Open AccessFast decoding for RaptorQ codes using matrix dimensionality reduction
Author(s) -
Guo Xiao,
Zhang GengXin,
Tian Chang,
Zhang Lei,
Zhao WengDong
Publication year - 2014
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2014.1381
Subject(s) - decoding methods , algorithm , parity check matrix , berlekamp–welch algorithm , sequential decoding , reduction (mathematics) , matrix (chemical analysis) , computer science , erasure , dimensionality reduction , overhead (engineering) , list decoding , erasure code , code (set theory) , curse of dimensionality , constraint (computer aided design) , mathematics , concatenated error correction code , block code , artificial intelligence , code word , set (abstract data type) , geometry , materials science , composite material , operating system , programming language
A very fast decoding algorithm using matrix dimensionality reduction for RaptorQ codes is proposed. The algorithm exploits a pre‐calculated inverse matrix to achieve dimensionality reduction for the received code constraint matrix. As a result, the decoding complexity is decreased significantly, whereas the failure‐overhead curve is still identical to that of conventional approaches. Simulations show that the decoding speed of the proposed algorithm can be as fast as 17.5 times the state‐of‐the‐art algorithm when the erasure probability is relatively low.