The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
The New Frontier in RAN Heterogeneity: Multi-Tier Drone-Cells
Open accessAbstract
In cellular networks, the locations of the RAN elements are determined mainly based on the long-term traffic behavior. However, when the random and hard-to-predict spatio-temporal distribution of the traffic (load, demand) does not fully match the fixed locations of the RAN elements (supply), some performance degradation becomes inevitable. The concept of multi-tier cells (heterogeneous networks, HetNets) has been introduced in 4G networks to alleviate this mismatch. However, as the traffic distribution deviates more and more from the long-term average, even the HetNet architecture will have difficulty in coping with the erratic supply-demand mismatch, unless the RAN is grossly over-engineered (which is a financially non-viable solution). In this article, we study the opportunistic utilization of low-altitude unmanned aerial platforms equipped with BSs (i.e., drone-BSs) in future wireless networks. In particular, we envisage a multi-tier drone-cell network complementing the terrestrial HetNets. The variety of equipment and non-rigid placement options allow utilizing multi-tier drone-cell networks to serve diversified demands. Hence, drone-cells bring the supply to where the demand is, which sets new frontiers for the heterogeneity in 5G networks. We investigate the advancements promised by dronecells and discuss the challenges associated with their operation and management. We propose a drone-cell management framework (DMF) benefiting from the synergy among SDN, network functions virtualization, and cloud computing. We demonstrate DMF mechanisms via a case study, and numerically show that it can reduce the cost of utilizing drone-cells in multi-tenancy cellular networks.
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Cites
Optical Communication in Space: Challenges and Mitigation Techniques
Kaushal, H., & Kaddoum, G. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2603518 · Cited by 1,927
Science, technology and the future of small autonomous drones
Floreano, D., & Wood, R. J. (2015) · Nature · doi:10.1038/nature14542 · Cited by 1,476
Handbook of Unmanned Aerial Vehicles
(2015) · doi:10.1007/978-90-481-9707-1 · Cited by 1,103
Cited by
Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges
Shakhatreh, H., Sawalmeh, A. H., Al-Fuqaha, A., Dou, Z., Almaita, E., Khalil, I., Othman, N. S., Khreishah, A., & Guizani, M. (2019) · IEEE Access · doi:10.1109/access.2019.2909530 · Cited by 2,529
UAV Communications for 5G and Beyond: Recent Advances and Future Trends
Li, B., Fei, Z., & Zhang, Y. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2887086 · Cited by 1,377
Chen, M., Mozaffari, M., Saad, W., Yin, C., Debbah, M., & Hong, C. S. (2017) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2017.2680898 · Cited by 742
A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future
Karabulut Kurt, G., Khoshkholgh, M. G., Alfattani, S., Ibrahim, A., Darwish, T. S. J., Alam, M. S., Yanikomeroglu, H., & Yongacoglu, A. (2021) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2021.3066905 · Cited by 538
Self-citationCellular-Enabled UAV Communication: A Connectivity-Constrained Trajectory Optimization Perspective
Zhang, S., Zeng, Y., & Zhang, R. (2019) · IEEE Transactions on Communications · doi:10.1109/tcomm.2018.2880468 · Cited by 426
Metadata
- Authors
- Bor-Yaliniz, I., & Yanikomeroglu, H.
- Venue
- IEEE Communications Magazine
- Published
- 2016-11
- Volume
- 54
- Issue
- 11
- Pages
- 48-55
- ISSN
- 0163-6804 (ISSN-L)
- OpenAlex
- W2322825271
- Cited by
- 460
- References
- 3
- FWCI
- 87.89
- Type
- journal article
- Language
- en
- Open access
- green
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