Price-Based Power Allocation for Non-Orthogonal Multiple Access Systems
Non-orthogonal multiple access (NOMA) is expected to be a promising multiple access technique for future wireless networks. In this letter, considering a cellular downlink NOMA system, we use game theory to model the interaction between the base station and multiple users as a Stackelberg game. The...
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| Veröffentlicht in: | IEEE wireless communications letters 2016-12, Vol.5 (6), p.664-667 |
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| creator | Li, Chongyang Zhang, Qi Li, Quanzhong Qin, Jiayin |
| description | Non-orthogonal multiple access (NOMA) is expected to be a promising multiple access technique for future wireless networks. In this letter, considering a cellular downlink NOMA system, we use game theory to model the interaction between the base station and multiple users as a Stackelberg game. The base station, which acts as the leader of the Stackelberg game, chooses a price on per transmitted power allocated to each user to maximize its own revenue. Each user chooses an optimal power to maximize its utility after the base station sets prices. The revenue function of the base station is ultimately expressed as a non-convex function of the power allocation among multiple users. We aim at solving the revenue maximization problem. We propose to decouple the problem into three optimization problems and employ alternating optimization algorithm to solve the problem. Simulation results show the proposed price-based power allocation scheme outperforms the uniform power allocation scheme. |
| doi_str_mv | 10.1109/LWC.2016.2613972 |
| format | Article |
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In this letter, considering a cellular downlink NOMA system, we use game theory to model the interaction between the base station and multiple users as a Stackelberg game. The base station, which acts as the leader of the Stackelberg game, chooses a price on per transmitted power allocated to each user to maximize its own revenue. Each user chooses an optimal power to maximize its utility after the base station sets prices. The revenue function of the base station is ultimately expressed as a non-convex function of the power allocation among multiple users. We aim at solving the revenue maximization problem. We propose to decouple the problem into three optimization problems and employ alternating optimization algorithm to solve the problem. Simulation results show the proposed price-based power allocation scheme outperforms the uniform power allocation scheme.</description><identifier>ISSN: 2162-2337</identifier><identifier>EISSN: 2162-2345</identifier><identifier>DOI: 10.1109/LWC.2016.2613972</identifier><identifier>CODEN: IWCLAF</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Alternating optimization ; Base stations ; Cellular communication ; Computer simulation ; Downlink ; Economic models ; Game theory ; NOMA ; non-orthogonal multiple access (NOMA) ; Nonorthogonal multiple access ; Optimization ; power allocation ; Resource management ; Revenue ; Stackelberg game ; Wireless communication ; Wireless networks</subject><ispartof>IEEE wireless communications letters, 2016-12, Vol.5 (6), p.664-667</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2016</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-1edc28f879915512007d94aaf32b35faf5e6e0473cc42bc50ec00def8f6006fb3</citedby><cites>FETCH-LOGICAL-c291t-1edc28f879915512007d94aaf32b35faf5e6e0473cc42bc50ec00def8f6006fb3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7577823$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7577823$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Li, Chongyang</creatorcontrib><creatorcontrib>Zhang, Qi</creatorcontrib><creatorcontrib>Li, Quanzhong</creatorcontrib><creatorcontrib>Qin, Jiayin</creatorcontrib><title>Price-Based Power Allocation for Non-Orthogonal Multiple Access Systems</title><title>IEEE wireless communications letters</title><addtitle>LWC</addtitle><description>Non-orthogonal multiple access (NOMA) is expected to be a promising multiple access technique for future wireless networks. In this letter, considering a cellular downlink NOMA system, we use game theory to model the interaction between the base station and multiple users as a Stackelberg game. The base station, which acts as the leader of the Stackelberg game, chooses a price on per transmitted power allocated to each user to maximize its own revenue. Each user chooses an optimal power to maximize its utility after the base station sets prices. The revenue function of the base station is ultimately expressed as a non-convex function of the power allocation among multiple users. We aim at solving the revenue maximization problem. We propose to decouple the problem into three optimization problems and employ alternating optimization algorithm to solve the problem. Simulation results show the proposed price-based power allocation scheme outperforms the uniform power allocation scheme.