A Stochastic Model for UAV Networks Positioned Above Demand Hotspots in Urban Environments

Galkin, Boris; Kibiłda, Jacek; DaSilva, Luiz A.

doi:10.1109/tvt.2019.2916429

Cited by 92 publications

(66 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In particular, the antenna gain of the main lobe can be approximated as G ≈ 2.285 Ψ 2 [59]. Such antenna modelling has been used for both scenarios when UAV is used as aerial BS [59]- [61] or aerial user [57].…”

Section: B Antenna Modelmentioning

confidence: 99%

Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond

2019

View full text Add to dashboard Cite

Unmanned aerial vehicles (UAVs) have found numerous applications and are expected to bring fertile business opportunities in the next decade. Among various enabling technologies for UAVs, wireless communication is essential and has drawn significantly growing attention in recent years. Compared to the conventional terrestrial communications, UAVs' communications face new challenges due to their high altitude above the ground and great flexibility of movement in the threedimensional (3D) space. Several critical issues arise, including the line-of-sight (LoS) dominant UAV-ground channels and resultant strong aerial-terrestrial network interference, the distinct communication quality of service (QoS) requirements for UAV control messages versus payload data, the stringent constraints imposed by the size, weight and power (SWAP) limitations of UAVs, as well as the exploitation of the new design degree of freedom (DoF) brought by the highly controllable 3D UAV mobility. In this paper, we give a tutorial overview of the recent advances in UAV communications to address the above issues, with an emphasis on how to integrate UAVs into the forthcoming fifth-generation (5G) and future cellular networks. In particular, we partition our discussions into two promising research and application frameworks of UAV communications, namely UAVassisted wireless communications and cellular-connected UAVs, where UAVs serve as aerial communication platforms and users, respectively. Furthermore, we point out promising directions for future research and investigation. KeywordsUnmanned aerial vehicle (UAV), wireless communication, cellular network, channel model, antenna model, energy efficiency, air-ground interference, 3D placement and trajectory, optimization. TechnologyDescription Advantages Disadvantages Direct linkDirect point-to-point communication with ground node Simple, low cost Limited range, low data rate, vulnerable to interference, non-scalable Satellite Communication and Internet access via satellite Global coverage Costly, heavy/bulky/energyconsuming communication equipment, high latency, large signal attenuation Ad-hoc network Dynamically self-organizing and infrastructure-free network Robust and adaptable, support for high mobility Costly, low spectrum efficiency, intermittent connectivity, complex routing protocol Cellular network Enabling UAV communications by using cellular infrastructure and technologies Almost ubiquitous accessibility, cost-effective, superior performance and scalability Unavailable in remote areas, potential interference with terrestrial communications and high reliability/throughput for both air-to-air and airto-ground wireless communications in the three-dimensional (3D) space. Towards this end, four candidate communication technologies are listed and compared in Table III, including i) direct link; ii) satellite; iii) ad-hoc network; and iv) cellular network. In the following, we discuss the advantages as well as limitations of each of these technologies in detail.1) Direct Link: Due to its simpli...

show abstract

Section: B Antenna Modelmentioning

confidence: 99%

Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond

2019

View full text Add to dashboard Cite

show abstract

“…This completes the proof. APPENDIX B PROOF OF COROLLARY 1 We first write the exponent power of (29) as…”

Section: Simulation Results and Analysismentioning

confidence: 99%

“…3D blockage is characterized by the fraction a of the total land area occupied by buildings, the mean number of buildings η per km 2 , and the height of buildings modeled by a Rayleigh PDF with a scale parameter c. Hence, the probability of having a LoS communication from a BS at horizontal-distance r i from an arbitrary UAV-UE is given, similar to [25] and [29], as:…”

Section: A Channel Modelmentioning

confidence: 99%

Mobility in the Sky: Performance and Mobility Analysis for Cellular-Connected UAVs

Amer

Saad

Marchetti

2020

IEEE Trans. Commun.

