压缩感知非凸优化超宽带信道估计方法研究

Abstract

Considering the complicated transfer propagation and low power spectrum density of ultra-wideband (UWB) signal, accurate estimation of UWB channel is crucial. However, it is difficult to sample UWB signal directly for its band width is ultra wide. Compressed sensing (CS) provides a feasible method for low speed sampling. Existing CS-based UWB channel estimation method generally adopts convex optimization form using l 1 -norm restriction, or non-sparse form using l 2 -norm restriction. These methods have a weak restriction on sparseness of objective vector, and l 0 -norm which is the sparsest lacks of effective reconstruction algorithm. To solve these problems, a CS-based UWB channel estimation method based on non-convex optimization is devised in this paper. Firstly, objective function is set as non-convex optimization form using l p -norm restriction; original non-convex function is then combined as convex function form, using the property that convex function obtains extremum easily. Convex function is used to approximate non-convex function at each iteration, for objective vector reconstruction and original channel estimation. Since l p -norm is closer to l 0 -norm, it has stronger restriction on sparseness of objective vector. Experimental results show that proposed method can effectively lower reconstruction error compared to existing CS-based UWB channel estimation method.