EM-Based Semi-Blind Channel Estimation in Amplify-and-Forward Two-Way Relay Networks

In this letter, we propose an expectation maximization (EM)-based algorithm for semi-blind channel estimation of reciprocal channels in amplify-and-forward (AF) two-way relay networks (TWRNs). By utilizing data samples as well as pilots, the proposed algorithm provides substantially higher estimation accuracy than the conventional training-based least squares (LS) estimator without incurring a significant computational cost. Simulation results also show that it performs very close to the corresponding semi-blind Cramer-Rao bound.