Volume 6, Issue 1, March 2018, Page: 25-29
RNS Based on Shannon Fano Coding for Data Encoding and Decoding Using {2n-1, 2n, 2n+1} Moduli Sets
Idris Abiodun Aremu, Computer Science Department, Lagos State Polytechnics, Lagos, Nigeria
Kazeem Alagbe Gbolagade, Department of Computer Science, Kwara State University, Kwara, Nigeria
Received: Jan. 23, 2018;       Accepted: Feb. 1, 2018;       Published: Mar. 16, 2018
DOI: 10.11648/j.com.20180601.15      View  664      Downloads  23
Abstract
The main objective of any communication system is to transmit data with minimum error rate in data communication. This paper presents information encryption and decryption in data communication with Shannon fano compression techniques using Residue Number System (RNS). The current network communication system involves exchange of information with highly secured data and reduction in both the space requirement and speed for data storage and transmission. For this purpose error detection and correction techniques are used, Our proposed scheme uses the Chinese Remainder Theorem (CRT) which are smaller and needs to be performed in parallel, therefore from the first decoding we can easily identify if error is in a channel. The algorithm applies CRT to detect, locate and correct error by eliminating look up table, therefore the scheme provides a memory less based scheme. It uses a pipelining approach to breakdown the problem with a level of complexity O(n) after decoding and performing consistent checks on all the residue, therefore the overall delay will be lesser and efficient.
Keywords
Shannon Fano, Residue Number System, Forward Conversion, Information Encryption and Decryption, Mixed Radix Conversion
To cite this article
Idris Abiodun Aremu, Kazeem Alagbe Gbolagade, RNS Based on Shannon Fano Coding for Data Encoding and Decoding Using {2n-1, 2n, 2n+1} Moduli Sets, Communications. Vol. 6, No. 1, 2018, pp. 25-29. doi: 10.11648/j.com.20180601.15
Copyright
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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