Class of cyclic-based estimators for frequency-offset estimation of OFDM systems

We present a new class of blind cyclic-based estimators for carrier frequency-offset and symbol-timing error estimation of orthogonal frequency-division multiplexing (OFDM) systems. The proposed approach exploits the properties of the cyclic prefix subset to reveal the synchronization parameters in the likelihood function of the received vector. A new likelihood function for the joint timing and frequency-offset estimation is derived, which globally characterizes the estimation problem. The resulting probabilistic measure is used to develop three classes of unbiased estimators, namely, maximum-likelihood, minimum variance unbiased, and moment estimator. In comparison to the previously proposed methods, the proposed estimators in this study are computationally and statistically efficient, which makes the estimators more attractive for real-time applications. The performance of the estimators is assessed by simulation for an OFDM system.