Statistical Delay QoS Driven Energy Efficiency and Effective Capacity Tradeoff for Uplink Multi-User Multi-Carrier Systems
In this paper, the total system effective capacity (EC) maximization problem for the uplink transmission, in a multi-user multi-carrier orthogonal frequency division multiple access system, is formulated as a combinatorial integer programming problem, subject to each user's link-layer energy ef...
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Veröffentlicht in: | IEEE transactions on communications 2017-08, Vol.65 (8), p.3494-3508 |
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description | In this paper, the total system effective capacity (EC) maximization problem for the uplink transmission, in a multi-user multi-carrier orthogonal frequency division multiple access system, is formulated as a combinatorial integer programming problem, subject to each user's link-layer energy efficiency (EE) requirement as well as the individual's average transmission power limit. To solve this challenging problem, we first decouple it into a frequency provisioning problem and an independent multi-carrier link-layer EE-EC tradeoff problem for each user. In order to obtain the subcarrier assignment solution, a low-complexity heuristic algorithm is proposed, which not only offers close-to-optimal solutions, while serving as many users as possible, but also has a complexity linearly relating to the size of the problem. After obtaining the subcarrier assignment matrix, the multi-carrier link-layer EE-EC tradeoff problem for each user is formulated and solved by using Karush-Kuhn-Tucker conditions. The per-user optimal power allocation strategy, which is across both frequency and time domains, is then derived. Further, we theoretically investigate the impact of the circuit power and the EE requirement factor on each user's EE level and optimal average power value. The low-complexity heuristic algorithm is then simulated to compare with the traditional exhaustive algorithm and a fair-exhaustive algorithm. Simulation results confirm our proofs and design intentions, and further show the effects of delay quality-of-service exponent, the total number of users, and the number of subcarriers on the system tradeoff performance. |
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To solve this challenging problem, we first decouple it into a frequency provisioning problem and an independent multi-carrier link-layer EE-EC tradeoff problem for each user. In order to obtain the subcarrier assignment solution, a low-complexity heuristic algorithm is proposed, which not only offers close-to-optimal solutions, while serving as many users as possible, but also has a complexity linearly relating to the size of the problem. After obtaining the subcarrier assignment matrix, the multi-carrier link-layer EE-EC tradeoff problem for each user is formulated and solved by using Karush-Kuhn-Tucker conditions. The per-user optimal power allocation strategy, which is across both frequency and time domains, is then derived. Further, we theoretically investigate the impact of the circuit power and the EE requirement factor on each user's EE level and optimal average power value. The low-complexity heuristic algorithm is then simulated to compare with the traditional exhaustive algorithm and a fair-exhaustive algorithm. Simulation results confirm our proofs and design intentions, and further show the effects of delay quality-of-service exponent, the total number of users, and the number of subcarriers on the system tradeoff performance.</description><identifier>ISSN: 0090-6778</identifier><identifier>EISSN: 1558-0857</identifier><identifier>DOI: 10.1109/TCOMM.2017.2699637</identifier><identifier>CODEN: IECMBT</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Combinatorial analysis ; Complexity ; Computer simulation ; Delay ; delay-outage probability ; Delays ; effective capacity ; Energy efficiency ; Energy management ; Energy transmission ; Frequency division multiple access ; Heuristic algorithms ; Heuristic methods ; Integer programming ; Kuhn-Tucker method ; Link-layer energy-rate tradeoff ; Multiple access ; OFDM ; Optimization ; Power efficiency ; Provisioning ; Quality of service ; Resource management ; Subcarriers ; System effectiveness ; Tradeoffs ; Uplink</subject><ispartof>IEEE transactions on communications, 2017-08, Vol.65 (8), p.3494-3508</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c339t-dad85f59f4d71392e001b6fb7735541e169f53ad2c171747510eff7a252edffc3</citedby><cites>FETCH-LOGICAL-c339t-dad85f59f4d71392e001b6fb7735541e169f53ad2c171747510eff7a252edffc3</cites><orcidid>0000-0002-4593-1656 ; 0000-0001-7364-7663 ; 0000-0002-5276-1157</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7914688$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,796,27923,27924,54757</link.rule.ids></links><search><creatorcontrib>Wenjuan Yu</creatorcontrib><creatorcontrib>Musavian, Leila</creatorcontrib><creatorcontrib>Qiang Ni</creatorcontrib><title>Statistical Delay QoS Driven Energy Efficiency and Effective Capacity Tradeoff for Uplink Multi-User Multi-Carrier Systems</title><title>IEEE transactions on communications</title><addtitle>TCOMM</addtitle><description>In this paper, the total system effective capacity (EC) maximization problem for the uplink transmission, in a multi-user multi-carrier orthogonal frequency division multiple access system, is formulated as a combinatorial integer programming problem, subject to each user's link-layer energy efficiency (EE) requirement as well as the individual's average transmission power limit. To solve this challenging problem, we first decouple it into a frequency provisioning problem and an independent multi-carrier link-layer EE-EC tradeoff problem for each user. In order to obtain the subcarrier assignment solution, a low-complexity heuristic algorithm is proposed, which not only offers close-to-optimal solutions, while serving as many users as possible, but also has a complexity linearly relating to the size of the problem. After obtaining the subcarrier assignment matrix, the multi-carrier link-layer EE-EC tradeoff problem for each user is formulated and solved by using Karush-Kuhn-Tucker conditions. The per-user optimal power allocation strategy, which is across both frequency and time domains, is then derived. Further, we theoretically investigate the impact of the circuit power and the EE requirement factor on each user's EE level and optimal average power value. The low-complexity heuristic algorithm is then simulated to compare with the traditional exhaustive algorithm and a fair-exhaustive algorithm. Simulation results confirm our proofs and design intentions, and further show the effects of delay quality-of-service exponent, the total number of users, and the number of subcarriers on the system tradeoff performance.</description><subject>Algorithms</subject><subject>Combinatorial analysis</subject><subject>Complexity</subject><subject>Computer simulation</subject><subject>Delay</subject><subject>delay-outage probability</subject><subject>Delays</subject><subject>effective capacity</subject><subject>Energy efficiency</subject><subject>Energy management</subject><subject>Energy transmission</subject><subject>Frequency division multiple access</subject><subject>Heuristic algorithms</subject><subject>Heuristic methods</subject><subject>Integer programming</subject><subject>Kuhn-Tucker method</subject><subject>Link-layer energy-rate tradeoff</subject><subject>Multiple access</subject><subject>OFDM</subject><subject>Optimization</subject><subject>Power efficiency</subject><subject>Provisioning</subject><subject>Quality of service</subject><subject>Resource management</subject><subject>Subcarriers</subject><subject>System effectiveness</subject><subject>Tradeoffs</subject><subject>Uplink</subject><issn>0090-6778</issn><issn>1558-0857</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><recordid>eNo9kF1LwzAUhoMoOD_-gN4EvO5MmqZpLqWbH7AxZNt1yNITyezammRC_fV2bnh1zgvPew48CN1RMqaUyMdVuZjPxymhYpzmUuZMnKER5bxISMHFORoRIkmSC1FcoqsQtoSQjDA2Qj_LqKML0Rld4wnUusfv7RJPvPuGBk8b8B89nlrrjIPG9Fg31SGCiQOAS91p42KPV15X0FqLbevxuqtd84nn-zq6ZB3An9ZSe--GtOxDhF24QRdW1wFuT_MarZ-nq_I1mS1e3sqnWWIYkzGpdFVwy6XNKkGZTIEQusntRgjGeUaB5tJypqvUUEFFJjglYK3QKU-hstawa_RwvNv59msPIaptu_fN8FJRmUo-CCPFQKVHyvg2BA9Wdd7ttO8VJergWP05VgfH6uR4KN0fSw4A_gtC0iwvCvYLZgN5Sg</recordid><startdate>20170801</startdate><enddate>20170801</enddate><creator>Wenjuan Yu</creator><creator>Musavian, Leila</creator><creator>Qiang Ni</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-4593-1656</orcidid><orcidid>https://orcid.org/0000-0001-7364-7663</orcidid><orcidid>https://orcid.org/0000-0002-5276-1157</orcidid></search><sort><creationdate>20170801</creationdate><title>Statistical Delay QoS Driven Energy Efficiency and Effective Capacity Tradeoff for Uplink