A Maximum Likelihood Frequency Offset Estimation with Improved Rangeand Performance in OFDM Systems

Maximum Likelihood (ML) estimation of the frequency offset between the transmitter and the receiver from known transmitted preambles is the dominant technique for the estimation of Carrier Frequency Offset (CFO) in OFDM systems. A general formulation of ML detection problem for OFDM systems is provided in this paper and it is described how different ML techniques can be treated as special cases. In addition, major newly proposed ML techniques are compared in a unified simulation framework in the presence of AWGN and their performance in terms of estimation range and complexity is compared. Furthermore, we proposed two new preamble structures which have comparable complexity to the simplest available methods while their estimation ranges are fairly large, comparable to the largest achieved ranges.