Holes-in-the-Sky: A field study on cellular-connected UAS

Teng, Ervin; Falcão, João; Iannucci, Bob

doi:10.1109/icuas.2017.7991402

Cited by 16 publications

(15 citation statements)

References 9 publications

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“…PL(dB) = 20 log( 4π d 0 λ ) + X di s + X f r eq + X h ei + X a ng , X di s , X f r eq , X h ei , X a ng : 3D distance, frequency, altitude and tilt angle dependent parameters [64] PL(dB) = α(h U AV )10 [66] PL(dB) = −20 log 10 |ν | + 40 log 10 (d) − 10 log 10 (h 2 B S h 2 U AV ), ν: Kirchoff diffraction parameter [72] PL(dB) = P t x − 10 log 10 (12.BW ) − RSRP + G U AV + G B S P t x : maximum transmit power, BW : transmission bandwidth, RSRP: measured reference signal received power, G U AV : gain of UAV antenna, G B S : gain of base station antenna α: path loss exponent, RSS: received signal strength, d: separation distance, d 0 : reference distance, d b : breakpoint distance, C P : foliage loss, σ:…”

Section: Empirical Channel Models From Measurement Campaignsmentioning

confidence: 99%

“…In this work, the model parameters are dependent on the angle between cellular base station and airborne UAV. In [66], the combinational model was developed to determine the low coverage zones in the cellular-connected UAV network. This model identified causes, such as two-ray ground reflections, diffraction losses and nulls in antenna radiation pattern as the predominant factors for path loss.…”

Section: Empirical Channel Models From Measurement Campaignsmentioning

confidence: 99%

“…However, these studies have ignored connectivity disruption issues occurred in the UAV-cellular systems due to diffraction losses and nulls in the radiation pattern of the base station's antenna. Therefore, in [66], the measurement campaign was conducted for an open area and a mock village in California, USA, with a 909 MHz cellular band. In this work, the authors proposed the compositional path loss model to account for two-ray ground reflection propagation and diffraction losses.…”

Section: Cellular-connected Uav Measurementsmentioning

confidence: 99%

See 2 more Smart Citations

A Survey of Channel Modeling for UAV Communications

Khuwaja

Chen

Zhao

et al. 2018

IEEE Commun. Surv. Tutorials

714

346

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Unmanned aerial vehicles (UAVs) have gained great interest for rapid deployment in both civil and military applications. UAV communication has its own distinctive channel characteristics compared with widely used cellular and satellite systems. Thus, accurate channel characterization is crucial for the performance optimization and design of efficient UAV communication systems. However, several challenges exist in UAV channel modeling. For example, propagation characteristics of UAV channels are still less explored for spatial and temporal variations in non-stationary channels. Also, airframe shadowing has not yet been investigated for small size rotary UAVs. This paper provides an extensive survey on the measurement campaigns launched for UAV channel modeling using low altitude platforms and discusses various channel characterization efforts. We also review the contemporary perspective of UAV channel modeling approaches and outline some future research challenges in this domain.

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Section: Empirical Channel Models From Measurement Campaignsmentioning

confidence: 99%

Section: Empirical Channel Models From Measurement Campaignsmentioning

confidence: 99%

Section: Cellular-connected Uav Measurementsmentioning

confidence: 99%

See 1 more Smart Citation

A Survey of Channel Modeling for UAV Communications

Khuwaja

Chen

Zhao

et al. 2018

IEEE Commun. Surv. Tutorials

714

346

View full text Add to dashboard Cite

show abstract

“…To assist path planning, we resort to aerial coverage maps, which can help UAVs to avoid "holes-in-the-sky" [11]. The superiority of the map-based approach has been verified in the positioning of a UAV relay [12] and trajectory optimization for UAV base stations [13].…”

Section: B Aerial Coverage Map Modelmentioning

confidence: 99%

Connectivity-Aware UAV Path Planning with Aerial Coverage Maps

Yang

Zhang

Song

et al. 2019

2019 IEEE Wireless Communications and Networking Conference (WCNC)

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Cellular networks are promising to support effective wireless communications for unmanned aerial vehicles (UAVs), which will help to enable various long-range UAV applications. However, these networks are optimized for terrestrial users, and thus do not guarantee seamless aerial coverage. In this paper, we propose to overcome this difficulty by exploiting controllable mobility of UAVs, and investigate connectivity-aware UAV path planning. To explicitly impose communication requirements on UAV path planning, we introduce two new metrics to quantify the cellular connectivity quality of a UAV path. Moreover, aerial coverage maps are used to provide accurate locations of scattered coverage holes in the complicated propagation environment. We formulate the UAV path planning problem as finding the shortest path subject to connectivity constraints. Based on graph search methods, a novel connectivity-aware path planning algorithm with low complexity is proposed. The effectiveness and superiority of our proposed algorithm are demonstrated using the aerial coverage map of an urban section in Virginia, which is built by ray tracing. Simulation results also illustrate a tradeoff between the path length and connectivity quality of UAVs.

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“…Pinto et al [ 20 ] provided a model for the quality of the UAV-to-UAV link regarding packet delivery ratio as a function of distance, packet size, and orientation, which was further supported by an extensive measurement campaign. Teng et al [ 21 ] modeled the contributors to path loss and formed a combined propagation model that more accurately reflects the reality of tested scenarios. Various types of MAC protocols, whether they are contention-based, contention-free [ 22 ], or hybrid MAC protocols [ 23 ] have been suggested for vehicle ad-hoc networks (VANETs) and tested in simulations.…”

Section: Related Workmentioning

confidence: 99%

Communication Architecture in Mixed-Reality Simulations of Unmanned Systems

Martin

Faigl

Rollo

2018

Sensors

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Verification of the correct functionality of multi-vehicle systems in high-fidelity scenarios is required before any deployment of such a complex system, e.g., in missions of remote sensing or in mobile sensor networks. Mixed-reality simulations where both virtual and physical entities can coexist and interact have been shown to be beneficial for development, testing, and verification of such systems. This paper deals with the problems of designing a certain communication subsystem for such highly desirable realistic simulations. Requirements of this communication subsystem, including proper addressing, transparent routing, visibility modeling, or message management, are specified prior to designing an appropriate solution. Then, a suitable architecture of this communication subsystem is proposed together with solutions to the challenges that arise when simultaneous virtual and physical message transmissions occur. The proposed architecture can be utilized as a high-fidelity network simulator for vehicular systems with implicit mobility models that are given by real trajectories of the vehicles. The architecture has been utilized within multiple projects dealing with the development and practical deployment of multi-UAV systems, which support the architecture’s viability and advantages. The provided experimental results show the achieved similarity of the communication characteristics of the fully deployed hardware setup to the setup utilizing the proposed mixed-reality architecture.

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Holes-in-the-Sky: A field study on cellular-connected UAS

Cited by 16 publications

References 9 publications

A Survey of Channel Modeling for UAV Communications

A Survey of Channel Modeling for UAV Communications

Connectivity-Aware UAV Path Planning with Aerial Coverage Maps

Communication Architecture in Mixed-Reality Simulations of Unmanned Systems

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