A metaheuristic-based downlink power allocation for LTE/LTE-A cellular deployments: A multiobjective strategy suitable for Self-Optimizing Networks
The explosive growth of cellular networks makes their deployment and maintenance more and more complex, time consuming, and expensive. Self-Organizing Networks have been recognized as a promising way to alleviate this problem by minimizing human intervention in such processes. This paper introduces...
Gespeichert in:
| Veröffentlicht in: | Wireless networks 2014-08, Vol.20 (6), p.1369-1386 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1386 |
|---|---|
| container_issue | 6 |
| container_start_page | 1369 |
| container_title | Wireless networks |
| container_volume | 20 |
| creator | González G., David García-Lozano, Mario Ruiz, Silvia Lee, Dong Seop |
| description | The explosive growth of cellular networks makes their deployment and maintenance more and more complex, time consuming, and expensive. Self-Organizing Networks have been recognized as a promising way to alleviate this problem by minimizing human intervention in such processes. This paper introduces a novel multiobjective framework, based on evolutionary optimization, aiming at improving network performance and users Quality of Service. By tuning the transmitted power at each cell, average intercell interference levels are minimized. The design of the proposed scheme is feasible for distributed implementations in Long Term Evolution (LTE) and LTE-Advanced networks and its operation is compatible with current specifications. The framework is able to provide effective network-specific optimization and obtained results show that gains in terms of network capacity and cell edge performance are 5 and 10 %, respectively. Energy savings always accompanied such enhancements with reductions up to 35 %. |
| doi_str_mv | 10.1007/s11276-013-0659-9 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1567086667</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3372290871</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3579-5d7f0495fee3169396853e2ee9f8b003654645b03953167da30a3ba527f4fd803</originalsourceid><addsrcrecordid>eNp1kMtKBDEQRRtR8PkB7hpEcBOtJJ3XchBfMCCIrkOmu6Ktmc6YdCP-vRlGRAQXoQJ16nK4VXVM4ZwCqItMKVOSAOUEpDDEbFV7VChGNDVyu_yBMQLA9W61n_MrAGhuzF71MKuXOLoXnFKfx74lC5exq7v4MYR-eKtX8QNT7UKIrRv7ONQ-pnr-eHVRHpnVLYYwBZfqDlchfi5xGPNhteNdyHj0PQ-qp-urx8tbMr-_ubuczUnLhTJEdMpDY4RH5FQabqQWHBmi8XpRTKVoZCMWwI0oe9U5Do4vnGDKN77TwA-qs03uKsX3CfNol31eC7kB45QtFVKBllKqgp78QV_jlIZiV6imSBjWiELRDdWmmHNCb1epX7r0aSnYdct207ItLdt1y9aUm9PvZJdbF3xyQ9vnn0OmhZFG6MKxDZfLanjG9Mvg3_AvEeeKPw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1544959245</pqid></control><display><type>article</type><title>A metaheuristic-based downlink power allocation for LTE/LTE-A cellular deployments: A multiobjective strategy suitable for Self-Optimizing Networks</title><source>SpringerLink Journals - AutoHoldings</source><creator>González G., David ; García-Lozano, Mario ; Ruiz, Silvia ; Lee, Dong Seop</creator><creatorcontrib>González G., David ; García-Lozano, Mario ; Ruiz, Silvia ; Lee, Dong Seop</creatorcontrib><description>The explosive growth of cellular networks makes their deployment and maintenance more and more complex, time consuming, and expensive. Self-Organizing Networks have been recognized as a promising way to alleviate this problem by minimizing human intervention in such processes. This paper introduces a novel multiobjective framework, based on evolutionary optimization, aiming at improving network performance and users Quality of Service. By tuning the transmitted power at each cell, average intercell interference levels are minimized. The design of the proposed scheme is feasible for distributed implementations in Long Term Evolution (LTE) and LTE-Advanced networks and its operation is compatible with current specifications. The framework is able to provide effective network-specific optimization and obtained results show that gains in terms of network capacity and cell edge performance are 5 and 10 %, respectively. Energy savings always accompanied such enhancements with reductions up to 35 %.</description><identifier>ISSN: 1022-0038</identifier><identifier>EISSN: 1572-8196</identifier><identifier>DOI: 10.1007/s11276-013-0659-9</identifier><language>eng</language><publisher>Boston: Springer US</publisher><subject>Algorithmics. Computability. Computer arithmetics ; Analysis ; Applied sciences ; Artificial intelligence ; Business metrics ; Cellular ; Cellular communication ; Communications Engineering ; Computer Communication Networks ; Computer science; control theory; systems ; Computer systems and distributed systems. User interface ; Connectionism. Neural networks ; Cost control ; Electrical Engineering ; Energy ; Energy consumption ; Engineering ; Equipments and installations ; Evolutionary ; Exact sciences and technology ; IT in Business ; Mobile radiocommunication systems ; Network management systems ; Networks ; Optimization ; Optimization algorithms ; Quality of service ; Quality of service architectures ; Radiocommunications ; Reduction ; Software ; Studies ; Telecommunications ; Telecommunications and information theory ; Theoretical computing ; Tuning ; Wireless networks</subject><ispartof>Wireless