The University of Southampton
University of Southampton Institutional Repository

Research Data: Entanglement-Assisted Classical Communication Over Quantum Channels for Binary Markov Sources

Research Data: Entanglement-Assisted Classical Communication Over Quantum Channels for Binary Markov Sources
Research Data: Entanglement-Assisted Classical Communication Over Quantum Channels for Binary Markov Sources
Dataset supports: Izhar, A., Babar, Z., Ng, S., & Hanzo, L. (2017). Entanglement-Assisted Classical Communication Over Quantum Channels for Binary Markov Sources. IEEE Transactions on Vehicular Technology. Symbol-based iterative decoding is proposed for the transmission of classical Markov source signals over a quantum channel using a three-stage serial concatenation of a convolutional code (CC), a unity-rate code and a two-qubit superdense (SD) protocol. A modified symbol-based maximum a posteriori algorithm is employed for CC decoding to exploit the Markov source statistics during the iterative decoding process. Extrinsic information transfer chart analysis is performed to evaluate the benefit of the extrinsic mutual information gleaned from the CC decoder for sources with different correlations. We evaluate the bit error rate performance of the proposed coding scheme and compare it to the relevant benchmark schemes, including the turbo coding-based SD scheme. We demonstrate that a near capacity performance can be achieved using the proposed scheme and when utilizing sources having a high correlation coefficient of \rho = 0.9, the proposed coding scheme performs within 0.53 dB from the entanglement-assisted classical capacity.
Entanglement-assisted classical communication, superdense coding, joint source-channel coding, source-assisted channel decoding, iterative decoding
University of Southampton
Izhar, Azri
896a2c9d-4eee-4ede-8306-5f7bd9b23789
Babar, Zunaira
23ede793-1796-449d-b5aa-93a297e5677a
Ng, Soon Xin
e19a63b0-0f12-4591-ab5f-554820d5f78c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Izhar, Azri
896a2c9d-4eee-4ede-8306-5f7bd9b23789
Babar, Zunaira
23ede793-1796-449d-b5aa-93a297e5677a
Ng, Soon Xin
e19a63b0-0f12-4591-ab5f-554820d5f78c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Izhar, Azri, Babar, Zunaira, Ng, Soon Xin and Hanzo, Lajos (2017) Research Data: Entanglement-Assisted Classical Communication Over Quantum Channels for Binary Markov Sources. University of Southampton doi:10.5258/SOTON/D0342 [Dataset]

Record type: Dataset

Abstract

Dataset supports: Izhar, A., Babar, Z., Ng, S., & Hanzo, L. (2017). Entanglement-Assisted Classical Communication Over Quantum Channels for Binary Markov Sources. IEEE Transactions on Vehicular Technology. Symbol-based iterative decoding is proposed for the transmission of classical Markov source signals over a quantum channel using a three-stage serial concatenation of a convolutional code (CC), a unity-rate code and a two-qubit superdense (SD) protocol. A modified symbol-based maximum a posteriori algorithm is employed for CC decoding to exploit the Markov source statistics during the iterative decoding process. Extrinsic information transfer chart analysis is performed to evaluate the benefit of the extrinsic mutual information gleaned from the CC decoder for sources with different correlations. We evaluate the bit error rate performance of the proposed coding scheme and compare it to the relevant benchmark schemes, including the turbo coding-based SD scheme. We demonstrate that a near capacity performance can be achieved using the proposed scheme and when utilizing sources having a high correlation coefficient of \rho = 0.9, the proposed coding scheme performs within 0.53 dB from the entanglement-assisted classical capacity.

Archive
Figures_matlab.zip - Dataset
Available under License Creative Commons Attribution.
Download (227kB)
Text
Readme.txt - Text
Available under License Creative Commons Attribution.
Download (3kB)

More information

Published date: 2017
Keywords: Entanglement-assisted classical communication, superdense coding, joint source-channel coding, source-assisted channel decoding, iterative decoding
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 416322
URI: http://eprints.soton.ac.uk/id/eprint/416322
PURE UUID: afce543d-5963-4bfb-b1c2-e01570da6189
ORCID for Zunaira Babar: ORCID iD orcid.org/0000-0002-7498-4474
ORCID for Soon Xin Ng: ORCID iD orcid.org/0000-0002-0930-7194
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 12 Dec 2017 17:30
Last modified: 06 Nov 2023 02:44

Export record

Altmetrics

Contributors

Creator: Azri Izhar
Creator: Zunaira Babar ORCID iD
Creator: Soon Xin Ng ORCID iD
Creator: Lajos Hanzo ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×