Channel estimation using Extended Kalman filter for superposition coded modulation system

In this paper Extended Kalman Filter(EKF)is implemented with the Superposition Coded Modulation(SCM) scheme. For time varying Rayleigh fast fading channel environment an Extended Kalman filtering algorithm is proposed. The Rayleigh fading channel is approximated to be a Jakes Process and modeled as Autoregressive model. With the utilization of training sequences and fundamental channel model this algorithm estimates the channel state information which in turn is utilized to estimate the information transmitted. This estimator algorithm is bandwidth efficient and requires less computation contrast to data-based only estimators. The results obtained prove that the proposed algorithm can be used to obtain the channel estimation with low computational complexity at the receiver.