Paper Info
Title
Zero-forcing pre-equalization with transmit antenna selection in MIMO systems
Abstract
In this paper, we jointly solve the problem of transmit antenna selection and zero-forcing (ZF) precoding in a multiple input multiple output (MIMO) system. A new problem formulation is proposed which enables efficient semi-definite programming (SDP) to solve the originally non-convex problem of antenna selection. This has been accomplished by imposing the Group Lasso sparsity promoting term in the precoding design criterium as a convex relaxation of the ℓ0-norm operation. For the selected set of antennas, we then minimize the overall transmit power, subject to a constraint on the maximum achievable throughput. Simulation results reveal the power saving advantage of the proposed algorithm compared to a randomly selected subset of antennas.
Year
DOI
Venue
2013
10.1109/ICASSP.2013.6638622
Acoustics, Speech and Signal Processing
Keywords
DocType
ISSN
MIMO communication,concave programming,mathematical programming,precoding,transmitting antennas,Group Lasso sparsity promoting term,MIMO systems,SDP,ZF precoding,convex relaxation,l0-norm operation,multiple input multiple output system,nonconvex problem,power saving,precoding design criterium,semidefinite programming,transmit antenna selection,zero-forcing preequalization,Group Lasso,Multiple input multiple output (MIMO),antenna selection,convex optimization,linear precoding
Conference
1520-6149
Citations 
PageRank 
References 
2
0.42
8
Authors
4
Name
Order
Citations
PageRank
Seyran Khademi1192.30
Sundeep Prabhakar Chepuri216220.74
G. Leus34344307.24
Jan van der Veen47711.53