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Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/6030
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dc.contributor.authorUpadhyay, Prabhat Kumaren_US
dc.date.accessioned2022-03-17T01:00:00Z-
dc.date.accessioned2022-03-17T15:45:43Z-
dc.date.available2022-03-17T01:00:00Z-
dc.date.available2022-03-17T15:45:43Z-
dc.date.issued2016-
dc.identifier.citationTiwari, S. K., & Upadhyay, P. K. (2016). Maximum likelihood estimation of SNR for diffusion-based molecular communication. IEEE Wireless Communications Letters, 5(3), 320-323. doi:10.1109/LWC.2016.2553034en_US
dc.identifier.issn2162-2337-
dc.identifier.otherEID(2-s2.0-84976488665)-
dc.identifier.urihttps://doi.org/10.1109/LWC.2016.2553034-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/6030-
dc.description.abstractWe investigate the problem of estimation of a signal-to-noise ratio (SNR) measure for diffusion-based molecular communication (DMC) systems. Considering molecular concentration-encoded signal with residual noise, we present the SNR estimation using maximum likelihood principle with sampled observations. Moreover, we derive the Cramer-Rao lower bound and assess the performance of our proposed estimator in terms of its mean square error. Our analysis helps in designing a reliable DMC system with a memoryless receiver nanomachine. © 2016 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceIEEE Wireless Communications Lettersen_US
dc.subjectCramer-Rao boundsen_US
dc.subjectDiffusionen_US
dc.subjectMaximum likelihooden_US
dc.subjectMean square erroren_US
dc.subjectNanotechnologyen_US
dc.subjectSignal to noise ratioen_US
dc.subjectCramer Rao lower bounden_US
dc.subjectEncoded signalsen_US
dc.subjectMaximum likelihood Principleen_US
dc.subjectMolecular communicationen_US
dc.subjectMolecular concentrationen_US
dc.subjectNanomachinesen_US
dc.subjectSampled observationsen_US
dc.subjectSNR estimationen_US
dc.subjectMaximum likelihood estimationen_US
dc.titleMaximum Likelihood Estimation of SNR for Diffusion-Based Molecular Communicationen_US
dc.typeJournal Articleen_US
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