Spatial–Temporal Multipath Clusters Joint Equalization for Deep-Sea Acoustic Communication in Large Delay Spread Channels

For deep-sea underwater acoustic (UWA) communication, large multipath time delay spread, that caused by spatial divergence effects of acoustic propagation along the deep-sea distance-depth dimension, exert extremely adverse influence on communication performance. Inspired by the fact that the large delay spread deep-sea channels tend to be clustered, and each cluster of which varies independently with respect to receiving element as well as time delay, in this article a multipath clusters (MCs) joint equalization approach is proposed to explore the spatial–temporal diversity of large delay spread deep-sea UWA channels. First we design a compact m-sequence synchronization sequence to extract MCs along different receiving element and time delay while achieving frame synchronization. Then, a sparsity-aware proportionate-type adaptive iterative algorithm is formulated under the recursive least squares (RLS) framework, by which, equalization output of each spatial–temporal-wise MC is aligned and combined to achieve joint equalization gain. Simulation results demonstrate that the proposed approach is capable of yielding superior performance in terms of output signal-to-noise ratio (SNR) and bit error rate (BER) compared to the traditional equalization approaches under large delay spread channels. Finally, in deep-sea trial error-free UWA communication with a maximum data rate of 6000 bps at a distance of 20 km is achieved by a two-element receiver, further demonstrating the effectiveness of the proposed algorithm.

Authors

Institutions

Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-11-04
DOI
https://doi.org/10.1109/jiot.2024.3489621
Citations
7
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
Field-Weighted Citation Impact
2.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatial–Temporal Multipath Clusters Joint Equalization for Deep-Sea Acoustic Communication in Large Delay Spread Channels

Weihua Jiang, Feng Tong, Yuehai Zhou, Yanfeng Zhao et al.
7 citations
IEEE Internet of Things Journal
Underwater Vehicles and Communication Systems
2.35
article

Spatial–Temporal Multipath Clusters Joint Equalization for Deep-Sea Acoustic Communication in Large Delay Spread Channels

Weihua Jiang, Feng Tong, Yuehai Zhou, Yanfeng Zhao, Qiaoning Zheng
article en
7 citations

Abstract

For deep-sea underwater acoustic (UWA) communication, large multipath time delay spread, that caused by spatial divergence effects of acoustic propagation along the deep-sea distance-depth dimension, exert extremely adverse influence on communication performance. Inspired by the fact that the large delay spread deep-sea channels tend to be clustered, and each cluster of which varies independently with respect to receiving element as well as time delay, in this article a multipath clusters (MCs) joint equalization approach is proposed to explore the spatial–temporal diversity of large delay spread deep-sea UWA channels. First we design a compact m-sequence synchronization sequence to extract MCs along different receiving element and time delay while achieving frame synchronization. Then, a sparsity-aware proportionate-type adaptive iterative algorithm is formulated under the recursive least squares (RLS) framework, by which, equalization output of each spatial–temporal-wise MC is aligned and combined to achieve joint equalization gain. Simulation results demonstrate that the proposed approach is capable of yielding superior performance in terms of output signal-to-noise ratio (SNR) and bit error rate (BER) compared to the traditional equalization approaches under large delay spread channels. Finally, in deep-sea trial error-free UWA communication with a maximum data rate of 6000 bps at a distance of 20 km is achieved by a two-element receiver, further demonstrating the effectiveness of the proposed algorithm.

IEEE Internet of Things JournalVol. 12(5)
Xiamen University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 12%
Underwater Vehicles and Communication Systems
2.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.