networks, 2014-08, Vol.20 (6), p.1369-1386</ispartof><rights>Springer Science+Business Media New York 2013</rights><rights>2015 INIST-CNRS</rights><rights>Springer Science+Business Media New York 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3579-5d7f0495fee3169396853e2ee9f8b003654645b03953167da30a3ba527f4fd803</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11276-013-0659-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11276-013-0659-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27923,27924,41487,42556,51318</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28596958$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>González G., David</creatorcontrib><creatorcontrib>García-Lozano, Mario</creatorcontrib><creatorcontrib>Ruiz, Silvia</creatorcontrib><creatorcontrib>Lee, Dong Seop</creatorcontrib><title>A metaheuristic-based downlink power allocation for LTE/LTE-A cellular deployments: A multiobjective strategy suitable for Self-Optimizing Networks</title><title>Wireless networks</title><addtitle>Wireless Netw</addtitle><description>The explosive growth of cellular networks makes their deployment and maintenance more and more complex, time consuming, and expensive. Self-Organizing Networks have been recognized as a promising way to alleviate this problem by minimizing human intervention in such processes. This paper introduces a novel multiobjective framework, based on evolutionary optimization, aiming at improving network performance and users Quality of Service. By tuning the transmitted power at each cell, average intercell interference levels are minimized. The design of the proposed scheme is feasible for distributed implementations in Long Term Evolution (LTE) and LTE-Advanced networks and its operation is compatible with current specifications. The framework is able to provide effective network-specific optimization and obtained results show that gains in terms of network capacity and cell edge performance are 5 and 10 %, respectively. Energy savings always accompanied such enhancements with reductions up to 35 %.</description><subject>Algorithmics. Computability. Computer arithmetics</subject><subject>Analysis</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Business metrics</subject><subject>Cellular</subject><subject>Cellular communication</subject><subject>Communications Engineering</subject><subject>Computer Communication Networks</subject><subject>Computer science; control theory; systems</subject><subject>Computer systems and distributed systems. User interface</subject><subject>Connectionism. Neural networks</subject><subject>Cost control</subject><subject>Electrical Engineering</subject><subject>Energy</subject><subject>Energy consumption</subject><subject>Engineering</subject><subject>Equipments and installations</subject><subject>Evolutionary</subject><subject>Exact sciences and technology</subject><subject>IT in Business</subject><subject>Mobile radiocommunication systems</subject><subject>Network management systems</subject><subject>Networks</subject><subject>Optimization</subject><subject>Optimization algorithms</subject><subject>Quality of service</subject><subject>Quality of service architectures</subject><subject>Radiocommunications</subject><subject>Reduction</subject><subject>Software</subject><subject>Studies</subject><subject>Telecommunications</subject><subject>Telecommunications and information theory</subject><subject>Theoretical computing</subject><subject>Tuning</subject><subject>Wireless networks</subject><issn>1022-0038</issn><issn>1572-8196</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kMtKBDEQRRtR8PkB7hpEcBOtJJ3XchBfMCCIrkOmu6Ktmc6YdCP-vRlGRAQXoQJ16nK4VXVM4ZwCqItMKVOSAOUEpDDEbFV7VChGNDVyu_yBMQLA9W61n_MrAGhuzF71MKuXOLoXnFKfx74lC5exq7v4MYR-eKtX8QNT7UKIrRv7ONQ-pnr-eHVRHpnVLYYwBZfqDlchfi5xGPNhteNdyHj0PQ-qp-urx8tbMr-_ubuczUnLhTJEdMpDY4RH5FQabqQWHBmi8XpRTKVoZCMWwI0oe9U5Do4vnGDKN77TwA-qs03uKsX3CfNol31eC7kB45QtFVKBllKqgp78QV_jlIZiV6imSBjWiELRDdWmmHNCb1epX7r0aSnYdct207ItLdt1y9aUm9PvZJdbF3xyQ9vnn0OmhZFG6MKxDZfLanjG9Mvg3_AvEeeKPw</recordid><startdate>20140801</startdate><enddate>20140801</enddate><creator>González G., David</creator><creator>García-Lozano, Mario</creator><creator>Ruiz, Silvia</creator><creator>Lee, Dong Seop</creator><general>Springer US</general><general>Springer</general><general>Springer Nature B.V</general><scope>IQODW</scope><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>8AO</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>20140801</creationdate><title>A metaheuristic-based downlink power allocation for LTE/LTE-A cellular deployments</title><author>González G., David ; García-Lozano, Mario ; Ruiz, Silvia ; Lee, Dong Seop</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3579-5d7f0495fee3169396853e2ee9f8b003654645b03953167da30a3ba527f4fd803</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Algorithmics. Computability. Computer arithmetics</topic><topic>Analysis</topic><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Business metrics</topic><topic>Cellular</topic><topic>Cellular communication</topic><topic>Communications Engineering</topic><topic>Computer Communication Networks</topic><topic>Computer science; control theory; systems</topic><topic>Computer systems and distributed