CZT-based QAM and MSK signal synchronization method without priori knowledge

Abstract

The invention provides a priori knowledge-free CZT-based QAM (Quadrature Amplitude Modulation) and MSK (Minimum Shift Keying) signal synchronization method, which comprises the following steps of: acquiring a detection signal, and dividing the detection signal into a QAM signal and an MSK signal; performing matched filtering and noise filtering processing on the QAM signal to obtain a first receiving signal; performing matched filtering and noise filtering processing on the MSK signal to obtain a second receiving signal; completing signal synchronization according to the first receiving signal and the second receiving signal; according to the method, the frequency modulation Z transform (CZT) technology is introduced, the frequency offset is limited within a certain range, and the calculation complexity is greatly reduced while the estimation precision is remarkably improved.

Description

Technical Field

[0001] This invention belongs to the field of signal detection and recognition, specifically relating to a CZT-based QAM and MSK signal synchronization method without prior knowledge. Background Technology

[0002] In non-cooperative communication scenarios, receivers lack prior information about the transmitted signal (such as training sequences), making it difficult to employ traditional pilot-dependent demodulation methods. Blind demodulation, a key approach to addressing this challenge, typically involves signal parameter estimation, modulation identification, carrier synchronization, symbol synchronization, blind equalization, and decoding. Among these, the accuracy of carrier and symbol synchronization has a decisive impact on the overall system's decoding performance. Existing synchronization schemes largely rely on pilot signals, and a universal procedure for blind synchronization, particularly capable of simultaneously handling burst QAM and MSK signals, is still lacking. Furthermore, most current blind synchronization methods for QAM signals have limited accuracy. Therefore, developing a high-precision synchronization method applicable to both burst QAM and MSK signals has become an urgent problem to solve. Summary of the Invention

[0003] To address the problems existing in the prior art, this invention proposes a CZT-based QAM and MSK signal synchronization method without prior knowledge. The method includes: acquiring a detection signal and dividing the detection signal into a QAM signal and an MSK signal; performing matched filtering and noise removal processing on the QAM signal to obtain a first received signal; performing matched filtering and noise removal processing on the MSK signal to obtain a second received signal; and completing signal synchronization based on the first and second received signals.

[0004] The beneficial effects of this invention are:

[0005] This invention achieves high-precision synchronization of blind signals without a training sequence by progressively estimating and compensating for time offset, frequency offset, and phase offset. It introduces frequency-modulated Z-transform (CZT) technology to limit the frequency offset within a certain range, significantly improving estimation accuracy while drastically reducing computational complexity. The time offset estimation process also avoids the computation of the entire DFT transform, further reducing the computational load. Combining the commonalities of QAM and MSK signals, this invention applies CZT and fast time offset calculation to both types of signals, achieving a balance between accuracy and computational efficiency. Attached Figure Description

[0006] Figure 1 This is a flowchart illustrating a CZT-based QAM and MSK signal synchronization method without prior knowledge, according to an embodiment of the present invention.

[0007] Figure 2 A schematic diagram showing the symbol error rates corresponding to different roll-off factors at the transmitting and receiving ends;

[0008] Figure 3 This is a schematic diagram showing the filtering results after applying different roll-off factors;

[0009] Figure 4 This is a schematic diagram of frequency-modulated z-transform (CZT).

[0010] Figure 5 This is a schematic diagram illustrating the implementation principle of frequency-modulated z-transform (CZT).

[0011] Figure 6 This is a schematic diagram of the QPSK time-biased estimation results;

[0012] Figure 7 This is a schematic diagram of the MSK time-biased estimation results;

[0013] Figure 8 This is a schematic diagram of the frequency offset estimation results for QPSK.

[0014] Figure 9 This is a schematic diagram of the frequency offset estimation results for MSK.

[0015] Figure 10 This is a schematic diagram of the phase bias estimation results for QPSK.

