AdaptCast: An integrated source to transmission scheme for wireless sensor networks
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AdaptCast.pdf
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462.62 KB
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Author(s)
Angelopoulos, Georgios
Medard, Muriel
Chandrakasan, Anantha P.
Date Issued
June 2015
Journal
Proceedings of the 2015 IEEE International Conference on Communications (ICC)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Angelopoulos, Georgios, Muriel Medard, and Anantha P. Chandrakasan. “AdaptCast: An Integrated Source to Transmission Scheme for Wireless Sensor Networks.” 2015 IEEE International Conference on Communications (ICC) (June 2015).
Version
Author's final manuscript
Abstract
This paper introduces AdaptCast, an integrated source to transmission scheme for wireless sensor networks (WSNs) that efficiently represents collected data and increases their robustness against channel errors across a wide range of signal to noise (SNR) values in a rateless fashion. AdaptCast leverages sparsity inherent in the majority of physical signals in order to parsimoniously represent them without relying on a specific signal model. The proposed scheme does not suffer from the sudden degradation in the tradeoff between distortion and SNR of rated channel coding schemes due to its direct, relative bit importance preserving modulation mapping. In addition, it does not require continuous feedback or channel state information (CSI) as a result of its rateless operation. Apart from point-to-point transmission, AdaptCast enables efficient multicasting to a set of nodes, serving each of them at a rate commensurate to its individual channel quality. We demonstrate AdaptCast's application-independent operation by using several typical signals captured in WSNs. Based on our analysis and simulation results, considering the tradeoff between distortion and channel quality, AdaptCast performs close in a point-to-point scenario to an idealized layered transmission scheme with instantaneous CSI and offers significant benefits in multiuser settings.
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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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/ICC.2015.7248766
