Coverage probability of multiple UAVs supported ground network

Guo, Zijun; Wei, Zhiqing; Feng, Zhiyong; Ning, Fan

doi:10.1049/el.2017.0800

Cited by 34 publications

(18 citation statements)

References 8 publications

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“…UAV-enabled relay networks in which UAV helps information transmission between far-apart or obstructed ground terminals without reliable direct communication links have attracted great attention recently. The existing literatures about UAV-enabled relay networks are mainly divided into three categories: review [10], performance analysis [11], [12], and optimization [13]- [17]. In [10], the UAV-assisted heterogeneous cellular where UAV acted as flight relay (FR) to deploy FR cells inside the macrocell was proposed to achieve dynamic and adaptive coverage.…”

Section: A Related Work and Motivationmentioning

confidence: 99%

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Physical Layer Security in Millimeter Wave SWIPT UAV-Based Relay Networks

et al. 2019

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Millimeter-wave (mmWave) communication is the rising technology for simultaneous wireless information and power transfer (SWIPT) unmanned aerial vehicle (UAV)-based relay networks for the abundant bandwidth and short wavelength. However, the secrecy performance of mmWave SWIPT UAV-based relay systems has not been investigated so far. In this paper, we consider secure transmissions of mmWave SWIPT UAV-based relay systems in the presence of multiple independent homogeneous Poisson point process (HPPP) eavesdroppers. Different from most existing works considering a free-space path loss model, the air-to-ground channels are modeled as Nakagami-m small-scale fading, and the effects of blockage to mmWave links on the ground and the 3D antenna gain model are considered. The closed-form expressions of the average achievable secrecy rate and energy coverage probability for amplify-and-forward (AF) and decode-and-forward (DF) relay protocols under power splitting (PS) SWIPT policy are derived to reveal the impact of various parameters on system performance. The simulation results show that there is the optimal UAV position to maximize the secrecy rate and the optimal position is closer to the node whose transmit power is relatively small. Furthermore, different carrier frequencies are suitable for different eavesdropping node density. INDEX TERMS Millimeter-wave (mmWave), UAV relay, SWIPT, physical-layer security. I. INTRODUCTION Low-altitude unmanned aerial vehicles (UAVs) are becoming more and more attractive for their high mobility, low-cost and flexible deployment. UAV-enabled Internet-of-things (IoT) network is a promising application with the widespread use of smart devices [1]. In some scenarios, UAVs need to support high data rate requirements, e.g., stream large real time video monitoring traffic data and high quality pictures to ground nodes. To support high data rate requirements, mmWave communication becomes a key enabler in UAV-enabled IoT network for its large available bandwidth [2], [3]. Since mmWave signals are particularly sensitive to blocking, communications on the ground will be interrupted when there are large obstacles such as hills or large buildings. Compared with the terrestrial systems, UAVs can easily move from one place to another to avoid blockages, which can maintain The associate editor coordinating the review of this manuscript and approving it for publication was Kuo-Hui Yeh.

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Section: A Related Work and Motivationmentioning

confidence: 99%

“…The achievable rate of a UAV-relayed cooperative cognitive radio MIMO system was investigated in [11]. In [12], the coverage probability of UAV-based relay network in disaster recovery was analyzed. In [13], the optimum altitude of UAV relaying for maximum reliability was investigated.…”

Section: A Related Work and Motivationmentioning

confidence: 99%

Physical Layer Security in Millimeter Wave SWIPT UAV-Based Relay Networks

et al. 2019

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“…UAV‐BS deployment from 2D scenario into 3D scenario: The previous studies on the 1‐tier network mainly focused on the analysis of a 2D scenario, but neglected the 3D deployment of UAV‐BSs, regardless of a difference in BS transmit power [23, 24]. For example, the shot‐noise analysis under a 2D scenario in stochastic geometry was discussed earlier in [25, 26], actually its results were hard to be directly applied to a 3D scenario because the computational complexity increased as an integration region changed from 2D space to 3D space, involving interference statistics and UAV‐BS density. In UAV‐BS systems, it was necessary to optimise the UAV‐BS deployment and improve the coverage from a 3D viewpoint.…”

Section: Introductionmentioning

confidence: 99%

Modelling and analysis of coverage for unmanned aerial vehicle base stations

2020

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“…The work of Reference [5] shows that for cases of Rician fading, there exists optimum height that maximizes the coverage area. In References [6,7], the coverage probability performance of multiple UAVs is studied, and the flexibility of the scalable dynamic network is considered. In Reference [8], a new method is proposed to deploy UAVs to collect uplink data from mobile ground IoT devices.…”

Section: Introductionmentioning

confidence: 99%

Joint Trajectory and Scheduling Optimization for The Mobile UAV Aerial Base Station: A Fairness Version

Chen

Zhong

et al. 2019

Applied Sciences

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Recently, unmanned aerial vehicles (UAVs) have been widely studied in the communication area to work as aerial base stations, due to the high probability of line of sight (LoS) and high flexibility. However, few works consider fairness for the users, which is one of the most important metrics for a network. In this paper, in order to maximize network capacity with the consideration of fairness, trajectory and scheduling of the mobile UAV aerial base station are jointly optimized. Firstly, the problem of maximizing network capacity with the consideration of fairness is formulated. On account of the coupling relationship of trajectory and scheduling, an alternate iteration approach that contains ant colony algorithm and genetic algorithm are then proposed to solve this intractable problem. Finally, the simulation results demonstrate the fairness enhance of the network and the validity and effectiveness of the proposed optimization approach.

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Coverage probability of multiple UAVs supported ground network

Cited by 34 publications

References 8 publications

Physical Layer Security in Millimeter Wave SWIPT UAV-Based Relay Networks

Physical Layer Security in Millimeter Wave SWIPT UAV-Based Relay Networks

Modelling and analysis of coverage for unmanned aerial vehicle base stations

Joint Trajectory and Scheduling Optimization for The Mobile UAV Aerial Base Station: A Fairness Version

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