Downlink Coverage Analysis for a Finite 3-D Wireless Network of Unmanned Aerial Vehicles

By Vishnu Vardhan Chetlur, Harpreet S. Dhillon. IEEE Transactions on Communications, 2017

347 citations recorded by the source corpus.

In this paper, we consider a finite network of unmanned aerial vehicles serving a given region. Modeling this network as a uniform binomial point process, we derive the downlink coverage probability of a reference receiver located at an arbitrary position on the ground assuming Nakagami-<inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> fading for all wireless links. The reference receiver is assumed to connect to its closest transmitting node as is usually the case in cellular systems. After deriving the distribution of distances from the reference receiver to the serving and interfering nodes, we derive an exact expression for downlink coverage probability in terms of the derivative of Laplace transform of interference power distribution. In the downlink of this system, it is not unusual to encounter scenarios in which the line-of-sight component is significantly stronger than the reflected multipath components. To emulate such scenarios, we also derive the coverage probability in the absence of fading from the results of Nakagami-<inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> fading by taking the limit <inline-formula> <tex-math notation="LaTeX">$m \to \infty$ </tex-math></inline-formula>. Using asymptotic expansion of incomplete gamma function, we concretely show that this limit reduces to a redundant condition. Consequently, we derive an accurate coverage probability approximation for this case using dominant interferer-based approach in which the effect of dominant interferer is exactly captured and the residual interference from other interferers is carefully approximated. We then derive the bounds of the approximate coverage probability using Berry-Esseen theorem. Our analyses reveal several useful trends in coverage probability as a function of height of the transmitting nodes and the location of reference receiver on the ground.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/0478a1cadc0cc1ecc1b57eff1587fc3b03f04fab

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Rui Zhang
2. Yong Zeng
3. Qingqing Wu
4. Merouane Debbah
5. Walid Saad
6. Medhi Bennis
7. Mohammad Mozaffari
8. Jie Xu

In Electrical and Electronic Engineering

1. Rui Zhang
2. Merouane Debbah
3. Qingqing Wu
4. Yong Zeng
5. Medhi Bennis
6. Walid Saad
7. Jie Xu
8. Mohamed-Slim Alouini

Citations in the corpus

• Digital Twin: Values, Challenges and Enablers From a Modeling Perspective (2019, background): “Unmanned Aerial Systems (UAS) cooperations have also recently attracted considerable attention to assist ground base stations in the case of crowded public events, natural disasters, or other temporal emergencies that require additional needs for network resources [442]–[444].”
• A Survey of Channel Modeling for UAV Communications (2018, methodology): “less environmental parameters [16]–[21].”
• Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond (2019, methodology): “[95] Multiple Static UAV BSs at the same altitude modelled as a BPP; each user associates with the closest UAV BS Log-distance path loss, Nakagami-m fading Coverage probability degrades as UAV altitude increases”
• UAV assistance paradigm: State-of-the-art in applications and challenges (2020, methodology): “To handle these issues, UAVs can be quickly deployed to assist VANETs as relays and forward data packets among vehicles when the communication between vehicles on the ground is not possible [131], as shown in Fig.”
• Energy Minimization for Wireless Communication With Rotary-Wing UAV (2018, background): “By exploiting such unique channel characteristics, significant efforts have been devoted to studying the various aspects of UAV-enabled BSs, such as UAV placement optimization [13]–[18], performance analysis [19]–[21], spectrum sharing [22], and cell association [23].”
• Wireless Communication Using Unmanned Aerial Vehicles (UAVs): Optimal Transport Theory for Hover Time Optimization (2017, background): “The authors in [15] derived an exact expression for downlink coverage probability for ground receivers which are served by multiple UAVs.”
• A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems (2018, methodology): “In particular, using tools from stochastic geometry, the work in [143] provided the coverage analysis in a finite UAV network considering a Nakagami-m fading channel for UAV-”