近年來，正交時頻空間 (orthogonal time frequency space; OTFS) 調變技術受到很大的關注，因為其在高移動場景下比正交分頻多工 (orthogonal frequency division multiplexing; OFDM) 技術具有顯著的效能優勢。在本論文中，我們針對OTFS系統提出一種使用領航訊號輔助之新的參數通道估測方法，包含使用理想波形和使用方波兩種情況；所提出之方法能夠提供良好的延遲、整數都卜勒頻移、分數都卜勒頻移及多路徑增益參數估測值，以有效重建延遲-都卜勒域 (delay-Doppler domain; DD domain) 通道矩陣，進而用於接收端的資料偵測。在本方法中，延遲乃透過一預設門檻值而估得，整數都卜勒頻移是經由尋找接收訊號的最大值而決定，分數都卜勒頻移是利用線性回歸技巧和最小平方法而求得，至於多路徑增益參數則是根據所估測出的延遲、整數都普勒頻移、分數都卜勒頻移以及OTFS的輸入輸出關係式而計算出。為了驗證所提出之參數通道估測方法的有效性，我們呈現廣泛的電腦模擬結果；與使用相同領航訊號進行直接通道估測之基於預設門檻值的現有方法相比，所提出之方法僅略微增加運算複雜度，但具有明顯較佳的正規化均方誤差和位元錯誤率效能。

Orthogonal time frequency space (OTFS) modulation has received great attention in recent years because it offers significant advantages over orthogonal frequency division multiplexing (OFDM) under high-mobility scenarios. In this thesis, we propose a new pilot-aided parametric channel estimation scheme for OTFS systems, including the case using ideal waveforms and the case using rectangular waveforms. The proposed scheme is able to provide good estimates of the delay, integer Doppler shift, fractional Doppler shift, and multipath-gain parameters for reconstructing an effective delay-Doppler domain channel matrix to be used for data detection at the receiver. The delay is estimated by using a preset threshold, the integer Doppler shift is determined through finding the maximum value of received symbols, the fractional Doppler shift is found based on the linear regression technique and the least-squares method, and the multipath-gain parameters are calculated according to the estimated delay, integer Doppler shift, and fractional Doppler shift as well as the OTFS input-output relationship. To verify the effectiveness of the proposed parametric channel estimation scheme for OTFS systems, extensive computer simulation results are presented. As compared with a related threshold-based scheme using the same pilot for direct channel estimation, the proposed one achieves much better performance, in terms of the normalized mean-squared error and the bit error rate, with only a slight increase in the computational complexity.

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