Abstract
Orthogonal frequency-division multiple-access (OFDMA) has been adopted for next-generation broadband satellite and terrestrial wireless standards due to its robustness to the channel frequency-selectivity. In an OFDMA-based communication system, due to the presence of carrier-frequency-offset (CFO) that is induced by time-varying Doppler shift and oscillators' mismatch, the orthogonality of subcarriers cannot be guaranteed. Amongst the factors that cause phase-mismatch, CFO is one of the most challenging parameters to counteract, which gives rise to inter-carrier interference (ICI) and multiuser interference (MUI). In the last decade, this topic has received intensive investigations for single-user orthogonal frequency-division multiplexing (OFDM) or downlink OFDMA and not many works have been reported so far on the CFO estimation for uplink OFDMA which is the subject of research in this thesis. The major contributions of this thesis are in three folds summarised as follows. First, a blind CFO estimation scheme was proposed for a linearly precoded (LP)-OFDMA system. The major idea was to take advantage of time correlation induced by the linear precoder, which offered a second-order moments-based blind CFO estimation. The second scheme was motivated by the fact that the best linear unbiased estimator (BLUE) that is used for CFO estimation is very sensitive to the MUI. The objective of this scheme was to improve the robustness of BLUE in multiuser scenarios by proposing three appropriately designed training sequences, The third scheme was based on a training-based iterative concatenated CFO estimation and compensation algorithm. Our results showed that firstly, the class of training sequence designs could offer close performance to that of the single-user equivalent scenario. Secondly, the iterative algorithm showed significant improvement in CFO estimation and overall system performance after only one iteration. Finally, the blind scheme outperformed state-of-the-art blind methods in both single-user and multiuser scenarios.