2D Graph-Based Soft Channel Estimation for MIMO-OFDM

We address joint channel estimation and data detection based on factor graphs. The considered graph-based approach utilizes reliability information of channel estimates to facilitate soft-output data detection, and in-turn reliability information about the data symbols is taken into account for channel estimation. In this paper graph-based soft channel estimation and detection is extended to an OFDM based air interface, where the channel response varies in two dimensions; time and frequency. Initial channel estimates obtained by training symbols are conveyed by a two dimensional (2D) factor-graph in time and frequency with only a linear increase in complexity. The required training overhead for the proposed 2D graph-based soft channel estimation scheme may be substantially reduced by taking the redundancy introduced by the channel coding into account.