Energy-Efficiency Optimization of UAV-Based Cognitive Radio System
Unmanned aerial vehicles (UAVs) equipped with data transmission and sensing facilities are gaining more popularity in different applications due to its miniaturization and mobility. In this paper, a UAV-based overlay cognitive radio (CR) network is investigated in which the UAV is used as a secondar...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8825775/ |
| _version_ | 1818910205363093504 |
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| author | Yu Pan Xinyu Da Hang Hu Zhengyu Zhu Ruiyang Xu Lei Ni |
| author_facet | Yu Pan Xinyu Da Hang Hu Zhengyu Zhu Ruiyang Xu Lei Ni |
| author_sort | Yu Pan |
| collection | DOAJ |
| description | Unmanned aerial vehicles (UAVs) equipped with data transmission and sensing facilities are gaining more popularity in different applications due to its miniaturization and mobility. In this paper, a UAV-based overlay cognitive radio (CR) network is investigated in which the UAV is used as a secondary user (SU). This paper proposes an efficient energy management solution to improve the performance of the UAV. When SUs opportunistically utilize the licensed spectrum of the primary network, spectrum sensing is needed to determine whether to transmit data or not, so the sensing time and secondary transmission power should be jointly optimized. We formulate this non-convex optimization problem subject to multiple constraints, which seeks to investigate on the effect of the sensing time and transmission power on the performance of the system. The problem is difficult to tackle, then we propose an algorithm applying the techniques of alternating optimization and dichotomy method. In addition, we compare the proposed algorithm with the particle swarm optimization (PSO) algorithm to verify its performance. Numerical results show that our proposed algorithm outperforms the PSO algorithm and significantly enhances the energy efficiency of the UAV-based CR system. |
| first_indexed | 2024-12-19T22:39:06Z |
| format | Article |
| id | doaj.art-999bfb2a59574b778b20444a8fc61225 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T22:39:06Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-999bfb2a59574b778b20444a8fc612252022-12-21T20:03:08ZengIEEEIEEE Access2169-35362019-01-01715538115539110.1109/ACCESS.2019.29396168825775Energy-Efficiency Optimization of UAV-Based Cognitive Radio SystemYu Pan0https://orcid.org/0000-0003-0174-3319Xinyu Da1Hang Hu2https://orcid.org/0000-0002-5391-010XZhengyu Zhu3https://orcid.org/0000-0001-6562-8243Ruiyang Xu4https://orcid.org/0000-0002-8521-3181Lei Ni5https://orcid.org/0000-0001-7307-2599Graduate College, Air Force Engineering University, Xi’an, ChinaInformation and Navigation College, Air Force Engineering University, Xi’an, ChinaInformation and Navigation College, Air Force Engineering University, Xi’an, ChinaSchool of Information Engineering, Zhengzhou University, Zhengzhou, ChinaGraduate College, Air Force Engineering University, Xi’an, ChinaGraduate College, Air Force Engineering University, Xi’an, ChinaUnmanned aerial vehicles (UAVs) equipped with data transmission and sensing facilities are gaining more popularity in different applications due to its miniaturization and mobility. In this paper, a UAV-based overlay cognitive radio (CR) network is investigated in which the UAV is used as a secondary user (SU). This paper proposes an efficient energy management solution to improve the performance of the UAV. When SUs opportunistically utilize the licensed spectrum of the primary network, spectrum sensing is needed to determine whether to transmit data or not, so the sensing time and secondary transmission power should be jointly optimized. We formulate this non-convex optimization problem subject to multiple constraints, which seeks to investigate on the effect of the sensing time and transmission power on the performance of the system. The problem is difficult to tackle, then we propose an algorithm applying the techniques of alternating optimization and dichotomy method. In addition, we compare the proposed algorithm with the particle swarm optimization (PSO) algorithm to verify its performance. Numerical results show that our proposed algorithm outperforms the PSO algorithm and significantly enhances the energy efficiency of the UAV-based CR system.https://ieeexplore.ieee.org/document/8825775/Unmanned aerial vehicle (UAV)cognitive radio (CR) networkopportunistic spectrum access (OSA)spectrum sensingenergy efficiency |
| spellingShingle | Yu Pan Xinyu Da Hang Hu Zhengyu Zhu Ruiyang Xu Lei Ni Energy-Efficiency Optimization of UAV-Based Cognitive Radio System IEEE Access Unmanned aerial vehicle (UAV) cognitive radio (CR) network opportunistic spectrum access (OSA) spectrum sensing energy efficiency |
| title | Energy-Efficiency Optimization of UAV-Based Cognitive Radio System |
| title_full | Energy-Efficiency Optimization of UAV-Based Cognitive Radio System |
| title_fullStr | Energy-Efficiency Optimization of UAV-Based Cognitive Radio System |
| title_full_unstemmed | Energy-Efficiency Optimization of UAV-Based Cognitive Radio System |
| title_short | Energy-Efficiency Optimization of UAV-Based Cognitive Radio System |
| title_sort | energy efficiency optimization of uav based cognitive radio system |
| topic | Unmanned aerial vehicle (UAV) cognitive radio (CR) network opportunistic spectrum access (OSA) spectrum sensing energy efficiency |
| url | https://ieeexplore.ieee.org/document/8825775/ |
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