{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:31:40Z","timestamp":1750307500902,"version":"3.41.0"},"reference-count":18,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2009,9,25]],"date-time":"2009-09-25T00:00:00Z","timestamp":1253836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGMOBILE Mob. Comput. Commun. Rev."],"published-print":{"date-parts":[[2009,9,25]]},"abstract":"<jats:p>Cognitive radio network (CRN) has created a significant research interest due to the unique opportunistic spectrum sharing of the channels when not used by the licensed users (known as white spaces). In this paper, we make a unique endeavor in developing a Game theoretic spectrum sharing strategy to compute maximum channel capacity under the following constraints: (i) quality of an available channel with respect to its neighboring channels and (ii) transmission power limitation so as not to interfere with licensed users. Such maximization is achieved by allocating multiple available channels to each unlicensed user. The availability of channels differs from one user to another depending upon its location with respect to the transmission range of the licensed user. We discuss allocation strategies of unused white spaces among the cognitive users to maximize the channel capacity. We introduce a cooperative N-person Game among N unlicensed users in a CRN to identify strategies that help achieve Nash equilibria. In addition, the knowledge of idle durations and transmission rate of available channels can also be utilized for designing an efficient spectrum allocation technique. Hence, with this information, we develop another Game theoretic strategy to allocate a single channel to each unlicensed user and identify the strategy which achieves Nash equilibrium. Extensive experimental results of the strategies proposed are also presented.<\/jats:p>","DOI":"10.1145\/1621076.1621078","type":"journal-article","created":{"date-parts":[[2009,10,6]],"date-time":"2009-10-06T18:18:59Z","timestamp":1254853139000},"page":"2-13","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Channel capacity maximization in cooperative cognitive radio networks using game theory"],"prefix":"10.1145","volume":"13","author":[{"given":"Chittabrata","family":"Ghosh","sequence":"first","affiliation":[{"name":"University of Cincinnati, Cincinnati"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dharma P.","family":"Agrawal","sequence":"additional","affiliation":[{"name":"University of Cincinnati, Cincinnati"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marepalli B.","family":"Rao","sequence":"additional","affiliation":[{"name":"University of Cincinnati, Cincinnati"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2009,9,25]]},"reference":[{"volume-title":"Elsevier","year":"2007","author":"Fette B.","key":"e_1_2_1_1_1"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2007.070403"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2007.358854"},{"key":"e_1_2_1_4_1","unstructured":"G. Owen Game Theory. Academic Press 1995.  G. Owen Game Theory. Academic Press 1995."},{"key":"e_1_2_1_5_1","unstructured":"M.J. Osborne An Introduction to Game Theory. Oxford University Press 2004.  M.J. Osborne An Introduction to Game Theory. 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