Channel estimation for high mobility MIMO system using particle filter

Channel estimation is an important part in a coherent detection of MIMO system. This paper proposes tracking of fast time varying channel coefficients for a MIMO system using particle filter algorithm. As the system is highly mobile, MIMO channel is fast time-varying, non-linear and non-Gaussian, particle filter is the best candidate to track the swiftly varying channel co-efficient. Even though there exist Kalman filter, the BLUE (Best Linear Unbiased Estimator), it is not suitable for nonlinear and non-Gaussian problems. Moreover Kalman filter variants namely EKF (Extended Kalman Filter) and UKF (Unscented Kalman Filter) are limited to Gaussian noise.