Computationally Efficient Single-Frequency Estimation Scheme in High-Rate WPAN Systems

Sub-optimal algorithms that avoid the complexity of the maximum likelihood scheme for estimating a frequency offset have been developed based on samples of the estimated auto-correlation function. However, their computation burden is still heavy for near-optimal performance. To overcome this problem, this paper proposes a reduced-complexity algorithm of single-frequency estimation for a high-rate wireless personal area network application. Accuracy and robustness of our frequency estimator are statistically assessed by Monte Carlo simulations. The results indicate that the proposed complexity effective algorithm closely conforms to the Cramer-Rao bound.