Polar Coding with CRC-Aided List Decoding

2015 ◽  
Author(s):  
David Wasserman
Keyword(s):  
List Decoding ◽  
Polar Coding

scholarly journals List Decoding of Arıkan’s PAC Codes

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 841
Author(s):  
Hanwen Yao ◽  
Arman Fazeli ◽  
Alexander Vardy
Keyword(s):  
Superior Performance ◽  
Polar Codes ◽  
Dramatic Improvement ◽  
List Decoding ◽  
Sequential Decoding ◽  
Worst Case ◽  
Low Snr ◽  
Successive Cancellation ◽  
Polar Coding ◽  
Wide Range

Polar coding gives rise to the first explicit family of codes that provably achieve capacity with efficient encoding and decoding for a wide range of channels. However, its performance at short blocklengths under standard successive cancellation decoding is far from optimal. A well-known way to improve the performance of polar codes at short blocklengths is CRC precoding followed by successive-cancellation list decoding. This approach, along with various refinements thereof, has largely remained the state of the art in polar coding since it was introduced in 2011. Recently, Arıkan presented a new polar coding scheme, which he called polarization-adjusted convolutional (PAC) codes. At short blocklengths, such codes offer a dramatic improvement in performance as compared to CRC-aided list decoding of conventional polar codes. PAC codes are based primarily upon the following main ideas: replacing CRC codes with convolutional precoding (under appropriate rate profiling) and replacing list decoding by sequential decoding. One of our primary goals in this paper is to answer the following question: is sequential decoding essential for the superior performance of PAC codes? We show that similar performance can be achieved using list decoding when the list size L is moderately large (say, L⩾128). List decoding has distinct advantages over sequential decoding in certain scenarios, such as low-SNR regimes or situations where the worst-case complexity/latency is the primary constraint. Another objective is to provide some insights into the remarkable performance of PAC codes. We first observe that both sequential decoding and list decoding of PAC codes closely match ML decoding thereof. We then estimate the number of low weight codewords in PAC codes, and use these estimates to approximate the union bound on their performance. These results indicate that PAC codes are superior to both polar codes and Reed–Muller codes. We also consider random time-varying convolutional precoding for PAC codes, and observe that this scheme achieves the same superior performance with constraint length as low as ν=2.

Minimum-Combinations Set based Rate-1 Decoder for Fast List Decoding of Polar Codes

2021 ◽  
pp. 1-1
Author(s):  
Yanlong Zhao ◽  
Zhendong Yin ◽  
Zhilu Wu ◽  
Mingdong Xu
Keyword(s):  
Polar Codes ◽  
List Decoding

Study of network time synchronisation security strategy based on polar coding

2021 ◽  
Vol 104 ◽  
pp. 102214
Author(s):  
Ting He ◽  
Yong Zheng ◽  
Zherui Ma
Keyword(s):  
Security Strategy ◽  
Polar Coding ◽  
Network Time

Hybrid Bucket Sorting Method for Successive Cancellation List Decoding of Polar Codes

2019 ◽  
Vol 23 (10) ◽  
pp. 1757-1760
Author(s):  
Jiahao Wang ◽  
Zhenyu Hu ◽  
Ning An ◽  
Dunfan Ye
Keyword(s):  
Polar Codes ◽  
List Decoding ◽  
Sorting Method ◽  
Successive Cancellation

Analysis and Adaptive Design of Polar Coded HARQ Transmission Under SC-List Decoding

2017 ◽  
Vol 6 (6) ◽  
pp. 798-801 ◽  
Author(s):  
Hao Liang ◽  
Aijun Liu ◽  
Yingxian Zhang ◽  
Qingshuang Zhang
Keyword(s):  
Adaptive Design ◽  
List Decoding
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