A UAV-Assisted Secure Communication System by Jointly Optimizing Transmit Power and Trajectory in the Internet of Things

Tian, Wen; Ding, Xufei; Liu, Guangjie; Dai, Yuewei; Han, Zhu

doi:10.1109/tgcn.2023.3235887

Cited by 5 publications

(7 citation statements)

References 37 publications

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“…At the terminal level, various scenarios, including intelligent vehicle networks, intelligent manufacturing, airborne networks, and seaborne networks, seamlessly join sensing communication and computation. 31 These scenarios enable data communication and transmission. The data is collected at this level and then transmitted to the edge level, where a base station employs beamforming (BF) to gather the data.…”

Section: Components For Uav-aided Isacmentioning

confidence: 99%

Multi‐UAV path planning utilizing the PGA algorithm for terrestrial IoT sensor network under ISAC framework

Azadur,

Pawase,

Chang

2023

Trans Emerging Tel Tech

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The integration of internet of things (IoT) technologies with unmanned aerial vehicles (UAVs) has initiated a groundbreaking revolution in data acquisition and communication systems across diverse domains. This document introduces an innovative endeavor, the integration of multi‐UAV path planning for integrated sensing and communication (ISAC) within ground‐based CAT‐M1 IoT sensor networks, accomplished through the application of the Pareto‐based genetic ant colony optimization (PGA) algorithm. The PGA algorithm is highly capable of UAV path planning due to its efficiency, adaptability, and seamless integration of domain expertise. By employing the PGA algorithm, we simultaneously minimize UAV travel distance while optimizing energy consumption, resulting in multi‐objective optimization. The synergy of ground‐based IoT sensors and seamless UAV communication, coupled with a convex optimization resource allocation algorithm, empowers real‐time data acquisition and heightens situational awareness. Our proposed UAV path planning PGA algorithm with resource allocation is crafted to maximize the efficiency of ground‐based sensor data acquisition. We stand at the forefront of advancing multi‐UAV data collection systems with this pioneering approach, promoting increased efficiency, robustness, and transformative solutions across diverse domains. The proposed system for ISAC achieves an impressive throughput of up to 95% of the system's capacity.

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Section: Components For Uav-aided Isacmentioning

confidence: 99%

Multi‐UAV path planning utilizing the PGA algorithm for terrestrial IoT sensor network under ISAC framework

Azadur,

Pawase,

Chang

2023

Trans Emerging Tel Tech

View full text Add to dashboard Cite

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“…Although the maximal secure rate is achieved, the secure EE was not investigated for such deployment in the work of Ji et al 19 Similarly, we see that in this work of Ji et al, 19 the UAV acts as a relay when the request content is not cached in the UAV. While the aforementioned works considered the case where the UAV acts as a mobile relay or BS, [8][9][10][11][12][13][14][15][16][17][19][20][21] the works of Chen et al and Xiong et al [20][21][22] investigated the UAV data collection paradigm. In practice, the UAV-assisted wireless data collection model can be regarded as the same type as the case where the UAV acts as relay or BS.…”

Section: Related Workmentioning

confidence: 99%

“…While the aforementioned works that considered the case where the UAV is used as a mobile relay or BS, [8][9][10][11][12][13][14][15][16][17][19][20][21][22][23] the works of Li et al [24][25][26][27] regarded the UAV as a mobile and friendly jammer to enhance the PL security by injecting the jamming signals over wiretap channels, which is also a promising application direction of UAVs. Specially, the work of Li et al 24 considered the case where two UAVs transmit confidential messages to their special ground destinations in the presence of a ground Eve.…”

Section: Related Workmentioning

confidence: 99%

“…The work of Tian et al focused on a UAV-relay assisted device-to-device (D2D) network with an Eve overhearing the confidential information delivered from the relay. 17 Specially, this work assumed that the UAV operates in FD mode. Though the work focused on the secure data collection through a UAV, the introduced mode is equivalent to a UAV-relay assisted mode under a malicious Eve.…”

Section: Related Workmentioning

confidence: 99%

“…, and the UAV trajectory q. With ( 24) and (17), this secure EE optimization problem is formulated as…”

Section: Energy-efficient Problem Formulationmentioning

confidence: 99%

See 2 more Smart Citations

Physical layer security‐oriented energy‐efficient resource allocation and trajectory design for UAV jammer over 5G millimeter wave cognitive relay system

Sun,

Jia,

Han

et al. 2023

Trans Emerging Tel Tech

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This work focuses on the optimal trajectory of a rotary‐wing unmanned aerial vehicle (UAV) jammer and the system power allocation with the objective of maximizing the total secure energy efficiency (EE) of a slotted relay‐assisted millimeter wave (mm‐Wave) cognitive radio system. The UAV flies from starting location to final one in a round of communication mission that is overheard by a malicious eavesdropper. The network terminals are equipped with multiple‐input multiple‐output (MIMO) antenna array. This work first develops a practical approximation propagation model by addressing three key challenges: path loss, small‐scale Nakagami‐m fading channel gains, and transceiver antenna beamforming gains. By using the approximate model, the upper and lower bounds of the ergodic rate of each communication link are derived. Second, with the objective of maximizing secure EE, the optimal UAV trajectory and system resource allocation framework is established by considering the constraints of interference at primary receiver (PR), information‐causality relationship, rotary‐wing UAV propulsion energy and so forth. The optimal framework is solved with a tractable CVX tool by using the derived upper and lower bounds and successive convex approximation. Finally, an iterative optimizing algorithm is established by using Dinkelbach's method. In the simulation, the work presents the comparison of UAV trajectories, secure rates, and secure EEs of three schemes, that is, the proposed EE scheme, the non‐EE scheme where only the optimal secure rate is considered, and the EE scheme with the consideration of all communication‐related energy consumption. The simulations show that the EE schemes achieve smoother UAV trajectory than non‐EE, but the non‐EE scheme has higher secure rate. The impact of communication energy consumption is negligible. In addition, the effect of MIMO antenna array and mm‐Wave on system performance is exploited.

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A survey on essential challenges in relay-aided D2D communication for next-generation cellular networks

Salim

El-Sayed

Abdalzaher

2023

Journal of Network and Computer Applications

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A UAV-Assisted Secure Communication System by Jointly Optimizing Transmit Power and Trajectory in the Internet of Things

Cited by 5 publications

References 37 publications

Multi‐UAV path planning utilizing the PGA algorithm for terrestrial IoT sensor network under ISAC framework

Multi‐UAV path planning utilizing the PGA algorithm for terrestrial IoT sensor network under ISAC framework

Physical layer security‐oriented energy‐efficient resource allocation and trajectory design for UAV jammer over 5G millimeter wave cognitive relay system

A survey on essential challenges in relay-aided D2D communication for next-generation cellular networks

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