Error detection algorithm for Lempel-Ziv-77 compressed data

Beom Kwon, Sanghoon Lee

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


In this study, we develop a novel error detection algorithm for Lempel-Ziv-77 (LZ77) compressed data. In the proposed algorithm, additional bits are not used to detect bit errors, unlike in conventional methods such as checksum, cyclic redundancy check, Hamming code, and repetition code. We also introduce eight special features of LZ77-compressed data for detecting the presence of errors. We demonstrate the feasibility of the algorithm based on simulations and evaluate it using two publicly available databases comprising the Calgary and Canterbury corpora. The error detection rate using the proposed algorithm is below those of conventional methods, but the compression ratio is better. The application of a parity bit in the algorithm improves the error detection performance. The number of redundant bits increases owing to the insertion of the parity bit, but the code rate is still greater than or equal to 0.9, whereas conventional methods obtain code rates less than 0.9. Simulations demonstrate that the algorithm obtains significant performance improvements when a parity bit is periodically inserted. In particular, we achieve an error detection rate of 100% using the parity bit when the number of bit errors is greater than seven.

Original languageEnglish
Article number8718090
Pages (from-to)100-112
Number of pages13
JournalJournal of Communications and Networks
Issue number2
Publication statusPublished - 2019 Apr

Bibliographical note

Funding Information:
Manuscript received August 29, 2018; approved for publication by Sang-Hyo Kim, Division I Editor, March 1, 2019. 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. B. Kwon and S. Lee are with the Department of Electrical and Electronic Engineering, Yonsei University, email: {hsm260, slee} S. Lee is the corresponding author. Digital Object Identifier: 10.1109/JCN.2019.000021

Publisher Copyright:
© 2011 KICS.

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Networks and Communications


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