M. Leinonen, M. Codreanu, M. Juntti and G. Kramer, "Rate-Distortion Performance of Lossy Compressed Sensing of Sparse Sources," in IEEE Transactions on Communications, vol. 66, no. 10, pp. 4498-4512, Oct. 2018. doi: 10.1109/TCOMM.2018.2834349
Rate-distortion performance of lossy compressed sensing of sparse sources
|Author:||Leinonen, Markus1; Codreanu, Marian1; Juntti, Markku1;|
1Centre for Wireless Communications–Radio Technologies, University of Oulu
2Institute for Communications Engineering, Technical University of Munich
|Online Access:||PDF Full Text (PDF, 1.2 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2018112348888
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2018-11-23
We investigate lossy compressed sensing (CS) of a hidden, or remote, source, where a sensor observes a sparse information source indirectly. The compressed noisy measurements are communicated to the decoder for signal reconstruction with the aim to minimize the mean square error distortion. An analytically tractable lower bound to the remote rate-distortion function (RDF), i.e., the conditional remote RDF, is derived by providing support side information to the encoder and decoder. For this setup, the best encoder separates into an estimation step and a transmission step. A variant of the Blahut-Arimoto algorithm is developed to numerically approximate the remote RDF. Furthermore, a novel entropy coding based quantized CS method is proposed. Numerical results illustrate the main rate-distortion characteristics of the lossy CS, and compare the performance of practical quantized CS methods against the proposed limits.
IEEE transactions on communications
|Pages:||4498 - 4512|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
The work of M. Leinonen, M. Codreanu, and M. Juntti was ﬁnancially supported by the Academy of Finland. The work of G. Kramer was supported by an Alexander von Humboldt Professorship through the German Federal Ministry of Education and Research.
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