Timing Synchronization for Fading Channels with Different Characterizations using Near ML Techniques

In this paper, we analyze the performance of a non-data aided near maximum likelihood (NDA-NML) estimator for symbol timing recovery in wireless communications. The performance of the estimator is evaluated for an additive noise only channel. Performance analysis is extended to fading channels characterized by Rayleigh fading, Weibull fading and log-normal fading, appropriate to a variety of transmission scenarios. The probability distribution of the maxima and probability distribution of timing estimates are derived, presented and compared with simulation results. The performance of the estimator is presented in terms of the bit error rate (BER) and the error variance of the estimates. The BER is computed when the estimator is operating under additive white Gaussian noise (AWGN) channel and fading channels. The variance of the estimates is computed for the noise only case and compared with the Cramer Rao bound (CRB) and modified Cramer Rao bound (MCRB).