Blind channel equalization using modified constant modulus algorithm
Prakhar Priyadarshi, C. S. Rai · 2016
In this paper authors have addressed the problems in blind adaptation technique implementations. Blind adaptation techniques shows poor convergence property in comparison to the supervised techniques which uses training sequences for adaption purpose e.g. least mean square algorithm. Gradient descent based adaption/estimation technique is one of the widely used blind channel adaptation/estimation schemes. The most commonly and widely used gradient descent based blind channel adaptation/estimation algorithm is the Constant Modulus Algorithm (CMA) which suffers from the poor convergence property. Also constant modulus algorithm is phase blind. In this work, authors have presented a new modified CMA Algorithm for blind equalization. The modified update equation is based on mean forth error criteria. Matlab Simulation results proves the claimed fast convergence, low BER value as compared to the CMA algorithm in noisy environment.