Random Parameter EM-Based Kalman Filter (REKF) for Joint Symbol Detection and Channel Estimation in Fast Fading STTC MIMO Systems

In this work, we present a novel random parameter-based expectation-maximization (EM) algorithm for joint symbol detection and channel estimation in fast fading space-time trellis coded (STTC) multiple-input multiple-output (MIMO) wireless communication systems. Employing the EM framework with the MIMO channel as the random parameter, we demonstrate that this paradigm reduces to the optimal Kalman filter (KF)-based channel update in the E-step followed by a modified path metric-based maximum likelihood sequence decoder (MLSD) in the M-step. Further, we also present the pairwise error probability (PEP) upper bound for the frame error rate (FER) and the Bayesian Cramer-Rao bound (BCRB) for the proposed joint estimation scheme. Simulation results are presented to demonstrate the performance of the proposed technique and validate the analytical bounds.