在本篇論文中，我們主要探討的是設計短碼長的低密度奇偶檢查( low density parity check , LDPC)的解碼演算法。一般來說，為了達到香農容量( Shannon capacity )必須使用長碼字( codelength )才能達到[12]，但是在應用上過長的碼字會造成過大的延遲( latency )，由於對於較短的碼長，傳統的置信傳遞( belief propagation)解碼演算法的解碼效能並不是很好，主要是因為短碼的LDPC會造成短迴圈導致置信傳播會出現問題。為了改善短碼長下的解碼效能的問題，我們提出了新的解碼方法，利用我們所提出的演算法來找出適合的停止集(Stopping set)，藉由選擇適當的停止集(Stopping set)來提高解碼效能，我們的模擬結果顯示出當使用5G標準URLLC下的低密度奇偶檢查碼時，我們所提出的演算法比起一般的置信傳遞的解碼效還更好，並且與先前改善停止集的演算法[3][5]做比較也能夠得到更好的結果，而且跟一般的置信傳遞法一樣，我們提出的演算法複雜度還是與碼長呈線性比例。

In this paper, we mainly discuss the design of short-code length low-density parity check (LDPC) decoding algorithm. Generally speaking, in order to achieve Shannon capacity, long codewords must be used to achieve [12], but the application of too long codewords will cause excessive delay (delay), due to the re-encoding The code length, the decoding performance of the traditional belief transfer (belief propagation) decoding algorithm is not very good, mainly because the short code LDPC will cause short loops and cause problems in placing the letter propagation. In order to improve the problem of decoding performance at short code lengths, we propose a new decoding method, using our proposed algorithm to find a suitable stop set (stop set), by selecting the appropriate stop set (stop set) To improve the decoding performance, our simulation results show that when using the low-density parity check code under the 5G standard URLLC, the proposed algorithm is better than the general decoding of the placement signal transmission, and it stops with the previous improvement. Compared with the set algorithm [3] [5], we can get better results, and like the general placement signal transmission method, the complexity of the algorithm we proposed is still linearly proportional to the code length.

參考文獻 (Reference)

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[14]3GPP TS 39.212 V16.1.0(2020-03)

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