City Research Online

Abstract

The recent development in Internet-of-Things (IoT) networks utilizing Unmanned Aerial Vehicles (UAVs) have greatly enhanced system analysis and management. For example, an energy management system can exploit UAVs to intelligently predict output from renewable resources and estimate grid supply. However, UAVs are battery-operated and need to be charged regularly. It has become crucial to maintain supply and achieve net-zero with negligible emissions for high energy demanding IoT networks, such as those incorporating UAVs. A promising solution is to utilize backup batteries of cellular base stations (BSs) which often remain idle when grid supply is consistent. A P2P energy exchange between a BS seller and UAV buyer is possible in exchange of some incentives. However, BS operators may become selfish and not share their energy. Also, they can behave maliciously by selling energy at unreasonably high prices or sharing false information about the original source of energy. This paper proposes an energy trading system between 5G BSs and UAVs. A Reinforcement Learning (RL) algorithm is used by UAVs to select BS which maximizes incentives for both BSs and UAVs. Blockchain security increase energy exchange by 0.26 kWh and 4.9 kWh in presence of malicious and selfish BS seller respectively.

Publication Type:	Conference or Workshop Item (Paper)
Additional Information:	© 2025 IEEE.
Publisher Keywords:	Base station, UAV, energy, blockchain
Subjects:	G Geography. Anthropology. Recreation > GE Environmental Sciences Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TJ Mechanical engineering and machinery T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TL Motor vehicles. Aeronautics. Astronautics
Departments:	School of Science & Technology School of Science & Technology > Computer Science
SWORD Depositor:	Symplectic Administrator

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