arrow
Return

Fast degree-distribution optimization for BATS codes

delete2017-07-04
delete2
PRE
AI
H
Huakai Zhao
S
Shenghao Yang *
G
Guinian Feng
DOI:10.1007/s11432-016-9011-8delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Batched sparse (BATS) codes have been proposed for communication through networks with packet loss. BATS codes include a matrix generalization of fountain codes as the outer code and random linear network coding at the intermediate network nodes as the inner code. BATS codes, however, do not possess a universal degree distribution that achieves an optimal rate for any distribution of the transfer matrix ranks. Therefore, it is important to have a fast degree-distribution optimization approach for finite-length BATS codes. In this paper, we propose the concept of batch release probability (BRP), and demonstrate some characteristics of BRPs from the degree distributions achieving nearly optimal performance. Based on these BRP characteristics, we propose a novel degree-distribution optimization approach that achieves the similar decoding performance with a much shorter optimization time, compared with the previous approach. Moreover, the universality of BRPs observed in this paper can further simplify the degree-distribution optimization of BATS codes.
Keywords:
network coding
batched sparse (BATS) code
finite-length analysis
degree distribution
batch release probability
optimization
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Science China Information Sciences cover
Science China Information Sciences
IF:
7.6
Papers:
4.9K
Citations:
8.9K

Organization

T
The Chinese University of Hong Kong, Shenzhen
Scholars:
4.3K
Papers: 4.0K
Citations: 7