Title: Fountain codes based on modulo and neural network

Authors: Zaihui Deng; Xiaojun Tong; Benshun Yi; Liangcai Gan

Addresses: College of Mathematics and Computer Science, Wuhan Textile University, Wuhan 430073, China ' College of Mathematics and Computer Science, Wuhan Textile University, Wuhan 430073, China ' Electronic Information School, Wuhan University, Wuhan 430072, China ' Electronic Information School, Wuhan University, Wuhan 430072, China

Abstract: In this paper, a new approach to fountain codes named Chinese transform (CT) codes is proposed. The encoding of CT codes transforms finite original symbols into theoretically infinite encoding symbols, which are generated by integers selected uniformly from the set of primes that are then enveloped into packets by a chaotic position scrambling algorithm. When a sufficient amount of packets are received, there is a 100% chance that the original symbols can be recovered by using the CT decoding algorithm. Using the improved Hopfield neural network to decode the CT codes can significantly increase efficiency and thus advancing the practical use of CT codes. The experiments in this paper demonstrate the feasibility and availability of the encoding and decoding of CT codes.

Keywords: fountain codes; Chinese transform codes; chaos theory; neural networks; encoding; decoding; modulo; chaotic position scrambling.

DOI: 10.1504/IJICT.2016.079960

International Journal of Information and Communication Technology, 2016 Vol.9 No.4, pp.463 - 472

Available online: 12 Oct 2016 *

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