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Energy harvesting assisted cognitive radio: random location-based transceivers scheme and performance analysis
We consider spectrum-sharing scenario where coexist two communication networks including primary network and secondary network using the same spectrum. While the primary network includes directional multi-transceivers, the secondary network consists of relaying-based transceiver forwarding signals b...
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Published in: | Telecommunication systems 2018, Vol.67 (1), p.123-132 |
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description | We consider spectrum-sharing scenario where coexist two communication networks including primary network and secondary network using the same spectrum. While the primary network includes directional multi-transceivers, the secondary network consists of relaying-based transceiver forwarding signals by energy harvesting assisted relay node. In cognitive radio, signals transmitted from secondary network are sufficiently small so that all of primary network receivers have signal to noise ratio (SNR) greater than a given threshold. In contrast, the transmitted signals from primary network cause increasing noise which is difficult to demodulate at secondary network nodes and hence it leads to the peak power constraint. In this paper, we focus on the influence of random location of transceivers at primary network using decode-and-forward protocol. Specifically, we derive closed-form outage probability expression of the secondary network under random location of transceivers and peak power constraint of primary network. This investigation shows the relationship between the fraction of energy harvesting time
α
of time switching-based relaying protocol on outage probability of secondary network and throughput. In addition, we analyse the influence of the number of primary network transceivers as well as primary network’s SNR threshold on secondary network. Furthermore, the trade-off between increasing energy harvesting and rate was investigated under the effect of energy conversion efficiency. The accuracy of the expressions is validated via Monte-Carlo simulations. Numerical results highlight the trade-offs associated with the various energy harvesting time allocations as a function of outage performance. |
doi_str_mv | 10.1007/s11235-017-0325-0 |
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α
of time switching-based relaying protocol on outage probability of secondary network and throughput. In addition, we analyse the influence of the number of primary network transceivers as well as primary network’s SNR threshold on secondary network. Furthermore, the trade-off between increasing energy harvesting and rate was investigated under the effect of energy conversion efficiency. The accuracy of the expressions is validated via Monte-Carlo simulations. Numerical results highlight the trade-offs associated with the various energy harvesting time allocations as a function of outage performance.</description><identifier>ISSN: 1018-4864</identifier><identifier>EISSN: 1572-9451</identifier><identifier>DOI: 10.1007/s11235-017-0325-0</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Allocations ; Artificial Intelligence ; Business and Management ; Cognitive radio ; Communication networks ; Computer Communication Networks ; Computer simulation ; Energy ; Energy conversion efficiency ; Energy harvesting ; IT in Business ; Monte Carlo simulation ; Probability Theory and Stochastic Processes ; Radio networks ; Relaying ; Signal to noise ratio ; Switching theory ; Telecommunications systems ; Tradeoffs ; Transceivers</subject><ispartof>Telecommunication systems, 2018, Vol.67 (1), p.123-132</ispartof><rights>Springer Science+Business Media New York 2017</rights><rights>Telecommunication Systems is a copyright of Springer, (2017). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-c3cd05b97076be2f512686bf5fead9ab61b7df73b6a77696d7cb3e9d0f30ab0b3</citedby><cites>FETCH-LOGICAL-c316t-c3cd05b97076be2f512686bf5fead9ab61b7df73b6a77696d7cb3e9d0f30ab0b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1985826915/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1985826915?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,11688,27924,27925,36060,44363,74895</link.rule.ids></links><search><creatorcontrib>Nam, Pham Minh</creatorcontrib><creatorcontrib>Do, Dinh-Thuan</creatorcontrib><creatorcontrib>Tung, Nguyen Tien</creatorcontrib><creatorcontrib>Tin, Phu Tran</creatorcontrib><title>Energy harvesting assisted cognitive radio: random location-based transceivers scheme and performance analysis</title><title>Telecommunication systems</title><addtitle>Telecommun Syst</addtitle><description>We consider spectrum-sharing scenario where coexist two communication networks including primary network and secondary network using the same spectrum. While the primary network includes directional multi-transceivers, the secondary network consists of relaying-based transceiver forwarding signals by energy harvesting assisted relay node. In cognitive radio, signals transmitted from secondary network are sufficiently small so that all of primary network receivers have signal to noise ratio (SNR) greater than a given threshold. In contrast, the transmitted signals from primary network cause increasing noise which is difficult to demodulate at secondary network nodes and hence it leads to the peak power constraint. In this paper, we focus on the influence of random location of transceivers at primary network using decode-and-forward protocol. Specifically, we derive closed-form outage probability expression of the secondary network under random location of transceivers and peak power constraint of primary network. This investigation shows the relationship between the fraction of energy harvesting time
α
