摘要
传统的多输入多输出-正交频分复用(MIMO-OFDM)无线通信系统信道估计算法,没有充分利用无线信道时域的固有稀疏性,导致估计精度不高且频谱利用率低等问题.在信道时域稀疏的前提下,研究了基于压缩感知的MIMO-OFDM系统信道估计算法,详细介绍了正交匹配追踪(OMP)和子空间追踪(SP)两种压缩感知算法原理和步骤,并同其它常用信道估计算法进行了比较分析.理论分析与仿真表明,所提出的压缩感知信道估计算法在频谱利用率以及估计性能方面比传统方法有显著提高,更具有效性.
In multiple-input multiple-output orthogonal frequency division multiplexing （MIMO-OFDM） wire- less communication systems, traditional channel estimation methods did not make full use of the channel spar- sity which leads to low precision estimation and low frequency spectrum utilization. Under the premise of time domain channel sparsity, this paper studies compressed sensing based sparse channel estimation in MIMO- OFDM systems, then introduces Orthogonal Matching Pursuit （0MP） and Subspace Pursuit （SP） compressed sensing methods in details and makes a comparative analysis with other commonly used algorithm. Theoretical analysis and simulation shows that the new channel estimation methods in spectrum utilization and performance than the traditional methods have improved significantly and are more efficient.
出处
《郑州大学学报（工学版）》
CAS
北大核心
2013年第6期6-9,19,共5页
Journal of Zhengzhou University（Engineering Science）
基金
国家自然科学基金项目(61201251
61172086)
教育部博士点科研基金项目(20104101120011)
关键词
无线通信系统
稀疏信道估计
压缩感知
多输入多输出
正交频分复用
wireless communication system
sparse channel estimation
compressed sensing
multiple-input multiple-output
orthogonal frequency division multiplexing
