A Reweighted Least Squares Approach to QAM Detector for Blind Equalization
Katsumi Konishi, Toshihiro Furukawa · IEEE Signal Processing Letters · 2011
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.