Variational Bayesian Sparse Decision-Feedback Equalization Based on RLS Algorithm in Underwater Acoustic Communications

IF 4.5 3区计算机科学 Q2 TELECOMMUNICATIONS

IEEE Communications Letters Pub Date : 2026-01-01 Epub Date: 2025-12-30 DOI:10.1109/LCOMM.2025.3649767

Yanbing Fu;Ruijie Shen;Xingbin Tu;Jiaxun Lu;Huajun Bai;Yan Wei;Fengzhong Qu

引用次数: 0

Abstract

This letter proposes a variational Bayesian sparse decision-feedback equalizer (VB-SDFE) based on the recursive least squares (RLS) algorithm for underwater acoustic communications. The method employs Bayesian inference to optimize the sparse pre-equalizer coefficients in overlapping subblocks and addresses the sensitivity of RLS-based decision-feedback equalizer (RLS-DFE) to channel variations. Key features include subblock processing with a forgetting factor, variational updates for sparsity control, and Doppler-resistant phase compensation. Simulations show that the proposed algorithm achieves superior and robust performance under different channel conditions. Sea trials demonstrate a 7.8-dB gain in SNR and error-free performance at 21.5 km.

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基于RLS算法的变分贝叶斯稀疏决策反馈均衡在水声通信中的应用

本文提出了一种基于递归最小二乘（RLS）算法的变分贝叶斯稀疏决策反馈均衡器（VB-SDFE）用于水声通信。该方法利用贝叶斯推理优化重叠子块中的稀疏预均衡器系数，解决了基于rls的决策反馈均衡器（RLS-DFE）对信道变化的敏感性问题。主要功能包括具有遗忘因子的子块处理，稀疏性控制的变分更新和抗多普勒相位补偿。仿真结果表明，该算法在不同信道条件下均具有较好的鲁棒性。海试表明，信噪比增益为7.8 db，在21.5公里处无误差。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Communications Letters 工程技术-电信学

CiteScore

8.10

自引率

7.30%

发文量

590

审稿时长

2.8 months

期刊介绍： The IEEE Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of communication over different media and channels including wire, underground, waveguide, optical fiber, and storage channels. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of communication systems.