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中文核心期刊

秦晔, 鄢社锋, 徐立军, 侯朝焕. 用于单载波频域均衡水声通信的可分近似稀疏信道估计[J]. 声学学报, 2018, 43(4): 526-537. DOI: 10.15949/j.cnki.0371-0025.2018.04.012
引用本文: 秦晔, 鄢社锋, 徐立军, 侯朝焕. 用于单载波频域均衡水声通信的可分近似稀疏信道估计[J]. 声学学报, 2018, 43(4): 526-537. DOI: 10.15949/j.cnki.0371-0025.2018.04.012
QIN Ye, YAN Shefeng, XU Lijun, HOU Chaohuan. Sparse channel estimation using separable approximation for underwater acoustic sc-fde communications[J]. ACTA ACUSTICA, 2018, 43(4): 526-537. DOI: 10.15949/j.cnki.0371-0025.2018.04.012
Citation: QIN Ye, YAN Shefeng, XU Lijun, HOU Chaohuan. Sparse channel estimation using separable approximation for underwater acoustic sc-fde communications[J]. ACTA ACUSTICA, 2018, 43(4): 526-537. DOI: 10.15949/j.cnki.0371-0025.2018.04.012

用于单载波频域均衡水声通信的可分近似稀疏信道估计

Sparse channel estimation using separable approximation for underwater acoustic sc-fde communications

  • 摘要: 针对单载波频域均衡水声通信中信道估计易受噪声干扰的问题,提出了一种低复杂度的信道估计方法。考虑水声信道的时域稀疏特性,导出频域输入、输出信号与信道冲激响应的关系式,并引入稀疏正则项,构造稀疏信道估计的目标函数。然后利用可分近似对目标函数进行迭代优化,再经过稀疏化与去偏处理,得到信道传递函数的最终估计。最后,利用数值仿真和海试数据对所提出方法的性能和运算效率进行评估。较之传统信道估计方法,所提出的方法在估计精度和计算复杂度方面具有一定的优势。

     

    Abstract: In underwater acoustic Single-Carrier Frequency Domain Equalization communications, the performance of channel estimation is often interfered by ambient noise. To solve the problem, a channel estimation method with low complexity is proposed. Firstly, Considering the sparseness of underwater acoustic channels in time domain, the relationship among the frequency-domain input and output signals and the channel impulse response is derived, and by introducing a sparsity-inducing regularizer, the objective function for sparse channel estimation is constructed. Then optimize the objective function iteratively with separable approximation, and by sparsification and debiasing, the final esimate of the channel transfer flmction is obtained. Finally, numerical simulation and sea-trial data are used to evaluate the performance and the computation efficiency of the proposed method, demonstrating that the proposed method outperforms the classical channel estimation methods in the aspects of estimation accuracy and computation complexity.

     

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