(2024). Optimal Power Control for Joint Wireless Information-Energy Transfers in Energy Harvesting Networks. In 2024 IEEE 29th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD) (pp. 1–6). IEEE. https://doi.org/10.1109/camad62243.2024.10942874
Περίληψη
In this paper, we propose a new framework for power control, routing-scheduling and congestion control for wireless networks relying on joint information-energy transfers, with the goal of maximally using the network capacity while ensuring efficient use of the available limited energy. Assuming that wireless devices can exchange data and energy, as well as harvest energy from their environments, we propose a convex problem formulation and employ dual decomposition combined with a maximum weight matching approach for the solution. The results demonstrate that controlling the power at which dataenergy should be exchanged in the scheduled links increases the source rates, while efficiently exploiting the available harvested enerzy over the network.
- DOI
- 10.1109/camad62243.2024.10942874
- Τύπος
- Άρθρο σε Πρακτικά Συνεδρίου
- Έτος
- 2024
Σύνδεσμοι
BibTeX
@inproceedings{kallitsis2024optimal,
title = {Optimal Power Control for Joint Wireless Information-Energy Transfers in Energy Harvesting Networks},
author = {Georgios Kallitsis and Eleni Stai and Vasileios Karyotis and Symeon Papavassiliou},
url = {https://doi.org/10.1109/camad62243.2024.10942874},
doi = {10.1109/camad62243.2024.10942874},
year = {2024},
date = {2024-01-01},
booktitle = {2024 IEEE 29th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)},
pages = {1–6},
publisher = {IEEE},
abstract = {In this paper, we propose a new framework for power control, routing-scheduling and congestion control for wireless networks relying on joint information-energy transfers, with the goal of maximally using the network capacity while ensuring efficient use of the available limited energy. Assuming that wireless devices can exchange data and energy, as well as harvest energy from their environments, we propose a convex problem formulation and employ dual decomposition combined with a maximum weight matching approach for the solution. The results demonstrate that controlling the power at which dataenergy should be exchanged in the scheduled links increases the source rates, while efficiently exploiting the available harvested enerzy over the network.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}