Improved pilot symbol aided estimation of Rayleigh fading channels with unknown autocorrelation statistics

New pragmatic pilot symbol assisted modulation (PSAM) techniques are proposed for the accurate estimation of time-selective Rayleigh fading channels. Unlike the optimal Wiener approach, the suggested techniques do not rely on knowledge of the fading autocorrelation function, and yet are shown to provide near-optimum channel estimation performance. While simple PSAM estimators published in the literature may appear to match this claim, we demonstrate that the gap in terms of estimation mean-squared error between existing techniques, which do not rely on the channel statistics, and the optimum Wiener estimator is about an entire order of magnitude for small Doppler rates. This gap is significantly reduced by employing estimators which operate with partial knowledge of the channel statistics. Moreover, we develop two novel channel interpolation methods which can exploit estimates of the Doppler frequency and, optionally, the channel SNR. The accuracies of the developed estimators are characterized and compared to those of existing suboptimal PSAM approaches. We demonstrate that the proposed estimators provide significant performance gains for slow fading scenarios. For example, a gain of approximately 2.5 dB in SNR is found for BPSK error rate calculations and simulations in channels with a normalized Doppler rate of 0.005.