OFDM水声通信系统的LS-OMP信道估计

对于正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)水声通信系统,最小二乘(Least Squares,LS)信道估计方法受噪声影响较大,并且使用的导频数量较多,影响通信效率。而基于压缩感知理论的正交匹配追踪(Orthogonal Matching Pursuit,OMP)信道估计方法可以充分利用水声信道的稀疏特性,同时能够有效地抑制系统噪声,但控制迭代运算次数的相关参数(稀疏度或误差容忍值)是OMP算法的关键条件。针对上述问题,提出了利用少量导频随机分布的LS和OMP联合的信道估计方法,该方法首先利用少量导频采用LS方法估计出OMP算法的误差容忍值,再利用OMP算法恢复数据子载波的信道信息。理论分析和仿真结果同时表明,与传统的LS算法或OMP算法相比,新算法能够在数据恢复的同时有效抑制系统噪声,应用稀疏特性及较少量的导频,进一步提高了系统的频谱效率,对时变稀疏水声信道具有更好的适应性。

LS-OMP channel estimation algorithm for underwater acoustic OFDM systems

For underwater acoustic OFDM(Orthogonal Frequency Division Multiplexing)systems, the conventional LS (Least Squares) channel estimation algorithm is very sensitive to noise, and the large number of pilots affects the efficiency of communication. OMP(Orthogonal Matching Pursuit)channel estimation algorithm based on CS (Compressed Sensing) theory can make full use of the sparse characteristics of underwater acoustic channel, and can effectively restrain the system noise at the same time. But the OMP algorithm requires some parameters, which may be sparse degree or error tolerance value, to control the iterative computation times. Aiming at the above problems, an improved LS-OMP channel estimation algorithm is proposed, which first utilizes a small amount of random pilots to estimate the error tolerance values for the OMP algorithm through LS method, and then revises the data information through OMP method. Compared with the traditional LS algorithm or OMP algorithm, theoretical analysis and simulation results all show that the feasible LS-OMP method can effectively restrain the system noise, further improve the system spectrum efficiency, and possess better adaptability to the time-varying sparse underwater acoustic channel.