Channel-Optimized Vector Quantizer Design for Compressed Sensing   Measurements
  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. 
Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund
cs.IT math.IT