Abstract

A deep learning-based cyclic shift keying spread spectrum (CSK-SS) underwater acoustic (UWA) communication system is proposed for improving the performance of the conventional system in low signal-to-noise ratio and multipath effects. The proposed deep learning-based system involves the long- and short-term memory (LSTM) architecture-based neural network model as the receiving module of the system. The neural network is fed with the communication signals passing through known channel impulse responses in the offline stage, and then directly used to demodulate the received signal in the online stage to reduce the influence of the above factors. Numerical simulation and actual data results suggest that the deep learning-based CSK-SS UWA communication system is more reliable communication than a conventional system. In particular, the collected experimental data show that after preprocessing, when the communication rate is less than 180 bps, a bit error rate of less than 10−3 can be obtained at a signal-to-noise ratio of −8 dB.

Highlights

  • IntroductionDirect-sequence spread spectrum (DSSS) communication technology has low spectrum density and strong resistance to multipath fading and the Doppler effect

  • The neural network model is used as the receiver structure of the DLbased cyclic shift keying spread spectrum (CSK-SS) underwater acoustic (UWA) communication system to demodulate the signal

  • The neural network model is trained based on the training samples with distortion caused by the influence of UWA channels and noise in the offline stage

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Summary

Introduction

Direct-sequence spread spectrum (DSSS) communication technology has low spectrum density and strong resistance to multipath fading and the Doppler effect. It is widely used in UWA communication scenarios [2,3]. Compared with the conventional DSSS system, the cyclic shift keying spread spectrum (CSK-SS) modulation can provide a higher data rate. He et al proposed a passive time reversal with CSK-SS using hyperbolic frequency-modulated (HFM) waveform for a reliable point-to-point UWA communication system [4]. Jing et al proposed a novel interleave-division multiple access system based on CSK-SS modulation for multiuser

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