Joint Transmit Precoding and Receive Antenna Selection for Uplink Multiuser Massive MIMO Systems

This paper considers the uplink of multiuser multiple-input multiple-output systems, where several mobile stations (MSs) cooperatively transmit hybrid messages, including common messages and private messages, to a single base station (BS). We aim to jointly design transmit precoding at the MSs'...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on communications Jg. 66; H. 11; S. 5249 - 5260
Hauptverfasser: Zhai, Xiongfei, Shi, Qingjiang, Cai, Yunlong, Zhao, Minjian
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.11.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
antenna selection
Antennas
Codes
Frank-Wolfe
Iterative algorithms
Iterative methods
large-scale MIMO
Linear precoders
Messages
MIMO (control systems)
MIMO communication
Optimization
Penalty function
Precoding
Receiving antennas
sparse optimization problem
Transmitting antennas
Uplink
weighted MMSE
ISSN:0090-6778, 1558-0857
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This paper considers the uplink of multiuser multiple-input multiple-output systems, where several mobile stations (MSs) cooperatively transmit hybrid messages, including common messages and private messages, to a single base station (BS). We aim to jointly design transmit precoding at the MSs' side and antenna selection at the BS side to maximize the achievable system throughput while reducing implementation complexity. The problem at hand is nonconvex and difficult to solve due to the antenna selection constraint. By exploiting the problem structure and linear relaxation, we propose using the Frank-Wolfe method and the well-known weighted mean-square error minimization approach to tackle the problem, leading to an efficient iterative algorithm. Moreover, due to the large number of antennas, the sparsity of antenna selection is also taken into account by introducing an <inline-formula> <tex-math notation="LaTeX">l_{0} </tex-math></inline-formula>-norm penalty function into the objective function. To tackle this nonconvex and discontinuous problem, we resort to quadratic approximation with smooth optimization and extend our proposed algorithm to the sparse optimization problem. The convergence of the proposed algorithms is analyzed and its effectiveness is verified by numerical examples in terms of the achieved system throughput.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2018.2854175