Multi-objective Optimization of Cognitive Radio Networks
<|reference_start|>Multi-objective Optimization of Cognitive Radio Networks: New generation networks, based on Cognitive Radio technology, allow dynamic allocation of the spectrum, alleviating spectrum scarcity. These networks also have a resilient potential for dynamic operation for energy saving. In this paper, we present a novel wireless network optimization algorithm for cognitive radio networks based on a cloud sharing-decision mechanism. Three Key Performance Indicators (KPIs) were optimized: spectrum usage, power consumption, and exposure of human beings. For a realistic suburban scenario in Ghent city, Belgium, we determine the optimality among the KPIs. Compared to a traditional Cognitive Radio network design, our optimization algorithm for the cloud-based architecture reduced the network power consumption by 27.5%, the average global exposure by 34.3%, and spectrum usage by 34.5% at the same time. Even for the worst optimization case, our solution performs better than the traditional architecture by 4.8% in terms of network power consumption, 7.3% in terms of spectrum usage and 4.3% in terms of global exposure.<|reference_end|>
@article{alonso2024multi-objective,
    title={Multi-objective Optimization of Cognitive Radio Networks},
    author={Rodney Martinez Alonso, David Plets, Margot Deruyck, Luc Martens,
  Glauco Guillen Nieto, Wout Joseph},
    journal={Computer Networks, Volume 184, 2021},
    year={2024},
    doi={10.1016/j.comnet.2020.107651},
    archivePrefix={arXiv},
    eprint={2405.02694},
    primaryClass={cs.NI}
}