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

  • Authors:

  • Usa Vilaipornsawai;Harry Leib

  • Affiliations:

  • Department of Electrical & Computer Engineering, McGill University, Montreal, Quebec, Canada;Department of Electrical & Computer Engineering, McGill University, Montreal, Quebec, Canada

  • Venue:
  • IEEE Transactions on Communications
  • Year:
  • 2009

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Abstract

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.