Energy-Efficient Cooperative Secure Transmission in Multi-UAV-Enabled Wireless Networks

Hua, Meng; Wang, Yi; Wu, Qingqing; Dai, Haibo; Huang, Yongming; Yang, Luxi

doi:10.1109/tvt.2019.2924180

Cited by 122 publications

(86 citation statements)

References 47 publications

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“…Global throughput maximization [92]- [94] G2A/A2G throughput maximization [83], [95], [96] Maximizing energy efficiency [97] Maximizing energy efficiency [98], [99] Dynamic topology/swarm [100], [101] A2G/G2A localization [102], [103] Multi-UAV's resource allocation [104]- [106] Edge computing [107] Dense UAV networks [108] Ground node access [109], [110] station is designed with the following functions: wireless communication modules, computing/storage units with large enough capacity, intelligent decision algorithms for centralized mission planning, remote monitoring mechanisms, and recall mechanisms. The communication modules are crucial to achieve remote control for UAVs.…”

Section: Research Issuesmentioning

confidence: 99%

Unmanned aerial vehicle for internet of everything: Opportunities and challenges

Liu

Dai

Wang

et al. 2020

Computer Communications

173

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The recent advances in information and communication technology (ICT) have further extended Internet of Things (IoT) from the sole "things" aspect to the omnipotent role of "intelligent connection of things". Meanwhile, the concept of internet of everything (IoE) is presented as such an omnipotent extension of IoT. However, the IoE realization meets critical challenges including the restricted network coverage and the limited resource of existing network technologies. Recently, Unmanned Aerial Vehicles (UAVs) have attracted significant attentions attributed to their high mobility, low cost, and flexible deployment. Thus, UAVs may potentially overcome the challenges of IoE. This article presents a comprehensive survey on opportunities and challenges of UAV-enabled IoE. We first present three critical expectations of IoE: 1) scalability requiring a scalable network architecture with ubiquitous coverage, 2) intelligence requiring a global computing plane enabling intelligent things, 3) diversity requiring provisions of diverse applications. Thereafter, we review the enabling technologies to achieve these expectations and discuss four intrinsic constraints of IoE (i.e., coverage constraint, battery constraint, computing constraint, and security issues). We then present an overview of UAVs. We next discuss the opportunities brought by UAV to IoE. Additionally, we introduce a UAV-enabled IoE (Ue-IoE) solution by exploiting UAVs's mobility, in which we show that Ue-IoE can greatly enhance the scalability, intelligence and diversity of IoE. Finally, we outline the future directions in Ue-IoE.

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Section: Research Issuesmentioning

confidence: 99%

Unmanned aerial vehicle for internet of everything: Opportunities and challenges

Liu

Dai

Wang

et al. 2020

Computer Communications

173

View full text Add to dashboard Cite

show abstract

“…Consider that UAV periodically flies over the area of interest with period of T [6]. For ease of discussion, the continuous time period is equally partitioned into discrete time slots N = {1, 2, · · · , N }, with N = T /τ and τ being the discrete time interval.…”

Section: System Modelmentioning

confidence: 99%

“…The initial position of UAV is denoted as r0. Regarding wireless links between the UAV and LUs (or Eve) are assumed to be dominated by LoS; and the Doppler impacts caused by UAV movement are able to be well compensated [6]. Thus, the CSI between the UAV and LU k at slot n is modeled as…”

Section: System Modelmentioning

confidence: 99%

“…denotes the distance between the UAV and LU k; r k denotes the coordinate of LU k; and h0 stands for reference channel gain at 1 m [6,12]. Similarly, the CSI between the UAV and Eve at slot n is given by he[n] = h 0 z 2 + r[n]−re 2 , where re denotes the coordinates of Eve [6,12].…”

Section: System Modelmentioning

confidence: 99%

“…However, due to the broadcast nature of line-of-slight (LoS) wireless channels between UAVs and legitimate users (LUs), content delivery is vulnerable to information leakage and likely to be wiretapped by eavesdropper (Eve) [6]. In particular, UAVs may move around and get close to Eve when supporting content transmissions for LUs.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Latency-Minimized Design of secure transmissions in UAV-Aided Communications

et al. 2020

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Unmanned aerial vehicles (UAVs) can be utilized as aerial base stations to provide communication service for remote mobile users due to their high mobility and flexible deployment. However, the lineof-sight (LoS) wireless links are vulnerable to be intercepted by the eavesdropper (Eve), which presents a major challenge for UAV-aided communications. In this paper, we propose a latency-minimized transmission scheme for satisfying legitimate users' (LUs') content requests securely against Eve. By leveraging physical-layer security (PLS) techniques, we formulate a transmission latency minimization problem by jointly optimizing the UAV trajectory and user association. The resulting problem is a mixed-integer nonlinear program (MINLP), which is known to be NP hard. Furthermore, the dimension of optimization variables is indeterminate, which again makes our problem very challenging. To efficiently address this, we utilize bisection to search for the minimum transmission delay and introduce a variational penalty method to address the associated subproblem via an inexact block coordinate descent approach. Moreover, we present a characterization for the optimal solution. Simulation results are provided to demonstrate the superior performance of the proposed design.

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Performance analysis for energy efficient communications aided by UAV with reconfigurable intelligent surface

Liu

Sun

2022

Int J Communication

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Summary The continuous growth of wireless connectivity and the emergence of the concept of the Internet of Everything in the future sixth‐generation (6G) network require a new communication paradigm. Different from the prior works that focus on performance optimization for communication networks, in this paper, we attempt to analyze the energy efficiency of unmanned aerial vehicles (UAVs) communication aided by reconfigurable intelligent surfaces (RIS) which is a new disruptive technology, for the reason that UAV has the line‐of‐sight (LoS) link transmission and flexibility and RIS has the low power for improving the communication reliability and network coverage. At firstly, when central limit theorem (CLT) assumption is used and the number of RIS reflecting elements is large, we derive the closed‐form expression of the average signal‐to‐interference‐plus‐noise ratio (SINR) of each user based on the new BS‐RIS‐user communication link and RIS‐user/BS association. Following this, we further gain the energy efficiency (EE) in closed‐form based on random access between BS and user. Finally, we further show the performance of EE under certain assumptions. In particular, the offered results demonstrate that the use of the RIS can significantly improve EE due to RIS assist in improving the SINR and has very low transmission power; meanwhile, the UAV equipped with RIS can also improve EE for the reason that RIS can be used as a mobile relay to take advantage of the LoS link transmission.

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Energy-Efficient Cooperative Secure Transmission in Multi-UAV-Enabled Wireless Networks

Cited by 122 publications

References 47 publications

Unmanned aerial vehicle for internet of everything: Opportunities and challenges

Unmanned aerial vehicle for internet of everything: Opportunities and challenges

Latency-Minimized Design of secure transmissions in UAV-Aided Communications

Performance analysis for energy efficient communications aided by UAV with reconfigurable intelligent surface

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