Abstract
This paper studies the UAV swarm energy optimization problem. The energy consumption is critical for the UAV swarm, which limited the operating time of the whole system. Cooperative relaying could increase energy efficiency (EE) in UAV swarm communications. Due to UAV swarm’s high dynamism on outside environment and its own inside topology, the central optimization approach may bring extremely high complexity and large control cost. We solve the UAV swarm energy optimization problem by using game theory and distributed learning algorithm. First, we propose a distributed optimal EE UAV relay game model, and prove that the proposed game is an exact potential game. Second, we design a distributed UAV relay decision algorithm to obtain the optimal solution to the UAV swarm energy optimization problem. Finally, simulation results verify the theoretic analysis and show that the proposed approach could achieve optimal EE.
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Acknowledgments
The work is supported by the National Natural Science Foundation of China (No. 61702543, 61271254, 71501186 and 71401176), the Natural Science Foundation of Jiangsu Province of China (No. BK20141071, BK20140065), the 333-high-level talent training project of Jiangsu Province of China (No. BRA 2016542).
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Zhu, L., Yao, C. & Wang, L. Optimal Energy Efficiency Distributed Relay Decision in UAV Swarms. Wireless Pers Commun 102, 2997–3008 (2018). https://doi.org/10.1007/s11277-018-5321-5
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DOI: https://doi.org/10.1007/s11277-018-5321-5