DocumentCode :
1676421
Title :
Zero-forcing pre-equalization with transmit antenna selection in MIMO systems
Author :
Khademi, Seyran ; Chepuri, Sundeep Prabhakar ; Leus, Geert ; van der Veen, A.-J.
Author_Institution :
Fac. of Electr. Eng., Tech. Univ. Delft, Delft, Netherlands
fYear :
2013
Firstpage :
5046
Lastpage :
5050
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.
Keywords :
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; MIMO; Receiving antennas; Throughput; Transmitting antennas; Group Lasso; Multiple input multiple output (MIMO); antenna selection; convex optimization; linear precoding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2013.6638622
Filename :
6638622
Link To Document :
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