of time switching-based relaying protocol on outage probability of secondary network and throughput. In addition, we analyse the influence of the number of primary network transceivers as well as primary network’s SNR threshold on secondary network. Furthermore, the trade-off between increasing energy harvesting and rate was investigated under the effect of energy conversion efficiency. The accuracy of the expressions is validated via Monte-Carlo simulations. Numerical results highlight the trade-offs associated with the various energy harvesting time allocations as a function of outage performance.</description><subject>Allocations</subject><subject>Artificial Intelligence</subject><subject>Business and Management</subject><subject>Cognitive radio</subject><subject>Communication networks</subject><subject>Computer Communication Networks</subject><subject>Computer simulation</subject><subject>Energy</subject><subject>Energy conversion efficiency</subject><subject>Energy harvesting</subject><subject>IT in Business</subject><subject>Monte Carlo simulation</subject><subject>Probability Theory and Stochastic Processes</subject><subject>Radio networks</subject><subject>Relaying</subject><subject>Signal to noise ratio</subject><subject>Switching theory</subject><subject>Telecommunications systems</subject><subject>Tradeoffs</subject><subject>Transceivers</subject><issn>1018-4864</issn><issn>1572-9451</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>M0C</sourceid><recordid>eNp1kE1LAzEQhoMoWKs_wFvA82qy2yQbb1L8goIXPYd8brd0k5rZFvrvzVIPXrzMTIbnfcm8CN1Sck8JEQ9Aad2wilBRkaYuwxmaUSbqSi4YPS8zoW21aPniEl0BbAiZVHKG4nP0uTvitc4HD2MfO6wBehi9wzZ1sR_7g8dZuz49lhZdGvA2WT32KVZGQ8HGsgbrC5cBg137weMC4p3PIeVBRzu99fZYbK_RRdBb8De_fY6-Xp4_l2_V6uP1ffm0qmxD-ViqdYQZKYjgxteB0Zq33AQWvHZSG06NcEE0hmshuOROWNN46UhoiDbENHN0d_Ld5fS9L4epTdrn8glQVLasrbmkrFD0RNmcALIPapf7QeejokRNAalTrKrEqqZYS5mj-qSBwsbO5z_O_4p-ADQ6fX0</recordid><startdate>2018</startdate><enddate>2018</enddate><creator>Nam, Pham Minh</creator><creator>Do, Dinh-Thuan</creator><creator>Tung, Nguyen Tien</creator><creator>Tin, Phu Tran</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7SP</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M2P</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope></search><sort><creationdate>2018</creationdate><title>Energy harvesting assisted cognitive radio: random location-based transceivers scheme and performance analysis</title><author>Nam, Pham Minh ; Do, Dinh-Thuan ; Tung, Nguyen Tien ; Tin, Phu Tran</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-c3cd05b97076be2f512686bf5fead9ab61b7df73b6a77696d7cb3e9d0f30ab0b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Allocations</topic><topic>Artificial Intelligence</topic><topic>Business and Management</topic><topic>Cognitive radio</topic><topic>Communication networks</topic><topic>Computer Communication Networks</topic><topic>Computer simulation</topic><topic>Energy</topic><topic>Energy conversion efficiency</topic><topic>Energy harvesting</topic><topic>IT in Business</topic><topic>Monte Carlo simulation</topic><topic>Probability Theory and Stochastic Processes</topic><topic>Radio networks</topic><topic>Relaying</topic><topic>Signal to noise ratio</topic><topic>Switching theory</topic><topic>Telecommunications systems</topic><topic>Tradeoffs</topic><topic>Transceivers</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nam, Pham Minh</creatorcontrib><creatorcontrib>Do, Dinh-Thuan</creatorcontrib><creatorcontrib>Tung, Nguyen Tien</creatorcontrib><creatorcontrib>Tin, Phu Tran</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Database (1962 - current)</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Global (ProQuest)</collection><collection>Science Database (ProQuest)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><jtitle>Telecommunication systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nam, Pham Minh</au><au>Do, Dinh-Thuan</au><au>Tung, Nguyen Tien</au><au>Tin, Phu Tran</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Energy harvesting assisted cognitive radio: random location-based transceivers scheme and performance analysis</atitle><jtitle>Telecommunication systems</jtitle><stitle>Telecommun Syst</stitle><date>2018</date><risdate>2018</risdate><volume>67</volume><issue>1</issue><spage>123</spage><epage>132</epage><pages>123-132</pages><issn>1018-4864</issn><eissn>1572-9451</eissn><abstract>We consider spectrum-sharing scenario where coexist two communication networks including primary network and secondary network using the same spectrum. While the primary network includes directional multi-transceivers, the secondary network consists of relaying-based transceiver forwarding signals by energy harvesting assisted relay node. In cognitive radio, signals transmitted from secondary network are sufficiently small so that all of primary network receivers have signal to noise ratio (SNR) greater than a given threshold. In contrast, the transmitted signals from primary network cause increasing noise which is difficult to demodulate at secondary network nodes and hence it leads to the peak power constraint. In this paper, we focus on the influence of random location of transceivers at primary network using decode-and-forward protocol. Specifically, we derive closed-form outage probability expression of the secondary network under random location of transceivers and peak power constraint of primary network. This investigation shows the relationship between the fraction of energy harvesting time
α
of time switching-based relaying protocol on outage probability of secondary network and throughput. In addition, we analyse the influence of the number of primary network transceivers as well as primary network’s SNR threshold on secondary network. Furthermore, the trade-off between increasing energy harvesting and rate was investigated under the effect of energy conversion efficiency. The accuracy of the expressions is validated via Monte-Carlo simulations. Numerical results highlight the trade-offs associated with the various energy harvesting time allocations as a function of outage performance.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11235-017-0325-0</doi><tpages>10</tpages></addata></record> |
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subjects | Allocations Artificial Intelligence Business and Management Cognitive radio Communication networks Computer Communication Networks Computer simulation Energy Energy conversion efficiency Energy harvesting IT in Business Monte Carlo simulation Probability Theory and Stochastic Processes Radio networks Relaying Signal to noise ratio Switching theory Telecommunications systems Tradeoffs Transceivers |
title | Energy harvesting assisted cognitive radio: random location-based transceivers scheme and performance analysis |
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