Quantization of Memoryless and Gauss-Markov Sources Over Binary Markov Channels

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dc.contributor.authorPhamdo, N.en_US
dc.contributor.authorAlajaji, Fadyen_US
dc.contributor.authorFarvardin, Narimanen_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:57:15Z
dc.date.available2007-05-23T09:57:15Z
dc.date.issued1994en_US
dc.description.abstractJoint source-channel coding for stationary memoryless and Gauss- Markov sources and binary Markov channels is considered. The channel is an additive-noise channel where the noise process is an M-th order Markov chain. Two joint source-channel coding schemes are considered. The first is a channel-optimized vector quantizer - optimized for both source and channel. The second scheme consists of a scalar quantizer and a maximum a posteriori detector. In this scheme, it is assumed that the scalar quantizer output has residual redundancy that can be exploited by the maximum a posteriori detector to combat the correlated channel noise. These two schemes are then compared against two schemes which use channel interleaving. Numerical results show that the proposed schemes outperform the interleaving schemes. For very noisy channels with high noise correlation, gains of 4 to 5 dB in signal-to-noise ratio are possible.en_US
dc.format.extent959138 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5549
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1994-79en_US
dc.subjectdata compressionen_US
dc.subjectdetectionen_US
dc.subjectdigital communicationsen_US
dc.subjectinformation theoryen_US
dc.subjectIntelligent Signal Processing en_US
dc.subjectCommunications Systemsen_US
dc.titleQuantization of Memoryless and Gauss-Markov Sources Over Binary Markov Channelsen_US
dc.typeTechnical Reporten_US

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