期刊
COMPUTER NETWORKS
卷 184, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.comnet.2020.107651
关键词
Cognitive radio; Spectrum efficiency; Network optimization
类别
资金
- Special Research Fund (BOF) of Ghent University, Belgium
This paper presents a novel wireless network optimization algorithm for cognitive radio networks based on a cloud sharing-decision mechanism, which significantly reduces network power consumption, exposure, and spectrum usage. Compared to traditional designs, the cloud-based architecture achieved better results even in worst-case scenarios.
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. For a realistic suburban scenario in Ghent city, Belgium, we determine the optimal trade-off between 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-case optimization (worst achieved result of a single KPI), 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.
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