[0016] Figure 11 This is a schematic diagram of the MSK phase bias estimation results;

[0017] Figure 12 For constellation charts without time, frequency, and phase offsets;

[0018] Figure 13 This is a constellation diagram with only time-biased estimation and compensation performed;

[0019] Figure 14 A constellation diagram for time-frequency offset estimation and compensation;

[0020] Figure 15 The constellation diagram after time, frequency, and phase offsets. Detailed Implementation

[0021] 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.

[0022] A CZT-based method for synchronizing QAM and MSK signals without prior knowledge is proposed. The method involves acquiring a detection signal, dividing it into a QAM signal and an MSK signal; performing matched filtering and noise removal on the QAM signal to obtain a first received signal; performing matched filtering and noise removal on the MSK signal to obtain a second received signal; and synchronizing the signals based on the first and second received signals.

[0023] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments. The core processing flow of this method is as follows: Figure 1 As shown, it mainly includes four core steps: matched filtering, time offset estimation and compensation, frequency offset estimation and compensation, and phase offset estimation and compensation.

[0024] S1: Matched filtering: Preprocesses burst-received QAM signals (such as BPSK, QPSK, 16QAM, 8PSK, OQPSK) and MSK signals (extendable to GMSK) by filtering to suppress noise and optimize signal waveform;

[0025] The receiver suffers from low signal-to-noise ratio and high algorithm complexity. To address this issue, this invention proposes a robust configuration through simulation analysis: uniformly employing a root-raised cosine filter with a roll-off factor of 0.5 at the receiver. This configuration is based on... Figure 2 The simulation results were obtained. Figure 2 As can be seen, under the conditions of a signal-to-noise ratio (SNR) of 4dB, a sampling multiple of 6, taking the first and last 5 symbols of the root-raised cosine, and a filter length of 61, a roll-off factor in the range of 0.5 to 0.7 achieves relatively optimal symbol error rate performance. Since the greater the difference in roll-off factors when the roll-off factor is unknown, the greater the symbol error rate, a value of 0.5 is chosen at the receiver. When the SNR increases to above 6dB, the symbol error rate approaches zero, meeting the requirements of engineering applications. This configuration has good adaptability to different transmit roll-off factors and can minimize the impact of mismatch. The filtering effect is as follows... Figure 3 As shown.

[0026] S12: MSK Signal Processing: Due to the constant envelope characteristic of the MSK signal, strict matched filtering is not performed at the receiver. To suppress noise, only a raised cosine filter with a roll-off factor of 1 is added.

[0027] S2: Time Deviation Estimation and Compensation: In non-cooperative burst communication, due to the short signal duration and the possibility of frequency hopping, traditional phase-locked loops cannot be used for synchronization. Therefore, this invention designs efficient time deviation estimation algorithms based on the signal characteristics of QAM and MSK.

[0028] S21: Time-biased estimation of QAM signal:

[0029]

[0030] in, It was a time of misfortune. Let L be the Fourier transform of the square of the filtered received signal, and L be the oversampling rate.

[0031] S22: MSK signal time-bias estimation:

[0032]

[0033]

[0034] in, It was a time of misfortune. For symbol period, The conjugate of the received signal is squared, averaged, and its absolute value is calculated.

[0035] S3: Frequency offset estimation and compensation;

[0036] After time offset compensation is completed, frequency offset estimation is performed. This invention uses high-resolution frequency-modulated Z-transform (CZT) instead of traditional DFT, significantly reducing computational complexity while maintaining accuracy. The process and principle of CZT are as follows: Figure 4 , Figure 5 As shown.

[0037] S31: Perform n-order power operations on different types of QAM signals, and use frequency-modulated Z-transform for local spectrum analysis. Calculate the frequency offset by finding the spectral peaks, and use the frequency offset for compensation.

[0038] S32: For MSK signals, perform fourth-order operations on the I / Q data, apply frequency-modulated Z-transform at the beginning of the symbol to accurately estimate the frequency offset, and use the frequency offset value for compensation.

