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Improving The Steady State error and Convergence based on Variable Step Size Constant Modulus Blind Equalization Algorithm


Raja Uyyala, P. Satyanarayana


Vol. 14  No. 10  pp. 107-110


In this paper presents improving the steady state error and convergence based on variable step size modulation (VSS-CMA) blind equalization algorithm. In the past, constant-modulus algorithm (CMA) has low convergence rate and high error rate. In CMA has less step size can decrease the convergence rate, but at the same time it decrease the steady-state error. This paper propose a new variable step size constant-modulus algorithm (new VSS-CMA) with an adjustable step size that greatly increases the convergence rate for noise colorings with large eigenvalue spreads. A new VSS-CMA is simpler in computational requirements, faster convergence and lower steady state error and compare to conventional CMA, and VSS-CMA. The experimental results shows that the proposed VSS-CMA algorithm has considerably better performance than the conventional CMA and VSS-CMA


Cross correlation, VSS-CMA, blind equalization, adaptive blind training