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.
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More From: International Journal of Machine Learning and Computing
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