On The Design Of Joint CFO And Channel Estimation For Fast Time-Varying MIMO-OFDM System

With the development of wireless communication, the fast increase in demand for high spectrum efficiency, high data rate and larger system capacity impose new challenge to the wireless communication design. MIMO and OFDM techniques provide promising solution to the aforementioned problems. Nonetheless, they also bring about some new problems. For example, OFDM system is very sensitive to carrier frequency offset (CFO) when compared with the single carrier system, the inter-carrier interference (ICI) caused by CFO will lead to serious performance degradation for OFDM system. Therefore, frequency synchronization is a key technique in OFDM system. At the same time, if we want to restore the data transmitted, channel estimation quality becomes important, especially over the complicated time-varying multipath delay and Doppler spread owing to the high mobility in the wireless communication. We may even say that, the channel estimation technique will dominate the achieved performance of wireless communication over fast time-varying channel. The objective of this thesis is to analyze the existing joint CFO and channel estimation algorithms in MIMO OFDM system over fast time-varying environment at first, and then to propose some promising techniques to improve the performance of CFO and channel estimation.The basic principles of MIMO and OFDM techniques will be firstly reviewed. Then effect of CFO on MIMO OFDM system will be highlighted. Meanwhile, the channel identificability problem is addressed as well to introduce the Basis Expansion Model over the fast time-varying scenario. It is shown through the analysis of the effect of CFO on channel estimation that if we want to improve the performance of channel estimation, we can start from improving the CFO estimation performance. The BEM based CFO and channel estimation algorithms under the situation of fast time-varying environment are introduced and compared in both the time and frequency domain system model. These algorithms include the maximum likelihood estimate, the Bayesian estimate, the Extended Kalman Filter and the EM estimate algorithm. The involved Cramer-Rao Bound (CRB) analyses are presented and all the above exsting algorithms are compared with the CRB to unveil the achieved estimate performance.Motivated by the challenges over the fast time-varying environment, three new schemes are investigated for the joint estimation of CFO and channel in MIMO OFDM system. Firstly, it is shown that the joint using of successive pilot symbols will give rise to the improved CFO and channel estimation. Simulation results are presented to validate that, with the increase number of pilots utilized, we may have better CFO and channel estimation performance. Secondly, the joint estimate scheme based on the modified measurement signal is proposed. It is shown that the modified received signal based ML estimation can achieve almost the same performance as the traditional ML estimate scheme, and the idea can be incorporated into the previous one for the improved joint estimation of CFO and channel. Lastly, the CFO estimation in the time domain combined with Kalman Filter (KF) in the frequency domain for the channel estimate is studied, our simulation results also reveal improved estimation performance.Finally, the paper addresses the joint estimation of multiple CFOs and fast time-varying channel for the MIMO OFDM system. Some of the existing algorithms for multiple CFOs estimation are outlined and simulated. Then the joint using of successive pilot symbols is utilized to improve the EKF based joint estimate of multiple CFOs and fast time-varying channel. Simulation results corroborate the improvement of the proposed schemes.