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dc.contributor.authorMoser, Stefan M.en_US
dc.date.accessioned2019-04-02T05:57:52Z-
dc.date.available2019-04-02T05:57:52Z-
dc.date.issued2012-01-01en_US
dc.identifier.issn0018-9448en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TIT.2011.2169541en_US
dc.identifier.urihttp://hdl.handle.net/11536/150441-
dc.description.abstractThis paper investigates a channel model describing optical communication based on intensity modulation. It is assumed that the main distortion is caused by additive Gaussian noise, however, with a noise variance depending on the current signal strength. Both the high-power and low-power asymptotic capacities under simultaneously both a peak-power and an average-power constraint are derived. The high-power results are based on a new firm (nonasymptotic) lower bound and a new asymptotic upper bound. The upper bound relies on a dual expression for channel capacity and the notion of capacity-achieving input distributions that escape to infinity. The lower bound is based on a new lower bound on the differential entropy of the channel output in terms of the differential entropy of the channel input. The low-power results make use of a theorem by Prelov and van der Meulen.en_US
dc.language.isoen_USen_US
dc.subjectChannel capacityen_US
dc.subjectdirect detectionen_US
dc.subjectescaping to infinityen_US
dc.subjectGaussian noiseen_US
dc.subjecthigh signal-to-noise ratio (SNR)en_US
dc.subjectlow signal-to-noise ratio (SNR)en_US
dc.subjectoptical communicationen_US
dc.titleCapacity Results of an Optical Intensity Channel With Input-Dependent Gaussian Noiseen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/TIT.2011.2169541en_US
dc.identifier.journalIEEE TRANSACTIONS ON INFORMATION THEORYen_US
dc.citation.volume58en_US
dc.citation.spage207en_US
dc.citation.epage223en_US
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.identifier.wosnumberWOS:000298989200017en_US
dc.citation.woscount42en_US
Appears in Collections:Articles