Secrecy Energy Efficiency Maximization for UAV-Enabled Multi-Hop Mobile Relay System

doi:10.19682/j.cnki.1005-8885.2022.1002

中国邮电高校学报(英文) ›› 2022, Vol. 29 ›› Issue (3): 81-91.doi: 10.19682/j.cnki.1005-8885.2022.1002

Secrecy Energy Efficiency Maximization for UAV-Enabled Multi-Hop Mobile Relay System

Beijing Laboratory of Advanced Information Networks, Beijing University of Posts and Telecommunications, Beijing 100876, China

收稿日期:2021-02-27 修回日期:2021-07-08 出版日期:2022-06-30 发布日期:2022-06-30
通讯作者: Miao Jiansong E-mail:lhr@bupt.edu.cn
基金资助:
This work was supported by the Natural Science Foundation of Beijing Municipality (19L2045)

Secrecy Energy Efficiency Maximization for UAV-Enabled Multi-Hop Mobile Relay System

Beijing Laboratory of Advanced Information Networks, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2021-02-27 Revised:2021-07-08 Online:2022-06-30 Published:2022-06-30
Contact: Miao Jiansong E-mail:lhr@bupt.edu.cn
Supported by:
This work was supported by the Natural Science Foundation of Beijing Municipality (19L2045)

摘要/Abstract

摘要：

To deal with the secrecy issues and energy efficiency issues in the unmanned aerial vehicles ( UAVs) assisted communication systems, an UAV-enabled multi-hop mobile relay system is studied in an urban environment. Multiple rotary-wing UAVs with energy budget considerations are employed as relays to forward confidential information between two ground nodes in the presence of multiple passive eavesdroppers. The system secrecy energy efficiency ( SEE), defined by the ratio of minimum achievable secrecy rate ( SR) to total propulsion energy consumption (PEC), is maximized via jointly optimizing the trajectory and transmit power of each UAV relay. To solve the formulated non-convex fractional optimization problem subject to mobility, transmit power and information-causality constraints, an effective iterative algorithm is proposed by applying the updated-rate-assisted block coordinate decent method, successive convex approximation (SCA) technique and Dinkelbach method. Simulation

results demonstrate the effectiveness of the proposed joint trajectory design and power control scheme.

关键词: secrecy transmission, unmanned aerial vehicle (UAV), trajectory optimization, mobile relay

Abstract:

results demonstrate the effectiveness of the proposed joint trajectory design and power control scheme.

Key words: secrecy transmission, unmanned aerial vehicle (UAV), trajectory optimization, mobile relay

Miao Jiansong, Li Hairui, Zheng Ziyuan, Wang Chu, Zhao Zhenmin. Secrecy Energy Efficiency Maximization for UAV-Enabled Multi-Hop Mobile Relay System[J]. The Journal of China Universities of Posts and Telecommunications, 2022, 29(3): 81-91.

参考文献

1. ZENG Y, ZHANG R, LIM T J. Wireless communications with unmanned aerial vehicles: Opportunities and challenges. IEEE Communications Magazine, 2016, 54(5): 36-42.

2. ZENG Y, ZHANG R, LIM T J. Throughput maximization for UAV-enabled mobile relaying systems. IEEE Transactions on Communications, 2016, 64(12): 4983-4996.

3. ZHANG S H, ZHANG H L, HE Q C, et al. Joint trajectory and power optimization for UAV relay networks. IEEE Communications Letters, 2018, 22(1): 161-164.

4. ZENG Y, ZHANG R. Energy-efficient UAV communication with trajectory optimization. IEEE Transactions on Wireless Communications, 2017, 16(6): 3747-3760.

5. ZENG Y, XU J, ZHANG R. Energy minimization for wireless communication with rotary-wing UAV. IEEE Transactions on Wireless Communications, 2019, 18(4): 2329-2345.

6. ZHANG G C, WU Q Q, CUI M, et al. Securing UAV communications via trajectory optimization and power control. IEEE Transactions on Wireless Communications, 2019, 18(2): 1376-1389.

7. LI A, WU Q Q, ZHANG R. UAV-enabled cooperative jamming for improving secrecy of ground wiretap channel. IEEE Wireless Communications Letters, 2019, 8(1): 181-184.

8. MIAO J S, ZHENG Z Y. Cooperative jamming for secure UAV-enabled mobile relay system. IEEE Access, 2020, 8: 48943-48957.

9. HUA M, WANG Y, WU Q Q, et al. Energy-efficient cooperative secure transmission in multi-UAV-enabled wireless networks. IEEE Transactions on Vehicular Technology, 2019, 68(8): 7761-7775.

10. CHEN Y F, ZHAO N, DING Z G, et al. Multiple UAVs as relays: Multi-hop single link versus multiple dual-hop links. IEEE Transactions on Wireless Communications, 2018, 17(9): 6348-6359.

11. ZHANG Y, MOU Z Y, GAO F F, et al. UAV-enabled secure communications by multi-agent deep reinforcement learning. IEEE Transactions on Vehicular Technology, 2020, 69(10): 11599-11611.

12. MUKHERJEE A, SWINDLEHURST A L. Detecting passive eavesdroppers in the MIMO wiretap channel. Proceedings of the 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’12), 2012, Mar 25-30, Kyoto, Japan. Piscataway, NJ, USA: IEEE, 2012: 2809-2812.

13. ALZAHRANI B, OUBBATI O S, BARNAWI A, et, al. UAV assistance paradigm: State-of-the-art in applications and challenges. Journal of Network and Computer Applications, 2020, 166: Article 102706/1-44.

14. MOZAFFARI M, SAAD W, BENNIS M, et al. Mobile unmanned aerial vehicles (UAVs) for energy-efficient Internet of things communications. IEEE Transactions on Wireless Communications, 2017, 16(11): 7574-7589.

15. ZHANG X C, ZHANG J, XIONG J, et, al. Energy-efficient multi-UAV-enabled multiaccess edge computing incorporating NOMA. IEEE Internet of Things Journal, 2020, 7(6): 5613-5627.

16. BOYD S, VANDENBERGHE L. Convex optimization. Cambridge, UK: Cambridge University Press, 2004.

17. PHILLIPS A T. Quadratic fractional programming: Dinkelbach method. Boston, MA, USA: Springer, 2001.

18. GRANT M, BOYD S. CVX: MATLAB software for disciplined convex programming. Austin, TX, USA: CVX Research, Inc, 2013.

19. BERTSEKAS D P. Nonlinear programming. Belmont, MA, USA: Athena Scientific, 1999.

20. WU L L, PALOMAR D P. Sequence design for spectral shaping via minimization of regularized spectral level ratio. IEEE Transactions on Signal Processing, 2019, 67(18): 4683-4695.

21. SCHAIBLE S. Fractional programming. II, on Dinkelbach’s algorithm. Management Science, 1976, 22(8): 868-873.

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Secrecy Energy Efficiency Maximization for UAV-Enabled Multi-Hop Mobile Relay System

Secrecy Energy Efficiency Maximization for UAV-Enabled Multi-Hop Mobile Relay System

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