An analytical approach to space-time block coding with decision feedback channel estimation

Abstract

We consider a space-time block coded system having L time slots and using decision feedback channel estimation with a finite window size. The channel matrix estimate is updated every L time slots by: 1) a least-squares (LS) estimate and 2) a minimum mean-square error (MMSE) estimate. Using a Markov model of the decision process, we analyze the decoding error probability (DEP) of this scheme in Rayleigh fading. The transition probability matrix is obtained by simulation of the decision process for a system using the Alamouti code. From this matrix, the DEP can be computed for any time shift. We find from computations that the DEP increases with increase in the time shift but tends to saturate with time to a steady-state value. It is also observed that both the state and the transition probabilities tend to saturate with the increase in average signal-to-noise ratio per diversity branch.