Title
Compressive Downlink Channel Estimation for FDD Massive MIMO Using Weighted $l_{p}$ Minimization
Abstract
We propose a weighted l(p) minimization method for downlink channel estimation in frequency division duplexing massive multiple-input multiple-output (MIMO) systems. The proposed algorithm involves two stages, in which it first diagnoses the downlink supports by utilizing the channel sparsity in angular domain and angular reciprocity for uplink and downlink channels. In stage two, a weighted l(p) minimization algorithm based on the diagnosed supports is used for downlink channel estimation. The diagnosed supports are used for generating the weighting matrix in the weighted l(p) minimization. The restricted isometry property (RIP)-based guarantees and upper bound of the recovery error are derived. Our analytical results have the universal forms for the l(p) (0 < p <= 1) minimization and the weighted l(p) (0 < p <= 1) minimization, and can reduce to the RIP-based analysis results for the l(1) minimization and the weighted l(1) minimization which have been discussed in the previous literature. The discussion on the weight selection is also presented which is based on the derived upper bound. Simulations show that the weighted l(p) minimization is preferred when the correct percentage of the estimated support is more than 0.5. For the channel estimation, the proposed method with support diagnosis and the weighted l(p) minimization can achieve higher estimation accuracy compared with the l(p) minimization, weighted subspace pursuit, weighted l(1) minimization, general l(1) minimization, joint orthogonal matching pursuit, and simultaneous orthogonal matching pursuit in the medium and high signal-to-noise-rate regions.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2926790
IEEE ACCESS
Keywords
DocType
Volume
Channel estimation,massive MIMO,weighted l(p) minimization
Journal
7
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Wei Lu131962.97
Yongliang Wang29016.21
Xiaoqiao Wen300.34
Xiaoqiang Hua4102.62
Shixin Peng501.01
Liang Zhong600.34