Semi-blind maximum likelihood joint channel estimation/data detection for MIMO fading channels

The aim of this paper is to investigate receiver techniques for ML joint channel/data estimation in flat fading MIMO channels that are both i) data efficient and ii) computationally attractive. The performance of iterative least squares (LS) for channel estimation combined with sphere decoding (SD) for data detection is examined in the first part, for block fading channels, demonstrating the data efficiency provided by the semi-blind approach. In the second part, the case of continuous fading channels is addressed with the aid of recursive least squares (RLS). The observed relative robustness of the ML solution to channel variations is exploited in deriving a block QR-based RLS-SD scheme, which allows significant complexity savings with little or no performance loss.