OFDM水声通信中基于压缩传感的稀疏信道估计

摘要

Conventional training-based methods , comprising linear least square ( LS) channel estimators are known to be optimal under the assumption of rich multipath channels. However, underwater acoustic (UWA) channels are naturally sparse, so the LS channel estimators can just get poor performance in UWA channels. A sparse UWA channel estimation algorithm based on compressive sensing (CS) for orthogonal frequency division multiplexing (OFDM) is proposed. Firstly, the training waveforms that consist of the elements of a complete orthogonal short-time Fourier (STF) basis are used as the pilots of OFDM to "sense" the UWA channel, and then, a CS recovery algorithm is adopted to estimate the channel. Simulation results based on the real UWA channel demonstrate that the performance of the proposed schemes is better than the conventional LS estimators for it can lead to significant reductions in the training energy, loss in spectral efficiency and improvement in the robustness to noise. This sparse channel estimator is matched to the UWA channel very well and especially adapt for the moving platform OFDM UWA communication system.%针对正交频分复用(orthogonal frequency division multiplexing,OFDM)水声通信中常规的最小均方(least square,LS)信道估计方法需要大量训练导额且得不到较高估计精度的问题,提出了一种基于压缩传感原理的OFDM稀疏水声信道估计方法.该方法首先以正交短时傅里叶基构成的训练波形为OFDM的导频来"感知"信道,然后利用压缩传感技术的稀疏重构算法来对信道进行重构.基于实测水声信道的仿真结果表明,在相同估计精度前提下,基于压缩传感的信道估计方法较常规的LS算法所需训练导频数得到大幅度减小,传输效率得以提高,且对噪声的鲁棒性增强,较好地适应了双扩展稀疏水声信道,尤其适用于动平台OFDM水声通信系统.