation times or not;

If not, jumping to the step of determining a sub-grid based on the composite grid and determining the branch path metric and the total path metric of the signal to be demodulated according to the sub-grid.

6. The digital demodulation method according to claim 5, wherein said backtracking of said viterbi demodulation according to said total path metric results in a demodulation result, comprising:

And if the second phase rotation times are added by one, the obtained new second phase rotation times are larger than the first phase rotation times, determining a target minimum value from the initial minimum values in all the total path metrics, and carrying out backtracking of the Viterbi demodulation according to the target minimum value to obtain the demodulation result.

7. The digital demodulation method according to any one of claims 1 to 6, wherein after the backtracking of the viterbi demodulation according to the total path metric obtains a demodulation result, further comprising:

Determining the data demodulation requirement of a preset back end, and converting the demodulation result into hard decision information or soft decision information according to the data demodulation requirement and outputting the hard decision information or soft decision information to the preset back end.

8. A digital demodulating apparatus, comprising:

The phase difference module is used for acquiring a filtered signal of the transmission signal after being filtered by the Gaussian filter and carrying out phase difference on the filtered signal by the differential phase detection network;

The signal determining module is used for extracting a differential phase obtained after the filtered signals are subjected to differential, and determining a signal to be demodulated according to the differential phase;

The grid construction module is used for determining a target differential phase corresponding to the filtered signal according to the current communication environment and constructing a composite grid according to the target differential phase;

a metric determining module, configured to determine a sub-grid based on the composite grid, and determine a branch path metric and a total path metric of the signal to be demodulated according to the sub-grid;

And the digital demodulation module is used for carrying out Viterbi demodulation based on the total path metric and carrying out backtracking of the Viterbi demodulation according to the total path metric to obtain a demodulation result.

9. An electronic device comprising a processor and a memory; wherein the memory is for storing a computer program that is loaded and executed by the processor to implement the digital demodulation method of any one of claims 1 to 7.

10. A computer readable storage medium for storing a computer program which, when executed by a processor, implements the digital demodulation method according to any one of claims 1 to 7.