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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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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 |
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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 |
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