在無線通訊傳輸環境中，利用錯誤更正碼來修正通信可靠度的方法是不可或缺的。而渦輪碼用於遞迴性系統上已被證實對通道造成的錯誤訊息有重大的改善。在眾多渦輪解碼的演算法中，軟式輸出維特比演算法（SOVA）在複雜度的比較上遠低於其他解碼演算法，諸如：最大事後機率演算法（MAP）及一些由MAP轉變而來的演算法（Log-MAP, Max-Log-MAP）。然而，在效能上卻比其他演算法來的差。因此一些改善SOVA效能的技術相繼被提出。

在本篇論文中，我們首先探討兩種可以改善SOVA效能的方法。第一種是利用雙向式軟式輸出維特比演算法將前進式與後進式軟式輸出維特比演算法的輸出值作一結合。其效能更接近Max-Log-MAP甚至在某些訊雜比範圍優於Max-Log-MAP。而第二種方法是利用權重因子對軟式輸出維特比演算法的輸出值作正規化（Normalization）。而權重因子與輸出值的統計性質具有高度的相關性。因此，我們提出將正規化方法運用在雙向式軟式輸出維特比演算法。從效能分析上發現，經過正規化處理後的雙向式軟式輸出維特比演算法其效能優於Max-Log-MAP且更接近最佳的MAP演算法。

In wireless communications, error-correcting coding is indispensable for the channel reliability. Turbo codes with iterative decoding has been proposed as a powerful tool in correcting the errors incurred by the channel. Among the decoding algorithms of turbo codes, the Soft-output Viterbi Algorithm (SOVA) has the advantage of lower complexity compared with other decoding algorithms like Maximum A-Posteriori algorithm (MAP), Log-MAP, and Max-Log-MAP. However, the performance of SOVA is inferior to the family of MAP algorithms, and there are some modified schemes proposed to improve the performance of SOVA.

In this thesis, we first study two methods that could improve the performance of SOVA. The first method is the bi-directional SOVA (Bi-SOVA) algorithm that combines both soft-outputs from forward and backward SOVA. The performance of Bi-SOVA is more close to the Max-Log-MAP, even superior to it at some signal-to-noise ratio (SNR). Another method is a scheme that uses a scaling factor to normalize the soft-outputs in SOVA. The scaling factor is highly related to the statistic characteristics of the soft-outputs. Based on our study, we propose an algorithm that applies the normalization in Bi-SOVA. We find that the Bi-SOVA with normalization has performance superior to the Max-Log-MAP and more close to the optimal MAP.

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