隨著未來的通訊系統支持更高移動性之通訊場域，傳統的正交分頻多工系統在高都卜勒位移之情況下，其錯誤率表現由於受到時變通道的影響而大幅衰減。為了能在高速移動的環境中保持良好通訊品質，並且抵抗多重路徑干擾，因此有許多通訊技術被提出，當中包括正交時頻空間系統。正交時頻空間系統是一項新的二維調變技術，透過在延遲-都卜勒域產生調變的訊息符元並且轉換至頻率-時間域，使得每一個傳送符元都能在整個頻率與時間上擴展，達到最大有效分集。此外在延遲-都卜勒域上的時變通道響應具有稀疏性，並且能夠清楚描述環境中移動物體各自的通道參數資訊。
本論文針對墊零OTFS系統提出一種二階段的通道估測方法，其中使用基底擴展模型對時域通道響應進行建模，首先在第一階段採用最小平方法與線性最小均方誤差估測法估計基底擴展模型係數，之後再透過BEM係數重建出時變通道。由於在高速移動環境下，只有一階段通道估測的效能有限，因此本論文也參考文獻中所使用的偽導引演算法之構想，將其應用在第二階段的BEM最小平方估測法當中。此外為了降低逆矩陣求解的運算複雜度，本論文提出了基於區塊的通道估測方式。最後，本論文所提出的通道估測演算法在第一階段可以兼容文獻中所使用的低複雜度線性內插估測法，最終模擬結果顯示其位元錯誤率表現可以非常接近最佳的完美通道估測之情況。

The recently proposed orthogonal time frequency space (OTFS) scheme is a novel two-dimensional modulation technique that generates modulated information symbols in the delay-Doppler domain and then transforms them to the frequency-time domain. This allows each transmitted symbol to be spread across the entire frequency and time resources, achieving maximum effective diversity. Furthermore, the time-varying channel response in the delay-Doppler domain exhibits sparsity and can clearly describe the channel parameter information of each moving object in the environment. This thesis proposes a two-stage channel estimation method for zero-padding OTFS (ZP-OTFS) systems. The method utilizes a basis expansion model (BEM) to represent the time-domain channel response. In the first stage, the least squares (LS) and linear minimum mean square error (LMMSE) estimation methods are employed to estimate the BEM coefficients. Subsequently, the time-varying channel is reconstructed from these BEM coefficients. Given the limited performance of single-stage channel estimation in high-mobility environments, this thesis adopts the concept of the pseudo-pilot algorithm from the literature and applies it to the second-stage BEM least squares (BEM-LS) estimation. Additionally, to reduce the computational complexity of matrix inversion, we propose a block-based channel estimation method. Finally, the low-complexity linear interpolation estimation method in the literature can be adopted as the first stage of the two-stage estimation algorithm to significantly reduce the computational complexity. Simulation results demonstrate that the bit error rate (BER) performance of the proposed method can be very close to the perfect channel estimation case.

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