RF-Based Energy Harvesting Cognitive Cellular Networks

Dinh, H; Dusit, N

RF-Based Energy Harvesting Cognitive Cellular Networks

Dinh, H

Dusit, N

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Publisher:: Springer
Publication Type:: Chapter
Citation:: Handbook of Cognitive Radio, 2019, 2-3, pp. 1235-1277
Issue Date:: 2019-05-01

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Field	Value	Language
dc.contributor.author	Dinh, H https://orcid.org/0000-0002-9528-0863
dc.contributor.author	Dusit, N
dc.contributor.editor	Wei, Z
dc.date.accessioned	2022-12-05T02:12:01Z
dc.date.available	2022-12-05T02:12:01Z
dc.date.issued	2019-05-01
dc.identifier.citation	Handbook of Cognitive Radio, 2019, 2-3, pp. 1235-1277
dc.identifier.isbn	978-981-10-1393-5
dc.identifier.uri	http://hdl.handle.net/10453/164108
dc.description.abstract	Recently, fundamental research has demonstrated great potentials of integrating radio frequency (RF) energy harvesting techniques into cognitive cellular networks (CCNs). Such an integration can improve spectrum utilization and energy efficiency of wireless communication services. In CCNs with RF energy harvesting capability, when cellular base stations, i.e., primary transmitters, transmit signals to their mobile devices, secondary users (SUs) can harvest energy from the cellular channel, i.e., the primary channel, and store the energy in their batteries. Then, when the cellular channel becomes idle, the SUs can use the harvested energy to transmit data to their receivers. As such, we can utilize not only the available spectrum when the channel is idle but also energy scavenging when the channel is busy. This chapter first presents an overview of RF-based energy harvesting CCNs. Then, limitations are discussed, and some new solutions using ambient backscattering communication techniques are introduced to overcome the limitations. Finally, the chapter concludes with a discussion on the development of such networks and possible research directions.
dc.format.extent	62
dc.language	en
dc.publisher	Springer
dc.relation.ispartof	Handbook of Cognitive Radio
dc.relation.isbasedon	10.1007/978-981-10-1394-2_34
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	RF-Based Energy Harvesting Cognitive Cellular Networks
dc.type	Chapter
utslib.citation.volume	2-3
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/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-12-05T02:11:58Z
pubs.place-of-publication	Switzerland
pubs.publication-status	Published
pubs.volume	2-3
dc.location	Switzerland

Abstract:

Recently, fundamental research has demonstrated great potentials of integrating radio frequency (RF) energy harvesting techniques into cognitive cellular networks (CCNs). Such an integration can improve spectrum utilization and energy efficiency of wireless communication services. In CCNs with RF energy harvesting capability, when cellular base stations, i.e., primary transmitters, transmit signals to their mobile devices, secondary users (SUs) can harvest energy from the cellular channel, i.e., the primary channel, and store the energy in their batteries. Then, when the cellular channel becomes idle, the SUs can use the harvested energy to transmit data to their receivers. As such, we can utilize not only the available spectrum when the channel is idle but also energy scavenging when the channel is busy. This chapter first presents an overview of RF-based energy harvesting CCNs. Then, limitations are discussed, and some new solutions using ambient backscattering communication techniques are introduced to overcome the limitations. Finally, the chapter concludes with a discussion on the development of such networks and possible research directions.

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http://hdl.handle.net/10453/164108