A simple Kalman channel Equalizer using adaptive algorithms for time variant channel

In this paper, Discrete Kalman filter is used as an equalizer for digital transmission because it suppresses the noise and intersymbol interference (ISI). Kalman equalizer is based on the least square optimization criterion and its structure is made adaptive by combining it in parallel with adaptive algorithms to estimate the channel coefficients. Least mean square (LMS) and Recursive Least Square (RLS) adaptive algorithms are used for identification of channel coefficients and have been implemented to study the performance of Kalman Equalizer. The performance index, Bit Error Rate (BER), of Kalman Equalizer with RLS and LMS adaptive algorithms named K-RLS and K-LMS respectively is studied via computer simulation for different SNR scenario. Simulation results shows that the performance of K-RLS has less BER as compared to that of K-LMS.