基于FBMP算法的水声信道估计
摘要
设计了一种基于贝叶斯压缩感知(bayesian compressing sensing,BCS)的水声信道(underwater acoustic channel,UWAC)估计方法,并具体采用快速贝叶斯匹配追踪算法(fast bayesian matching pursuit,FBMP)对水声正交频分复用(OFDM)通信系统下的信道脉冲响应进行估计。在水声信道中,信道的抽头的位置及系数通常分别服从伯努利和复高斯分布,利用这一先验知识,首先对抽头的位置进行检测,然后通过最小均方误差准则得到准确的信道估计。仿真分析了导频数量、信噪比对FBMP、正交匹配追踪(orthogonal matching pursuit,OMP)、变换域(discrete fourier transform,DFT)、最小二乘法(least square,LS)信道估计算法的性能的影响,仿真结果表明,在稀疏信道下,基于FBMP的信道估计方法明显优于OMP、DFT、LS信道估计方法。
引文
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[2]W.Li and J.C.Preisig,"Estimation of Rapidly Time-Varying Sparse Channels,"in?IEEE Journal of Oceanic Engineering,vol.32,no.4,pp.927-939,Oct.2007.
[3]D.L.Donoho,"Compressed sensing,"in?IEEE Transactions on Information Theory,vol.52,no.4,pp.1289-1306,April 2006.
[4]J.Meng,W.Yin,Y.Li,N.T.Nguyen and Z.Han,"Compressive Sensing Based High-Resolution Channel Estimation for OFDM System,"in?IEEE Journal of Selected Topics in Signal Processing,vol.6,no.1,pp.15-25,Feb.2012.
[5]H.Chen and C.Qi,"Underwater acoustic channel estimation via fast Bayesian matching pursuit,"?2017 9th International Conference on Wireless Communications and Signal Processing(WCSP),Nanjing,2017,pp.1-6.
[6]Poor H V.An Introduction to Signal Detection and Estimation[J].1994.