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Receiver-Only Optimized Vector Quantization for Noisy Channels

Murthy, Chandra R (2008) Receiver-Only Optimized Vector Quantization for Noisy Channels. In: 19th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, SEP 15-18, 2008, Cannes, FRANCE, pp. 1940-1944.

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Abstract

This paper considers the design and analysis of a filter at the receiver of a source coding system to mitigate the excess Mean-Squared Error (MSE) distortion caused due to channel errors. It is assumed that the source encoder is channel-agnostic, i.e., that a Vector Quantization (VQ) based compression designed for a noiseless channel is employed. The index output by the source encoder is sent over a noisy memoryless discrete symmetric channel, and the possibly incorrect received index is decoded by the corresponding VQ decoder. The output of the VQ decoder is processed by a receive filter to obtain an estimate of the source instantiation. In the sequel, the optimum linear receive filter structure to minimize the overall MSE is derived, and shown to have a minimum-mean squared error receiver type structure. Further, expressions are derived for the resulting high-rate MSE performance. The performance is compared with the MSE obtained using conventional VQ as well as the channel optimized VQ. The accuracy of the expressions is demonstrated through Monte Carlo simulations.

Item Type: Conference Paper
Additional Information: Copyright 2008 IEEE. Personal use of this material is permitted.However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords: Source coding;data compression;vector quantization
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 12 Apr 2011 07:52
Last Modified: 12 Apr 2011 07:52
URI: http://eprints.iisc.ernet.in/id/eprint/36773

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