EDA-78: A Novel Error Detection Algorithm for Lempel-Ziv-78 Compressed Data

Beom Kwon, Myongsik Gong, Sanghoon Lee

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents an error detection algorithm for Lempel-Ziv-78 (LZ78) compressed data. LZ78 data compression involves dictionary coding and aims to compress the original data without loss. For detecting bit errors in compressed data, methods such as parity bit and Hamming code approaches have been applied. However, in these conventional methods, the insertion of additional bits is required for error detection, increasing the data redundancy. For error detection of LZ78 compressed data, we introduced four unique properties of LZ78 compressed data and developed an algorithm that detects bit errors in LZ78 compressed data according to these properties, without the insertion of additional bits. The proposed algorithm, which is called EDA-78 (Error Detection Algorithm for LZ78 compressed data), achieved an error detection rate of nearly 100% in the case of six or more bit errors. However, when the number of bit errors was smaller than six, the error detection rate was degraded. To overcome this drawback, we employed parity bits, significantly improving the error detection rate for a small number of bits.

Original languageEnglish
Pages (from-to)2177-2189
Number of pages13
JournalWireless Personal Communications
Volume111
Issue number4
DOIs
Publication statusPublished - 2020 Apr 1

Bibliographical note

Funding Information:
This work was supported by the research fund of Signal Intelligence Research Center supervised by Defense Acquisition Program Administration and Agency for Defense Development of Korea.

Funding Information:
This work was supported by the research fund of Signal Intelligence Research Center supervised by Defense Acquisition Program Administration and Agency for Defense Development of Korea. 1 i is encoded using 4 bytes and c is encoded using 7 bits, according to the American Standard Code for Information Interchange (ASCII).

Publisher Copyright:
© 2019, Springer Science+Business Media, LLC, part of Springer Nature.

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

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