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Exploiting dynamic sparsity for time reversal underwater acoustic communication under rapidly time varying channels
Applied Acoustics ( IF 3.4 ) Pub Date : 2021-01-01 , DOI: 10.1016/j.apacoust.2020.107648
Weihua Jiang , Feng Tong

Abstract Underwater acoustic (UWA) communication encounters significant difficulties posed by the simultaneous presence of multipath and time variations. It has been recognized that, under the assumption that channel keeps static within the processing windows, time reversal (TR) processing approach is capable of mitigating multipath via the spatial–temporal focusing. However, for a rapidly time-varying UWA channel, the replica channel impulse response in time reversal processor need to be updated frequently to avoid performance degradation, which leads to huge computational complexity and significant overhead. Consider that after time reversal processing the resulting time-reversed channel response exhibits much more slow time variations compared to the original channel impulse response, previously Kalman filtering has been adopted to track the time-reversed channel response to alleviate the requirement of frequent channel update. Under the framework of dynamic compressed sensing (DCS), in this paper the time-reversed channel is formulated as a sparse set consisting of constant and slowly time-varying supports to derive the Kalman Filtered Compressed Sensing (KF-CS) channel estimation algorithm for time reversal communication. Based on the receiver structure by coupling the KF-CS estimator driven time reversal processor with a single channel decision-feedback equalizer (TR-DCS-DFE), shallow water experimental results with field data are provided to demonstrate the effectiveness of the proposed algorithm, compared to the classic time reversal communication scheme.

中文翻译:

在快速时变信道下利用动态稀疏性进行时间反转水声通信

摘要 水下声学 (UWA) 通信面临着多径和时间变化同时存在所带来的重大困难。已经认识到,在信道在处理窗口内保持静态的假设下,时间反转 (TR) 处理方法能够通过时空聚焦来减轻多径。然而,对于快速时变的 UWA 信道,时间反转处理器中的副本信道脉冲响应需要经常更新以避免性能下降,从而导致巨大的计算复杂度和显着的开销。考虑到经过时间反转处理后,与原始通道脉冲响应相比,得到的时间反转通道响应表现出更慢的时间变化,以前采用卡尔曼滤波来跟踪时间反转的信道响应,以减轻频繁信道更新的要求。在动态压缩感知 (DCS) 的框架下,在本文中,时间反向信道被公式化为一个由常数和缓慢时变支持组成的稀疏集,以推导出卡尔曼滤波压缩感知 (KF-CS) 信道估计算法:时间倒转通信。基于通过将 KF-CS 估计器驱动的时间反转处理器与单通道决策反馈均衡器 (TR-DCS-DFE) 耦合的接收器结构,提供带有现场数据的浅水实验结果,以证明所提出算法的有效性,与经典的时间反转通信方案相比。
更新日期:2021-01-01
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