通信系統很容易受到脈衝雜訊干擾，特別是當脈衝的統計特性隨時
間變化，且難以精確地建立模型。為了解決脈衝雜訊的挑戰，本論文提出
一個適用於具記憶效應的脈衝雜訊通道的強健且高效率的維特比（Viterbi）
和渦輪（Turbo）解碼方法。首先，此方法在不依賴脈衝的統計模型的前
提下，於任意連續的迴旋編碼狀態下擴展格狀態的概念，也就是說，考量
通道的記憶狀態（過渡機率），進而持用眾所皆知的維特比算法（VA）
來執行最大相似解碼（Maximum Likelihood Decoding）。此外，論文
詳述此類似維特比解碼，並由分析的結果強調出該方法與傳統的維特比算
法於效率上做比較。緊接著，我們也使用前述的概念，提出應用於馬爾可
夫高斯（Markov Gaussian）通道的強健渦輪解碼；適當的替代了提出之
VA 的二維網格圖所獲得的VA 分支量度（Branch Metrics）於渦輪解碼
器。
模擬結果指出，我們所提之維特比和渦輪解碼方式的非常地強健：
此解碼器的位元錯誤率（Bit Error Rate）效能非常接近使用脈衝統計資
訊的最佳譯碼器；此外，提出的維特比解碼器並與α-逞罰函數解碼器
（α- PFD）相比較。經由模擬的結果表示，提出的維特比解碼器比α-
PFD 來得優秀，因為在普遍的條件下α- PFD 忽略通道的記憶特性並因
此遭遇到無法壓低的錯誤率。相同的特徵也表現在本論文提出之強健型渦
輪解碼器：位元錯誤率效能與使用脈衝統計資訊的最佳譯碼器所演繹出的
結果非常接近。

Communication systems are susceptible to impulse noise, particularly when
the impulse statistics are not time-invariant and are difficult to accurately
model. To address the challenge of impulse noise, a robust and efficient Viterbi
and turbo decoding schemes were devised over memory impulse noise channels.
By accommodating channel states, but without relying on statistical knowledge
of impulses, the Viterbi algorithm (VA) based on an expanded set of trellis
states, was employed to perform maximum likelihood decoding. A detailed
analysis of complexity for the proposed Viterbi decoding was offered; the analytical
results reinforced the efficiency of the proposed scheme compared with
the traditional VA. We also proposed robust turbo decoding algorithm over a
Markov Gaussian channel. The branch metrics obtained from the two- dimensional
trellis diagram of the proposed VA was adapted to propose robust turbo
decoding scheme.
The simulation results indicated that the proposed Viterbi and turbo decoding
schemes are compellingly robust: the bit error probability performance
level attained using the proposed decoders is remarkably close to that of an
optimal decoder, which uses impulse statistics; furthermore, the proposed decoders
were compared with the alpha-penalty function decoder (alpha-PFD).
The reported result showed that the proposed decoders are superior to an
alpha-PFD because alpha-PFD neglects the channel memory property and experiences
an error floor, in fairly general circumstances.

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