[Paper Review] Unmanned Aerial Vehicle and Optimal Relay for Extending Coverage in Post-Disaster Scenarios

Abdu Saif, Kaharudin Dimyati+6 more|arXiv (Cornell University)|Apr 13, 2021

UAV Applications and Optimization18 references17 citations

TL;DR

This paper proposes a UAV-enabled multihop relay network to extend wireless coverage in post-disaster scenarios, optimizing relay hop distance and UAV positioning to enhance system capacity and connectivity. Results show that dense relay deployment improves coverage area and energy efficiency by enabling decentralized device-to-device communication with improved line-of-sight reliability.

ABSTRACT

The malfunction or interruption of wireless coverage services has been shown to increase the mortality rate during natural disasters. Wireless coverage by an unmanned aerial vehicle (UAV) provides network coverage to ground user devices during and post-disaster events. The relay hops receive wireless coverage and can be forwarded to user devices that are out of coverage allowing reliable connectivity for large-scale user devices. This work evaluates the optimal relay hops performance to improve wireless coverage services and establish connectivity in post-disaster scenarios. The results demonstrate the UAV line of sights understanding to select an optimal relay for improving wireless coverage services. The path loss probability and system capacity were all affected by the user device distance and relay densities. The optimal relay hop distance and the UAV positions static are also investigated to improve coverage likelihood which could be especially useful for UAV deployment design. It is found that the dense relays node in UAV systems enhances the capacity coverage area and energy efficiency by decentralized connectivity through a multihop device to device wireless network.

Motivation & Objective

• To address the critical issue of wireless network disruption during natural disasters, which increases mortality rates.
• To improve connectivity for large-scale ground user devices in post-disaster environments with limited or no infrastructure.
• To evaluate the performance of optimal relay hops in enhancing wireless coverage using UAVs.
• To determine the optimal relay hop distance and UAV positioning for maximizing coverage likelihood and system capacity.
• To assess the impact of relay density and user device distance on path loss probability and network performance.

Proposed method

• The study models a UAV-based multihop device-to-device network to extend coverage in post-disaster scenarios.
• It employs a line-of-sight (LoS) model to evaluate UAV positioning and its impact on signal propagation and coverage.
• Path loss probability is analyzed as a function of user device distance and relay density.
• System capacity is evaluated under varying relay hop distances and UAV altitudes.
• Optimal relay hop distance is derived based on trade-offs between coverage range and signal reliability.
• The UAV's static positioning is optimized to maximize the likelihood of LoS links and minimize path loss.

Experimental results

Research questions

• RQ1 What is the optimal relay hop distance that maximizes coverage and system capacity in UAV-assisted post-disaster networks?
• RQ2 How does user device distance affect path loss probability and network reliability?
• RQ3 How does relay density influence system capacity and energy efficiency in UAV-based multihop networks?
• RQ4 What UAV altitude and positioning strategy maximize line-of-sight links and coverage likelihood?
• RQ5 How does decentralized device-to-device connectivity improve network resilience in post-disaster scenarios?

Key findings

• Dense relay deployment significantly enhances the capacity coverage area by enabling multihop device-to-device communication.
• Optimal relay hop distance improves system capacity and reduces path loss probability by balancing range and signal quality.
• UAV positioning with line-of-sight to ground users increases connectivity reliability and coverage likelihood.
• Relay density has a direct impact on system capacity, with higher densities improving overall network performance.
• Energy efficiency is improved through decentralized connectivity, reducing reliance on single-hop transmission.
• User device distance is a critical factor in path loss probability, with longer distances degrading signal quality and coverage.