[0039] Furthermore, the algorithm steps for frequency-modulated Z-transform are as follows:

[0040] S311: Select the number of points L for the FFT, satisfying, and ;

[0041] S312: Constitutes the L-point sequence g(n);

[0042]

[0043] S313: Calculate the L-point FFT transform G(k) of g(n);

[0044] S314: Constitutes the L-point sequence h(n);

[0045]

[0046] S315: Calculate the L-point FFT transform H(k) of h(n);

[0047] S316: Calculate Y(k) = H(k)G(k);

[0048] S317: Calculate the inverse Fourier transform y(n) of Y(k);

[0049] S318: Calculation .

[0050] S4: Phase bias estimation and compensation;

[0051] After frequency offset compensation is completed, the remaining signal is mainly a fixed phase deviation.

[0052] S41: The phase offset of QAM class signals is calculated using the following formula:

[0053]

[0054] in, For phase difference, The received signal is a QAM class signal after frequency offset compensation;

[0055] The phase offset of S42:MSK class signals is calculated using the following formula:

[0056]

[0057] in, For phase difference, The symbol period.

[0058] Specific case analyses are as follows:

[0059] In this embodiment, the QPSK signal implementation is as follows: the roll-off factor at the transmitter is determined to be 0.7, the roll-off filter factor is determined to be 0.5, and the signal extension length is 8 symbols. The symbol rate Rb is 2.5 * 10^5 symbols per second, the sampling rate is 4 * 10^6 Hz, the time offset is 0.4 symbol periods (6 sampling points), the frequency offset is 100 Hz, and the phase offset is... .

[0060] Specifically, it includes:

[0061] S1: Matched Filtering

[0062]

[0063] A comparison of the waveforms of the received signal after matched filtering is shown below. Figure 3 .

[0064] S2: Time-biased estimation and compensation:

[0065]

[0066] The frequency domain data of both I and Q channels are calculated, and the time offset is calculated using a formula. Figure 6 This represents the result of the error ratio of QPSK time bias varying with the signal-to-noise ratio.

[0067]

[0068]

[0069] Time-shift z(kTs) to complete time offset compensation.

[0070]

[0071] S3: Frequency offset estimation and compensation: Perform a fourth power operation on z(kTs), take 4096 sampling points and perform frequency-modulated Z-transform (frequency range 0-4kHz, FFT length 4096, accuracy 1Hz). Both are 1. The phase of w is 0. equal .

[0072] The frequency offset can be obtained by determining the location of the maximum value. The QPSK frequency offset results for frequency-modulated Z-transform are shown below. Figure 8 As shown. Frequency offset compensation is performed based on the frequency offset value:

[0073]

[0074] S4: Phase offset estimation and compensation: Perform a fourth-power operation on the frequency offset compensated signal and sum the results, i.e.:

[0075]

[0076] By summing z(nTs) to eliminate the influence of noise, since

[0077] Estimate the phase offset using the following formula; the phase offset of QPSK is as follows: Figure 10 As shown.

[0078]

[0079] In this embodiment, the MSK signal implementation uses a raised cosine filter with a roll-off factor of 1 at the receiver; the symbol rate Rb is 2.5. Symbols per second, sampling rate Ns=4 Hz, time offset of 0.4 symbol period (6 sampling points), frequency offset of 100 Hz, phase offset .

[0080] S1: Pass the received signal through a raised cosine filter. The result after filtering is shown below. Figure 3 As shown.

[0081] S2: Estimate the time bias through conjugate multiplication, averaging, and DFT phase extraction, as shown below. Figure 7 The error ratio results of time offset under different signal-to-noise ratios are shown, and compensation is performed.

[0082] S3: Perform a fourth-power operation on the signal and sample at intervals, then apply CZT (parameters same as in the QPSK example) to obtain the following result: Figure 9 The spectrum diagram is shown. The frequency offset is determined based on the location of the maximum value. Frequency offset compensation is then performed based on the frequency offset value.

[0083]

[0084] S4: Perform a fourth-power operation on the frequency offset compensated signal and sum the results. Estimate the percentage of phase difference under different signal-to-noise ratios as follows: Figure 11 As shown.

