Empirical rate-distortion study of compressive sensing-based joint source-channel coding
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Author(s)
Rambeloarison, Muriel L.
Feizi-Khankandi, Soheil
Angelopoulos, Georgios
Medard, Muriel
Date Issued
November 2012
Journal
Proceedings of the 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Rambeloarison, Muriel L., Soheil Feizi, Georgios Angelopoulos, and Muriel Medard. “Empirical Rate-Distortion Study of Compressive Sensing-Based Joint Source-Channel Coding.” 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR) (November 2012).
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Author's final manuscript
Abstract
In this paper, we present an empirical rate-distortion study of a communication scheme that uses compressive sensing (CS) as joint source-channel coding. We investigate the rate-distortion behavior of both point-to-point and distributed cases. First, we propose an efficient algorithm to find the I[subscript 1]-regularization parameter that is required by the Least Absolute Shrinkage and Selection Operator which we use as a CS decoder. We then show that, for a point-to-point channel, the rate distortion follows two distinct regimes: the first one corresponds to an almost constant distortion, and the second one to a rapid distortion degradation, as a function of rate. This constant distortion increases with both increasing channel noise level and sparsity level, but at a different gradient depending on the distortion measure. In the distributed case, we investigate the rate-distortion behavior when sources have temporal and spatial dependencies. We show that, taking advantage of both spatial and temporal correlations over merely considering the temporal correlation between the signals allows us to achieve an average of a factor of approximately 2.5× improvement in the rate-distortion behavior of the joint source-channel coding scheme.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Research Laboratory of Electronics
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DOI of Published Version
https://doi.org/10.1109/ACSSC.2012.6489217
