Neighbor Discovery for Unmanned Aerial Vehicle Networks
The unmanned aerial vehicle (UAV) networks have wide civil applications. However, due to the 3D deployment and high mobility of UAVs, the neighbor discovery for UAV networks faces great challenges. In this paper, we have designed a two-way handshaking neighbor discovery scheme for UAV networks. A sc...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8468195/ |
| _version_ | 1818876895286001664 |
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| author | Zhiqing Wei Xinyi Liu Chenyang Han Zhiyong Feng |
| author_facet | Zhiqing Wei Xinyi Liu Chenyang Han Zhiyong Feng |
| author_sort | Zhiqing Wei |
| collection | DOAJ |
| description | The unmanned aerial vehicle (UAV) networks have wide civil applications. However, due to the 3D deployment and high mobility of UAVs, the neighbor discovery for UAV networks faces great challenges. In this paper, we have designed a two-way handshaking neighbor discovery scheme for UAV networks. A scanning path for 3D UAV networks is proposed. In order to reduce the overhead of neighbor discovery, each UAV varies among the states of transmit, receive, and sleep with certain probabilities. The sleep probability is closely related to the probability of topology change of UAV networks. The optimal sleep probability is derived according to the mobility model of UAVs. The efficiency of the proposed neighbor discovery scheme is analyzed via the Markov process. The optimal transmission probability of UAVs is derived to improve the efficiency of neighbor discovery. Besides, the impact of various parameters on the efficiency of neighbor discovery is analyzed by simulation results. This paper has considered the deployment and mobility of UAVs in the design of neighbor discovery scheme, which provides an insight in the design of neighbor discovery schemes for UAV networks. |
| first_indexed | 2024-12-19T13:49:39Z |
| format | Article |
| id | doaj.art-8b769340ba45475a880612e0d5472261 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T13:49:39Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-8b769340ba45475a880612e0d54722612022-12-21T20:18:47ZengIEEEIEEE Access2169-35362018-01-016682886830110.1109/ACCESS.2018.28711328468195Neighbor Discovery for Unmanned Aerial Vehicle NetworksZhiqing Wei0https://orcid.org/0000-0001-7940-2739Xinyi Liu1Chenyang Han2Zhiyong Feng3https://orcid.org/0000-0001-5322-222XKey Laboratory of Universal Wireless Communications, Ministry of Education, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, ChinaKey Laboratory of Universal Wireless Communications, Ministry of Education, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, ChinaKey Laboratory of Universal Wireless Communications, Ministry of Education, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, ChinaKey Laboratory of Universal Wireless Communications, Ministry of Education, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, ChinaThe unmanned aerial vehicle (UAV) networks have wide civil applications. However, due to the 3D deployment and high mobility of UAVs, the neighbor discovery for UAV networks faces great challenges. In this paper, we have designed a two-way handshaking neighbor discovery scheme for UAV networks. A scanning path for 3D UAV networks is proposed. In order to reduce the overhead of neighbor discovery, each UAV varies among the states of transmit, receive, and sleep with certain probabilities. The sleep probability is closely related to the probability of topology change of UAV networks. The optimal sleep probability is derived according to the mobility model of UAVs. The efficiency of the proposed neighbor discovery scheme is analyzed via the Markov process. The optimal transmission probability of UAVs is derived to improve the efficiency of neighbor discovery. Besides, the impact of various parameters on the efficiency of neighbor discovery is analyzed by simulation results. This paper has considered the deployment and mobility of UAVs in the design of neighbor discovery scheme, which provides an insight in the design of neighbor discovery schemes for UAV networks.https://ieeexplore.ieee.org/document/8468195/Unmanned aerial vehicle networksneighbor discoverysleep probabilitymobility |
| spellingShingle | Zhiqing Wei Xinyi Liu Chenyang Han Zhiyong Feng Neighbor Discovery for Unmanned Aerial Vehicle Networks IEEE Access Unmanned aerial vehicle networks neighbor discovery sleep probability mobility |
| title | Neighbor Discovery for Unmanned Aerial Vehicle Networks |
| title_full | Neighbor Discovery for Unmanned Aerial Vehicle Networks |
| title_fullStr | Neighbor Discovery for Unmanned Aerial Vehicle Networks |
| title_full_unstemmed | Neighbor Discovery for Unmanned Aerial Vehicle Networks |
| title_short | Neighbor Discovery for Unmanned Aerial Vehicle Networks |
| title_sort | neighbor discovery for unmanned aerial vehicle networks |
| topic | Unmanned aerial vehicle networks neighbor discovery sleep probability mobility |
| url | https://ieeexplore.ieee.org/document/8468195/ |
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