摘要
正交频分复用(OFDM)系统中,由于频率发生选择性衰落会导致信道在数据传输中产生符号间干扰,因此接收机往往需要知道信道状态信息。而在海上通信的情况下,信道传输会受到多种外界因素的干扰,往往需要预先进行信道探测估计。为了提高估计性能,该文提出一种基于奇异值分解优化观测矩阵的快速贝叶斯匹配追踪稀疏信道估计优化算法(FBMPO),该算法不仅能够充分考虑海上通信的信道稀疏性,也能够降低信道的不确定性带来的影响。计算机仿真实验表明,与传统的信道估计算法相比,该算法能够提高信道估计的精确度。
In the Orthogonal Frequency Division Multiplexing(OFDM) system, the receiver often needs to know the channel state information, because the frequency selective fading channel will generate inter-symbol interference in the data transmission. In the case of maritime communication, the method of channel estimation is often needed to detect the channel subjected to the interference of various external factors. In order to improve the estimation performance, the Fast Bayesian Matching Pursuit based on singular-value-decomposition for Optimizing observation matrix(FBMPO) is proposed, which fully considers not only the sparse channel of maritime communication, but also reduces the influence of uncertainty of the unpredictable channel. Computer simulation shows, compared with traditional channel estimation algorithms, the proposed algorithm can effectively improve the accuracy of channel estimation.
作者
张颖
姚雨丰
ZHANG Ying;YAO Yufeng(College of Information Engineering,Shanghai Maritime University,Shanghai 201306,China)
出处
《电子与信息学报》
EI
CSCD
北大核心
2020年第2期534-540,共7页
Journal of Electronics & Information Technology
基金
国家自然科学基金(61673259)~~
关键词
信道估计
贝叶斯准则
稀疏信道
匹配追踪
Channel estimation
Bayesian criterion
Sparse channel
Matching pursuit
