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Entropy 2013, 15(9), 3877-3891; doi:10.3390/e15093877

Blind Demodulation of Chaotic Direct Sequence Spread Spectrum Signals Based on Particle Filters

College of Mechatronics Engineering and Automation, National University of Defense Technology, Deya Road, Changsha 410073, China
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Received: 9 July 2013 / Revised: 22 August 2013 / Accepted: 10 September 2013 / Published: 13 September 2013
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Abstract

Applying the particle filter (PF) technique, this paper proposes a PF-based algorithm to blindly demodulate the chaotic direct sequence spread spectrum (CDS-SS) signals under the colored or non-Gaussian noises condition. To implement this algorithm, the PFs are modified by (i) the colored or non-Gaussian noises are formulated by autoregressive moving average (ARMA) models, and then the parameters that model the noises are included in the state vector; (ii) the range-differentiating factor is imported into the intruder’s chaotic system equation. Since the range-differentiating factor is able to make the inevitable chaos fitting error advantageous based on the chaos fitting method, thus the CDS-SS signals can be demodulated according to the range of the estimated message. Simulations show that the proposed PF-based algorithm can obtain a good bit-error rate performance when extracting the original binary message from the CDS-SS signals without any knowledge of the transmitter’s chaotic map, or initial value, even when colored or non-Gaussian noises exist.
Keywords: blind demodulation; chaotic direct sequence spread spectrum; particle filter; colored non-Gaussian noise blind demodulation; chaotic direct sequence spread spectrum; particle filter; colored non-Gaussian noise
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Li, T.; Zhao, D.; Huang, Z.; Liu, C.; Su, S.; Zhang, Y. Blind Demodulation of Chaotic Direct Sequence Spread Spectrum Signals Based on Particle Filters. Entropy 2013, 15, 3877-3891.

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