LDPC碼解碼運算量精簡之研究

本論文介紹多種不同類型的低密度同位檢查（LDPC）碼，並且提出了一種低複雜度的LDPC碼解碼算法。常規下的LDPC解碼算法是基於置信傳播（BF）解碼的演算法，該演算法會直到獲得了一個有效碼字，或者是疊代次數達到設定的次數，可計算出Tanner圖中的所有變數節點和所有檢查節點之間的訊息。然而，在疊代解碼過程中，一些概似比的對數（LLR）可能已經在最初的幾個疊代達到高可靠度的值。因此，高可靠度的節點的決策可被提前進行。表示此變量節點可以從該Tanner圖除去，因此對於後續的疊代解碼來說，節省了計算的複雜度。模擬的結果顯示，該LDPC解碼器的複雜性可降低30.77％，此外在過程中沒有顯著的性能損失。

關鍵字

訊息傳遞演算法；和積演算法；疊代解碼演算法；線性區段碼；低密度同位檢查碼

並列摘要

This thesis introduces various types of low-density parity check (LDPC) codes and proposes a low-complexity decoding algorithm for LDPC codes. Conventional LDPC decoding algorithm are based on the belief propagation (BF) decoding algorithm, which passes messages between all variable nodes and all check nodes in the Tanner graph until a valid codeword is obtained or the number of iterations reaches a predefined number. However, during the ierative decoding process, some log-likelihood ratios (LLR) of the variable nodes may already reach high reliability values during the first few iterations. Therefore, the hard decisions of the high reliable nodes can be made earlier. The variable nodes with hard desicisions can then be removed from the Tanner graph and hence save the computational compelxity for the subsequent iterative decoding. Simulation results show that the complexity of the LDPC decoder can be saved by 30.77% without significant performance loss.

並列關鍵字

iterative decoding algorithm ； linear block codes ； Low-density parity-check codes ； sum-product algorithm ； message passing algorithm

參考文獻

[1] 蕭志豪 Design of multi-code rate LDPC decoder for IEEE 802.16e standard

[2] D. J. C. MacKay and R. M. Neal. “Good codes based on very sparse matrices,”

Error-Correcting Coding and Decoding: Turbo Codes,” IEEE Proc. of the Intl.

[4] R. G. Gallager, “Low Density Parity-Check Codes,” IRE Trans. Inform. Theroy,

[5] J. Pearl, “Probabilistic Reasoning in Intelligent Systems: Networks of Plausible

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LDPC碼解碼運算量精簡之研究

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