Compressive Channel Estimation Based on Weighted IRLS in FDD Massive MIMO

被引：1
|
作者：
Lu, Wei [1 ]
Wang, Yongliang [1 ]
Fang, Qiqing [1 ]
Peng, Shixin [2 ]
机构：
[1] Air Force Early Warning Acad, Wuhan, Hubei, Peoples R China
[2] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China
来源：
WIRELESS PERSONAL COMMUNICATIONS | 2019年 / 105卷 / 01期
基金：
美国国家科学基金会; 中国博士后科学基金;
关键词：
Weighted IRLS; Channel estimation; Massive MIMO; FDD;
D O I：
10.1007/s11277-018-6111-9
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
In this letter a weighted iteratively reweighted least-square (IRLS) algorithm is proposed for FDD massive MIMO channel estimation. The priori support information is merged into the weighted IRLS to improve the recovery performance. The priori support information is obtained from the uplink channel by reciprocity in angle domain, and a support estimation algorithm is proposed from the analysis of basis mismatch and angle deviation between uplink and downlink which is more practical in the real scenario. A brief convergence analysis of weighted IRLS is given out. Simulations show that the proposed weighted IRLS outperforms the standard IRLS, subspace pursuit (SP) and weighted SP.
引用
收藏
页码：257 / 266
页数：10
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