A Communication Channel Modeled on Contagion

dc.contributor.authorAlajaji, Fadyen_US
dc.contributor.authorFuja, Tom E.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:54:36Z
dc.date.available2007-05-23T09:54:36Z
dc.date.issued1993en_US
dc.description.abstractWe introduce a binary additive communication channel with memory. The noise process of the channel is generated according to the contagion model of George Polya; our motivation is the empirical observation of Stapper et. al. that defects in semiconductor memories are well described by distributions derived from Polya's urn scheme. The resulting channel is stationary but not ergodic, and it has many interesting properties.<P>We First derive a maximum likelihood (ML) decoding algorithm for the channel; it turns out that ML decoding is equivalent to decoding a received vector onto either the closest codeword or the codeword that is farthest away, depending on whether an ﲡpparent epidemic has occurred. We next show that the Poly-contagion channel is an ﲡveraged channel in the sense of Ahlswede (and others) and that its capacity is zero. We then demonstrate that the Poly- contagion channel is a counter-example to the adage, ﲭemory cannot decrease capacity ; the capacity of the Poly-contagion channel is actually less than that of the associated memoryless channel. Finally, we consider a finite-memory version of the Poly-contagion model; this channel is (unlike the original) ergodic with a non-zero capacity that increases with increasing memory.en_US
dc.format.extent939337 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5422
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1993-78en_US
dc.subjectchannels with memoryen_US
dc.subjectadditive noiseen_US
dc.subjectcapacityen_US
dc.subjectdigital communicationsen_US
dc.subjectinformation theoryen_US
dc.subjectCommunication en_US
dc.subjectSignal Processing Systemsen_US
dc.titleA Communication Channel Modeled on Contagionen_US
dc.typeTechnical Reporten_US

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