Channel-Optimized Vector Quantizer Design for Compressed Sensing Measurements

Amirpasha Shirazinia; Saikat Chatterjee; Mikael Skoglund

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arXiv · 1404.7648

Channel-Optimized Vector Quantizer Design for Compressed Sensing Measurements

Amirpasha Shirazinia·Saikat Chatterjee·Mikael Skoglund

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Abstract

We consider vector-quantized (VQ) transmission of compressed sensing (CS) measurements over noisy channels. Adopting mean-square error (MSE) criterion to measure the distortion between a sparse vector and its reconstruction, we derive channel-optimized quantization principles for encoding CS measurement vector and reconstructing sparse source vector. The resulting necessary optimal conditions are used to develop an algorithm for training channel-optimized vector quantization (COVQ) of CS measurements by taking the end-to-end distortion measure into account.

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Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund. 2014-04-30. Channel-Optimized Vector Quantizer Design for Compressed Sensing Measurements. https://arxiv.org/abs/1404.7648

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