Quantization Over Discrete Noisy Channels Using Rate-One Convolutional Codes

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dc.contributor.authorPhamdo, N.en_US
dc.contributor.authorFarvardin, Narimanen_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:53:49Z
dc.date.available2007-05-23T09:53:49Z
dc.date.issued1993en_US
dc.description.abstractWe consider high-rate scalar quantization of a memoryless source for transmission over a binary symmetric channel. It is assumed that, due to its suboptimality, the quantizer's output is redundant. Our aim is to make use of this redundancy to combat channel noise. A rate-one convolutional code is introduced to convert this natural redundancy into a usable form. at the receiver, a maximum a posteriori decoder is employed. An upper bound on the average distortion of the proposed system is derived. An approximation of this bound is computable and we search for that convolutional code which minimizes the approximate upper bound. simulation results for a generalized Gaussian source with parameter a = 0.5 at rate 4 bits/sample and channel crossover provability 0.005 show improvement of 11.9 dB in signal-to-noise ratio over the Lloyd-Max quantizer and 4.6 dB over Farvardin and Vaishampayan's channel-optimized scalar quantizer.en_US
dc.format.extent675723 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5380
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1993-35en_US
dc.subjectconvolutional codeen_US
dc.subjectnon-equiprobable memoryless dataen_US
dc.subjectcombined source-channel codingen_US
dc.subjectCommunication en_US
dc.subjectSignal Processing Systemsen_US
dc.titleQuantization Over Discrete Noisy Channels Using Rate-One Convolutional Codesen_US
dc.typeTechnical Reporten_US

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