This paper proposes a MPSK demodulation algorithm based on pattern recognition theory, which processes MPSK order recognition, error estimate and signals demodulation together. The algorithm does not require prior inf...
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ISBN:
(纸本)9781424423101
This paper proposes a MPSK demodulation algorithm based on pattern recognition theory, which processes MPSK order recognition, error estimate and signals demodulation together. The algorithm does not require prior information about MPSK order and the initial phase, but recognizes these parameters from received signals by pattern clustering method, then demodulates signals by pattern classification. Computer simulation results in terms of Bit-Error-Rate (BER) on additive white Gaussian noise (AWGN) channel show that the algorithm is able to effectively recognize MPSK order and optimal cluster centers. For QPSK, the correct recognition rate achieves 100% when Signal Noise Ratio (SNR) is 2dB and 1280 symbols are used for clustering. Moreover, employing this algorithm, signal phase jitter is automatic cancelled, and BER performance overmatches original coherent demodulation that decision center points are fixed.
A novel approach based on the theory of wavelet analysis is proposed for automatic modulation classification of MPSK and MFSK by Gaussian wavelet transform. The approach recognizes the modulation signal through extrac...
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A novel approach based on the theory of wavelet analysis is proposed for automatic modulation classification of MPSK and MFSK by Gaussian wavelet transform. The approach recognizes the modulation signal through extracting the value of amplitude and the transient information by Gaussian wavelet transform. It does not need the prior knowledge, overcomes the problem of undetected information of Haar wavelet transform method and increase the applicability of the method of automaticmodulation recognition based on wavelet transform. Moreover, we compare the new method and the Haar wavelet transform method from the point of view of theoretical analysis and computer simulation, furthermore, we justify the efficiency superiority of the new method.
A modulation recogniser that automatically reports modulation types of constant-envelope modulated signals is developed using zero-crossing techniques. The zero-crossing sampler, as a signal conditioner, has the advan...
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A modulation recogniser that automatically reports modulation types of constant-envelope modulated signals is developed using zero-crossing techniques. The zero-crossing sampler, as a signal conditioner, has the advantage of providing accurate phase transition information over a wide dynamic frequency range. Signal parameters such as zero-crossing variance, carrier-to-noise ratio (CNR) and carrier frequency are estimated. Phase difference and zero-crossing interval histograms play the role of features for modulation recognition. The classifier performance is given in the form of a confusion matrix. The simulation results obtained demonstrate that a reasonable average probability of correct classification is achievable for CNR ≥ 15 dB.
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