Optimized Degree Distribution of Rateless Codes With Lower Complexity

被引：0

作者：

Yin, Junpeng ^{[1
,2
]}

Fu, Yusun ^{[3
,4
]}

Tang, Jinhui ^{[1
,2
]}

Huang, Haobo ^{[1
,2
]}

机构：

[1] Shanghai Jiao Tong Univ, Ningbo Artificial Intelligence Inst, Ningbo 315000, Peoples R China

[2] Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Shanghai 200240, Peoples R China

[3] Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Key Lab Syst Control & Informat Proc, Minist Educ China, Shanghai 200240, Peoples R China

[4] Shanghai Jiao Tong Univ, Shanghai Engn Res Ctr Intelligent Control & Manage, Shanghai 200240, Peoples R China

来源：

IEEE COMMUNICATIONS LETTERS | 2024年 / 28卷 / 03期

关键词：

Symbols; Decoding; Codes; Encoding; Complexity theory; Optimization; Fluctuations; Rateless codes; degree distribution; short codes; expected ripple size; age of information;

D O I：

10.1109/LCOMM.2024.3355431

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

The traditional degree distributions for the design of rateless codes do not perform well in latency and decoding success rate for short codes, and their encoding and decoding complexity is relatively high. This letter proposes an optimized degree distribution with lower encoding and decoding complexity. It keeps the average degree constant at a smaller value with the increasing of the source symbol length k , making the encoding and decoding complexity reduced and no longer grow exponentially with k . By increasing the mean of the ripple size, reducing its variance, and limiting the number of repeated degree-1 encoded symbols in the ripple, a convex optimization model is established and solved by Sequential Quadratic Programming. Simulation results show that compared with other degree distributions, the optimized degree distribution performs better in latency and decoding success rate for short codes and has lower encoding and decoding complexity.

引用

页码：458 / 462

页数：5

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