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Joint Temporal-sparse Recovery Approach for Estimation of Underwater Acoustic MIMO Channels

机译:接合时间稀疏恢复方法,用于估计水下声学MIMO通道

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摘要

MIMO communication offers a potential solution for high speed underwater acoustic communication. However, the simultaneous presence of multipath and co-channel interference (Co-channel interference, CoI) poses serious difficulty for estimating acoustic MIMO channels. For MIMO channels with serous CoI, the performance gain achieved by exploiting the sparsity of a single acoustic channel is insufficient to meet the need of MIMO acoustic communication. In this paper, a temporal joint sparse recovery approach is proposed to exploit the sparse correlation between adjacent blocks and improve the performance of channel estimation. A joint sparse model under the framework of distributed compressed sensing (DCS) is adopted to derive a joint sparse recovery algorithm for estimating MIMO channels. Finally, underwater MIMO communication experimental results obtained in a shallow water channel are provided to demonstrate the effectiveness of the proposed method compared to the classic estimation methods.
机译:MIMO通信为高速水下通信提供了一种潜在的解决方案。然而,多径和共信道干扰的同时存在(共信道干扰,COI)对估计声学MIMO通道来说是严重的困难。对于具有静脉COI的MIMO通道,通过利用单个声道的稀疏而实现的性能增益不足以满足MIMO声学通信的需要。在本文中,提出了一种时间关节稀疏恢复方法来利用相邻块之间的稀疏相关性并提高信道估计的性能。采用分布式压缩检测(DCS)框架下的联合稀疏模型​​来导出用于估计MIMO通道的关节稀疏恢复算法。最后,提供了在浅水通道中获得的水下MIMO通信实验结果,以证明所提出的方法与经典估计方法相比的有效性。

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