Abstract

This paper formulates a new problem for the optimal placement of Unmanned Aerial Vehicles (UAVs) geared towards wireless coverage provision for Voice over WiFi (VoWiFi) service to a set of ground users confined in an open area. Our objective function is constrained by coverage and by VoIP speech quality and minimizes the ratio between the number of UAVs deployed and energy efficiency in UAVs, hence providing the layout that requires fewer UAVs per hour of service. Solutions provide the number and position of UAVs to be deployed, and are found using well-known heuristic search methods such as genetic algorithms (used for the initial deployment of UAVs), or particle swarm optimization (used for the periodical update of the positions). We examine two communication services: (a) one bidirectional VoWiFi channel per user; (b) single broadcast VoWiFi channel for announcements. For these services, we study the results obtained for an increasing number of users confined in a small area of 100 m2 as well as in a large area of 10,000 m2. Results show that the drone turnover rate is related to both users’ sparsity and the number of users served by each UAV. For the unicast service, the ratio of UAVs per hour of service tends to increase with user sparsity and the power of radio communication represents 14–16% of the total UAV energy consumption depending on ground user density. In large areas, solutions tend to locate UAVs at higher altitudes seeking increased coverage, which increases energy consumption due to hovering. However, in the VoWiFi broadcast communication service, the traffic is scarce, and solutions are mostly constrained only by coverage. This results in fewer UAVs deployed, less total power consumption (between 20% and 75%), and less sensitivity to the number of served users.

Highlights

  • Unmanned Aerial Vehicles (UAVs) for wireless communications have experienced rapid growth in a broad range of application domains [1]

  • In a context similar to ours, in [12], we proposed a 3D placement algorithm that minimized the number of aerial APs deployed to provide Voice over WiFi (VoWiFi) to ground users

  • All terms in Equation (1) are known but the network delay d and packet loss rate Ppl. The values for these two factors will be obtained from our WiFi mac-sublayer analytical model for each UAV deployed (we assume that backhaul networks do not introduce any negative impacts into Quality of Service (QoS), or it can be considered as a constant in R)

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Summary

Introduction

Unmanned Aerial Vehicles (UAVs) for wireless communications have experienced rapid growth in a broad range of application domains [1]. Deploying UAVs for wireless networks brings in new opportunities, such as creating a provisional communication infrastructure in Search and Rescue (SAR) missions [1,8]. It brings multiple challenges such as optimal 3D placement, performance analysis, path planning, backhaul. We deal with the challenge of optimal multi-UAV 3D placement in the context of creating a provisional WLAN (i.e., UAVs are used as aerial Access Points—AP) to provide ground users with VoIP over WiFi (VoWiFi) service.

Motivation
Contribution of This Paper
Related Works
Objective
QoS and UAVs Endurance in VoWiFi Networks
Modeling QoS in VoWiFi
Modeling UAV Endurance
Terminology and Assumptions
Problem Definition
Solving a Pseudo-Static Scenario
Search Algorithm
Checking the Fitness of Individuals
Example Solution
Solving a Dynamic Scenario
Periodical Search Algorithm
Convergence Speed
Numerical Results
Individual VoIP Channels
Broadcast Channel
Comparing with Other Approaches
Conclusions and Future Research
Full Text
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