Handover Management for Drones in Future Mobile Networks—A Survey
Drones have attracted extensive attention for their environmental, civil, and military applications. Because of their low cost and flexibility in deployment, drones with communication capabilities are expected to play key important roles in Fifth Generation (5G), Sixth Generation (6G) mobile network...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/17/6424 |
| _version_ | 1827665083042365440 |
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| author | Ibraheem Shayea Pabiola Dushi Mohammed Banafaa Rozeha A. Rashid Sawsan Ali Mohd Adib Sarijari Yousef Ibrahim Daradkeh Hafizal Mohamad |
| author_facet | Ibraheem Shayea Pabiola Dushi Mohammed Banafaa Rozeha A. Rashid Sawsan Ali Mohd Adib Sarijari Yousef Ibrahim Daradkeh Hafizal Mohamad |
| author_sort | Ibraheem Shayea |
| collection | DOAJ |
| description | Drones have attracted extensive attention for their environmental, civil, and military applications. Because of their low cost and flexibility in deployment, drones with communication capabilities are expected to play key important roles in Fifth Generation (5G), Sixth Generation (6G) mobile networks, and beyond. 6G and 5G are intended to be a full-coverage network capable of providing ubiquitous connections for space, air, ground, and underwater applications. Drones can provide airborne communication in a variety of cases, including as Aerial Base Stations (ABSs) for ground users, relays to link isolated nodes, and mobile users in wireless networks. However, variables such as the drone’s free-space propagation behavior at high altitudes and its exposure to antenna sidelobes can contribute to radio environment alterations. These differences may render existing mobility models and techniques as inefficient for connected drone applications. Therefore, drone connections may experience significant issues due to limited power, packet loss, high network congestion, and/or high movement speeds. More issues, such as frequent handovers, may emerge due to erroneous transmissions from limited coverage areas in drone networks. Therefore, the deployments of drones in future mobile networks, including 5G and 6G networks, will face a critical technical issue related to mobility and handover processes due to the main differences in drones’ characterizations. Therefore, drone networks require more efficient mobility and handover techniques to continuously maintain stable and reliable connection. More advanced mobility techniques and system reconfiguration are essential, in addition to an alternative framework to handle data transmission. This paper reviews numerous studies on handover management for connected drones in mobile communication networks. The work contributes to providing a more focused review of drone networks, mobility management for drones, and related works in the literature. The main challenges facing the implementation of connected drones are highlighted, especially those related to mobility management, in more detail. The analysis and discussion of this study indicates that, by adopting intelligent handover schemes that utilizing machine learning, deep learning, and automatic robust processes, the handover problems and related issues can be reduced significantly as compared to traditional techniques. |
| first_indexed | 2024-03-10T01:16:35Z |
| format | Article |
| id | doaj.art-e2aeb3b15cb6432aa8d7ec5617d1eeba |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T01:16:35Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e2aeb3b15cb6432aa8d7ec5617d1eeba2023-11-23T14:08:15ZengMDPI AGSensors1424-82202022-08-012217642410.3390/s22176424Handover Management for Drones in Future Mobile Networks—A SurveyIbraheem Shayea0Pabiola Dushi1Mohammed Banafaa2Rozeha A. Rashid3Sawsan Ali4Mohd Adib Sarijari5Yousef Ibrahim Daradkeh6Hafizal Mohamad7Department of Electronics and Communication Engineering, Istanbul Technical University (ITU), 34467 Istanbul, TurkeyDepartment of Electronics and Communication Engineering, Istanbul Technical University (ITU), 34467 Istanbul, TurkeyDepartment of Electronics and Communication Engineering, Istanbul Technical University (ITU), 34467 Istanbul, TurkeyTelecommunication Software and System Research Group, Communication Engineering Department, School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, UTM, Skudai 81310, Johor, MalaysiaDepartment of Computer Engineering, University of Ha’il, Ha’il 55211, Saudi ArabiaTelecommunication Software and System Research Group, Communication Engineering Department, School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, UTM, Skudai 81310, Johor, MalaysiaDepartment of Computer Engineering and Networks, College of Engineering in Wadi Alddawasir, Prince Sattam bin Abdulaziz University, Al-Kharj 16436, Saudi ArabiaFaculty of Engineering and Built Environment, Universiti Sains Islam Malaysia, Bandar Baru Nilai, Nilai 71800, Negeri Sembilan, MalaysiaDrones have attracted extensive attention for their environmental, civil, and military applications. Because of their low cost and flexibility in deployment, drones with communication capabilities are expected to play key important roles in Fifth Generation (5G), Sixth Generation (6G) mobile networks, and beyond. 6G and 5G are intended to be a full-coverage network capable of providing ubiquitous connections for space, air, ground, and underwater applications. Drones can provide airborne communication in a variety of cases, including as Aerial Base Stations (ABSs) for ground users, relays to link isolated nodes, and mobile users in wireless networks. However, variables such as the drone’s free-space propagation behavior at high altitudes and its exposure to antenna sidelobes can contribute to radio environment alterations. These differences may render existing mobility models and techniques as inefficient for connected drone applications. Therefore, drone connections may experience significant issues due to limited power, packet loss, high network congestion, and/or high movement speeds. More issues, such as frequent handovers, may emerge due to erroneous transmissions from limited coverage areas in drone networks. Therefore, the deployments of drones in future mobile networks, including 5G and 6G networks, will face a critical technical issue related to mobility and handover processes due to the main differences in drones’ characterizations. Therefore, drone networks require more efficient mobility and handover techniques to continuously maintain stable and reliable connection. More advanced mobility techniques and system reconfiguration are essential, in addition to an alternative framework to handle data transmission. This paper reviews numerous studies on handover management for connected drones in mobile communication networks. The work contributes to providing a more focused review of drone networks, mobility management for drones, and related works in the literature. The main challenges facing the implementation of connected drones are highlighted, especially those related to mobility management, in more detail. The analysis and discussion of this study indicates that, by adopting intelligent handover schemes that utilizing machine learning, deep learning, and automatic robust processes, the handover problems and related issues can be reduced significantly as compared to traditional techniques.https://www.mdpi.com/1424-8220/22/17/6424dronedrone networkconnected droneUnmanned Aerial Vehicle (UAV)handover decision algorithmhandover management |
| spellingShingle | Ibraheem Shayea Pabiola Dushi Mohammed Banafaa Rozeha A. Rashid Sawsan Ali Mohd Adib Sarijari Yousef Ibrahim Daradkeh Hafizal Mohamad Handover Management for Drones in Future Mobile Networks—A Survey Sensors drone drone network connected drone Unmanned Aerial Vehicle (UAV) handover decision algorithm handover management |
| title | Handover Management for Drones in Future Mobile Networks—A Survey |
| title_full | Handover Management for Drones in Future Mobile Networks—A Survey |
| title_fullStr | Handover Management for Drones in Future Mobile Networks—A Survey |
| title_full_unstemmed | Handover Management for Drones in Future Mobile Networks—A Survey |
| title_short | Handover Management for Drones in Future Mobile Networks—A Survey |
| title_sort | handover management for drones in future mobile networks a survey |
| topic | drone drone network connected drone Unmanned Aerial Vehicle (UAV) handover decision algorithm handover management |
| url | https://www.mdpi.com/1424-8220/22/17/6424 |
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