基于混沌序列的压缩感知超宽带信道估计  

Compressed Sensing Ultra-Wide Band Channel Estimation Based on Chaos Sequence

作　　者：李皓天[1] 龙敏[1] 

机构地区：[1]长沙理工大学计算机与通信工程学院,长沙410004

出　　处：《计算机工程》2014年第12期316-320,共5页Computer Engineering

基　　金：国家自然科学基金资助项目(61001004);湖南省教育厅基金资助项目(11B002);湖南省海外名师基金资助项目(2013008)

摘　　要：通过分析超宽带信道本身特性,利用混沌序列良好的随机性,提出一种基于Logistic混沌序列的超宽带信道估计方法。通过Logistic映射产生伪随机序列,对准托普利兹矩阵进行正交变换,产生新的改进型矩阵,并将该矩阵作为压缩感知的测量矩阵,建立贝叶斯压缩感知数学模型对超宽带信道进行估计。仿真结果表明,在同等的实验条件下,与传统的重构算法相比,该方法具有更高的抗噪声性能和重构精度。Through the analysis of Ultra-Wide Band（ UWB） channel characters,this paper proposes an UWB channel estimation method based on logistic chaos sequence according to the pseudo-random property of chaos sequence. It uses the Logistic chaotic system to generate the pseudo-random sequence, and uses the sequence to construct orthogonal transformation for quasi-Toeplitz modified measurement matrix. This paper presents a Bayesian Compressed Sensing （ BCS） mathematical model. Simulation results show that under the same conditions, the method has better anti-noise ability and recovery accuracy than those of the traditional reconstruction algorithm.

关 键 词：超宽带信道估计 混沌 LOGISTIC映射 正交变换 测量矩阵 贝叶斯压缩感知 Bayesian Compressed Sensing( BCS) 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]