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Efficient Resource Allocation Utilizing Q-Learning in Multiple UA Communications
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DOI：10.1109/TNSE.2018.2842246.png)
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摘要
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In recent years, unmanned aircraft systems (UASs) have garnered significant attention, and the demand for communication utilizing unmanned aircrafts (UAs) has increased. However, the limited available frequency for UA communication, despite the increasing utilization, poses a problem. Moreover, for the practical application of UA communication, the changes and differences in the propagation environment and communication demand of each UA communication must be considered because of the variety of supposed services, and the considerable interference caused by obstacles and reflected waves, due to high UA mobility. In this research, we construct a UA communication management system at the UAS operating frequency, with reference to the physical channel configuration of the LTE and LTE Sidelink, utilizing Q-Learning. In addition, we determine the effectiveness of the proposed method by evaluating various propagation-environment scenarios and communication demands.
Keyword:
UAS
physical channel configuration
reinforcement learning
Q-Learning
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