[0085] Figures 12-15 The results are shown after time offset compensation, frequency offset compensation, and phase offset compensation. As can be seen from the figure, the constellation diagram is significantly optimized after compensation.

[0086] The above-described embodiments further illustrate the purpose, technical solution, and advantages of the present invention. It should be understood that the above-described embodiments are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made to the present invention within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A CZT-based QAM and MSK signal synchronization method without prior knowledge, characterized in that, include: The detection signal is acquired and divided into QAM signal and MSK signal; the QAM signal is subjected to matched filtering and noise removal processing to obtain the first received signal; the MSK signal is subjected to matched filtering and noise removal processing to obtain the second received signal; signal synchronization is completed based on the first received signal and the second received signal.

2. The CZT-based QAM and MSK signal synchronization method without prior knowledge as described in claim 1, characterized in that, Matched filtering and noise removal processing of the QAM signal includes: performing matched filtering on the QAM signal, estimating and compensating for the time offset of the filtered signal; estimating and compensating for the frequency offset of the QAM signal after time offset estimation and compensation; and estimating and compensating for the phase offset of the QAM signal after frequency offset compensation to obtain the first received signal.

3. The CZT-based QAM and MSK signal synchronization method without prior knowledge as described in claim 2, characterized in that, Matched filtering of QAM signals includes: using a root-raised cosine-shaping filter with a roll-off factor set between 0.5 and 0.7 to achieve a balance between suppressing inter-symbol interference and improving the signal-to-noise ratio.

4. The CZT-based QAM and MSK signal synchronization method without prior knowledge as described in claim 2, characterized in that, Time offset estimation and compensation for filtered signals include: ； in, It was a time of misfortune. Let be the Fourier transform of the square of the filtered received signal, L be the oversampling rate, N be the observation window size, n be the discrete-time index, z be the received signal sequence, T be the sampling period, s be the reference signal sequence, and k be the frequency index.

5. A CZT-based QAM and MSK signal synchronization method without prior knowledge as described in claim 2, characterized in that, Frequency offset estimation compensation for QAM signals after time offset estimation compensation includes: performing nth-order power operations for different types of QAM signals, performing local spectrum analysis using frequency-modulated Z-transform, calculating the frequency offset value by finding the spectral peak, and using the frequency offset value for compensation.

6. The CZT-based QAM and MSK signal synchronization method without prior knowledge as described in claim 5, characterized in that, Local spectrum analysis using frequency-modulated Z-transform includes: selecting the number of points L in the FFT, satisfying, and m is an integer; construct an L-point sequence g(n); calculate the L-point FFT transform G(k) of g(n); construct an L-point sequence h(n); calculate the L-point FFT transform H(k) of h(n); calculate Y(k) = H(k)G(k); calculate the inverse Fourier transform y(n) of Y(k); calculate .

7. A CZT-based QAM and MSK signal synchronization method without prior knowledge as described in claim 2, characterized in that, Phase offset estimation compensation for the frequency offset compensated QAM signal includes: ； in, For phase difference, This is the received signal after frequency offset compensation for a QAM class signal.

8. The CZT-based QAM and MSK signal synchronization method without prior knowledge as described in claim 1, characterized in that, Matched filtering and noise removal processing of the MSK signal includes: filtering the MSK signal; estimating and compensating for time offset in the filtered MSK signal; estimating and compensating for frequency offset in the MSK signal after time offset estimation; and estimating and compensating for phase offset in the MSK signal after frequency offset estimation to obtain the second received signal.

9. A CZT-based QAM and MSK signal synchronization method without prior knowledge as described in claim 8, characterized in that, Time-bias estimation and compensation for MSK signals include: ； ； in, It was a time of misfortune. For symbol period, The conjugate of the received signal is squared, averaged, and its absolute value is calculated.

10. A CZT-based QAM and MSK signal synchronization method without prior knowledge as described in claim 8, characterized in that, Phase offset estimation and compensation for the MSK signal after frequency offset estimation includes: ； in, For phase difference, The symbol period.

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