Walsh码软扩频信号降噪算法

doi:10.3969/j.issn.1001-506X.2020.04.06

Abstract

Abstract:

In order to solve the problem of soft spread spectrum signals with low signal-to-noise ratio (SNR) so that it is difficult to realize blind dispreading and blind separation, an improved soft spread spectrum noise reduction algorithm is presented. This algorithm uses the empirical mode decomposition (EMD) algorithm to realize the soft spread spectrum signal denoising, judges the location of the dividing point according to the difference between the soft spread spectrum signal and the noise auto-correlation function and applies wavelet threshold filtering to the intrinsic mode function (IMF) component before the dividing point. Finally, the soft spread spectrum signals are constructed by processed low order IMF components and IMF components after the dividing point. The algorithm makes use of lower IMF components and judges the location of the dividing point according to the auto-correlation characteristics of the IMF component to reduce the signal loss caused by noise reduction. Simulation results show that within a certain SNR range, the denoising algorithm achieves demodulation with low bit error rate (BER) and less signal loss.

Key words: Walsh code, soft spread spectrum signal, noise reduction, empirical mode decomposition algorithm

CLC Number:

TN911.7

Danna ZHAGN, Feng QIAN, Hui FENG, Niancheng WEN. Noise reduction algorithm of Walsh code soft spread spectrum signal[J]. Systems Engineering and Electronics, 2020, 42(4): 773-780.

Figures/Tables 6

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References 20

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Noise reduction algorithm of Walsh code soft spread spectrum signal

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