Multi-User Multi-Carrier Systems</title><author>Wenjuan Yu ; Musavian, Leila ; Qiang Ni</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c339t-dad85f59f4d71392e001b6fb7735541e169f53ad2c171747510eff7a252edffc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Algorithms</topic><topic>Combinatorial analysis</topic><topic>Complexity</topic><topic>Computer simulation</topic><topic>Delay</topic><topic>delay-outage probability</topic><topic>Delays</topic><topic>effective capacity</topic><topic>Energy efficiency</topic><topic>Energy management</topic><topic>Energy transmission</topic><topic>Frequency division multiple access</topic><topic>Heuristic algorithms</topic><topic>Heuristic methods</topic><topic>Integer programming</topic><topic>Kuhn-Tucker method</topic><topic>Link-layer energy-rate tradeoff</topic><topic>Multiple access</topic><topic>OFDM</topic><topic>Optimization</topic><topic>Power efficiency</topic><topic>Provisioning</topic><topic>Quality of service</topic><topic>Resource management</topic><topic>Subcarriers</topic><topic>System effectiveness</topic><topic>Tradeoffs</topic><topic>Uplink</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wenjuan Yu</creatorcontrib><creatorcontrib>Musavian, Leila</creatorcontrib><creatorcontrib>Qiang Ni</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wenjuan Yu</au><au>Musavian, Leila</au><au>Qiang Ni</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Statistical Delay QoS Driven Energy Efficiency and Effective Capacity Tradeoff for Uplink Multi-User Multi-Carrier Systems</atitle><jtitle>IEEE transactions on communications</jtitle><stitle>TCOMM</stitle><date>2017-08-01</date><risdate>2017</risdate><volume>65</volume><issue>8</issue><spage>3494</spage><epage>3508</epage><pages>3494-3508</pages><issn>0090-6778</issn><eissn>1558-0857</eissn><coden>IECMBT</coden><abstract>In this paper, the total system effective capacity (EC) maximization problem for the uplink transmission, in a multi-user multi-carrier orthogonal frequency division multiple access system, is formulated as a combinatorial integer programming problem, subject to each user's link-layer energy efficiency (EE) requirement as well as the individual's average transmission power limit. To solve this challenging problem, we first decouple it into a frequency provisioning problem and an independent multi-carrier link-layer EE-EC tradeoff problem for each user. In order to obtain the subcarrier assignment solution, a low-complexity heuristic algorithm is proposed, which not only offers close-to-optimal solutions, while serving as many users as possible, but also has a complexity linearly relating to the size of the problem. After obtaining the subcarrier assignment matrix, the multi-carrier link-layer EE-EC tradeoff problem for each user is formulated and solved by using Karush-Kuhn-Tucker conditions. The per-user optimal power allocation strategy, which is across both frequency and time domains, is then derived. Further, we theoretically investigate the impact of the circuit power and the EE requirement factor on each user's EE level and optimal average power value. The low-complexity heuristic algorithm is then simulated to compare with the traditional exhaustive algorithm and a fair-exhaustive algorithm. Simulation results confirm our proofs and design intentions, and further show the effects of delay quality-of-service exponent, the total number of users, and the number of subcarriers on the system tradeoff performance.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TCOMM.2017.2699637</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-4593-1656</orcidid><orcidid>https://orcid.org/0000-0001-7364-7663</orcidid><orcidid>https://orcid.org/0000-0002-5276-1157</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Combinatorial analysis Complexity Computer simulation Delay delay-outage probability Delays effective capacity Energy efficiency Energy management Energy transmission Frequency division multiple access Heuristic algorithms Heuristic methods Integer programming Kuhn-Tucker method Link-layer energy-rate tradeoff Multiple access OFDM Optimization Power efficiency Provisioning Quality of service Resource management Subcarriers System effectiveness Tradeoffs Uplink |
title | Statistical Delay QoS Driven Energy Efficiency and Effective Capacity Tradeoff for Uplink Multi-User Multi-Carrier Systems |
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