Optimal LAP Altitude for Maximum Coverage

Abstract

Low-altitude aerial platforms (LAPs) have recently gained significant popularity as key enablers for rapid deployable relief networks where coverage is provided by onboard radio heads. These platforms are capable of delivering essential wireless communication for public safety agencies in remote areas or during the aftermath of natural disasters. In this letter, we present an analytical approach to optimizing the altitude of such platforms to provide maximum radio coverage on the ground. Our analysis shows that the optimal altitude is a function of the maximum allowed pathloss and of the statistical parameters of the urban environment, as defined by the International Telecommunication Union. Furthermore, we present a closed-form formula for predicting the probability of the geometrical line of sight between a LAP and a ground receiver.Index Terms-Low altitude platform, air-to-ground communication, radio propagation, probability of line of sight.

A Survey of Channel Modeling for UAV Communications

“…Simulation results demonstrated that the impact of elevation angle was significant on the excess path loss. In [10], the closed-form expression was formulated for determining the coverage performance in terms of the maximum cell radius and the optimal altitude. In this study, the free space path loss model was extended using the excessive attenuation factor for different LOS and NLOS propagation conditions.…”

“…Such models are useful for studying large-scale fading effects in the channel [6], [7]. Hence the propagation conditions [8], [9] can provide coverage analysis and indicate the optimal UAV position [10]- [12]. The second approach is to develop a tapped delay line (TDL) model to characterize the direct path as well as the multipath components.…”

Dynamic Base Station Repositioning to Improve Performance of Drone Small Cells

“…The propagation channel is modeled by probabilistic LoS, in which the probability of having a LoS connection between a user and the drone is as follows [9] …”

Drone Empowered Small Cellular Disaster Recovery Networks for Resilient Smart Cities

“…The study does not explore cross-tier interference management in the presence of large scale DSCN deployment. The authors in [8], based on the results of [9], present a 3D optimization problem for DSCs with the aim to maximize the number of users to be covered by such DSCs using a numerical search algorithm to satisfy the defined quality of service (QoS) measures. The paper focuses on drone empowered future cellular networks for disaster recovery/ public safety.…”