在OFDMA系統中，實際傳送端與接收端的石英振盪器不匹配，或是相對運動所產生的都普勒效應，皆會導致載波頻率偏移的發生，進而使得系統性能下降，因此對其進行估計並補償有其必要性。本文採用基於訓練符號的方法來估計載波頻率偏移與通道。首先，根據基頻離散訊號系統模型推導出對數似然函數，並且針對待估計參數透過迭代的過程以網格搜尋方式找出估計值並更新參數，直到結果收斂為止。而本文提出以傳統頻域估計CFO演算法之結果作為初始值進行網格搜尋之迭代，以此加快收斂速度並能提高搜尋效率，根據模擬結果顯示本文中使用之演算法能接近CRLB (Cramer-Rao Lower Bound)，並改善了搜尋效率低的情形。

In practical OFDMA systems, frequency mismatch between the transmitter and receiver crystal oscillators or Doppler effect resulted from relative motion will lead to carrier frequency offset (CFO), resulting in the performance degradation. Hence, it is necessary to conduct the estimation and compensation processes. In this thesis, we estimate the carrier frequency offsets and the channel impulse response by adopting training symbol-based method. First, we derive log-likelihood function based on discrete-time baseband model. Then, execute grid-search over the interval spanned by trial values through an iterative process, and updating the parameter till the values converges. We propose to use the CFO estimates obtained by the conventional frequency-domain approach as the initial values and carry out grid-search iterations so that we can accelerate the rate of convergence and improve the search efficiency. According to the simulation results, the proposed method demonstrates the mean square error (MSE) performance is close to Cramer-Rao Lower Bound (CRLB); furthermore, it also ameliorates the search efficiency effectively.

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