Drone-Assisted Cellular Networks: A Multi-Agent Reinforcement Learning Approach

Seif Eddine Hammami, Hossam Afifi, Hassine Moungla, Ahmed Kamel
2019 ICC 2019 - 2019 IEEE International Conference on Communications (ICC)  
Drone-assisted cellular networks: a multi-agent reinforcement learning approach. Abstract-Drone-cell technology is emerging as a solution to support and backup the cellular network architecture. cell-drones are flexible and provide a more dynamic solution for resource allocation in both scales: spatial and geographic. They allow to increase the bandwidth availability anytime and everywhere according the continuous rate demands. Their fast deployment provide network operators with a reliable
more » ... tion to face sudden network overload or peak data demands during mass events, without interrupting services and guaranteeing better QoS for users. With these advantages, drone-cell network management is still a complex task. We propose in this paper, a multiagent reinforcement learning approach for dynamic drones-cells management. Our approach is based on an enhanced joint action selection. Results show that our model speed up network learning and provide better network performance.
doi:10.1109/icc.2019.8762079 dblp:conf/icc/HammamiAMK19 fatcat:iu5jowqrrjgrph4iuioiogpfhu