摘要
在正交频分复用(OFDM)系统中,接收信号易受频率选择性衰落信道的影响产生失真,准确的信道估计变得必不可少。考虑到无线信道的内在稀疏性、压缩感知技术挖掘信道稀疏特征的有效性,研究了基于压缩感知技术的OFDM稀疏信道估计。针对导频位置影响信道估计性能的问题,提出了一种反馈型的导频优化算法,该算法基于离散傅里叶变换(DFT)子矩阵中各个列之间互相干性最小的原则,同时结合信道状态信息的反馈机制,实现了对导频序列的联合优化。仿真结果表明,与当前的随机优化算法、传统最小二乘信道估计相比,该优化方法有效降低干扰和噪声对信道估计的影响,从而改善了信道估计的性能。
In orthogonal frequency division multiplexing( OFDM) systems,the received signals are easily affected by the frequency selective fading channel,the accurate channel estimation is indispensable at receiver. Considering the inherent sparsity of the wireless channel and the effectiveness of the compressed sensing technology,this paper investigated the OFDM sparse channel estimation utilizing the compressed sensing technology. Aiming at the problem that the position of pilot sequence significantly affects the channel estimation performance,we propose a pilot optimization algorithm using the feedback mechanism,which is combining the criterion of minimizing the coherence between the columns of the Discrete Fourier Transform( DFT) sub-matrix and the feedback mechanism of the channel state information to jointly optimize the pilot sequence. Simulation results show that compared with the known stochastic optimization algorithms and the traditional least squares channel estimation,the proposed algorithm can effectively reduce the impact of the interference and noise on the channel estimation,which further improve the channel estimation performance.
出处
《科学技术与工程》
北大核心
2015年第29期148-152,共5页
Science Technology and Engineering
基金
国家自然科学基金资助项目(61271249)资助
关键词
OFDM
稀疏信道估计
压缩感知
反馈
导频设计
OFDM sparse channel estimation compres sed sensing feedback pilot design