EI / SCOPUS / CSCD 收录

中文核心期刊

深海远程单载波水声通信交叉域信道估计与均衡

Cross-domain channel estimation and equalization for deep-sea long-range single-carrier underwater acoustic communication

  • 摘要: 深海远程水声信道通常呈现出簇稀疏结构, 多种算法利用此类结构信息提高信道估计精度, 但均需信道簇结构先验信息。为此, 提出一种自适应簇稀疏贝叶斯学习信道估计算法, 建立分层贝叶斯模型, 同时利用稀疏性和簇结构, 通过变分贝叶斯推断推导自适应更新公式。所提算法通过联合利用稀疏性与簇结构, 在无需簇大小、簇数量及簇位置等信道先验信息的情况下, 实现信道估计精度的提升。为了对抗水声信道的时变性, 结合自适应簇稀疏贝叶斯学习信道估计算法, 进一步提出基于交叉域处理的Turbo均衡器。该Turbo均衡器由工作在时延–多普勒域的均衡器和工作在时域的信道估计器与软解码器组成。时变信道经过时延–多普勒域变换转换为准静态信道, 以减轻信道时变对通信系统可靠性的影响。所提Turbo均衡器通过酉变换实现时延–多普勒域和时域之间的跨域软信息交互, 降低了错误传播概率, 提高了迭代均衡增益。仿真结果证明了所提方法应用于深海远程水声通信的适用性和鲁棒性。深海远程试验结果表明, 所提方法在324.9 km和595.1 km的通信距离中实现了无差错传输, 可有效应用于深海远程水声通信。

     

    Abstract: Deep-sea long-range underwater acoustic channels typically exhibit cluster-sparse structures. Although various algorithms exploit such structural information to enhance channel estimation accuracy, these algorithms generally require prior knowledge of cluster parameters. This paper proposes an adaptive cluster-sparse Bayesian learning (ACSBL) channel estimation algorithm that constructs a hierarchical Bayesian model to jointly leverage sparsity and cluster structures, with variational Bayesian inference derived for adaptive parameter updating. The proposed algorithm enhances channel estimation accuracy by jointly exploiting sparsity and cluster structure, without requiring prior channel information such as cluster size, number of clusters, or cluster locations. To improve distortions caused by time-varying underwater acoustic channel, a turbo equalizer based on cross-domain processing is proposed, incorporating the adaptive cluster-sparse Bayesian learning channel estimation algorithm. The turbo equalizer consists of an equalizer operating in the delay-Doppler domain, a channel estimator, and a soft decoder operating in the time domain. The time-frequency domain channel is transformed into a quasi-static channel through delay-Doppler domain transformation, thereby mitigating the impact of channel variations on communication reliability. The proposed turbo equalizer enables cross-domain soft information exchange between the delay-Doppler domain and time domain through unitary transformation, effectively reducing error propagation probability and enhancing iterative equalization gain. Simulation results demonstrate the feasibility and robustness of the proposed method in deep-sea long-range underwater acoustic communications. Deep-sea long-range experimental results indicate that the proposed method achieves error-free transmission over communication distances of 324.9 km and 595.1 km, demonstrating its effectiveness in deep-sea long-range underwater acoustic communications.

     

/

返回文章
返回