# Efficient Drone Mobility Support Using Reinforcement Learning

arXiv: https://arxiv.org/abs/1911.09715 · HTML: https://mlsanity.com/paper/1911.09715/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Nov 2019.

## Built on by (most cited first, 6 of 6)

- [Multi-UAV Speed Control with Collision Avoidance and Handover-aware Cell Association: DRL with Action Branching](https://mlsanity.com/paper/2307.13158/) (2023)
- [Hierarchical and Collaborative LLM-Based Control for Multi-UAV Motion and Communication in Integrated Terrestrial and Non-Terrestrial Networks](https://mlsanity.com/paper/2506.06532/) (2025)
- [RL-Based Cargo-UAV Trajectory Planning and Cell Association for Minimum Handoffs, Disconnectivity, and Energy Consumption](https://mlsanity.com/paper/2312.02478/) (2023)
- [Hierarchical Multi-Agent DRL Based Dynamic Cluster Reconfiguration for UAV Mobility Management](https://mlsanity.com/paper/2412.16167/) (2024)
- [Explainable AI for UAV Mobility Management: A Deep Q-Network Approach for Handover Minimization](https://mlsanity.com/paper/2504.18371/) (2025)
- [Hierarchical LLM-Driven Control for HAPS-Assisted UAV Networks: Joint Optimization of Flight and Connectivity](https://mlsanity.com/paper/2605.11509/) (2026)

## Abstract (arXiv)

Flying drones can be used in a wide range of applications and services from surveillance to package delivery. To ensure robust control and safety of drone operations, cellular networks need to provide reliable wireless connectivity to drone user equipments (UEs). To date, existing mobile networks have been primarily designed and optimized for serving ground UEs, thus making the mobility support in the sky challenging. In this paper, a novel handover (HO) mechanism is developed for a cellular-connected drone system to ensure robust wireless connectivity and mobility support for drone-UEs. By leveraging tools from reinforcement learning, HO decisions are dynamically optimized using a Q-learning algorithm to provide an efficient mobility support in the sky. The results show that the proposed approach can significantly reduce (e.g., by 80%) the number of HOs, while maintaining connectivity, compared to the baseline HO scheme in which the drone always connects to the strongest cell.