Vector quantization and signal compression
Vector quantization and signal compression
Error Control Coding, Second Edition
Error Control Coding, Second Edition
IEEE Transactions on Information Theory - Part 1
Bounded-distance decoding: algorithms, decision regions, and pseudo nearest neighbors
IEEE Transactions on Information Theory
On the complexity of bounded distance decoding for the AWGN channel
IEEE Transactions on Information Theory
An adaptive two-stage algorithm for ML and sub-ML decoding of binary linear block codes
IEEE Transactions on Information Theory
Progressive transmission of images over memoryless noisy channels
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper, a communication system using vector quantization (VQ) and channel coding is considered. Here, a design scheme has been proposed to optimize source codebooks in the transmitter and the receiver. In the proposed algorithm, the overall distortion including both the quantization error and channel distortion is minimized. The proposed algorithm is different from the previous work by the facts that the channel encoder is used in the VQ-based communication system, and the source VQ codebook used in the transmitter is different from the one used by the receiver, i.e. asymmetric VQ system. And the bounded-distance decoding (BDD) technique is used to combat the ambiguousness in the channel decoder. We can see from the computer simulations that the optimized system based on the proposed algorithm outperforms a conventional system based on a symmetric VQ codebook. Also, the proposed algorithm enables a reliable image communication over noisy channels.