基于压缩传感的MIMO-OFDM水声通信信道估计算法

充分利用水声信道的稀疏特征，提出一种基于压缩传感理论的多输入多输出正交频分复用(multiple-input multiple-output orthogonal frequency division multiplexing, MIMO-OFDM)水声通信系统信道估计算法。在MIMO-OFDM水声通信系统模型的基础上，考虑Doppler频移的影响设计符合压缩传感理论框架的过完备字典，利用一系列非正交基在过完备字典下描述待重建信号。通过对比分析基追踪降噪、丹茨格选择器以及正交匹配跟踪3种算法的信道估计性能，进一步证明了算法的有效性。仿真实验结果表明，基于压缩传感的稀疏信道估计算法具有优于传统最小二乘算法的信道估计精度，并且在最小二乘矩阵求逆奇异的情况下仍能准确地估计出信道参数；在计及Doppler频移的影响时，直接压缩传感估计优于补偿后的压缩传感估计方法。

Channel estimation for MIMO-OFDM underwater acoustic communication based on compressed sensing

An estimation algorithm of multiple-input multiple-output orthogonal frequency division multi-plexing(MIMO-OFDM) underwater acoustic channels,based on compressed sensing(CS) theory,is proposed,which makes full use of sparse feature of the underwater acoustic channels.A complete dictionary is designed to meet the framework of CS theory under the effect of Doppler frequency shift,which is based on MIMO-OFDM underwater acoustic communication system model,and then a series of non-orthogonal basis in a complete dictionary is used to describe the signal under reconstruction.The effectiveness of the proposed algorithm is demonstrated by comparing the channel estimation performances of three algorithms: basis pursuit de-noising,Dantzig selector and orthogonal matching pursuit.The experimental results show that the sparse channel estimation algorithm based on CS is superior to the traditional least square algorithm of channel estimation in terms of accuracy,and can still estimate channel parameters accurately even in the case of least square matrix inverse singular.In relation to the effect of Doppler frequency shift,the direct CS estimation method overcomes the estimation method with compensated CS.