Paper Info
Title
Convex optimization for joint zero-forcing and antenna selection in multiuser MISO systems
Abstract
The problem of joint zero-forcing (ZF) beamforming (BF) together with optimal power allocation (PA) and antenna selection (AS) for throughput maximization is considered in this paper for multi-user multiple input single output (MU-MISO) systems. We introduce a new formulation for the joint ZF and PA problem by adapting the algebraic subspace approach which finds a proper set for the optimization variable that inherently satisfies the ZF constraints. Also, the squared group Lasso penalty on the BF matrix is used to linearize (relax) the non-convex, NP-hard problem of joint BF and AS. Extensive simulations show that for the throughput problem, the proposed algorithm performs very closely to the optimal (exhaustive search) joint approach.
Year
DOI
Venue
2014
10.1109/SPAWC.2014.6941311
Signal Processing Advances in Wireless Communications
Keywords
Field
DocType
MIMO communication,antenna arrays,array signal processing,computational complexity,concave programming,convex programming,group theory,matrix algebra,multiuser channels,set theory,BF matrix,NP-hard problem,PA problem,algebraic subspace approach,antenna selection,convex optimization,joint ZF problem,joint zero-forcing beamforming problem,multiple input multiple output systems,multiuser MISO systems,multiuser multiple input single output systems,nonconvex problem,squared group Lasso penalty,throughput maximization,Multiple input multiple output (MIMO),antenna selection,convex optimization,group Lasso,linear precoding
Beamforming,Mathematical optimization,Square (algebra),Algebraic number,Brute-force search,Subspace topology,Matrix (mathematics),Computer science,Electronic engineering,Throughput,Convex optimization
Conference
ISSN
Citations 
PageRank 
2325-3789
1
0.37
References 
Authors
12
4
Name
Order
Citations
PageRank
Seyran Khademi132.26
Evan DeCorte210.37
G. Leus34344307.24
Alle-Jan van der Veen449579.07