Efficient Variational Bayesian Method for Joint Channel Estimation and Signal Detection in OFDM-Based AF Relay Networks

We propose improved joint channel estimation and data detection in orthogonal frequency division multiplexing (OFDM) amplify-and-forward (AF) relay network in the case of imperfect partial channel knowledge at the destination. To improve the detection accuracy, we adopt the variational Bayesian approximation (VBA) which is an iterative Bayesian method for channel estimation. We derive a modified iterative estimator that takes into account the channel estimation errors at the previous iteration, to reduce the impact of channel uncertainty at the next iteration, and hence, to improve the overall detection accuracy. By comparison with state of the art VBA-based estimators through numerical analysis, we highlight the superiority of our new VBA method and demonstrate a notable improvement in terms of bit error rate and mean square error between the true and the estimated channel.