138

View full text Add to dashboard Cite

Providing connectivity to unmanned aerial vehicle-user equipments (UAV-UEs), such as drones or flying taxis, is a major challenge for tomorrow's cellular systems. In this paper, the use of coordinated multi-point (CoMP) transmission for providing seamless connectivity to UAV-UEs is investigated. In particular, a network of clustered ground base stations (BSs) that cooperatively serve a number of UAV-UEs is considered. Two scenarios are studied: scenarios with static, hovering UAV-UEs and scenarios with mobile UAV-UEs. Under a maximum ratio transmission, a novel framework is developed and leveraged to derive upper and lower bounds on the UAV-UE coverage probability for both scenarios.Using the derived results, the effects of various system parameters such as collaboration distance, UAV-UE altitude, and UAV-UE velocity on the achievable performance are studied. Results reveal that, for both static and mobile UAV-UEs, when the BS antennas are tilted downwards, the coverage probability of a high-altitude UAV-UE is upper bounded by that of ground users regardless of the transmission scheme. Moreover, for low signal-to-interference-ratio thresholds, it is shown that CoMP transmission can improve the coverage probability of UAV-UEs, e.g., from 28% under the nearest association scheme to 60% for a collaboration distance of 200 m. Meanwhile, key results on mobile UAV-UEs unveil that not only the spatial displacements of UAV-UEs but also their vertical motions affect their handover rate and coverage probability. In particular, UAV-UEs that have frequent vertical movements and high direction switch rates are expected to have low handover probability and handover rate. Finally, the effect of the UAV-UE vertical movements on its coverage probability is marginal if the UAV-UE retains the same mean altitude.The past few years have witnessed a tremendous increase in the use of unmanned aerial vehicles (UAVs), popularly called drones, in many applications, such as aerial surveillance, package delivery, and even flying taxis [2]- [6]. Enabling such UAV-centric applications requires ubiquitous wireless connectivity that can be potentially provided by the pervasive wireless cellular network [7] and [8]. However, in order to operate cellular-connected UAVs using existing wireless systems, one must address a broad range of challenges that include interference mitigation, reliable communications, resource allocation, and mobility support [9]. Next, we review some of the works relevant to the cellular-connected UAV-enabled networks. A. State of the Art and Prior WorksRecently, cellular-connected UAVs have received significant attention, whereby UAVs as new user equipments (UEs) are integrated into the cellular network in order to ensure reliable and secure connectivity for the operations of UAV systems. However, it has been established that the dominance of line-of-sight (LoS) links makes inter-cell interference a critical issue for cellular systems with hybrid terrestrial and aerial UEs. In this regard, extensive real-world simulations...

show abstract

“…For the AU, we assume a wireless channel that is characterized by both large-scale and small-scale fading. For the large-scale fading, the channel between BS i and the AU includes LoS and NLoS components, which are considered separately along with their probabilities of occurrence [11]. For small-scale fading, we adopt a Nakagami-mv model for the channel between each single antenna and the AU, as done in [9], [11], [12], with the following probability distribution function (PDF):…”

Section: System Modelmentioning

confidence: 99%

Toward a Connected Sky: Performance of Beamforming With Down-Tilted Antennas for Ground and UAV User Co-Existence

2019

View full text Add to dashboard Cite

Providing connectivity to aerial users (AUs) such as cellularconnected unmanned aerial vehicles (UAVs) is a key challenge for tomorrow's cellular systems. In this paper, the use of conjugate beamforming (CB) for simultaneous content delivery to an AU co-existing with multiple ground users (GUs) is investigated. In particular, a content delivery network of uniformly distributed massive multiple-input multiple-output (MIMO)-enabled ground base stations (BSs) serving both aerial and ground users through spatial multiplexing is considered. For this model, the successful content delivery probability (SCDP) is derived as a function of the system parameters. The effects of various system parameters such as antenna down-tilt angle, AU's altitude, number of scheduled users, and number of antennas on the achievable performance are then investigated. Results reveal that whenever the AU's altitude is below the BS height, the antennas' down-tilt angles yield an inherent tradeoff between the performance of the AU and the GUs. However, if the AU's altitude exceeds the BS height, down-tilting the BS antennas with a considerably large angle improves the performance of both the AU and the GUs.

show abstract

A Stochastic Model for UAV Networks Positioned Above Demand Hotspots in Urban Environments

Cited by 92 publications

References 27 publications

Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond

Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond

Mobility in the Sky: Performance and Mobility Analysis for Cellular-Connected UAVs

Toward a Connected Sky: Performance of Beamforming With Down-Tilted Antennas for Ground and UAV User Co-Existence

Contact Info

Product

Resources

About