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  • 學位論文

LDPC碼之信息傳遞解碼演算法—調適性選擇位元節點之分析

Message Passing Decoding Algorithm of LDPC Codes—Analysis of Adaptively Selecting Bit Nodes

指導教授 : 賀嘉律
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摘要


LDPC(Low-Density Parity-Check)碼為下個世代的先進通訊標準所採用的錯誤更正碼,其優異的錯誤更正能力可以逼近Shannon的理論值,配合訊息傳遞(Message Passing , MP)演算法,可以快速得到傳送端所發出的訊息,雖然該演算法在解碼方面有很好的效能,但因為其複雜度偏高,所以,很多研究都在探討如何改善複雜度,又不會使其效能嚴重的衰減。在本論文中,基於和積演算法(Sum-Product algorithm , SPA)為軟式解碼法中最佳的解碼演算法,而針對此解碼法提出三種不同疊代分配的方式來做分析,調適的選擇出部份位元節點來替代所有的位元節點,減少其運算量,在疊代解碼失敗時,依所分配的疊代次數,增加位元節點的運算來更新檢查節點,其在最後幾次疊代時將回歸至Sum-Product演算法,有效的降低運算複雜度,在效能上也沒有嚴重的衰減。

並列摘要


LDPC code is an error-correcting code which is adopted for the next generation''s advanced communication standard. Its error-correcting ability may approach the Shannon’s theoretical value. With the MP algorithm, it can decode received samples in high speed from transmitter. This algorithm has a good performance in the decoding aspect, but its complexity is higher. Thus, many researchers discuss how to improve complexity without making the performance reduced seriously. In this thesis, the SPA(Sum-Product algorithm) is the best decoding algorithm in soft-decoding to aim at this decoding method which proposes three different ways in the distribution of iteration to do analysis. The method adjusts bit nodes to substitute all bit nodes, and reduces the quantity of operations. When the iteration decoding fails, we increase number of bit nodes and update the message of the check nodes according to the result of the iteration. Finally, its several iterations will return to Sum-Product algorithm. Therefore, it effectively reduces the complexity and without seriously weaken its performance.

並列關鍵字

Sum-Product algorithm LDPC Adaptive

參考文獻


[1] C. E. Shannon, “A Mathematical Theory of Communication,” Bell Syst. Tech. J., pp. 379-423(Part 1); pp. 623-56(Part 2), July 1948.
[2] R. G. Gallager, “Low-density parity-check codes,” IRE Trans. Inform. Theory, pp. 21-28, vol. 8, no. 1, Jan. 1962.
[3] R. G. Gallager, “Low-Density Parity-Check Codes,” MIT Press, Cambridge, MA, 1963.
[4] R. M. Tanner, “A recursive approach to low complexity codes,” IEEE Trans. Inform. Theory, vol. 74, no. 2, pp. 533-547, Sept. 1981.
[5] D. J. C. MacKay and R. M. Neal, “Near Shannon limit performance of low density parity check codes,” IEE Electron. Lett., vol. 32, no. 18, pp. 1645-1646, Aug. 1996.

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