Channel-optimized Vector Quantizer Design for Compressed Sensing Measurements
2013 (English)In: 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2013, New York: IEEE , 2013, 4648-4652 p.Conference paper (Refereed)
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.
Place, publisher, year, edition, pages
New York: IEEE , 2013. 4648-4652 p.
, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, ISSN 1520-6149
Channel-optimized vector quantizer, com- pressed sensing, sparsity, channel, mean-square error
IdentifiersURN: urn:nbn:se:kth:diva-119085DOI: 10.1109/ICASSP.2013.6638541ISI: 000329611504162ScopusID: 2-s2.0-84890466070ISBN: 978-1-4799-0356-6ISBN: 978-1-4799-0355-9OAI: oai:DiVA.org:kth-119085DiVA: diva2:609437
38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP); Vancouver Convention & Exhibition Centre, Vancouver, Canada, May 26 - 31 2013
QC 201402252013-03-052013-03-052014-02-25Bibliographically approved