An Iterative ML-Based Algorithm for the Joint Estimation of Carrier Frequency Offset, Channel Impulse Response and Data in OFDM Transmissions

This paper provides an approximate closed form solution to the problem of data-aided joint maximum likelihood estimation of the carrier frequency offset and of the channel impulse response in an Orthogonal Frequency Division Multiplexing transmission over a multipath fading channel. This results in a novel data-aided feedforward estimator, that can be employed for pilot-based receiver training. It is also shown how the novel joint estimation strategy can be exploited in an iterative (turbo) receiver structure to track the fast channel and frequency offset changes occurring during the transmission of information symbols. The performance of this structure is assessed by computer simulations and is compared with that provided by other estimation/detection strategies.