IEEE Transactions on Signal Processing
ML estimation of time and frequency offset in OFDM systems
IEEE Transactions on Signal Processing
Optimal training for block transmissions over doubly selective wireless fading channels
IEEE Transactions on Signal Processing
Wireless Personal Communications: An International Journal
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This paper introduces a novel method to estimate fractional carrier frequency offset (CFO) under time-varying multipath channels in OFDM systems based on the approximation of Basis Expansion Model (BEM). Due to the symmetrical character of the BEM basis, we propose a new design of training sequence with trailing zeros. This training sequence can be used at the receiver to estimate the frequency offset without channel estimation only in one OFDM symbol. We also compare our method with Beek's ML estimator and Lv's fine synchronization estimator. The numerical results demonstrate that the proposed method provides an improved performance when the training sequence has a short length.