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General Information
Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2012 Vol.2(1): 30-34 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2012.V2.85

New Variable Step-Size Blind Equalization Based on Modified Constant Modulus Algorithm

Roozbeh Hamzehyan, Reza Dianat, and Najmeh Cheraghi Shirazi

Abstract—This paper presents a new blind equalization algorithm based on MCMA to attain fast convergence speed and low steady-state error. The channel equalization without resorting to training sequence is called blind equalization. The CMA (Constant Modulus Algorithm) and MCMA (Modified Constant Modulus Algorithm) are two widely referenced algorithms for blind equalization of a QAM system. These algorithms exhibit very slow convergence rates and large steady-state mean square error when compared to algorithms employed in conventional equalization schemes. To obtain better results, we used varying step-size in MCMA, based on estimate of error at the output of equalizer. Simulation results show that the proposed algorithm has a better convergence rates and lower steady state error in comparison to CMA and MCMA algorithms.

Index Terms—Blind equalization, constant modulus algorithm (CMA), inter symbol interference (ISI), modifiled constant modulus algorithm (MCMA)

R. Hamzehyan, R. Dianat and N. Cheraghi Shirazi are with Engineering Department Azad University Bushehr Branch, Bushehr Iran (e-mail: r_Hamzehyan@yahoo.com; Dianat@pgu.ac.ir; nch_shirazi@yahoo.com).

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Cite: Roozbeh Hamzehyan, Reza Dianat, and Najmeh Cheraghi Shirazi, "New Variable Step-Size Blind Equalization Based on Modified Constant Modulus Algorithm," International Journal of Machine Learning and Computing vol. 2, no. 1, pp.30-34, 2012.

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