Version 1
: Received: 3 October 2018 / Approved: 5 October 2018 / Online: 5 October 2018 (12:58:17 CEST)
How to cite:
Yang, T.; Yao, K.; Sun, Y.; Song, F.; Yang, Y.; Zhang, Y. Joint Power and Bandwidth Allocation for UAV Backhaul Networks: A Hierarchical Learning Approach. Preprints2018, 2018100100. https://doi.org/10.20944/preprints201810.0100.v1
Yang, T.; Yao, K.; Sun, Y.; Song, F.; Yang, Y.; Zhang, Y. Joint Power and Bandwidth Allocation for UAV Backhaul Networks: A Hierarchical Learning Approach. Preprints 2018, 2018100100. https://doi.org/10.20944/preprints201810.0100.v1
Yang, T.; Yao, K.; Sun, Y.; Song, F.; Yang, Y.; Zhang, Y. Joint Power and Bandwidth Allocation for UAV Backhaul Networks: A Hierarchical Learning Approach. Preprints2018, 2018100100. https://doi.org/10.20944/preprints201810.0100.v1
APA Style
Yang, T., Yao, K., Sun, Y., Song, F., Yang, Y., & Zhang, Y. (2018). Joint Power and Bandwidth Allocation for UAV Backhaul Networks: A Hierarchical Learning Approach. Preprints. https://doi.org/10.20944/preprints201810.0100.v1
Chicago/Turabian Style
Yang, T., Yang Yang and Yuli Zhang. 2018 "Joint Power and Bandwidth Allocation for UAV Backhaul Networks: A Hierarchical Learning Approach" Preprints. https://doi.org/10.20944/preprints201810.0100.v1
Abstract
Unmanned Aerial Vehicles (UAVs) severing as the relay is an effective technology method to extend the coverage. It can also alleviate the congestion and increase the throughput, especially applied in UAV networks. However, since the energy of UAVs is limited and the resources in UAV networks are scarce, how to optimize the network delay performance under these constraints should be well investigated. Besides, the relationship among different resources, e.g. power and bandwidth, is coupled which makes the optimization more complex. This article investigates the problem of joint power and bandwidth allocation in UAV backhaul networks, which considers both the delay performance and the resource utilization efficiency. Considering the heterogeneous locations characteristics of different UAVs, we formulate the optimization problem as a Stackelberg game. The relay UAV acts as the leader and extended UAVs act as followers. Their utility functions take both the delay durance and the resource consumption into account. To capture the competitive relationship among followers, the sub-game is proved to be an exact potential game and exists Nash equilibriums (NE). The Stackelberg Equilibrium (SE) is proved afterwards. We utilize a hierarchical learning algorithm (HLA) to find out the best resource allocation strategies, which also reduces the computational complexity. Simulation results demonstrate the effectiveness of the proposed method.
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
