渦輪碼是用於改進通信可靠度的最強大錯誤控制碼之一。為了去解這樣的碼，維特比演算法藉由導入軟式值去修正以適合去解碼遞歸系統性迴旋碼。這個改進過的維特比演算法稱作軟式輸出維特比演算法(SOVA)。與最大事後機率演算法(MAP)比較，SOVA的優點就是提供了低複雜性的解碼器。然而，SOVA的效能卻不如MAP演算法。

　　爲了改善SOVA效能，在這篇論文裡，一個新的權重參數被導入SOVA內。它與在格子區段內發生的最好的路徑的機率有關。藉由模擬，我們將證明這個修正可以改善原先SOVA的效能。

　　Turbo codes are among the most powerful error-correcting codes for improving the communication reliability. To decode such codes, the Viterbi algorithm was modified by introducing the soft values to be suitable for decoding recursive systematic convolutional codes. The modified Viterbi algorithm is referred to as the Soft-Output Viterbi algorithm (SOVA). Comparing with the Maximum A-Posteriori Probability algorithm (MAP), the advantage of the SOVA is providing a low complexity decoder. However, the performance of the SOVA is inferior to the MAP algorithm.

　　In order to improve the performance of the SOVA, in this thesis, a new weighting parameter is introduced for the SOVA. It is associated with the probability of the best path occurring in the trellis. By the simulation, we will show that this modification can improve the performance of the original SOVA.

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