Optimal Placement of UAVs for Minimum Outage Probability

Erdem Koyuncu; Maryam Shabanighazikelayeh

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Optimal Placement of UAVs for Minimum Outage Probability

Maryam Shabanighazikelayeh, Erdem Koyuncu

Information Theory · Submitted 15 Apr 2019

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim For a wide class of GT densities, it is shown that all UAVs should be placed to the same location in an optimal deployment.

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What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.22 · human participants 0.02 · controlled comparison 0.11 · randomized assignment 0.07 · states quantitative result 0.88 · compares with prior results 0.20 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v2. Results and the main claim are underlined; show every role.

We consider multiple unmanned aerial vehicles (UAVs) serving a density of ground terminals (GTs) as base stations. The objective is to minimize the outage probability of GT-to-UAV transmissions. Optimal placement of UAVs under different UAV altitude constraints and GT densities is studied. First, using a random deployment argument, a general upper bound on the optimal outage probability is found for any density of GTs and any number of UAVs. A matching lower bound is also derived to show that the optimal outage probability decays exponentially with the number of UAVs. Next, the structure of optimal deployments is studied when the common altitude constraint is large. For a wide class of GT densities, it is shown that all UAVs should be placed to the same location in an optimal deployment. A design implication is that one can use a single multi-antenna UAV as opposed to multiple single-antenna UAVs without loss of optimality. This result is also extended to a practical variant of the Rician fading model recently developed by Azari et al. for UAV communications. Numerical deployment of UAVs in the centralized and practical distributed settings are carried out using the particle swarm optimization and modified gradient descent algorithms, respectively.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#	sentence	role	the authors' own work	states the main conclusion	strength
s0	We consider multiple unmanned aerial vehicles (UAVs) serving a density of ground terminals (GTs) as base stations.	background 0.95	0.24	0.02	asserted 0.90
s1	The objective is to minimize the outage probability of GT-to-UAV transmissions.	background 0.58	0.25	0.04	asserted 0.95
s2	Optimal placement of UAVs under different UAV altitude constraints and GT densities is studied.	contribution 0.96	0.88	0.05	asserted 0.91
s3	First, using a random deployment argument, a general upper bound on the optimal outage probability is found for any density of GTs and any number of UAVs.	result 0.53	0.95	0.06	asserted 1.00
s4	A matching lower bound is also derived to show that the optimal outage probability decays exponentially with the number of UAVs.	result 0.98	0.96	0.12	asserted 1.00
s5	Next, the structure of optimal deployments is studied when the common altitude constraint is large.	contribution 0.93	0.85	0.04	asserted 0.53
s6	For a wide class of GT densities, it is shown that all UAVs should be placed to the same location in an optimal deployment.	result 1.00	0.94	0.46	asserted 1.00
s7	A design implication is that one can use a single multi-antenna UAV as opposed to multiple single-antenna UAVs without loss of optimality.	interpretation 0.99	0.83	0.25	asserted 0.77
s8	This result is also extended to a practical variant of the Rician fading model recently developed by Azari et al. for UAV communications.	contribution 0.63	0.78	0.05	asserted 1.00
s9	Numerical deployment of UAVs in the centralized and practical distributed settings are carried out using the particle swarm optimization and modified gradient descent algorithms, respectively.	method 0.97	0.93	0.04	asserted 0.99

What kind of paper the classifier reports this is: theoretical result 1.00 · evidence from proof or derivation 0.99.

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arXiv listing abstract v2

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full text
figures and tables
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relations to other papers

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T body sentences
C citations
R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper

Original abstract

We consider multiple unmanned aerial vehicles (UAVs) serving a density of ground terminals (GTs) as base stations. The objective is to minimize the outage probability of GT-to-UAV transmissions. Optimal placement of UAVs under different UAV altitude constraints and GT densities is studied. First, using a random deployment argument, a general upper bound on the optimal outage probability is found for any density of GTs and any number of UAVs. A matching lower bound is also derived to show that the optimal outage probability decays exponentially with the number of UAVs. Next, the structure of optimal deployments is studied when the common altitude constraint is large. For a wide class of GT densities, it is shown that all UAVs should be placed to the same location in an optimal deployment. A design implication is that one can use a single multi-antenna UAV as opposed to multiple single-antenna UAVs without loss of optimality. This result is also extended to a practical variant of the Rician fading model recently developed by Azari et al. for UAV communications. Numerical deployment of UAVs in the centralized and practical distributed settings are carried out using the particle swarm optimization and modified gradient descent algorithms, respectively.

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2 arXiv papers cite this in 5 sentences

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

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Uses its method or tool 1 paper

An interesting aspect of Theorem [ref](iv) is its proof, which uses an abstract desingularization result from [ref] , see Appendix [ref].

On particle systems and critical strengths of general singular interactions · Attraction and repulsion · 1.00

What it cites · 1 sentence without a confident label

Cites as background 4 papers

Trajectory control of UAVs for maximizing the worst terrestrial user's spectral efficiency is studied in [ref] .

Base-Stations Up in the Air: Multi-UAV Trajectory Control for Min-Rate Maximization in Uplink C-RAN · Background and Motivation · 0.98
Since then, several variations including limited-range node interactions have been studied [ref] .

Movement-efficient Sensor Deployment in Wireless Sensor Networks with Limited Communication Range · Summary of Main Contributions · 0.89
The problem of interference-aware joint trajectory and power control of multiple UAVs have been explored [ref] .

Multi-UAV Interference Coordination via Joint Trajectory and Power Control · Background and Motivation · 0.99

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