Abstract
As an extensive prospect in communication technology, multi-hop unmanned aerial vehicle (UAV) faces some challenges as well. How to ensure the availability of time slots in high dynamic scenarios and the rationality and robustness of power allocation in massive scenarios remains to be resolved. In this paper, we propose a robust mean field game (MFG) framework to manage time slot resources and power resources. On the one hand, this framework can predict the potential conflicts of time slots and avoid them in time. On the other hand, it can well adapt to the massive scenarios with complex interference, in order to realize power control. The simulation results show that the robust MFG-based resource management scheme can not only reduce the probability of packet collision and packet loss, but also improve communication energy efficiency (EE) with better robustness.
Highlights
OPPORTUNITIES AND CHALLENGESW ITH the rapid unmanned aerial vehicle (UAV) enabled communication technologies, a flying ad hoc network (FANET) has gradually expanded from several and slow-rate UAVs to massive and high-dynamic UAVs [1]
Time allocation: On the one hand, unmanned aerial vehicle (UAV) are with the characteristic of high-speed movement, which leads to rapid topology changes
We mainly focus on two aspects of the resources allocation strategy: the time slot allocation strategy and the power control strategy
Summary
W ITH the rapid UAV enabled communication technologies, a flying ad hoc network (FANET) has gradually expanded from several and slow-rate UAVs to massive and high-dynamic UAVs [1]. Improve performance: Multi-UAV cooperation can perform more complex tasks. There exist many other reasons, such as rapid deployment and quick information dissemination, that are driving the widespread use of multiple cooperation UAVs. the multi-hop UAV communication technology still faces. Time allocation: On the one hand, UAVs are with the characteristic of high-speed movement, which leads to rapid topology changes. The high dynamics and uncertainty of UAVs put forward higher adaptability requirements for resource management strategies. These challenges will cause UAV nodes to exchange information unsuccessfully and consume more energy when performing tasks. The goal is to spend less energy, but deliver more data in FANET
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