Title
Joint Channel Estimation and Data Detection in Cell-Free Massive MU-MIMO Systems
Abstract
We propose a joint channel estimation and data detection (JED) algorithm for densely-populated cell-free massive multiuser (MU) multiple-input multiple-output (MIMO) systems, which reduces the channel training overhead caused by the presence of hundreds of simultaneously transmitting user equipments (UEs). Our algorithm iteratively solves a relaxed version of a maximum a-posteriori JED problem and simultaneously exploits the sparsity of cell-free massive MU-MIMO channels as well as the boundedness of QAM constellations. In order to improve the performance and convergence of the algorithm, we propose methods that permute the access point and UE indices to form so-called virtual cells, which leads to better initial solutions. We assess the performance of our algorithm in terms of root-mean-squared-symbol error, bit error rate, and mutual information, and we demonstrate that JED significantly reduces the pilot overhead compared to orthogonal training, which enables reliable communication with short packets to a large number of UEs.
Year
DOI
Venue
2022
10.1109/TWC.2021.3126646
IEEE Transactions on Wireless Communications
Keywords
DocType
Volume
Cell-free communication system,joint channel estimation and data detection (JED),massive multi-user (MU) multiple-input multiple-output (MIMO)
Journal
21
Issue
ISSN
Citations 
6
1536-1276
2
PageRank 
References 
Authors
0.39
45
6
Name
Order
Citations
PageRank
Haochuan Song131.07
Tom Goldstein255.84
xiaohu you32529272.49
Chuan Zhang410013.67
Olav Tirkkonen51940202.67
Christoph Studer6109785.83