Carrier-frequency estimation for transmissions over selective channels

This paper deals with carrier-frequency estimation for burst transmissions over frequency-selective channels. Three estimation schemes are proposed, all based on the use of known training sequences. The first scheme employs an arbitrary sequence and provides joint maximum-likelihood (ML) estimates of the carrier frequency and the channel response. Its implementation complexity is relatively high but its accuracy achieves the Cramer-Rao bound. The second scheme is still based on the ML criterion, but the training sequence is periodic, which helps to reduce the computational load. The third scheme also employs periodic sequences, but its structure comes from heuristic reasoning. Theoretical analysis and simulations are employed to assess the performance of the three schemes.