Structured Compressive Sensing-Based Channel Estimation for Time Frequency Training OFDM Systems Over Doubly Selective Channel

被引：25

作者：

Ma, Xu ^{[1
,2
]}

Yang, Fang ^{[1
,2
]}

Liu, Sicong ^{[1
,2
]}

Ding, Wenbo ^{[1
,2
]}

Song, Jian ^{[1
,2
]}

机构：

[1] Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol, Res Inst Informat Technol, Beijing 100084, Peoples R China

[2] Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol, Elect Engn Dept, Beijing 100084, Peoples R China

来源：

IEEE WIRELESS COMMUNICATIONS LETTERS | 2017年 / 6卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Channel estimation; doubly selective channel; structured compressive sensing (SCS); TFT-OFDM;

D O I：

10.1109/LWC.2017.2669974

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This letter proposes a novel doubly selective channel estimation scheme based on structured compressive sensing (SCS) for time-frequency training orthogonal frequency division multiplexing systems. By exploiting the proposed pilot pattern, an SCS model is built by utilizing the jointly sparse property of the coefficient vectors corresponding to the channel expansion bases. The doubly selective channel can be recovered through the proposed adaptive support-aware block orthogonal matching pursuit algorithm. Simulation results demonstrate that the proposed scheme has superior performance than conventional counterparts over doubly selective channel with lower computational complexity.

引用

页码：266 / 269

页数：4

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