Energy Tradeoff in Ground-to-UAV Communication via Trajectory Design

Yang, Dingcheng; Wu, Qingqing; Zeng, Yong; Zhang, Rui

doi:10.1109/tvt.2018.2816244

Cited by 372 publications

(229 citation statements)

References 19 publications

(37 reference statements)

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“…Another adaptive algorithm for filtering UAV movements using Kalman Filters is presented in [34]. UAV deployment and movement models are also considered in [35][36][37][38].…”

Section: Literature Reviewmentioning

confidence: 99%

An Efficient Mobility Model for Improving Transmissions in Multi-UAVs Enabled WSNs

Sayeed

Kumar

2018

Drones

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Multi-Unmanned Aerial Vehicle (UAV) enabled Wireless Sensor Networks (WSNs) provide a wide range of applications, covering civilian and military expeditions along with geographical navigation, control, and reconnaissance. The coordinated networks formed between the UAVs and the WSNs help in enhancing the issues related to quality as well as coverage. The overall coverage issues result in starvation as an effect of long waiting time for the nodes, while forwarding the traffic. The coverage problem can be resolved by an intelligent choice of UAV way-points. Therefore, a specialized UAV mobility model is required which takes into account the topological structure as well as the importance of strategic locations to fix UAV way-points and decide the data transmission paradigm. To resolve this problem, a novel mobility model is proposed, which takes into account the attraction factor for setting up the way-points for UAV movements. The model is capable of deciding between the locations which result in more coverage, increased throughput with lesser number of UAVs employed, as justified by the simulation results and comparative evaluations.

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“…Another adaptive algorithm for filtering UAV movements using Kalman Filters is presented in [34]. UAV deployment and movement models are also considered in [35][36][37][38].…”

Section: Literature Reviewmentioning

confidence: 99%

An Efficient Mobility Model for Improving Transmissions in Multi-UAVs Enabled WSNs

Sayeed

Kumar

2018

Drones

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“…In multi-UAV enabled multiuser system, joint power control and trajectory optimization problem is studied in [11]. Some important informationtheoretical results in the trade-off problem are obtained via joint power and trajectory optimization in [12], [13].…”

Section: Introductionmentioning

confidence: 99%

A Novel Alternative Optimization Method for Joint Power and Trajectory Design in UAV-Enabled Wireless Network

Tang

et al. 2019

IEEE Trans. Veh. Technol.

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This letter aims to maximize the average throughput via the joint design of the transmit power and trajectory for unmanned aerial vehicle (UAV)-enabled network. The conventional way to tackle this problem is based on the alternating optimization (AO) method by iteratively updating power and trajectory until convergence, resulting in a non-convex trajectory subproblem which is difficult to deal with. To develop more efficient methods, we propose a novel AO method by incorporating both power and trajectory into an intermediate variable, and then iteratively updating power and the newly introduced variable. This novel variable transformation makes it easier to decompose the original problem into two convex subproblems, namely a throughput maximization subproblem and a feasibility subproblem. Consequently, both of these subproblems can be solved in a globally optimal fashion. We further propose a lowcomplexity algorithm for the feasibility subproblem by exploiting the alternating directional method of multipliers (ADMM), whose updating step is performed in closed-form solutions. Simulation results demonstrate that our proposed method reduces the computation time by orders of magnitude, while achieving higher performance than the conventional methods.Index Terms-Alternative Optimization, ADMM, joint power and trajectory design, unmanned aerial vehicle, throughput maximization.

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“…Prior research [16]- [19] has therefore been focused on the energy-saving issues of UAV communications in applications where long-term operations are needed. The authors of [16] concentrated on a UAV-enabled 1 Electric power can be obtained through energy harvesting. Energy harvesting, however, falls outside the scope of this paper.…”

mentioning

confidence: 99%

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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Energy Tradeoff in Ground-to-UAV Communication via Trajectory Design

Cited by 372 publications

References 19 publications

An Efficient Mobility Model for Improving Transmissions in Multi-UAVs Enabled WSNs

An Efficient Mobility Model for Improving Transmissions in Multi-UAVs Enabled WSNs

A Novel Alternative Optimization Method for Joint Power and Trajectory Design in UAV-Enabled Wireless Network

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

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