Structured Compressed Sensing of Double Selective Channel for High-Frequency OFDM Systems

被引：2

作者：

Wang Kai ^{[1
]}

Liu Jingzhi ^{[1
]}

Liu Haibo ^{[1
]}

Zhang Fengbin ^{[1
]}

机构：

[1] Army Engn Univ PLA, Commun NCO Acad, Chongqing 400035, Peoples R China

来源：

PROCEEDINGS OF 2020 IEEE 10TH INTERNATIONAL CONFERENCE ON ELECTRONICS INFORMATION AND EMERGENCY COMMUNICATION (ICEIEC 2020) | 2020年

关键词：

high-frequency; OFDM; double selective channel; structured compressed sensing; high mobility;

D O I：

10.1109/iceiec49280.2020.9152331

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to realize the real-time acquisition of the state information of the double selective channel with low pilot cost, a structured compressed sensing (SCS) based channel estimation method is proposed for high-frequency (HF) in this paper. Combining with the transmission model and sky wave channel model of HF OFDM systems, the channel estimation problem is formulated under the framework of compressed sensing. The block-structured sparsity of channel coefficients in transformed domain of double selective sky wave channel is proved. On this basis, the channel coefficients are reconstructed by structured compressed sensing algorithm. Simulation results show that the proposed structured compression sensing method can significantly reduce the pilot overhead and ensure the accuracy of channel estimation.

引用

页码：65 / 68

页数：4

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