systems. User interface</topic><topic>Connectionism. Neural networks</topic><topic>Cost control</topic><topic>Electrical Engineering</topic><topic>Energy</topic><topic>Energy consumption</topic><topic>Engineering</topic><topic>Equipments and installations</topic><topic>Evolutionary</topic><topic>Exact sciences and technology</topic><topic>IT in Business</topic><topic>Mobile radiocommunication systems</topic><topic>Network management systems</topic><topic>Networks</topic><topic>Optimization</topic><topic>Optimization algorithms</topic><topic>Quality of service</topic><topic>Quality of service architectures</topic><topic>Radiocommunications</topic><topic>Reduction</topic><topic>Software</topic><topic>Studies</topic><topic>Telecommunications</topic><topic>Telecommunications and information theory</topic><topic>Theoretical computing</topic><topic>Tuning</topic><topic>Wireless networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>González G., David</creatorcontrib><creatorcontrib>García-Lozano, Mario</creatorcontrib><creatorcontrib>Ruiz, Silvia</creatorcontrib><creatorcontrib>Lee, Dong Seop</creatorcontrib><collection>Pascal-Francis</collection><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 Global (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</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 Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection (ProQuest)</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</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</collection><collection>Science Database</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>Wireless networks</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>González G., David</au><au>García-Lozano, Mario</au><au>Ruiz, Silvia</au><au>Lee, Dong Seop</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A metaheuristic-based downlink power allocation for LTE/LTE-A cellular deployments: A multiobjective strategy suitable for Self-Optimizing Networks</atitle><jtitle>Wireless networks</jtitle><stitle>Wireless Netw</stitle><date>2014-08-01</date><risdate>2014</risdate><volume>20</volume><issue>6</issue><spage>1369</spage><epage>1386</epage><pages>1369-1386</pages><issn>1022-0038</issn><eissn>1572-8196</eissn><abstract>The explosive growth of cellular networks makes their deployment and maintenance more and more complex, time consuming, and expensive. Self-Organizing Networks have been recognized as a promising way to alleviate this problem by minimizing human intervention in such processes. This paper introduces a novel multiobjective framework, based on evolutionary optimization, aiming at improving network performance and users Quality of Service. By tuning the transmitted power at each cell, average intercell interference levels are minimized. The design of the proposed scheme is feasible for distributed implementations in Long Term Evolution (LTE) and LTE-Advanced networks and its operation is compatible with current specifications. The framework is able to provide effective network-specific optimization and obtained results show that gains in terms of network capacity and cell edge performance are 5 and 10 %, respectively. Energy savings always accompanied such enhancements with reductions up to 35 %.</abstract><cop>Boston</cop><pub>Springer US</pub><doi>10.1007/s11276-013-0659-9</doi><tpages>18</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1022-0038 |
| ispartof | Wireless networks, 2014-08, Vol.20 (6), p.1369-1386 |
| issn | 1022-0038 1572-8196 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1567086667 |
| source | SpringerLink Journals - AutoHoldings |
| subjects | Algorithmics. Computability. Computer arithmetics Analysis Applied sciences Artificial intelligence Business metrics Cellular Cellular communication Communications Engineering Computer Communication Networks Computer science control theory systems Computer systems and distributed systems. User interface Connectionism. Neural networks Cost control Electrical Engineering Energy Energy consumption Engineering Equipments and installations Evolutionary Exact sciences and technology IT in Business Mobile radiocommunication systems Network management systems Networks Optimization Optimization algorithms Quality of service Quality of service architectures Radiocommunications Reduction Software Studies Telecommunications Telecommunications and information theory Theoretical computing Tuning Wireless networks |
| title | A metaheuristic-based downlink power allocation for LTE/LTE-A cellular deployments: A multiobjective strategy suitable for Self-Optimizing Networks |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T14%3A43%3A33IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20metaheuristic-based%20downlink%20power%20allocation%20for%20LTE/LTE-A%20cellular%20deployments:%20A%20multiobjective%20strategy%20suitable%20for%20Self-Optimizing%20Networks&rft.jtitle=Wireless%20networks&rft.au=Gonz%C3%A1lez%20G.,%20David&rft.date=2014-08-01&rft.volume=20&rft.issue=6&rft.spage=1369&rft.epage=1386&rft.pages=1369-1386&rft.issn=1022-0038&rft.eissn=1572-8196&rft_id=info:doi/10.1007/s11276-013-0659-9&rft_dat=%3Cproquest_cross%3E3372290871%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1544959245&rft_id=info:pmid/&rfr_iscdi=true |