New M.E. Thesis Submitted from ECE Student

IMPLEMENTATION OF TWO STEP LMS ADAPTIVE ALGORITHM FOR RAYLEIGH FADING CHANNEL By Manu Bharti,Electronics

Abstract
The thesis presents implementation of the two-step least-mean-square (LMS)-type adaptive algorithm motivated by the work of Kohli and Mehra. This describes the nonstationary adaptation characteristics of this modified two-step LMS (MG-LMS) algorithm for the system identification problem. It ensures stable behavior during convergence as well as improved tracking performance in the smoothly time-varying environments. The estimated weight increment vector is used for the prediction of weight vector for the next iteration. The proposed modification includes the use of a control parameter to scale the estimated weight increment vector in addition to a smoothing parameter used in the two-step LMS (G-LMS) algorithm, which controls the initial oscillatory behavior of the algorithm. The analysis focuses on the effects of these parameters on the lag-misadjustment in the tracking process. The mathematical analysis for a nonstationary case, where the plant coefficients are assumed to follow a first-order Markov process, shows that the MG-LMS algorithm contributes less lag-misadjustment than the conventional LMS and G-LMS algorithms. Further, the stability criterion imposes upper bound on the value of the control parameter, which clearly show that the lag-misadjustment reduces with increasing values of the smoothing and control parameters under permissible limits.





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