Analytical and experimental studies on carrier frequency offset estimation algorithms for OFDM systems

In this paper, we perform numerical and experimental studies on preamble based nonlinear least squares (NLS) and maximum likelihood estimation (MLE) algorithms used for carrier frequency offset estimation in orthogonal frequency division multiplexing (OFDM) communication systems. Further, a reduced complexity data aided nonlinear least squares (NLS) algorithm for carrier frequency offset estimation is proposed. The estimator uses the short symbols in the preamble field for estimating the carrier frequency offset. The proposed NLS estimator is also the maximum likelihood estimator (MLE) when the additive noise is white and Gaussian. The estimator maintains estimation accuracy and offers the widest estimation range. The mean square error performance of the algorithm is compared against other preamble based NLS and MLE algorithms under several practical scenarios. The simulation results are verified using the data obtained from Stevens wireless testbed.