Joint Trajectory and Resource Allocation Design for Energy-Efficient Secure UAV Communication Systems

Cai, Yuanxin; Wei, Zhiqiang; Li, Ruide; Ng, Derrick Wing Kwan; Yuan, Jinhong

doi:10.1109/tcomm.2020.2982152

Cited by 214 publications

(132 citation statements)

References 52 publications

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“…However, the security issue is not considered in these works and thus secure transmission cannot be guaranteed. Recently, the PLS techniques have been increasingly applied in UAV-enabled communication systems to enhance system security [27], [28]. For instance, a secure transmission system consisting of two UAVs is investigated in [28], where a UAV communicates with multiple legitimate users with OFDMA, and the other multi-antenna UAV acts as a jammer to interfere with Eves.…”

Section: B Related Work 1) Terrestrial Networkmentioning

confidence: 99%

“…Recently, the PLS techniques have been increasingly applied in UAV-enabled communication systems to enhance system security [27], [28]. For instance, a secure transmission system consisting of two UAVs is investigated in [28], where a UAV communicates with multiple legitimate users with OFDMA, and the other multi-antenna UAV acts as a jammer to interfere with Eves. The system energy efficiency maximization problem is studied by jointly optimizing the UAV trajectory, resource allocation and jammer policy.…”

Section: B Related Work 1) Terrestrial Networkmentioning

confidence: 99%

“…Note that the work in [25] investigates the UAV trajectory at the edge of multiple cells for data offloading. The works in [26] and [28] study the joint UAV trajectory and resource allocation optimization for solar-powered UAV communications and energy-efficient secure UAV communications, respectively. However, in comparison with [25], [26], [28], we consider CR-NOMA based UAV communications, which brings additional challenges to the trajectory design and power allocation since NOMA introduces varying binary SIC order determined by the UAV trajectory.…”

Section: Contribution and Organizationmentioning

confidence: 99%

“…Specifically, SRs and PRs can obtain their locations via a global positioning system (GPS) and report location information to the UAV by performing handshaking with the UAV at the beginning of each time slot. The Eve location can be detected by using an optical camera or synthetic aperture radar (SAR) equipped on the UAV [27], [28]. This provides key insights for practical designs with partial/imperfect knowledge of location information.…”

Section: System Model and Problem Formulation A System Modelmentioning

confidence: 99%

“…Hence, the channel state information (CSI) between each node and UAV can be determined by its location. Therefore, based on location information, the UAV can easily obtain CSI of SRs, PRs and Eves for all the time slots for any positions of the UAV [27], [28]. Thus, the channel power gains from the UAV to k-th SR, i-PR and Eve in time slot n follow the free-space path loss model, which are respectively given as…”

Section: System Model and Problem Formulation A System Modelmentioning

confidence: 99%

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Cognitive NOMA for UAV-Enabled Secure Communications: Joint 3D Trajectory Design and Power Allocation

Tang

2020

IEEE Access

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In the paper, we investigate the physical layer security (PLS) of an unmanned aerial vehicle (UAV) enabled communication system that integrates non-orthogonal multiple access (NOMA) with cognitive radio (CR), namely CR-NOMA. Specifically, the secondary UAV transmits confidential information to multiple secondary legitimate receivers with NOMA by sharing the spectrum with the primary networks, while an eavesdropper (Eve) attempts to wiretap the communication. We aim to jointly optimize the three-dimensional (3D) UAV trajectory and power allocation to maximize the worst-case average secrecy sum rate of all secondary receivers (SRs) while keeping the interference to primal receivers (PRs) below a certain threshold. The formulated problem is mixed-binary non-convex and is generally NP-hard. To address this issue, we first equivalently transform the binary variables into continuous ones by introducing tractable inequality constraints. Then, we decompose the optimization problem into two subproblems and develop an efficient iterative algorithm based on the successive convex approximate (SCA) technique, block coordinate descent (BCD) technique, and penalty function method. Numerical results are extensively studied to show that the proposed joint design significantly outperforms the benchmark schemes in terms of secrecy rate. INDEX TERMS UAV communications, physical layer security, NOMA, cognitive radio, 3D trajectory design, power allocation.

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Section: B Related Work 1) Terrestrial Networkmentioning

confidence: 99%

Section: B Related Work 1) Terrestrial Networkmentioning

confidence: 99%

Section: Contribution and Organizationmentioning

confidence: 99%

Section: System Model and Problem Formulation A System Modelmentioning

confidence: 99%

Section: System Model and Problem Formulation A System Modelmentioning

confidence: 99%

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Cognitive NOMA for UAV-Enabled Secure Communications: Joint 3D Trajectory Design and Power Allocation

Tang

2020

IEEE Access

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A survey on green unmanned aerial vehicles‐based fog computing: Challenges and future perspective

Gupta

2022

Trans Emerging Tel Tech

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In the area of unmanned aerial vehicles (UAVs) and the Internet of Things (IoT), enormous technological advancement has transformed the way we choose to live. UAVs link everything in the modern world, and it is an attractive area for academia to focus on. UAVs are proven to be a boon for the whole world as it provides flying services in critical and medical emergencies. UAVs are futuristic technology that enriches human needs by providing numerous benefits or services to proceed toward the smart world. In UAV‐assisted traditional networks, multiple sensors and flying nodes consume a lot of energy resources, and Fifth Generation (5G)/Beyond 5G enabled devices to excrete high radiations, which may cause damage to our environment as well as our society. So, it is very important to maintain a balance between the environment and modern technologies for a better lifestyle. To maintain this, many steps need to be put further to reduce the energy consumption of nodes, consume fewer data resources, and encourage effective energy‐use techniques. Green UAV‐based fog computing is a promising solution to balance environmental issues and provide energy‐efficient data computation and aerial to ground network communication for building an intelligent world with improved Quality of Services (QoS). This article provides a comprehensive survey on green technologies and applications for UAV‐Fog. We also highlight research issues, current challenges, lessons learned, and the future direction of the UAV‐Fog network.

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UAV Jamming Localization Against Random Eavesdropper Positions Using Cuckoo Search Algorithm

Taleb,

Benssalah

2024

Security and Privacy

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Unmanned Aerial Vehicle (UAV) jammer localization refers to the process of determining the optimal location for a UAV jammer to be placed to interfere with an eavesdropper's communication with a target. In fact, the main goal is to maximize the jamming signal power at the eavesdropper's position while minimizing the jamming signal power at the target's position. This paper leverages Cuckoo Search algorithm for the secrecy rate optimization which refers to the amount of secure information transmitted from the target to the intended receiver. The model is composed with an UAV jammer, two ground nodes and an illegitimate user with unknown position. True uniform random deployment processes is used to model the randomness of the eavesdropper location. Further, a novel summed secrecy approach is proposed to determine the overall optimal UAV position. Simulations demonstrate the superiority of the novel approach versus other benchmark algorithms across various numbers of eavesdroppers.

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Joint Trajectory and Resource Allocation Design for Energy-Efficient Secure UAV Communication Systems

Cited by 214 publications

References 52 publications

Cognitive NOMA for UAV-Enabled Secure Communications: Joint 3D Trajectory Design and Power Allocation

Cognitive NOMA for UAV-Enabled Secure Communications: Joint 3D Trajectory Design and Power Allocation

A survey on green unmanned aerial vehicles‐based fog computing: Challenges and future perspective

UAV Jamming Localization Against Random Eavesdropper Positions Using Cuckoo Search Algorithm

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