Demodulation of Chaos Phase Modulation Spread Spectrum Signals Using Machine Learning Methods and Its Evaluation for Underwater Acoustic Communication

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.

Analysis and Simulation of BER Performance of Chaotic Underwater Wireless Optical Communication Systems

“…In addition, attempts are being made to apply the features of nonlinear dynamics and chaotic systems in the design of networks for the joint operation of a large number of underwater vehicles and various underwater equipment [22]. Thus, in [23], the authors proposed a scheme for using the Chebyshev chaotic maps to create a secure network authentication scheme for subscribers.…”

Synchronizing Analog - Discrete Nonlinear Systems

“…The properties of nonlinear systems exhibiting complex dynamic behavior are studied with great interest due to their useful applications in secure communication, such as wide spectrum modulation (Li et al, 2018;Singh, 2021), chaotic encryption (Kocarev, 2002;Andreatos and Volos, 2014;Yasser et al, 2020;Yousif et al, 2020), nonlinear synchronization (Pecora and Carrroll, 2015;Eroglu et al, 2017;Sambas et al, 2015) and system parameters statistic and dynamic influence (Grigoras and Grigoras, 2015). In order to ensure a better security of the communication system, the chaotic circuit involved should have a high dynamic complexity, with larger Lyapunov exponents achievable by designing higher complexity emitter sub-systems.…”

A Systematic Review on Recent Trends, Challenges, Privacy and Security Issues of Underwater Internet of Things

“…sues Methods used to support trust management, security management, hardware protection, etc., in UIoT networks.19[42,107,113,[270][271][272][273][274][275][276][277][278][279][280][281][282][283][284][285] Figure13. Results based on the systematic analysis of UIoT applications.…”