A Reweighted Least Squares Approach to QAM Detector for Blind Equalization

This letter proposes a reweighted least squares algorithm for quadrature amplitude modulation (QAM) detector in blind equalization. Because the QAM detection problem is a non-convex combinatorial optimization problem, it is relaxed into a problem of minimizing the sum of logarithmic functions in ord...

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Bibliographic Details
Published in:IEEE signal processing letters Vol. 18; no. 4; pp. 259 - 262
Main Authors: Konishi, Katsumi, Furukawa, Toshihiro
Format: Journal Article
Language:English
Published: IEEE 01.04.2011
Subjects:
Blind equalization
Blind equalizers
iteratively reweighted least squares
maximum likelihood detection
MIMO
Polynomials
Programming
Quadrature amplitude modulation
Signal processing algorithms
ISSN:1070-9908, 1558-2361
Online Access:Get full text
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Summary:This letter proposes a reweighted least squares algorithm for quadrature amplitude modulation (QAM) detector in blind equalization. Because the QAM detection problem is a non-convex combinatorial optimization problem, it is relaxed into a problem of minimizing the sum of logarithmic functions in order to overcome the combinatorial complexity. To find a local optimal solution of the problem, an iterative reweighted least squares based algorithm is proposed. Simulation results show that the proposed algorithm improves the accuracy of QAM detection in blind equalization.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2011.2118202