Optimal time sharing in RF-powered backscatter cognitive radio networks

Hoang, DT; Niyato, D; Wang, P; Kim, DI

Optimal time sharing in RF-powered backscatter cognitive radio networks

Hoang, DT

Niyato, D Wang, P Kim, DI

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Communications, 2017
Issue Date:: 2017-07-28

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Field	Value	Language
dc.contributor.author	Hoang, DT https://orcid.org/0000-0002-9528-0863	en_US
dc.contributor.author	Niyato, D	en_US
dc.contributor.author	Wang, P	en_US
dc.contributor.author	Kim, DI	en_US
dc.date.issued	2017-07-28	en_US
dc.identifier.citation	IEEE International Conference on Communications, 2017	en_US
dc.identifier.isbn	9781467389990	en_US
dc.identifier.issn	1550-3607	en_US
dc.identifier.uri	http://hdl.handle.net/10453/125905
dc.description.abstract	© 2017 IEEE. In this paper, we propose a novel network model for RF-powered cognitive radio networks and ambient backscatter communications. In the network under consideration, each secondary transmitter is able to backscatter primary signals to the gateway for data transfer or to harvest energy from the primary signals and then use that energy to transmit data to the gateway. To maximize overall network throughput of the network, we formulate an optimization problem with the aim of finding not only an optimal tradeoff between data backscattering time and energy harvesting time, but also time sharing among multiple secondary transmitters. Through the numerical results, we demonstrate that the solution of the optimization problem always achieves the best performance compared with two other baseline schemes.	en_US
dc.relation.ispartof	IEEE International Conference on Communications	en_US
dc.relation.isbasedon	10.1109/ICC.2017.7996410	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Optimal time sharing in RF-powered backscatter cognitive radio networks	en_US
dc.type	Conference Proceeding
utslib.for	1005 Communications Technologies	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US

Abstract:

© 2017 IEEE. In this paper, we propose a novel network model for RF-powered cognitive radio networks and ambient backscatter communications. In the network under consideration, each secondary transmitter is able to backscatter primary signals to the gateway for data transfer or to harvest energy from the primary signals and then use that energy to transmit data to the gateway. To maximize overall network throughput of the network, we formulate an optimization problem with the aim of finding not only an optimal tradeoff between data backscattering time and energy harvesting time, but also time sharing among multiple secondary transmitters. Through the numerical results, we demonstrate that the solution of the optimization problem always achieves the best performance compared with two other baseline schemes.

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http://hdl.handle.net/10453/125905