On Green Cognitive Radio Cellular Networks: Dynamic Spectrum and Operation Management

Handle URI:
http://hdl.handle.net/10754/617237
Title:
On Green Cognitive Radio Cellular Networks: Dynamic Spectrum and Operation Management
Authors:
Sboui, Lokman ( 0000-0003-1134-4055 ) ; Ghazzai, Hakim ( 0000-0002-8636-4264 ) ; Rezki, Zouheir; Alouini, Mohamed-Slim ( 0000-0003-4827-1793 )
Abstract:
We study a profit maximization problem related to cognitive radio cellular networks in an environmentally- friendly framework. The objective of the primary network (PN) and secondary network (SN) is to maximize their profits while respecting a certain carbon dioxide (CO2) emissions threshold. In this study, the PN can switch off some of its base stations (BSs) powered by mircogrids, and hence leases the spectrum in the corresponding cells, to reduce its footprint. The corresponding users are roamed to the SN infrastructure. In return, the SN receives a certain roaming cost and its users can freely exploit the spectrum. We study two scenarios in which the profits are either separately or jointly maximized. In the disjoint maximization problem, two low complexity algorithms for PN and SN BS on/off switching are proposed to maximize the profit per CO2 emissions utility and determine the amount of the shared bandwidth. In the joint maximization approach, the low complexity algorithm is based on maximizing the sum of weighted profits per CO2. Selected numerical results illustrate the collaboration performance versus various system parameters. We show that the proposed algorithms achieve performances close to those obtained with the exhaustive search method, and that the roaming price and the renewable energy availability are crucial parameters that control the collaboration of both networks.
KAUST Department:
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Citation:
On Green Cognitive Radio Cellular Networks: Dynamic Spectrum and Operation Management 2016:1 IEEE Access
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Access
Issue Date:
18-Jul-2016
DOI:
10.1109/ACCESS.2016.2592178
Type:
Article
ISSN:
2169-3536
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7514956
Appears in Collections:
Articles

Full metadata record

DC FieldValue Language
dc.contributor.authorSboui, Lokmanen
dc.contributor.authorGhazzai, Hakimen
dc.contributor.authorRezki, Zouheiren
dc.contributor.authorAlouini, Mohamed-Slimen
dc.date.accessioned2016-07-19T09:56:19Z-
dc.date.available2016-07-19T09:56:19Z-
dc.date.issued2016-07-18-
dc.identifier.citationOn Green Cognitive Radio Cellular Networks: Dynamic Spectrum and Operation Management 2016:1 IEEE Accessen
dc.identifier.issn2169-3536-
dc.identifier.doi10.1109/ACCESS.2016.2592178-
dc.identifier.urihttp://hdl.handle.net/10754/617237-
dc.description.abstractWe study a profit maximization problem related to cognitive radio cellular networks in an environmentally- friendly framework. The objective of the primary network (PN) and secondary network (SN) is to maximize their profits while respecting a certain carbon dioxide (CO2) emissions threshold. In this study, the PN can switch off some of its base stations (BSs) powered by mircogrids, and hence leases the spectrum in the corresponding cells, to reduce its footprint. The corresponding users are roamed to the SN infrastructure. In return, the SN receives a certain roaming cost and its users can freely exploit the spectrum. We study two scenarios in which the profits are either separately or jointly maximized. In the disjoint maximization problem, two low complexity algorithms for PN and SN BS on/off switching are proposed to maximize the profit per CO2 emissions utility and determine the amount of the shared bandwidth. In the joint maximization approach, the low complexity algorithm is based on maximizing the sum of weighted profits per CO2. Selected numerical results illustrate the collaboration performance versus various system parameters. We show that the proposed algorithms achieve performances close to those obtained with the exhaustive search method, and that the roaming price and the renewable energy availability are crucial parameters that control the collaboration of both networks.en
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7514956en
dc.rights(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.subjectCollaborative cellular networksen
dc.subjectdynamic spec- trum managementen
dc.subjectgreen cognitive radioen
dc.subjectmicrogriden
dc.titleOn Green Cognitive Radio Cellular Networks: Dynamic Spectrum and Operation Managementen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Divisionen
dc.identifier.journalIEEE Accessen
dc.eprint.versionPost-printen
dc.contributor.institutionQatar Mobility Innovations Center (QMIC), Qatar University , Doha, Qataren
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorSboui, Lokmanen
kaust.authorRezki, Zouheiren
kaust.authorAlouini, Mohamed-Slimen
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