標題: 適用於最小和重組LDPC解碼演算法之補償技術
Compensation Technique of Min-Sum Shuffled LDPC decoding algorithm
作者: 陳美宇
Mei -Yu Chen
劉志尉
Chih-Wei Liu
電機學院IC設計產業專班
關鍵字: 低密度同位檢查碼解碼演算法之補償技術;LDPC
公開日期: 2008
摘要: Shuffled BP(belief propagation) algorithm是一種低密度同位檢查碼(low density parity check,LDPC)的解碼演算法,它的解碼錯誤更正效能高而且解碼遞迴次數收斂快。由於shuffled BP algorithm使用了非線性的計算,使得硬體的設計變得十分複雜。針對這個問題,設計者常使用最小項來近似此種複雜的非線性運算,以簡化硬體,此演算法稱為min-sum shuffled BP algorithm。然而,min-sum shuffled BP algorithm雖然達到硬體簡化的目的,卻造成解碼錯誤更正效能的下降。為了解決這個問題,本論文探討對min-sum shuffled BP algorithm的補償技術,包括了一維,二維 normalization、或offset之靜態補償方法,以及動態補償技術等,希望藉由補償技術將min-sum shuffled BP algorithm的編碼增益修正,使其達到與傳統的shuffled BP algorithm一樣好的效能。我們以IEEE 802.11n系統做模擬實驗,模擬結果顯示,經過補償後的compensated min-sum shuffled BP algorithm,不但保有硬體簡化的特性,其解碼錯誤更正效能也十分接近傳統的shuffled BP algorithm。
Shuffled belief propagation (BP) algorithm for the decoding of low-density parity-check (LDPC) codes achieves a remarkable error performance and fast convergence. Nevertheless, it seems to be too complex for hardware implementation. The shuffled BP algorithm can be simplified by using the min-sum approximation, namely the min-sum shuffled BP algorithm; however, the min-sum shuffled BP algorithm suffers from remarkable performance degradation. In this thesis, to solve this problem, we explore some compensation techniques for the min-sum shuffled BP algorithm, including 1D-, 2D-normalization/-offset static schemes and the dynamic scaling approach. Simulations show that the compensated min-sum shuffled BP algorithm achieves the performance very close to that of the original shuffled BP algorithm in IEEE 802.11n system.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT009395533
http://hdl.handle.net/11536/80366
顯示於類別:畢業論文


文件中的檔案:

  1. 553302.pdf