Multi-Objective Optimization Approaches for Physical Layer Secure Communications Based on Collaborative Beamforming in UAV Networks

Unmanned aerial vehicle (UAV) communications and networks are promising technologies in the forthcoming 5G/6G wireless communications. However, they have challenges for realizing secure communications. In this paper, we consider to construct a virtual antenna array consists UAV elements and use coll...

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Vydáno v:	IEEE/ACM transactions on networking Ročník 31; číslo 4; s. 1 - 16
Hlavní autoři:	Li, Jiahui, Sun, Geng, Kang, Hui, Wang, Aimin, Liang, Shuang, Liu, Yanheng, Zhang, Ying
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.08.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Antenna arrays Autonomous aerial vehicles Beamforming Collaboration collaborative beamforming Energy consumption evolutionary computation Excitation Ground stations Jamming multi-objective optimization problem Multiple objective analysis Networks Optimization physical layer security Receivers Sidelobes Trajectory Transmitters UAV communications Unmanned aerial vehicles Wireless communications
ISSN:	1063-6692, 1558-2566
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Abstract	Unmanned aerial vehicle (UAV) communications and networks are promising technologies in the forthcoming 5G/6G wireless communications. However, they have challenges for realizing secure communications. In this paper, we consider to construct a virtual antenna array consists UAV elements and use collaborative beamforming (CB) to achieve the UAV secure communications with different base stations (BSs), subject to the known and unknown eavesdroppers on the ground. To achieve a better secure performance, the UAV elements can fly to optimal positions with optimal excitation current weights for performing CB transmissions. However, this leads to extra motion energy consumption. We formulate a physical layer secure communication multi-objective optimization problem (MOP) of UAV networks to simultaneously improve the total secrecy rates, total maximum sidelobe level (SLL) and total motion energy consumption of UAVs by jointly optimizing the positions and excitation current weights of UAVs, and the order of communicating with different BSs. Due to the complexity and NP-hardness of the formulated MOP, we propose an improved multi-objective dragonfly algorithm with chaotic solution initialization and hybrid solution update operators (IMODACH) and a parallel-IMODACH (P-IMODACH) to solve the problem. Simulation results verify that the proposed approaches can effectively solve the formulated MOP and it has better performance than some other benchmark algorithms and approaches. Moreover, some unexpected circumstances are considered and discussed.
AbstractList	Unmanned aerial vehicle (UAV) communications and networks are promising technologies in the forthcoming 5G/6G wireless communications. However, they have challenges for realizing secure communications. In this paper, we consider to construct a virtual antenna array consists UAV elements and use collaborative beamforming (CB) to achieve the UAV secure communications with different base stations (BSs), subject to the known and unknown eavesdroppers on the ground. To achieve a better secure performance, the UAV elements can fly to optimal positions with optimal excitation current weights for performing CB transmissions. However, this leads to extra motion energy consumption. We formulate a physical layer secure communication multi-objective optimization problem (MOP) of UAV networks to simultaneously improve the total secrecy rates, total maximum sidelobe level (SLL) and total motion energy consumption of UAVs by jointly optimizing the positions and excitation current weights of UAVs, and the order of communicating with different BSs. Due to the complexity and NP-hardness of the formulated MOP, we propose an improved multi-objective dragonfly algorithm with chaotic solution initialization and hybrid solution update operators (IMODACH) and a parallel-IMODACH (P-IMODACH) to solve the problem. Simulation results verify that the proposed approaches can effectively solve the formulated MOP and it has better performance than some other benchmark algorithms and approaches. Moreover, some unexpected circumstances are considered and discussed.
Author	Kang, Hui Liu, Yanheng Liang, Shuang Sun, Geng Zhang, Ying Wang, Aimin Li, Jiahui
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SubjectTerms	Algorithms Antenna arrays Autonomous aerial vehicles Beamforming Collaboration collaborative beamforming Energy consumption evolutionary computation Excitation Ground stations Jamming multi-objective optimization problem Multiple objective analysis Networks Optimization physical layer security Receivers Sidelobes Trajectory Transmitters UAV communications Unmanned aerial vehicles Wireless communications
Title	Multi-Objective Optimization Approaches for Physical Layer Secure Communications Based on Collaborative Beamforming in UAV Networks
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