Secrecy Energy Efficiency Maximization for UAV-Aided Communication Systems

  • Meng Hua
  • Chunguo Li
  • Luxi YangEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11743)


This paper investigates unmanned aerial vehicle (UAV) enabled secure transmission systems, where a source UAV (SUAV) intends to send confidential signals to the legitimate user in the presence of a potential eavesdropper. To improve the system’s secrecy rate, a jamming UAV (JUAV) is leveraged to cooperatively send interference signals to the potential eavesdropper. By taking into account the limited energy budget of UAV, our goal is to maximize the system secrecy energy efficiency (SEE), namely the achievable secrecy rate per energy consumption unit, by jointly optimizing UAV trajectory and transmit power under the constraints of UAV mobility as well as the maximum transmit power. The formulated problem is shown to be a non-convex fractional optimization problem, which is challenging to solve. To this end, we decompose the original problem into two sub-problems, and then an efficient iterative algorithm is proposed by leveraging block coordinate descent and Dinkelbach method in combination with successive convex approximation techniques. Simulation results show that the proposed scheme outperforms other benchmarks significantly in terms of the system SEE.


Secure transmission UAV Trajectory optimization Cooperative jamming 



This work was supported by National High Technology Project of China 2015AA-01A703, Scientific and Technological Key Project of Henan Province under Grant 182102210449 and China Postdoctoral Science Foundation under Grant 2018M63- 3733, Scientific Research Foundation of Graduate School of Southeast University under Grand YBPY1859, National Natural Science Foundation of China under Grant 61801435, Grant 61671144, Grant 61372101, Grant 61720106003, in part by the Scientific Key Research Project of Henan Province for Colleges and Universities under Grand 19A510024.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Information Science and EngineeringSoutheast UniversityNanjingChina

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