A reweighted least squares algorithm for detection of QAM signaling in MIMO channels

This paper proposes a reweighted least squares algorithm for quadrature amplitude modulation (QAM) detector in multiple-input multiple-output (MIMO) channels. Although the QAM detection problem is a non-convex combinatorial optimization problem, it is reformulated into a problem of minimizing the su...

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Bibliographic Details
Published in:2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 3876 - 3879
Main Authors: Konishi, Katsumi, Furukawa, Toshihiro
Format: Conference Proceeding
Language:English
Japanese
Published: IEEE 01.05.2011
Subjects:
Computational complexity
Detectors
iteratively reweighted least squares
maximum likelihood detection
MIMO
MIMO systems
Programming
Quadrature amplitude modulation
Signal processing algorithms
Signal to noise ratio
ISBN:9781457705380, 1457705389
ISSN:1520-6149
Online Access:Get full text
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Summary:This paper proposes a reweighted least squares algorithm for quadrature amplitude modulation (QAM) detector in multiple-input multiple-output (MIMO) channels. Although the QAM detection problem is a non-convex combinatorial optimization problem, it is reformulated into a problem of minimizing the sum of logarithmic functions. In order to find a local optimal solution of the problem, an iterative reweighted least squares (IRLS) based algorithm is proposed. The proposed algorithm is fast real-time applicable due to its low computational complexity. Numerical experiments in a random MIMO system show the effectiveness of the proposed algorithm.
ISBN:9781457705380
1457705389
ISSN:1520-6149
DOI:10.1109/ICASSP.2011.5947198