Paper Info
Title
Channel feedback based on complex 1-bit Bayesian compressed sensing in FDD massive MIMO systems
Abstract
In frequency division duplex (FDD) massive multi-input multi-output (MIMO) system, channel feedback is critical for beamforming and precoding. The previous codebook-based feedback scheme in 4G system cannot be reused since the codebook size will scale exponentially with the number of antennas. In the paper, we propose a 1-bit compressed sensing (CS) based channel feedback scheme. The sparse massive MIMO channel is estimated at the user equipment (UE), then it is compressed by 1-bit quantization at the UE. The quantized bits are fed back to the base station (BS) and are recovered by the complex 1-bit Bayesian CS algorithm which can also be used for other complex 1-bit CS models. The recovered channel is used for zero forcing beamforming for multiple user (MU) massive MIMO. The performance of the proposed algorithm is compared with other feedback schemes in view of per-user capacity in MU massive MIMO.
Year
DOI
Venue
2019
10.1145/3371425.3371443
Proceedings of the International Conference on Artificial Intelligence, Information Processing and Cloud Computing
Keywords
Field
DocType
1-bit compressed sensing, channel feedback, massive MIMO
Beamforming,Computer science,Algorithm,MIMO,Communication channel,User equipment,Quantization (signal processing),Precoding,Compressed sensing,Codebook
Conference
ISBN
Citations 
PageRank 
978-1-4503-7633-4
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Wei Lu131962.97
Bin Deng210.70
Wei Zhang301.69
Jingjing Wang400.34
Liang Zhong511.03
Shixin Peng601.01