Iterative channel estimation and equalization of STBC-OFDM system over time-varying ISI channels
SPPRA'06 Proceedings of the 24th IASTED international conference on Signal processing, pattern recognition, and applications
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In multiple input multiple output systems (MIMO), the increase in the number of channel parameters, renders less reliable conventional training based schemes. For a reasonable performance, conventional training based methods require a larger number of training symbols which reduces system bandwidth efficiency. In this paper, a semiblind channel estimation and tracking technique is proposed for concatenated turbo codes (TC) with space-time and frequency block codes (STFBC) over time-varying Rayleigh fading channels. The paper describes an effective approach to reduce the number of training symbols to half by implementing the Kalman filter (KF) with the constant modulus algorithm (CMA). Computer simulations show good estimation and tracking by the Kalman filter and CMA with only few training symbols (less than 7% of bandwidth efficiency loss) even when signals experience deep fades. The proposed method is shown to obtain fast channel estimation and tracking which is a requirement in fast fading channels.