Structured Compressive Sensing Based Narrowband Interference Mitigation for Vehicular Communications

被引：0
|
作者：
Liu, Sicong [1 ,2 ]
Yang, Fang [1 ,2 ]
Ding, Wenbo [1 ,2 ]
Song, Jian [1 ,2 ,3 ]
机构：
[1] Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol TNList, Res Inst Informat Technol, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol TNList, Dept Elect Engn, Beijing 100084, Peoples R China
[3] Key Lab Digital TV Syst Guangdong Prov & Shenzhen, Shenzhen 518057, Peoples R China
来源：
2015 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION WORKSHOP (ICCW) | 2015年
关键词：
Narrowband interference; structured compressive sensing; structured sparsity adaptive matching pursuit; dependable vehicular communications; OFDM SYSTEMS; CHANNEL ESTIMATION; CANCELLATION; RECOVERY; PURSUIT;
D O I：
暂无
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 this paper, a novel narrowband interference (NBI) cancellation scheme based on structured compressive sensing (SCS) for dependable vehicular communications systems is proposed. The temporal joint correlation of the repeated training sequences in the preamble are exploited by SCS-based differential measuring (SCS-DM) to acquire the joint measurements matrix of the NBI. Using the proposed structured sparsity adaptive matching pursuit (S-SAMP) algorithm, the sparse high-dimensional NBI signal can be accurately recovered and cancelled out at the receiver. Simulation results validate that the proposed SCS-DM approach outperforms conventional CS-based and non-CS-based NBI mitigation schemes under wireless vehicular channels.
引用
收藏
页码：2375 / 2380
页数：6
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