Abstract
The chaos phase modulation sequences consist of complex sequences with a constant envelope, which has recently been used for direct-sequence spread spectrum underwater acoustic communication. It is considered an ideal spreading code for its benefits in terms of large code resource quantity, nice correlation characteristics and high security. However, demodulating this underwater communication signal is a challenging job due to complex underwater environments. This paper addresses this problem as a target classification task and conceives a machine learning-based demodulation scheme. The proposed solution is implemented and optimized on a multi-core center processing unit (CPU) platform, then evaluated with replay simulation datasets. In the experiments, time variation, multi-path effect, propagation loss and random noise were considered as distortions. According to the results, compared to the reference algorithms, our method has greater reliability with better temporal efficiency performance.
Highlights
The underwater acoustic communication has always been a crucial research topic [1,2,3,4,5,6]
The results demonstrate that the proposed method achieves the best accuracy performance with high temporal efficiency within the experimental protocol of this paper
This paper presents a novel machine learning available demodulation scheme for underwater communication applications based on the chaos phase modulation spread spectrum techniques
Summary
The underwater acoustic communication has always been a crucial research topic [1,2,3,4,5,6]. The direct-sequence spread spectrum (DSSS) communication is one of the most effective potential solutions to the problem of confidential underwater acoustic communication. It spreads the frequency spectrum of the carrier wave with a spreading code sequence, so the modulated signal is hard to be detected by a third party within the underwater noise, possessing greater concealment [7,8]. Sequences, such as m-, Gold and Kasami sequences [9,10,11] These PN sequences can only provide finite keyings and limited code resources, (e.g., binary phase-shift modulation keying, quadrature amplitude modulation, frequency shift keying), so the transmitted DSSS signals usually possess binary-value and periodic characters.
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