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Secrecy rate analysis of UAV-enabled mmWave networks using matern hardcore point processes

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journal contribution
posted on 09.07.2018, 10:03 by Yongxu Zhu, Gan Zheng, Michael Fitch
IEEE Communications aided by low-altitude unmanned aerial vehicles (UAVs) have emerged as an effective solution to provide large coverage and dynamic capacity for both military and civilian applications, especially in unexpected scenarios. However, because of their broad coverage, UAV communications are prone to passive eavesdropping attacks. This paper analyzes the secrecy performance of UAVs networks at the millimeter wave (mmWave) band and takes into account unique features of air-toground channels and practical constraints of UAV deployment. To be specific, it explores the 3D antenna gain in the air-toground links and uses the Matérn hardcore point process to guarantee the safety distance between the randomly deployed UAV base stations. In addition, we propose the transmit jamming strategy to improve the secrecy performance in which part of UAVs send jamming signals to confound the eavesdroppers. Simulation results verify our analysis and demonstrate the impact of different system parameters on the achievable secrecy rate. It is also revealed that optimizing the density of jamming UAVs will significantly improve security of UAV-enabled networks.

Funding

This work was supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/N007840/1.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Journal on Selected Areas in Communications

Citation

ZHU, Y., ZHENG, G. and FITCH, M., 2018. Secrecy rate analysis of UAV-enabled mmWave networks using matern hardcore point processes. IEEE Journal on Selected Areas in Communications, 36(7), pp. 1397 - 1409.

Publisher

© IEEE

Version

AM (Accepted Manuscript)

Acceptance date

01/02/2018

Publication date

2018

Notes

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

ISSN

0733-8716

Language

en

Exports