Multiuser detection in a dynamic environment — Part II: Joint user identification and parameter estimation

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• dc.contributor.author Angelosante, Danieleca
• dc.contributor.author Biglieri, Ezioca
• dc.contributor.author Lops, Marcoca
• dc.contributor.other Universitat Pompeu Fabraca
• dc.date.accessioned 2013-02-27T15:45:09Z
• dc.date.available 2013-02-27T15:45:09Z
• dc.date.issued 2009ca
• dc.description.abstract The problem of jointly estimating the number, the identities, and the data of active users in a time-varying multiuser environment was examined in a companion paper (IEEE Trans. Information Theory, vol. 53, no. 9, September 2007), at whose core was the use of the theory of finite random sets on countable spaces. Here we extend that theory to encompass the more general problem of estimating unknown continuous parameters of the active-user signals. This problem is solved here by applying the theory of random finite sets constructed on hybrid spaces. We do/nso deriving Bayesian recursions that describe the evolution with/ntime of a posteriori densities of the unknown parameters and data./nUnlike in the above cited paper, wherein one could evaluate the/nexact multiuser set posterior density, here the continuous-parameter Bayesian recursions do not admit closed-form expressions. To circumvent this difficulty, we develop numerical approximations/nfor the receivers that are based on Sequential Monte Carlo (SMC)/nmethods (“particle filtering”). Simulation results, referring to a/ncode-divisin multiple-access (CDMA) system, are presented to/nillustrate the theory.
• dc.description.sponsorship The work of E. Biglieri was supported by the STREP Project No. IST-026905 (MASCOT) within the 6th framework program of the European Commission, and by the Spanish Ministry of Education and Science under Project TEC2006-01428/TCM.
• dc.format.mimetype application/pdfca
• dc.identifier.citation Angelosante D, Biglieri E, Lops M. Multiuser detection in a dynamic environment — Part II: Joint user identification and parameter estimation. IEEE Trans. Inf. Theory. 2009; 55 (5): 2365-2374. DOI 10.1109/TIT.2009.2016008ca
• dc.identifier.doi http://dx.doi.org/10.1109/TIT.2009.2016008
• dc.identifier.issn 0018-9448ca
• dc.identifier.uri http://hdl.handle.net/10230/20434
• dc.language.iso engca
• dc.publisher Institute of Electrical and Electronics Engineers (IEEE)ca
• dc.relation.ispartof IEEE Transactions on Information Theory. 2009; 55 (5)
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP6/026905
• dc.rights © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works./nThe final published article can be found at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4839032ca
• dc.rights.accessRights info:eu-repo/semantics/openAccessca
• dc.subject.keyword Bayesian recursions
• dc.subject.keyword Multiuser detection
• dc.subject.keyword Particle filtering
• dc.subject.keyword Random-set theory
• dc.subject.other Montecarlo, Mètode de
• dc.subject.other Conjunts, Teoria de
• dc.subject.other Informació, Teoria de la
• dc.title Multiuser detection in a dynamic environment — Part II: Joint user identification and parameter estimationca
• dc.type info:eu-repo/semantics/articleca
• dc.type.version info:eu-repo/semantics/publishedVersionca