Ultra-Reliable and Low-Latency Communications in Unmanned Aerial Vehicle Communication Systems

She, Changyang; Liu, Chenxi; Quek, Tony Q. S.; Yang, Chenyang; Li, Yonghui

doi:10.1109/tcomm.2019.2896184

Cited by 120 publications

(60 citation statements)

References 28 publications

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“…Therefore non-negligible packet error probability exists and effective throughput may drop. In [12], the authors derived the maximum range between UAVs and a ground control station such that the transmission delay and the overall packet loss probability requirement can be guaranteed. In [13], the UAV serves as a relay to provide URLLC services between the controller and the robot.…”

Section: Introductionmentioning

confidence: 99%

Packet Error Probability and Effective Throughput for Ultra-Reliable and Low-Latency UAV Communications

Wang

Pan

Ren

et al. 2021

IEEE Trans. Commun.

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In this paper, we study the average packet error probability (APEP) and effective throughput (ET) of the control link in unmanned-aerial-vehicle (UAV) communications, where the ground central station (GCS) sends control signals to the UAV that requires ultra-reliable and low-latency communications (URLLC). To ensure the low latency, short packets are adopted for the control signal. As a result, the Shannon capacity theorem cannot be adopted here due to its assumption of infinite channel blocklength. We consider both free space (FS) and 3-Dimensional (3D) channel models by assuming that the locations of the UAV are randomly distributed within a restricted space. We first characterize the statistical characteristics of the signal-to-noise ratio (SNR) for both FS and 3D models. Then, the closed-form analytical expressions of APEP and ET are derived by using Gaussian-Chebyshev quadrature. Also, the lower bounds are derived to obtain more insights. Finally, we obtain the optimal value of packet length with the objective of maximizing the ET by applying one-dimensional search. Our analytical results are verified by the Monte-Carlo simulations.

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Section: Introductionmentioning

confidence: 99%

Packet Error Probability and Effective Throughput for Ultra-Reliable and Low-Latency UAV Communications

Wang

Pan

Ren

et al. 2021

IEEE Trans. Commun.

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“…We note that the location uncertainty of the eavesdropping UAVs makes it challenging to obtain a mathematically tractable expression of the objective function in (19). To do so, we consider the eavesdropper location that results in the worst-case lower bound on the secrecy capacity of the i-th offloading user, which is given by 2 when v e =ṽ e − y−ṽe ||y−ṽe|| χ. Therefore, to make (19) more tractable, we have transformed the objective function to maximize the minimum lower bound secrecy capacity min i∈Nas C lb i .…”

Section: Problem Formulationmentioning

confidence: 99%

“…U NMANNED aerial vehicles (UAVs) are promising for on-demand deployment in wireless networks due to their mobility and flexibility [1], [2]. The strong line-of-sight (LoS) characteristics of UAV air-to-ground communications have also attracted significant commercial interest for delivering high-quality aerial services.…”

Section: Introductionmentioning

confidence: 99%

Secure Communications for UAV-Enabled Mobile Edge Computing Systems

Zhou

Pan

Yeoh

et al. 2020

IEEE Trans. Commun.

Self Cite

192

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In this paper, we propose a secure unmanned aerial vehicle (UAV) mobile edge computing (MEC) system where multiple ground users offload large computing tasks to a nearby legitimate UAV in the presence of multiple eavesdropping UAVs with imperfect locations. To enhance security, jamming signals are transmitted from both the full-duplex legitimate UAV and non-offloading ground users. For this system, we design a low-complexity iterative algorithm to maximize the minimum secrecy capacity subject to latency, minimum offloading and total power constraints. Specifically, we jointly optimize the UAV location, users' transmit power, UAV jamming power, offloading ratio, UAV computing capacity, and offloading user association. Numerical results show that our proposed algorithm significantly outperforms baseline strategies over a wide range of UAV selfinterference (SI) efficiencies, locations and packet sizes of ground users. Furthermore, we show that there exists a fundamental tradeoff between the security and latency of UAV-enabled MEC systems which depends on the UAV SI efficiency and total UAV power constraints.

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“…With Massive MIMO, further functionalities can be added, for example: control signals for re-orienting drone's antenna towards the GS and selection of antenna polarization. In order to achieve high reliability, instead of spatial multiplexing, it is preferred to transmit the control information on orthogonal resource elements [54].…”

Section: What and How Much Massive Mimo Can Provide For Drone Commentioning

confidence: 99%

“…For example, in some applications, at mmWave frequencies, the drones themselves can be equipped with antenna arrays to achieve additional capacity gains [81]- [83]. In other applications, the antenna elements may be distributed over a large geographical region [54]. Massive…”

Section: Networking Challengesmentioning

confidence: 99%

Massive MIMO for Connectivity With Drones: Case Studies and Future Directions

Chandhar¹,

Larsson

2019

IEEE Access

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Unmanned aerial vehicles (UAVs), also known as drones, are proliferating. Applications such as surveillance, disaster management, and drone racing place high requirements on the communication with the drones in terms of throughout, reliability and latency. Existing wireless technologies, notably WiFi, that are currently used for drone connectivity are limited to short ranges and low-mobility situations. A new, scalable technology is needed to meet future demands on long connectivity ranges, support for fast-moving drones, and the possibility to simultaneously communicate with entire swarms of drones. Massive multiple-input and multiple-output (MIMO), a main technology component of emerging 5G standards, has the potential to meet these requirements.

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Ultra-Reliable and Low-Latency Communications in Unmanned Aerial Vehicle Communication Systems

Cited by 120 publications

References 28 publications

Packet Error Probability and Effective Throughput for Ultra-Reliable and Low-Latency UAV Communications

Packet Error Probability and Effective Throughput for Ultra-Reliable and Low-Latency UAV Communications

Secure Communications for UAV-Enabled Mobile Edge Computing Systems

Massive MIMO for Connectivity With Drones: Case Studies and Future Directions

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