Compressive Sensing Based Channel Estimation for MIMO-OFDM Systems

被引：0

作者：

Kong, Weisi ^{[1
]}

Li, Hui ^{[1
]}

Song, Shuangshuang ^{[1
]}

Fan, Yujie ^{[1
]}

Zhang, Wenjie ^{[1
]}

机构：

[1] Northwestern Polytech Univ, Sch Elect & Informat, Xian, Shaanxi, Peoples R China

来源：

PROCEEDINGS OF THE 2018 13TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2018) | 2018年

基金：

中国国家自然科学基金;

关键词：

MIMO; TDS-OFDM; channel estimation; gOMP algorithm; structured compressed sensing;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, an adaptive structured-generalized orthogonal matching pursuit (AS-gOMP) algorithm is proposed for time domain channel estimation by utilizing the characteristics of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. This algorithm uses the properties of the PN sequence to obtain partial channel prior information firstly, then the remaining support sets are obtained by the improved generalized orthogonal matching pursuit (gOMP) algorithm in MIMO system. A good channel estimation result is achieved by exploiting the characteristics of PN sequence and the common sparsity in spatial and time domain. The simulation results show that the proposed method can reduce the bit error rate (BER) of channel estimation and improve the performance of the MIMO-OFDM system.

引用

页码：2164 / 2169

页数：6

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