Research Article
Energy Efficiency Maximization for Green Cognitive Internet of Things with Energy Harvesting
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@INPROCEEDINGS{10.1007/978-3-030-32388-2_24, author={Xin Liu and Xueyan Zhang and Weidang Lu and Mudi Xiong}, title={Energy Efficiency Maximization for Green Cognitive Internet of Things with Energy Harvesting}, proceedings={Machine Learning and Intelligent Communications. 4th International Conference, MLICOM 2019, Nanjing, China, August 24--25, 2019, Proceedings}, proceedings_a={MLICOM}, year={2019}, month={10}, keywords={CIoT Energy efficiency Energy harvesting Joint optimization}, doi={10.1007/978-3-030-32388-2_24} }- Xin Liu
Xueyan Zhang
Weidang Lu
Mudi Xiong
Year: 2019
Energy Efficiency Maximization for Green Cognitive Internet of Things with Energy Harvesting
MLICOM
Springer
DOI: 10.1007/978-3-030-32388-2_24
Abstract
In this paper, a green cognitive Internet of Things (CIoT) has been proposed to collect the radio frequency (RF) energy of primary user (PU) by using energy harvesting. The CIoT nodes are divided into two independent groups to perform spectrum sensing and energy harvesting simultaneously in the sensing slot. The energy efficiency of the CIoT is maximized by through jointly optimizing sensing time, number of sensing nodes and transmission power. The suboptimal solution to the optimization problem is achieved using a joint optimization algorithm based on alternating direction optimization. Simulation results have indicated that the optimal solution is existed and the green CIoT outperforms the traditional scheme.
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