Iterative maximum-likelihood sequence estimation for space-time coded systems

In recent work on decoding space-time codes, it is either assumed that perf ect channel state information (CSI) is present, or a channel estimate is ob tained using pilot symbols and then used as if it were perfect to extract s ymbol estimates, In the latter case, a loss in performance is incurred, sin ce the resulting overall receiver is not optimal. In this letter we look at maximum-likelihood (ML) sequence estimation for space-time coded systems w ithout assuming CSI, The log-likelihood function is presented for both quas i-static and nonstatic fading channels, and an expectation-maximization (EM )-based algorithm is introduced for producing ML data estimates, whose comp lexity is much smaller than a direct evaluation of the log-likelihood funct ion. Simulation results indicate the EM-based algorithm achieves a performa nce close to that of a receiver which knows the channel perfectly.