單載波分頻多重存取系統於嚴重之頻率選擇性衰減通道下，混和式決策回授等化器雖能消除符號間干擾，但會受到錯誤蔓延影響。本論文中，我們使用混和式雙重決策回授等化器以降低混和式決策回授等化器之錯誤蔓延效應。其做法為先找出決策錯誤機率高之決策前信號，並將其所對應之兩種最有可能的決策值於不同之決策回授器分別運作一段時間後，獲得之兩組決策信號也納入考慮，才對整組信號做出最佳之決策。模擬結果顯示混和式雙重決策回授等化器之效能比混和式決策回授等化器之效能佳。

為了使接收端於信號處理時更接近實際之情形，因此將混和式雙重決策回授等化器結合兩種通道估測技術，分別為最小平方法與線性最小均方誤差法。模擬結果顯示線性最小均方誤差法之效能比最小平方法之效能佳，且與通道為完美估測之效能差距很小。但使用線性最小均方誤差法時，須知道通道之功率延遲分布，且其複雜度相當高。

In severe frequency-selective fading channels, the performance of the hybrid decision feedback equalizer
(H-DFE) in single-carrier frequency division multiple access (SC-FDMA) systems is somewhat limited because of error propagation. In the thesis, we use the hybrid dual decision feedback equalizer (H-DDFE) to mitigate the error propagation effect of the H-DFE. First, the decision variables that are deemed prone to errors are identified. Then, the two most probable decisions associated with the given decision variable are retained and used to separately drive two independently operated decision feedback equalizers (DFEs) for a certain period of times, resulting in two sequences of decisions. In the end, the better sequence of the two is chosen. Simulation results show that the H-DDFE has the better performance than the H-DFE with only a modest increase in complexity.

In addition, we investigate the impact of imperfect channel estimation, e.g., least squares (LS) and linear minimum mean square error (LMMSE) channel estimation techniques, on the equalizer performance. Simulation results show that the equalizer with the LMMSE channel estimation has the better performance than that with the LS method, and performs very closely to that with the perfect channel estimates. But the LMMSE channel estimator has a higher complexity and requires the knowledge of the channel’s power delay profile.

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