Data detection and kalman estimation for multiple space-time trellis codes

This work presents a joint channel estimation and data detection algorithm over high Doppler fading channels, for space-time trellis codes (STTCs) having more than one code vector per trellis branch. Such codes are referred to as multiple STTCs (MSTTCs). This algorithm belongs to the per-survivor processing (PSP) family, where a survivor sequence associated with a trellis state can be considered as the data sequence aiding per-path channel estimation in a joint detection and estimation procedure.We propose a smoothed data detection technique that utilizes past, present and future received symbols to increase the probability of the survivor being a correct data sequence. A symbol by symbol maximum a posteriori probability (MAP) criterion, with a fixed delay D, is employed for data detection, combined with a Kalman Predictor (KP) for channel estimation. This novel algorithm, called smoothed data detection and Kalman estimation (SDD-KE), provides a significant performance gain when D > 0 over D = 0, with a linear increase in complexity when D increases. Comparison with the delayed mixture Kalman filtering (D-MKF) technique shows that the SDD-KE algorithm provides important performance and complexity advantages.