TY - GEN
T1 - An energy-aware distributed open market model for UAV-assisted communications
AU - Ansari, Rafay Iqbal
AU - Ashraf, Nouman
AU - Politis, Christos
N1 - Funding Information:
The work in this paper is supported by the UK Engineering and Physical Science Research Council (EPSRC) Project DARE under Global Challenge Research Fund (GCRF) Grant no. EP/P028764/1.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - Unmanned aerial vehicles (UAVs) have opened up numerous opportunities in terms of connectivity, especially in the context of realizing the vision of ubiquitous connectivity for 5G and beyond (B5G). The ease of mobility makes the UAV base stations (UAV-BSs) a viable candidate for providing 'on demand' services to the users. Moreover, viewing the spectrum crunch experienced by traditional cellular networks, the UAV-BSs can share the burden of providing connectivity. UAV-BSs can open up several business opportunities for mobile network operators (MNOs). In this paper, we propose an open market model, where a UAV-BS has the opportunity to establish a link with a terrestrial BS (TBS) of an MNO that provides the best connectivity and offers a lower price. A distributed model is considered where the decision making power lies with the UAV-BS. The TBS-selection problem is modeled as an integer linear programming problem, where we compare the performance of the Greedy heuristic algorithm (GHA) and the backtracking algorithm (BA) to solve our selection problem. We also incorporate an energy prediction model which impacts the selection criteria. We analyze the performance GHA and BA algorithm by presenting a tradeoff between the two algorithms in terms of accuracy of TBS selection and convergence time.
AB - Unmanned aerial vehicles (UAVs) have opened up numerous opportunities in terms of connectivity, especially in the context of realizing the vision of ubiquitous connectivity for 5G and beyond (B5G). The ease of mobility makes the UAV base stations (UAV-BSs) a viable candidate for providing 'on demand' services to the users. Moreover, viewing the spectrum crunch experienced by traditional cellular networks, the UAV-BSs can share the burden of providing connectivity. UAV-BSs can open up several business opportunities for mobile network operators (MNOs). In this paper, we propose an open market model, where a UAV-BS has the opportunity to establish a link with a terrestrial BS (TBS) of an MNO that provides the best connectivity and offers a lower price. A distributed model is considered where the decision making power lies with the UAV-BS. The TBS-selection problem is modeled as an integer linear programming problem, where we compare the performance of the Greedy heuristic algorithm (GHA) and the backtracking algorithm (BA) to solve our selection problem. We also incorporate an energy prediction model which impacts the selection criteria. We analyze the performance GHA and BA algorithm by presenting a tradeoff between the two algorithms in terms of accuracy of TBS selection and convergence time.
KW - backtracking algorithm
KW - greedy heuristic algorithm
KW - mmWave
KW - open market
KW - unmanned aerial vehicle
UR - http://www.scopus.com/inward/record.url?scp=85088310064&partnerID=8YFLogxK
U2 - 10.1109/VTC2020-Spring48590.2020.9128475
DO - 10.1109/VTC2020-Spring48590.2020.9128475
M3 - Conference contribution
AN - SCOPUS:85088310064
T3 - IEEE Vehicular Technology Conference
BT - 2020 IEEE 91st Vehicular Technology Conference, VTC Spring 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 91st IEEE Vehicular Technology Conference, VTC Spring 2020
Y2 - 25 May 2020 through 28 May 2020
ER -