水声单载波分块传输中基于压缩感知的稀疏信道估计方法

为利用水声信道的稀疏特性,提高循环前缀单载波分块传输系统的信道估计精度和误比特率性能,提出一种新的基于压缩感知的稀疏信道估计方法.新方法利用任意具有单位能量的导频构造满足约束等距条件的频域测量矩阵,通过Dantzig selector算法重构稀疏水声信道冲激响应.基于实测湖试信道模型的仿真结果表明,在相同训练序列长度条件下,利用频域最小均方误差检测方法,新的压缩感知信道估计方法较传统最小二乘信道估计方法有近5 dB的性能增益.

Compressed Sensing Based Sparse Channel Estimation Method for Underwater Single Carrier Block Transmission

In order to exploit the sparsity inherent in underwater acoustic channel, and improve the channel estimation accuracy as well as the bit error rate of a cyclic prefixed single carrier block transmission system, a new sparse channel estimation scheme based on compressed sensing is proposed. The new method uses a pilot sequence with unit energy to construct frequency domain measurement matrix that satisfies restricted isometry property, and recovers sparse channel impulse response of the underwater acoustic channel from limited number of observation measurements by using Dantzig selector. Computer simulations based on real lake channel profile shows that the new method can significantly improve the channel estimation accuracy, the proposed compressed sensing based channel estimation method can outperform the traditional frequency domain least square method by about 5 dB when using frequency domain minimum mean square error detection method at the same training sequence length.