基于压缩感知和粒子滤波的OFDM超宽信道估计  

Ultra Wideband Channel Estimation Based on Compressed Sensing and Particle Filter

作　　者：马永强[1] 孙伟[1] 

机构地区：[1]集宁师范学院计算机系,内蒙古乌兰察布012000

出　　处：《计算机测量与控制》2015年第6期2175-2177,2181,共4页Computer Measurement &Control

摘　　要：针对通信系统中的正交频分复用(OFDM)超宽信道具有的稀疏多径和含噪声特征,将信道估计问题转换为稀疏信号的重构和优化问题,设计了一种基于压缩感知理论和粒子滤波的OFDM信道估计方法;首先定义和描述了OFDM数学模型,然后在对压缩感知理论模型研究的基础上,采用改进的正交匹配算法对OFDM超宽信道进行重构,为了进一步减少信道重构的误差,将由于正交匹配算法得到的重构信道作为初始的粒子,并将OFDM数学模型转换为动态参数模型,并通过粒子滤波来更新模型中的参数和频率响应,通过不断迭代获得信道的估计值;为了验证文中方法的优越性,将文中方法与经典的正交匹配算法与粒子滤波算法进行比较,结果表明:文中方法能有效地对含噪声的稀疏信号进行估计,具有较小的重构误差,且与其它方法相比,具有较小的归一化均方误差。Aiming at the features of ultra wideband channel in communication system such as sparse multi path and noise feature, the channel estimation problem is transferred to the construction and optimization of sparse signal, a channel estimation method based on com- pressing sensing theory and particle filter is proposed. Firstly, the OFDM mathematical model is defined and specified, then on the basis of the compressing sensing theory model, the improved orthogonal matching algorithm is used to construct the OFDM ultra wideband channel. In order to further reducing the error of the channel construction, the construction channel is used as the initial particle generated from the improved orthogonal matching algorithm, and the OFDM model is transferred to the dynamic parameter model, and the particle filter is used to renew the parameter and frequency response, the result shows the method in this paper can estimate the sparse signal effectively with less construction error, and compared with the other method, it has less standardized square error.

关 键 词：压缩感知 信道估计 正交匹配 粒子滤波 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]