本篇論文主要探討在多輸入多輸出正交分頻多工系統下之期望值最大化通道估測演算法。本論文主要分為二部分，在第一個部分為，我們假設演算法中所使用的通道脈衝響應之長度大於實際通道長度，因此原始期望值最大化通道估測的結果會含有多餘的雜訊而無法消除；為降低多餘雜訊的影響，提出在期望值最大化通道估測演算法中加入雜訊消除方法以增進效能。另外，當可利用的領航訊號數目增加時，通道估測之效能亦會隨之增加；所以在論文第二部分中，我們提出二維期望值最大化通道估測演算法，並分別考慮靜態通道與時變通道下討論演算法之效能。最後模擬結果顯示，期望值最大化通道估測加入雜訊消除方法後對於通道長度的精確度之效應較不敏感；二維期望值最大化通道估測不論在靜態通道或時變通道下皆能有效提升效能。

In this thesis, expectation-maximization (EM) channel estimation algorithms for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems are investigated. This work can be mainly divided into two parts. In the first part, the condition that the channel length used in algorithms is greater than the real channel length is assumed and thus channel impulse response (CIR) estimated by the original EM algorithms may contain extra noise components which cannot be completely eliminated. To mitigate the effects of these noise components, a noise reduction method is proposed to increase the performance. Moreover, since the performance can be increased when more useful pilot symbols are applied, a two-dimension EM channel estimation method is proposed in the second part of this thesis. Simulation results show that the EM channel estimation with the proposed noise reduction method is insensitive to the effects of inaccurate channel length. Additionally, the proposed two-dimension EM channel estimation method also has better performance under static or time-varying channel environments.

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