Reduced complexity in antenna selection for polarized MIMO system with SVD for the practical MIMO communication channel environment

Maung Sann Maw, Iwao Sasase

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

In the conventional multi-input multi-output (MIMO) communication systems, most of the antenna selection methods considered are suitable only for spatially separated uni-polarized system under Rayleigh fading channel in non-line of sight (NLOS) condition. There have a few antenna selection schemes for the cross-polarized system in LOS condition and Ricean fading channel, and no antenna selection scheme for the MIMO channel with both LOS and NLOS. In the practical MIMO channel case, influence of LOS and NLOS conditions in the channel can vary from time to time according to the channel parameters and user movement in the system. Based on these influences and channel condition, uni-polarized system may outperform a cross-polarized. Thus, we should consider this kind of practical MIMO channel environment when developing the antenna selection scheme. Moreover, no research work has been done on reducing the complexity of antenna selection for this kind of practical MIMO channel environment. In this paper, reduced complexity in antenna selection is proposed to give the higher throughput in the practical MIMO channel environment. In the proposed scheme, suitable polarized antennas are selected based on the calculation of singular value decomposition (SVD) of channel matrix and then adaptive bit loading is applied. Simulation results show that throughput of the system can be improved under the constraint of target BER and total transmit power of the MIMO system.

Original languageEnglish
Pages (from-to)2389-2399
Number of pages11
JournalIEICE Transactions on Communications
VolumeE93-B
Issue number9
DOIs
Publication statusPublished - 2010 Sep

Keywords

  • Adaptive modulation
  • Antenna selection
  • MIMO
  • Polarization
  • Spatial multiplexing
  • ZF linear receiver

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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