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dc.contributor.authorOlama, M. M.en
dc.contributor.authorDjouadi, S. M.en
dc.contributor.authorCharalambous, Charalambos D.en
dc.creatorOlama, M. M.en
dc.creatorDjouadi, S. M.en
dc.creatorCharalambous, Charalambos D.en
dc.date.accessioned2019-04-08T07:47:31Z
dc.date.available2019-04-08T07:47:31Z
dc.date.issued2009
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/44414
dc.description.abstractMobile-to-mobile networks are characterized by node mobility that makes the propagation environment time varying and subject to fading. As a consequence, the statistical characteristics of the received signal vary continuously, giving rise to a Doppler power spectral density (DPSD) which varies from one observation instant to the next. The current models do not capture and track the time varying characteristics. This paper is concerned with dynamical modeling of time varying mobile-to-mobile channels, parameter estimation and identification from received signal measurements. The evolution of the propagation environment is described by stochastic differential equations, whose parameters can be determined by approximating the band-limited DPSD using the Gauss-Newton method. However, since the DPSD is not available online, we propose to use a filter-based expectation maximization algorithm and Kalman filter to estimate the channel parameters and states, respectively. The scheme results in a finite dimensional filter which only uses the first and second order statistics. The algorithm is recursive allowing the inphase and quadrature components and parameters to be estimated online from received signal measurements. The algorithms are tested using experimental data collected from moving sensor nodes in indoor and outdoor environments demonstrating the method's viability. © 2006 IEEE.en
dc.sourceIEEE Transactions on Wireless Communicationsen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-65949102543&doi=10.1109%2fTWC.2009.071068&partnerID=40&md5=765c8c17014d8faee83baa2c4b421cb8
dc.subjectKalman filteren
dc.subjectOptimizationen
dc.subjectRandom processesen
dc.subjectDifferential equationsen
dc.subjectStochastic control systemsen
dc.subjectStochastic differential equationsen
dc.subjectMeasurement theoryen
dc.subjectWireless networksen
dc.subjectMobile telecommunication systemsen
dc.subjectSignal processingen
dc.subjectParameter estimationen
dc.subjectControl theoryen
dc.subjectMaximum principleen
dc.subjectFading channelsen
dc.subjectKalman filtersen
dc.subjectFading (radio)en
dc.subjectSensor nodesen
dc.subjectTelecommunication equipmenten
dc.subjectEstimation and identificationen
dc.subjectDoppler spectral densityen
dc.subjectExpectation maximizationen
dc.subjectMulipath fading channelsen
dc.subjectNewton-raphson methoden
dc.subjectTime varying networksen
dc.titleStochastic differential equations for modeling, estimation and identification of mobile-to-mobile communication channelsen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1109/TWC.2009.071068
dc.description.volume8
dc.description.issue4
dc.description.startingpage1754
dc.description.endingpage1763
dc.author.facultyΠολυτεχνική Σχολή / Faculty of Engineering
dc.author.departmentΤμήμα Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών / Department of Electrical and Computer Engineering
dc.type.uhtypeArticleen
dc.source.abbreviationIEEE Trans.Wireless Commun.en
dc.contributor.orcidCharalambous, Charalambos D. [0000-0002-2168-0231]
dc.gnosis.orcid0000-0002-2168-0231


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