在這篇論文中我們提出一個能有效估測軟式輸入輸出解碼器的額外相互資訊的方法，此方法能夠能利用軟式輸入輸出檢測器給的事前相互資訊與對數概似比數值的變異數來更準確地估測軟式輸入輸出解碼器的額外相互資訊，利用此方法，我們可以在多輸入多輸出系統中為軟式輸入輸出檢測器中選擇出最佳的內部遞迴次數，其中軟式輸入輸出檢測器是基於將接收端接收到的訊號看成高斯複數隨機變數，該方法有效地解決當軟式輸入輸出檢測器做內部遞迴時，會因為內部遞迴次數變多而使得效能變差的情況。我們基於這種方法提出兩種演算法，並用將此方法用在連續干擾消除的最小均方誤差的軟式輸入輸出檢測器以使得效能提升，第一種方法：利用估測軟式輸入輸出解碼器的額外相互資訊來選擇最佳的軟式輸入輸出檢測器的內部遞迴次數，這種方法能夠有效地提高效能；而第二種方法：利用計算不同內部遞迴的對數概似比數值的平均值與變異數之間的變化關係來選擇最適合的內部遞迴次數，儘管第二種方法也可以提高效能，但與第一種方法相比還是會有些差距，不過第二種方法可以以較低的複雜度來實現。

This thesis proposes a method to estimate extrinsic mutual information of the soft-in soft-out (SISO) decoder, where the a priori mutual information given by SISO detector, more accurately. Using the method, we select the best number of iterations of SISO detector for multiple-input multiple-output (MIMO) communication systems. The SISO detector is based on the assumption that the received signal has a joint complex Gaussian probability density function (PDF). This method solves the situation that the iterative SISO detectors will be worse when the number of iterations increasing. We also propose two algorithms based on our proposed method to improve the performance of minimum mean-square error with soft interference cancellation (MMSE-SIC) SISO detector, which is the most commonly used detection algorithm. The first method is selecting the best number of iterations by estimating the extrinsic mutual information and it provides a great improvement in performance. The second method is selecting the suitable number of iterations by calculating the relationship between the mean and variance of log-likelihood ratios (LLR) values of different iterations. Although the performance of second method is not as good as the first method, the second method is abler to achieve in the implementation with lower complexity.

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