Spectrum on Demand: A Competitive Open Market Model for Spectrum Sharing for UAV-assisted Communications

Ansari, Rafay, Ashraf, Nouman, Hassan, Syed Ali, Deepak, G.C., Pervaiz, Haris and Politis, Christos (2020) Spectrum on Demand: A Competitive Open Market Model for Spectrum Sharing for UAV-assisted Communications. IEEE Network, 34 (6). pp. 318-324. ISSN 0890-8044

G-C-Deepak-46939-AAM.pdf - Accepted Version

Download (649kB) | Preview
Official URL: https://doi.org/10.1109/mnet.011.2000253


Unmanned aerial vehicles (UAVs)-assisted communication has gathered significant interest of the industry, especially with regards to the vision of providing ubiquitous connectivity for beyond 5G (B5G) networks. In this article, we motivate the need for utilizing licensed spectrum for UAV-assisted communication and discuss its advantages such as reliability and security. Moreover, we explore a new dimension to spectrum sharing by proposing a decentralized competitive open market approach based model, where the different mobile network operators (MNOs) have the opportunity to lease the spectrum to UAV base stations (UAV-BSs), leading to new revenue generation opportunities. The proposed spectrum sharing mechanism is based on the logarithmic utility function and willingness to pay of each UAV-BS. We provide a tradeoff analysis between spectrum sharing and price offered by the MNOs, highlighting the impact of the willingness to pay on the spectrum sharing. The results also highlight the behaviour of price and spectrum shared w.r.t. time, thereby providing an insight into different performance regions until the algorithm converges to it’s optimal value. In addition, we also present future directions that could lead to interesting analyses, especially with regards to incentive-based spectrum sharing and security.

Item Type: Article
Uncontrolled Keywords: Communication networks, Quality of service, Reliability, Safety, Security, Smart cities, Unmanned aerial vehicles
Subjects: G400 Computer Science
G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: John Coen
Date Deposited: 01 Oct 2020 11:10
Last Modified: 31 Jul 2021 14:46
URI: http://nrl.northumbria.ac.uk/id/eprint/44368

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics