A Super-Resolution Channel Estimation Algorithm Using Convex Programming

被引:2
|
作者
Hao, Huan [1 ]
Wang, Huali [1 ]
Lv, Wanghan [2 ]
Chen, Liang [1 ]
机构
[1] PLA Univ Sci & Technol, Inst Commun Engn, Nanjing 210007, Jiangsu, Peoples R China
[2] Nanjing Univ Sci & Technol, Sch Elect & Opt Engn, Nanjing 210094, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
continuous super-resolution; Doppler shift; multipath delay; chirp signal; TOA ESTIMATION; DIVERSITY; ARRAYS;
D O I
10.1587/transfun.E100.A.1236
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes an effective continuous super-resolution (CSR) algorithm for the multipath channel estimation. By designing a preamble including up-chirp and down-chirp symbols, the Doppler shift and multipath delay are estimated jointly by using convex programming. Simulation results show that the proposed CSR can achieve better detection probability of the number of multipaths than the eigenvalue based methods. Moreover, compared with conventional super-resolution techniques, such as MUSIC and ESPRIT methods, the proposed CSR algorithm demonstrates its advantage in root mean square error of the Doppler shift and multipath delay, especially for the closely located paths within low SNR.
引用
收藏
页码:1236 / 1239
页数:4
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