scholarly journals Study of the Performance of DSSS UAC System Depending on the System Bandwidth and the Spreading Sequence

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2484
Author(s):  
Iwona Kochanska ◽  
Roman Salamon ◽  
Jan H. Schmidt ◽  
Aleksander M. Schmidt
Keyword(s):  
Spread Spectrum ◽  
Transmission Rate ◽  
Multipath Propagation ◽  
Water Channel ◽  
Experimental Tests ◽  
Direct Sequence Spread Spectrum ◽  
Underwater Acoustic Communication ◽  
Underwater Acoustic ◽  
Spreading Sequence ◽  
Code Division Multiple

A signal transmitted in an Underwater Acoustic Communication (UAC) system operating in a shallow-water channel suffers from strong time dispersion due to multipath propagation. This causes the Inter-Symbol Interference (ISI) observed in the received signal, which significantly limits the communication system’s reliability and transmission rate. In such propagation conditions, the Direct-Sequence Spread Spectrum (DSSS) method is one of the solutions that make reliable data transmission possible. In systems with one-to-one communication, it ensures communication with a satisfactory Bit Error Rate (BER). Additionally, it makes it possible to implement the Code-Division Multiple Access (CDMA) protocol in underwater acoustic networks. This paper presents the results of simulation and experimental communication tests on a DSSS-based UAC system using three types of spreading sequence, namely m-sequences, Kasami codes and Gold codes, and occupying different bandwidths from 1 kHz to 8 kHz around a carrier frequency equal to 30 kHz. The UAC channel was simulated by impulse responses calculated by the virtual sources method and the UAC chanel models available in the Watermark simulator. The experimental tests were conducted in a model pool. Based on the obtained results, a transmission rate was estimated, which is possible to achieve in strong multipath propagation conditions, assuming reliability expressed as BER less than 0.001.

Experimental Multipath Delay Profile of Underwater Acoustic Communication Channel in Shallow Water

2016 ◽  
Vol 2 (2) ◽  
pp. 351 ◽  
Author(s):  
Yasin Yousif Al_Aboosi ◽  
Ahmad Zuri Sha'ameri
Keyword(s):  
Shallow Water ◽  
Acoustic Communication ◽  
Multipath Propagation ◽  
Water Channel ◽  
Underwater Acoustic Communication ◽  
Communication Performance ◽  
Underwater Acoustic ◽  
Research Fields ◽  
Different Depths ◽  
Major Factors

<p>The shallow water channel is an environment that is of particular interest to many research fields. An underwater acoustic channel is characterized as a multipath channel. Time-varying multipath propagation is one of the major factors that limit the acoustic communication performance in shallow water. This study conducts two underwater acoustic experiments in Tanjung Balau, Johor, Malaysia. A transducer and a hydrophone are submerged at different depths and separated by different distances. Linear frequency modulated (LFM) pulses are chosen as the main transmit signal for the experiments. The cross-correlation between the transmitted and received signals represents the impulse response of the channel (multipath profile). The results show that the amplitude of the successive paths will not rapidly decline, and vice versa, when the distance between the sender and the receiver increases. Moreover, the time difference between the different paths will be small in the case of distance increase. In other words, the successive paths will converge in time.</p>

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

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4217
Author(s):  
Chao Li ◽  
Franck Marzani ◽  
Fan Yang
Keyword(s):  
Machine Learning ◽  
Acoustic Communication ◽  
Spread Spectrum ◽  
Phase Modulation ◽  
Direct Sequence Spread Spectrum ◽  
Propagation Loss ◽  
Underwater Acoustic Communication ◽  
Processing Unit ◽  
Underwater Acoustic ◽  
Communication Signal

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.

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