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基于汉明距离优化的水下声学OTFS-IM系统

Hamming Distance Optimized Underwater Acoustic OTFS-IM Systems.

作者信息

Guo Xiaopeng, Wang Biao, Zhu Yunan, Fang Zide, Han Zhaoyue

机构信息

Ocean College, Jiangsu University of Science and Technology, Zhenjiang 212100, China.

出版信息

Entropy (Basel). 2023 Jun 24;25(7):972. doi: 10.3390/e25070972.

DOI:10.3390/e25070972
PMID:37509919
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10378051/
Abstract

The orthogonal time frequency space (OTFS) modulation technique can provide reliable communication in time-varying channels. Due to the dispersive characteristics of underwater acoustic channels, this paper proposes an OTFS-IM underwater acoustic communication system based on Hamming distance optimization to reduce the impact of dispersion in underwater acoustic communication. Firstly, the OTFS-IM underwater acoustic communication system is introduced, which introduces index modulation into the Delay-Doppler (DD) domain to make the OTFS system have stronger anti-Delay-Doppler capability. In contrast, since there is index sequence redundancy in a specific index combination, a Hamming distance optimization model is used to eliminate the redundant combination in the specific index combination sequence and further improve the bit error rate performance of the system. In addition, the Hamming distance optimized OTFS-IM underwater acoustic communication system is verified by simulation analysis. The results show that the proposed Hamming distance optimized OTFS-IM can achieve more reliable bit error rate performance.

摘要

正交时频空间（OTFS）调制技术能够在时变信道中提供可靠通信。由于水声信道的色散特性，本文提出一种基于汉明距离优化的OTFS-IM水声通信系统，以降低色散在水声通信中的影响。首先，介绍了OTFS-IM水声通信系统，该系统将索引调制引入延迟-多普勒（DD）域，使OTFS系统具有更强的抗延迟-多普勒能力。相比之下，由于特定索引组合中存在索引序列冗余，采用汉明距离优化模型消除特定索引组合序列中的冗余组合，进一步提高系统的误码率性能。此外，通过仿真分析验证了汉明距离优化的OTFS-IM水声通信系统。结果表明，所提出的汉明距离优化的OTFS-IM能够实现更可靠的误码率性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/f8285b6c30d9/entropy-25-00972-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/7a4826a36c25/entropy-25-00972-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/4424a72955e9/entropy-25-00972-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/5b495ffa482b/entropy-25-00972-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/1a4007416def/entropy-25-00972-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/e5e2a77a874d/entropy-25-00972-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/4016c62a0a7b/entropy-25-00972-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/771be6a0f7a0/entropy-25-00972-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/f8285b6c30d9/entropy-25-00972-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/7a4826a36c25/entropy-25-00972-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/4424a72955e9/entropy-25-00972-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/5b495ffa482b/entropy-25-00972-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/1a4007416def/entropy-25-00972-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/e5e2a77a874d/entropy-25-00972-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/4016c62a0a7b/entropy-25-00972-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/771be6a0f7a0/entropy-25-00972-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f315/10378051/f8285b6c30d9/entropy-25-00972-g008.jpg

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