Explicit topology management for continental-scale airborne networks

Newton, Ben; Aikat, Jay; Jeffay, Kevin

doi:10.1109/infcomw.2017.8116355

Cited by 5 publications

(5 citation statements)

References 10 publications

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“…1) (Proposed) Joint Algorithm is a result with the proposed Algorithm 1, in which the variables of association, power, and deployment (i.e., {A, P, Q, H}) are jointly optimized by taking account of the practical conditions of limited FSO backhaul, limited HAP transmit power, and so on. The initial HAPS positions are chosen as [15,15,20], [15,35,20], [35,15,20] and [35,35,20] in [km].…”

Section: E Performance Comparison: Throughput and Energy Efficiencymentioning

confidence: 99%

Spectral-Efficient Network Design for High-Altitude Platform Station Networks With Mixed RF/FSO System

Lee

Park

et al. 2022

IEEE Trans. Wireless Commun.

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Integrating terrestrial networks with burgeoning high-altitude platform stations (HAPSs) will be a disruptive challenge for beyond-5G systems provisioning large-scale threedimensional connectivity. Here, we study the problem of forwarding packets between terrestrial terminals and backhaul through multi-HAPS relaying. Considering the limited wireless backhaul, which is the practical constraint of HAPS relaying, dual-hop mixed radiofrequency/free-space optical (RF/FSO) networks are investigated, where backhaul-to-relay and relay-to-user communications employ FSO and RF links, respectively. To maximize the end-to-end network throughput, including downlink and uplink rate, we formulate the optimization problem for variables; the association between aerial and terrestrial terminals, transmit power, and deployment of multiple HAPSs, respectively. We tackle this problem using an iterative algorithm with proposed surrogate functions to efficiently obtain the locally optimal solution. Simulation results corroborate that our proposed optimal method achieves up to 11.3% spectral efficiency compared to the conventional heuristic method. Furthermore, we answer three questions; 1) what the wireless backhaul requirements are, 2) how the number of HAPSs and terrestrial terminals impact the network, and 3) what if a certain user terminal has a particular demand on data rate.

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Section: E Performance Comparison: Throughput and Energy Efficiencymentioning

confidence: 99%

Spectral-Efficient Network Design for High-Altitude Platform Station Networks With Mixed RF/FSO System

Lee

Park

et al. 2022

IEEE Trans. Wireless Commun.

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“…Also note that the optimal trajectory for the UAV in the low-complexity scheme, q lc , can be readily resized using N ′ and W(θ). 8 In summary, if this low complexity scheme finds optimal values (e.g., q lc , v lc , and a lc ) with a much lower number of time slots N ′ , we can use the rotation transformation with W(θ) to draw a patterned trajectory set to meet the desired time slot size.…”

Section: Low-complexity Scheme For Flight Time Maximizationmentioning

confidence: 99%

“…Accordingly, UAVmounted fronthaul and backhaul frameworks have been considered as a promising approach to handle unexpected or temporarily large amounts of information that is commonly required by user terminals [5], [6]. By leveraging the UAV-mounted fronthaul and backhaul links, large-scale projects are now underway in several research groups and information technology companies,including Global Access to the Internet for All (GAIA) [7], Project Loon by Google [8], and internet.org by Facebook [9], [10].…”

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confidence: 99%

“…including Global Access to the Internet for All (GAIA) [7], Project Loon by Google [8], and internet.org by Facebook [9], [10].…”

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confidence: 99%

“…FSOC has several known advantages, such as an unlicensed broad spectrum, immunity to electromagnetic interference, and security. For example, by taking advantage of these, Facebook has launched project Aquila in the hope of providing internet access to the world, by leveraging UAVs such that free space laser communication systems may be adopted [8], [10]. Academic research groups have also suggested some specific platforms where UAVs can carry out various missions [5], [15].…”

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A UAV-Mounted Free Space Optical Communication: Trajectory Optimization for Flight Time

Lee

Park

et al. 2020

IEEE Trans. Wireless Commun.

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In this work, we address the trajectory optimization of a fixed-wing unmanned aerial vehicle (UAV) using free space optical communication (FSOC). Here, we focus on maximizing the flight time of the UAV by considering practical constraints for wireless UAV communication, including limited propulsion energy and required data rates. We find optimized trajectories in various atmospheric environments (e.g., moderate-fog and heavy-fog conditions), while also considering the channel characteristics of FSOC. In addition to maximizing the flight time, we consider the energy efficiency maximization and operation-time minimization problem to find the suboptimal solutions required to meet those constraints.Furthermore, we introduce a low-complexity approach to the proposed framework. In order to address the optimization problem, we conduct a bisection method and sequential programming and introduce a new feasibility check algorithm. Although our design considers suboptimal solutions owing to the nonconvexity of the problems, our simulations indicate that the proposed scheme exhibits a gain of approximately 44.12% in terms of service time when compared to the conventional scheme. Free space optical communication (FSOC), wireless communications with an unmanned aerial vehicle (UAV), UAV-mounted FSOC, flight time maximization, trajectory design. I. INTRODUCTION Recently, unmanned aerial vehicles (UAVs) have attracted a great deal of attention in the area of wireless communication networks. Owing to their mobility and flexibility, UAVs can be dispatched as a mobile entity in a network. It can provide new opportunities in various communication applications and have the capability to complement conventional fixed networks. UAV-assisted communications can efficiently support already existing terrestrial communication infrastructure, including data offloading at a hot spot [1], [2]. For example, in case of a catastrophic event, UAV-mounted infrastructures can temporarily support service recovery initiatives and local interim communication facilities for potentially damaged infrastructures [3]. In addition, UAV-assisted relaying can help to extend base station connectivity, from one station to another, in situations where the nodes are widely scattered and/or obstacles such as hills or large buildings are present [4].Principally, we envision that most future networks will be highly user-centric, increasing the user demand information due to an exponential increase in the internet of things (IoT), fifth-generation (5G) mobile networks, and beyond-5G wireless networks. Accordingly, UAVmounted fronthaul and backhaul frameworks have been considered as a promising approach to handle unexpected or temporarily large amounts of information that is commonly required by user terminals [5], [6]. By leveraging the UAV-mounted fronthaul and backhaul links, large-scale projects are now underway in several research groups and information technology companies,including Global Access to the Internet for All (GAIA) [7], Project Loon by Google [8], and...

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