SPAWC · 2016
Fundamental limits and achievable strategies for low energy compressed sensing with applications in wireless communication
IEEE International Workshop on Signal Processing Advances in Wireless Communications
What energy is required to decode a sparse signal?
A communication complexity model measures the energy required to move information during support recovery. Upper and lower bounds show how adaptive message scheduling can reduce decoding energy, with an application to multiuser detection in wireless systems.
Research themes
Cite this paper
Tongxin Li, Mayank Bakshi, Pulkit Grover. Fundamental limits and achievable strategies for low energy compressed sensing with applications in wireless communication. IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2016. https://doi.org/10.1109/SPAWC.2016.7536775
BibTeX
@inproceedings{tongxin-energy-sensing,
title = {{Fundamental limits and achievable strategies for low energy compressed sensing with applications in wireless communication}},
author = {Tongxin Li and Mayank Bakshi and Pulkit Grover},
year = {2016},
booktitle = {IEEE International Workshop on Signal Processing Advances in Wireless Communications},
url = {https://doi.org/10.1109/SPAWC.2016.7536775},
doi = {10.1109/SPAWC.2016.7536775}
}
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