Symbol timing estimation using near ML techniques and statistical performance evaluation for binary communications

In this paper, we analyze the performance of a non-data aided near maximum likelihood (NDA-NML) estimator for symbol timing recovery in binary digital communications. The analysis of the estimator is performed for an additive noise only channel and the simulation results are extended to a flat fading channel. The probability distribution of the timing estimates is 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 Rayleigh fading channel. 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).