(A) study on secrecy energy efficiency maximization for secure UAV-assisted SWIPT systems

Abstract

Unmanned aerial vehicle (UAV)-based technology has recently become a significant growing fields thanks to advantages such as high mobility, affordable installation costs, and flexible deployment. In terms of wireless communication technology, UAV have been paid attention as a major element for Internet-of-Things (IoT) networks. In particular, attempts are being made to fully demonstrate the strengths of UAVs in infra-limited or infra-less environments, such as rural areas, disaster and emergency response, and military service situations. UAV-enabled communication is emerging as a technology that replaces the role of ground base stations such as distributing data traffic and enhancing coverage of cellular communications, and guarantees data transmission and reception as a temporary base station in special circumstances. Compared to quasi-stationary terrestrial communication systems, UAV-based systems can be flexibly deployed through high mobility and can increase stability by securing air-to-ground channels dominated by line-of-sight (LOS). Behind flexibilities and strengths, UAV-based communication systems have a significant problem of security vulnerabilities due to the LOS channels. By exploiting the characteristics of UAVs, physical layer security of UAV-assisted communication systems is being studied. In addition, the limitation of battery capacity is an inevitable physical limitation of UAVs. In this dissertation, a secure UAV-assisted simultaneous wireless information and power transfer (SWIPT) system is proposed to maximize the secrecy energy efficiency (SEE) of ground network, where a base station transmits a confidential message to an energy-constrained device in the presence of a passive eavesdropper (Eve) with an UAV as a helper node. In terms of energy management to overcome the limitation of battery capacity, UAV-assisted SWIPT system is considered and deals with the maximization problem of SEE. For the SEE maximization of UAV, we formulate the problem of jointly optimizing transmit powers for source and UAV, power splitting ratio of energy harvesting (EH), and flying trajectory of the UAV, and develop the algorithm to address the solution by leveraging successive convex approximation (SCA) and Dinkelbach’s algorithm. Via numerical results, it is verified that the proposed algorithm for joint optimization outperforms other benchmark schemes, which corroborates its feasibility and effectiveness.