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dc.contributor.authorLi, William Wei-Liang
dc.contributor.authorZhang, Ying Jun (Angela)
dc.contributor.authorSo, Anthony Man-Cho
dc.contributor.authorWin, Moe Z.
dc.date.accessioned2011-11-29T19:33:53Z
dc.date.available2011-11-29T19:33:53Z
dc.date.issued2010-07
dc.date.submitted2009-07
dc.identifier.issn1053-587X
dc.identifier.urihttp://hdl.handle.net/1721.1/67306
dc.description.abstractAdaptive orthogonal frequency division multiple access (OFDMA) has recently been recognized as a promising technique for providing high spectral efficiency in future broadband wireless systems. The research over the last decade on adaptive OFDMA systems has focused on adapting the allocation of radio resources, such as subcarriers and power, to the instantaneous channel conditions of all users. However, such “fast” adaptation requires high computational complexity and excessive signaling overhead. This hinders the deployment of adaptive OFDMA systems worldwide. This paper proposes a slow adaptive OFDMA scheme, in which the subcarrier allocation is updated on a much slower timescale than that of the fluctuation of instantaneous channel conditions. Meanwhile, the data rate requirements of individual users are accommodated on the fast timescale with high probability, thereby meeting the requirements except occasional outage. Such an objective has a natural chance constrained programming formulation, which is known to be intractable. To circumvent this difficulty, we formulate safe tractable constraints for the problem based on recent advances in chance constrained programming. We then develop a polynomial-time algorithm for computing an optimal solution to the reformulated problem. Our results show that the proposed slow adaptation scheme drastically reduces both computational cost and control signaling overhead when compared with the conventional fast adaptive OFDMA. Our work can be viewed as an initial attempt to apply the chance constrained programming methodology to wireless system designs. Given that most wireless systems can tolerate an occasional dip in the quality of service, we hope that the proposed methodology will find further applications in wireless communications.en_US
dc.description.sponsorshipUniversity Grants Committee (Hong Kong, China) (Competitive Earmarked Research Grant (Project number 418707))en_US
dc.description.sponsorshipUniversity Grants Committee (Hong Kong, China) (Competitive Earmarked Research Grant (Project number 419509))en_US
dc.description.sponsorshipShun Hing Institute of Advanced Engineering (Hong Kong, China)en_US
dc.description.sponsorshipChinese University of Hong Kongen_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant ECCS-0636519)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (grant ECCS-0901034)en_US
dc.description.sponsorshipUnited States. Office of Naval Research (Presidential Early Career Award for Scientists and engineers (PECASE) N00014-09-1-0435)en_US
dc.description.sponsorshipMassachusetts Institute of Technology. Institute for Soldier Nanotechnologiesen_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/tsp.2010.2046434en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceIEEEen_US
dc.titleSlow Adaptive OFDMA Systems Through Chance Constrained Programmingen_US
dc.typeArticleen_US
dc.identifier.citationLi, William Wei-Liang et al. “Slow Adaptive OFDMA Systems Through Chance Constrained Programming.” IEEE Transactions on Signal Processing 58 (2010): 3858-3869. ©2011 IEEE.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronauticsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Laboratory for Information and Decision Systemsen_US
dc.contributor.approverWin, Moe Z.
dc.contributor.mitauthorWin, Moe Z.
dc.relation.journalIEEE Transactions on Signal Processingen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsLi, William Wei-Liang; Zhang, Ying Jun (Angela); So, Anthony Man-Cho; Win, Moe Z.en
dc.identifier.orcidhttps://orcid.org/0000-0002-8573-0488
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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