</description><subject>Alternating optimization</subject><subject>Base stations</subject><subject>Cellular communication</subject><subject>Computer simulation</subject><subject>Downlink</subject><subject>Economic models</subject><subject>Game theory</subject><subject>NOMA</subject><subject>non-orthogonal multiple access (NOMA)</subject><subject>Nonorthogonal multiple access</subject><subject>Optimization</subject><subject>power allocation</subject><subject>Resource management</subject><subject>Revenue</subject><subject>Stackelberg game</subject><subject>Wireless communication</subject><subject>Wireless networks</subject><issn>2162-2337</issn><issn>2162-2345</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1LAzEQhoMoWGrvgpcFz1vzsfk61qJVqLag4jGk2Ylu2TY12VL6701p6VxmDs87vDwI3RI8JATrh-n3eEgxEUMqCNOSXqAeJYKWlFX88nwzeY0GKS1xHoEJJaqHJvPYOCgfbYK6mIcdxGLUtsHZrgnrwodYvId1OYvdb_gJa9sWb9u2azYtFCPnIKXiY586WKUbdOVtm2Bw2n309fz0OX4pp7PJ63g0LR3VpCsJ1I4qr6TWhHNCMZa1rqz1jC4Y99ZzEIAryZyr6MJxDA7jGrzyInf2C9ZH98e_mxj-tpA6swzbmIslQxTHlEmlRabwkXIxpBTBm01sVjbuDcHmYMxkY-ZgzJyM5cjdMdIAwBmXXEqVzf0DgW9mHA</recordid><startdate>20161201</startdate><enddate>20161201</enddate><creator>Li, Chongyang</creator><creator>Zhang, Qi</creator><creator>Li, Quanzhong</creator><creator>Qin, Jiayin</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope></search><sort><creationdate>20161201</creationdate><title>Price-Based Power Allocation for Non-Orthogonal Multiple Access Systems</title><author>Li, Chongyang ; Zhang, Qi ; Li, Quanzhong ; Qin, Jiayin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-1edc28f879915512007d94aaf32b35faf5e6e0473cc42bc50ec00def8f6006fb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Alternating optimization</topic><topic>Base stations</topic><topic>Cellular communication</topic><topic>Computer simulation</topic><topic>Downlink</topic><topic>Economic models</topic><topic>Game theory</topic><topic>NOMA</topic><topic>non-orthogonal multiple access (NOMA)</topic><topic>Nonorthogonal multiple access</topic><topic>Optimization</topic><topic>power allocation</topic><topic>Resource management</topic><topic>Revenue</topic><topic>Stackelberg game</topic><topic>Wireless communication</topic><topic>Wireless networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Chongyang</creatorcontrib><creatorcontrib>Zhang, Qi</creatorcontrib><creatorcontrib>Li, Quanzhong</creatorcontrib><creatorcontrib>Qin, Jiayin</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE/IET Electronic Library</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE wireless communications letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Li, Chongyang</au><au>Zhang, Qi</au><au>Li, Quanzhong</au><au>Qin, Jiayin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Price-Based Power Allocation for Non-Orthogonal Multiple Access Systems</atitle><jtitle>IEEE wireless communications letters</jtitle><stitle>LWC</stitle><date>2016-12-01</date><risdate>2016</risdate><volume>5</volume><issue>6</issue><spage>664</spage><epage>667</epage><pages>664-667</pages><issn>2162-2337</issn><eissn>2162-2345</eissn><coden>IWCLAF</coden><abstract>Non-orthogonal multiple access (NOMA) is expected to be a promising multiple access technique for future wireless networks. In this letter, considering a cellular downlink NOMA system, we use game theory to model the interaction between the base station and multiple users as a Stackelberg game. The base station, which acts as the leader of the Stackelberg game, chooses a price on per transmitted power allocated to each user to maximize its own revenue. Each user chooses an optimal power to maximize its utility after the base station sets prices. The revenue function of the base station is ultimately expressed as a non-convex function of the power allocation among multiple users. We aim at solving the revenue maximization problem. We propose to decouple the problem into three optimization problems and employ alternating optimization algorithm to solve the problem. Simulation results show the proposed price-based power allocation scheme outperforms the uniform power allocation scheme.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/LWC.2016.2613972</doi><tpages>4</tpages></addata></record> |
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| source | IEEE/IET Electronic Library |
| subjects | Alternating optimization Base stations Cellular communication Computer simulation Downlink Economic models Game theory NOMA non-orthogonal multiple access (NOMA) Nonorthogonal multiple access Optimization power allocation Resource management Revenue Stackelberg game Wireless communication Wireless networks |
| title | Price-Based Power Allocation for Non-Orthogonal Multiple Access Systems |
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