Signal reconstruction performance under quantized noisy compressed sensing
Leinonen, Markus; Codreanu, Marian; Juntti, Markku (2019-05-13)
M. Leinonen, M. Codreanu and M. Juntti, "Signal Reconstruction Performance Under Quantized Noisy Compressed Sensing," 2019 Data Compression Conference (DCC), Snowbird, UT, USA, 2019, pp. 586-586. doi: 10.1109/DCC.2019.00098
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https://urn.fi/URN:NBN:fi-fe2019060318153
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Abstract
We study rate-distortion (RD) performance of various single-sensor compressed sensing (CS) schemes for acquiring sparse signals via quantized/encoded noisy linear measurements, motivated by low-power sensor applications. For such a quantized CS (QCS) context, the paper combines and refines our recent advances in algorithm designs and theoretical analysis. Practical symbol-by-symbol quantizer based QCS methods of different compression strategies are proposed. The compression limit of QCS — the remote RDF — is assessed through an analytical lower bound and a numerical approximation method. Simulation results compare the RD performances of different schemes.
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