Pilot-aided Bayesian MMSE channel estimation for OFDM systems: Algorithm and performance analysis
This paper proposes a computationally efficient pilot-aided minimum mean square error (MMSE) channel estimation algorithm for OFDM systems. The proposed approach employs a convenient representation of the discrete multipath fading channel based on the Karhunen-Loeve (KL) orthogonal expansion and estimates uncorrelated series expansion coefficients. Moreover optimal rank reduction is achieved in the proposed approach by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the estimation algorithm. The performance of the proposed approach is studied through analytical and experimental results. We first consider the stochastic Cramer-Rao hound and derive the closed-form expression for the random KL coefficients. We then exploit the performance of the MMSE channel estimator based on the evaluation of minimum Bayesian MSE.