基于改进梯度投影算法的压缩感知超宽带信道估计  

UWB Channel Estimation Through Compressed Sensing Based on an Improved Gradient Projection Algorithm

作　　者：王蔚东[1,2] 杨俊安[1,2] 

机构地区：[1]电子工程学院,合肥230037 [2]安徽省电子制约技术重点实验室,合肥230037

出　　处：《信号处理》2012年第3期376-383,共8页Journal of Signal Processing

摘　　要：超宽带是近年来兴起的一种高速无线通信技术,考虑其过高带宽带来的采样难度较高的问题,压缩感知理论提供了一种可行的低速采样方法。针对梯度投影稀疏重构算法应用于超宽带信道估计中效果不佳的问题,提出了改进的梯度投影算法。改进算法采用原始算法的目标函数形式,取消原始算法中沿负梯度方向搜索和负梯度向可行集合投影后再搜索的交替搜索方式,改为一直沿负梯度方向搜索的单一搜索方式,从而避免了原始算法的高运算复杂度和过于严格的约束条件对算法的限制,同时该目标函数相对于梯度追踪算法加上了对稀疏噪声的约束条件,变成了1范数优化问题。实验结果表明该算法相对于梯度投影稀疏重构算法能够显著降低运算复杂度,提高运算速度,同时相对于梯度追踪算法也有重构性能上的提升。Ultra-Wide Band（UWB） is a newly developing high-speed wireless communication technology.It is difficult to sample it directly as its wider band width.However,Compressed Sensing（CS） provides a feasible way with lower sampling speed.Considering the poor performance of the Gradient Projection for Sparse Reconstruction（GPSR） algorithm which has been used in UWB channel estimation,an improved algorithm is proposed in this paper.The improved algorithm adopts the objective function form of original algorithm.It cancels the alternating searching method including search at negative gradient direction or search after projecting the gradient direction onto feasible set,change it to the single method of searching straight at negative gradient direction.This method avoids to solve the high dimensional compute problem of original algorithm and get rid of the confinement of strict restrict condition.Comparing with the Gradient Pursuit（GP）,it adds an restrict condition to the sparse noise and translates into a _1-norm optimization problem.The experiment results show that this improved algorithm can reduce the computation complexity and enhance the speed compared with GPSR algorithm remarkable,while it can also promote the reconstruction performance compared with GP algorithm.

关 键 词：超宽带 信道估计 压缩感知 1范数优化 负梯度 

分 类 号：TN911.5[电子电信—通信与信息系统]