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A polynomial matrix QR decomposition with application to MIMO channel equalisation

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conference contribution
posted on 08.12.2009, 17:03 by Joanne Foster, John McWhirter, Jonathon Chambers
An algorithm for computing the QR decomposition of a polynomial matrix is introduced. The algorithm proceeds to perform the decomposition by following the same strategy in eliminating entries of the matrix as is used in the Givens method for a QR decomposition of a scalar matrix, however polynomial Givens rotations are now required. A possible application of the decomposition is in MIMO communications, where it is often required to reconstruct data sequences that have been distorted due to the effects of co-channel interference and multipath propagation, leading to intersymbol interference. If the channel matrix for the system is known, its QR decomposition can be calculated and used to transform the MIMO channel equalisation problem into a set of single channel problems, which can then be solved using a maximum likelihood sequence estimator. Some simulated average bit error rate results are presented to support the potential application to MIMO channel equalisation.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Citation

FOSTER, J., MCWHIRTER, J. and CHAMBERS, J., 2007. A polynomial matrix QR decomposition with application to MIMO channel equalisation. IN: Forty-First Asilomar Conference on Signals, Systems and Computers, (ACSSC 2007), Pacific Grove, California, Nov. 4-7, pp. 1379-1383

Publisher

© IEEE

Version

VoR (Version of Record)

Publication date

2007

Notes

This is a conference paper [© IEEE]. It is also available from: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

ISBN

9781424421091

ISSN

1058-6393

Language

en

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