Stable matching with evolving preference for adaptive handover in cellular-connected UAV networks

Abstract

Unmanned Aerial Vehicles (UAVs) can effectively and reliably complete aerial tasks in various fields. However, the high-speed mobility of UAVs and the 6G ultra-dense heterogeneous network architecture in future will lead to frequent handover of UAVs during aerial tasks in cellular networks, increasing the potential service interruption rate. Therefore, there is an urgent requirement to address the lack of service adaptability in the overall time-space dimension. To achieve the seamless handover in highly dynamic and stochastic scenarios, we firstly transform the handover problem into a stable matching model. We then extend the stable matching of single time slot to the overall time-space dimension, and transform the dynamically changing time-space information into the preference relations evolution. By flexibly adapting the evolution of the preference lists to current network topology, we propose a Dynamic Stable Matching based Adaptive Handover (DSMAH) algorithm to find stable matching efficiently in a dynamic environment. Simulation results show that the proposed algorithm can achieve a better trade-off between communication quality, handover frequency, and convergence speed and significantly improves the stability of the cellular-connected network as compared to benchmark schemes. The proposed scheme not only effectively addresses the challenges posed by frequent handovers and ping-pong effect, but also shows its notable advantages in dynamic environments.