Cargando…

Zero-Error Coding via Classical and Quantum Channels in Sensor Networks

Today’s sensor networks need robustness, security and efficiency with a high level of assurance. Error correction is an effective communicational technique that plays a critical role in maintaining robustness in informational transmission. The general way to tackle this problem is by using forward e...

Descripción completa

Detalles Bibliográficos
Autores principales: Yu, Wenbin, Xiong, Zijia, Dong, Zanqiang, Wang, Siyao, Li, Jingya, Liu, Gaoping, Liu, Alex X.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6928839/
https://www.ncbi.nlm.nih.gov/pubmed/31757066
http://dx.doi.org/10.3390/s19235071
_version_ 1783482565362974720
author Yu, Wenbin
Xiong, Zijia
Dong, Zanqiang
Wang, Siyao
Li, Jingya
Liu, Gaoping
Liu, Alex X.
author_facet Yu, Wenbin
Xiong, Zijia
Dong, Zanqiang
Wang, Siyao
Li, Jingya
Liu, Gaoping
Liu, Alex X.
author_sort Yu, Wenbin
collection PubMed
description Today’s sensor networks need robustness, security and efficiency with a high level of assurance. Error correction is an effective communicational technique that plays a critical role in maintaining robustness in informational transmission. The general way to tackle this problem is by using forward error correction (FEC) between two communication parties. However, by applying zero-error coding one can assure information fidelity while signals are transmitted in sensor networks. In this study, we investigate zero-error coding via both classical and quantum channels, which consist of n obfuscated symbols such as Shannon’s zero-error communication. As a contrast to the standard classical zero-error coding, which has a computational complexity of [Formula: see text] , a general approach is proposed herein to find zero-error codewords in the case of quantum channel. This method is based on a n-symbol obfuscation model and the matrix’s linear transformation, whose complexity dramatically decreases to [Formula: see text]. According to a comparison with classical zero-error coding, the quantum zero-error capacity of the proposed method has obvious advantages over its classical counterpart, as the zero-error capacity equals the rank of the quantum coefficient matrix. In particular, the channel capacity can reach n when the rank of coefficient matrix is full in the n-symbol multilateral obfuscation quantum channel, which cannot be reached in the classical case. Considering previous methods such as low density parity check code (LDPC), our work can provide a means of error-free communication through some typical channels. Especially in the quantum case, zero-error coding can reach both a high coding efficiency and large channel capacity, which can improve the robustness of communication in sensor networks.
format Online
Article
Text
id pubmed-6928839
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-69288392019-12-26 Zero-Error Coding via Classical and Quantum Channels in Sensor Networks Yu, Wenbin Xiong, Zijia Dong, Zanqiang Wang, Siyao Li, Jingya Liu, Gaoping Liu, Alex X. Sensors (Basel) Article Today’s sensor networks need robustness, security and efficiency with a high level of assurance. Error correction is an effective communicational technique that plays a critical role in maintaining robustness in informational transmission. The general way to tackle this problem is by using forward error correction (FEC) between two communication parties. However, by applying zero-error coding one can assure information fidelity while signals are transmitted in sensor networks. In this study, we investigate zero-error coding via both classical and quantum channels, which consist of n obfuscated symbols such as Shannon’s zero-error communication. As a contrast to the standard classical zero-error coding, which has a computational complexity of [Formula: see text] , a general approach is proposed herein to find zero-error codewords in the case of quantum channel. This method is based on a n-symbol obfuscation model and the matrix’s linear transformation, whose complexity dramatically decreases to [Formula: see text]. According to a comparison with classical zero-error coding, the quantum zero-error capacity of the proposed method has obvious advantages over its classical counterpart, as the zero-error capacity equals the rank of the quantum coefficient matrix. In particular, the channel capacity can reach n when the rank of coefficient matrix is full in the n-symbol multilateral obfuscation quantum channel, which cannot be reached in the classical case. Considering previous methods such as low density parity check code (LDPC), our work can provide a means of error-free communication through some typical channels. Especially in the quantum case, zero-error coding can reach both a high coding efficiency and large channel capacity, which can improve the robustness of communication in sensor networks. MDPI 2019-11-20 /pmc/articles/PMC6928839/ /pubmed/31757066 http://dx.doi.org/10.3390/s19235071 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yu, Wenbin
Xiong, Zijia
Dong, Zanqiang
Wang, Siyao
Li, Jingya
Liu, Gaoping
Liu, Alex X.
Zero-Error Coding via Classical and Quantum Channels in Sensor Networks
title Zero-Error Coding via Classical and Quantum Channels in Sensor Networks
title_full Zero-Error Coding via Classical and Quantum Channels in Sensor Networks
title_fullStr Zero-Error Coding via Classical and Quantum Channels in Sensor Networks
title_full_unstemmed Zero-Error Coding via Classical and Quantum Channels in Sensor Networks
title_short Zero-Error Coding via Classical and Quantum Channels in Sensor Networks
title_sort zero-error coding via classical and quantum channels in sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6928839/
https://www.ncbi.nlm.nih.gov/pubmed/31757066
http://dx.doi.org/10.3390/s19235071
work_keys_str_mv AT yuwenbin zeroerrorcodingviaclassicalandquantumchannelsinsensornetworks
AT xiongzijia zeroerrorcodingviaclassicalandquantumchannelsinsensornetworks
AT dongzanqiang zeroerrorcodingviaclassicalandquantumchannelsinsensornetworks
AT wangsiyao zeroerrorcodingviaclassicalandquantumchannelsinsensornetworks
AT lijingya zeroerrorcodingviaclassicalandquantumchannelsinsensornetworks
AT liugaoping zeroerrorcodingviaclassicalandquantumchannelsinsensornetworks
AT liualexx zeroerrorcodingviaclassicalandquantumchannelsinsensornetworks