Maximizing Energy Efficiency in Hybrid Overlay-Underlay Cognitive Radio Networks Based on Energy Harvesting-Cooperative Spectrum Sensing

Spectrum demand has increased with the rapid growth of wireless devices and wireless service usage. The rapid development of 5G smart cities and the industrial Internet of Things makes the problem of spectrum resource shortage and increased energy consumption even more severe. To address the issues...

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Bibliographic Details
Main Authors: Fu, J. (Author), Huang, Y. (Author), Liu, Y. (Author), Qin, X. (Author), Tang, L. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02893nam a2200445Ia 4500
001 10.3390-en15082803
008 220510s2022 CNT 000 0 und d
020 |a 19961073 (ISSN) 
245 1 0 |a Maximizing Energy Efficiency in Hybrid Overlay-Underlay Cognitive Radio Networks Based on Energy Harvesting-Cooperative Spectrum Sensing 
260 0 |b MDPI  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.3390/en15082803 
520 3 |a Spectrum demand has increased with the rapid growth of wireless devices and wireless service usage. The rapid development of 5G smart cities and the industrial Internet of Things makes the problem of spectrum resource shortage and increased energy consumption even more severe. To address the issues of high energy consumption for spectrum sensing and low user access rate in the cognitive radio networks (CRN) model powered entirely by energy harvesting, we propose a novel energy harvesting (EH)-distributed cooperative spectrum sensing (DCSS) architecture that allows SUs to acquire from the surrounding environment and radio frequency (RF) signals energy, and an improved distributed cooperative spectrum sensing scheme based on energy-correlation is proposed. First, we formulate an optimization problem to select a leader for each channel; then formulate another optimization problem to select the corresponding cooperative secondary users (SUs). Each channel has a fixed SUs cluster in each time slot to sense the main user state, which can reduce the energy consumption of SUs sensing and can reduce the sensing time, and the remaining time can be used for data transmission to improve throughput, and finally achieve the purpose of improving energy efficiency. Simulation results show that our proposed scheme significantly outperforms the centralized scheme in terms of SUs access capability and energy efficiency. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. 
650 0 4 |a 5G mobile communication systems 
650 0 4 |a Cognitive radio 
650 0 4 |a Cognitive radio network 
650 0 4 |a cognitive radio networks 
650 0 4 |a cooperative spectrum sensing 
650 0 4 |a Co-operative spectrum sensing 
650 0 4 |a Energy efficiency 
650 0 4 |a energy harvesting 
650 0 4 |a Energy harvesting 
650 0 4 |a Energy utilization 
650 0 4 |a Energy-consumption 
650 0 4 |a energy-efficiency 
650 0 4 |a hybrid underlay-overlay scheme 
650 0 4 |a Hybrid underlay-overlay scheme 
650 0 4 |a Network-based 
650 0 4 |a Optimization 
650 0 4 |a Optimization problems 
650 0 4 |a Radio 
650 0 4 |a Secondary user 
650 0 4 |a Spectrum demand 
650 0 4 |a Underlay cognitive radios 
650 0 4 |a Users access 
700 1 |a Fu, J.  |e author 
700 1 |a Huang, Y.  |e author 
700 1 |a Liu, Y.  |e author 
700 1 |a Qin, X.  |e author 
700 1 |a Tang, L.  |e author 
773 |t Energies