Residual frequency offset correction for coherently modulated OFDM systems in wireless communication

Abstract—Orthogonal Frequency Division Multiplex (OFDM) systems are very sensitive to frequency offset caused by tuning oscillator instabilities and Doppler shifts induced by the channel. The Schmidl and Cox Algorithm (SCA) is quite robust in estimating the frequency offset for systems with large OFDM symbol lengths. It uses two OFDM symbols for training with the first one having two identical halves. The frequency offset is estimated by correlating a received sequence of samples equal to half the OFDM symbol length with the following received samples. The effect of Additive White Gaussian Noise (AWGN) in the estimation process is mitigated only if the number of samples used in the correlation, and hence the OFDM symbol size is large. However to be successfully applied to Broadband Fixed Wireless Access (BFWA) systems, OFDM should perform well even with smaller symbol lengths. In this paper we present the Residual Frequency Offset Correction Algorithm (RFOCA), which uses the SCA for initial frequency offset acquisition and follows it with a stage which reduces the initial residual frequency offset by tracking the phase of the decoded data. We show through simulation that the RFOCA achieves an error variance that is many orders of magnitude lower than at the end of the acquisition stage using the SCA alone.