User association and bandwidth allocation for terrestrial and aerial base stations with backhaul considerations

In this paper, we study the joint 3D placement of unmanned aerial vehicles (UAVs) and UAVs-users association under bandwidth limitation and quality of service constraint. In particular, in order to allow to UAVs to dynamically improve their 3D locations in a distributed fashion while maximizing the network's sum-rate, we break the underlying optimization into 3 subproblems where we separately solve the 2D UAVs positioning, the altitude optimization, and the UAVs-users association. First, given fixed 3D positions of UAVs, we propose a fully distributed matching based association that alleviates the bottlenecks of bandwidth allocation and guarantees the required quality of service. Next, to address the 2D positions of UAVs, we adopt a modified version of K-means algorithm, with a distributed implementation, where UAVs dynamically change their 2D positions in order to reach the barycenter of the cluster that is composed of the served ground users. In order to optimize the UAVs altitudes, we study a naturally defined game-theoretic version of the problem and show that under fixed UAVs 2D coordinates, a predefined association scheme, and limited-interferences, the UAVs altitudes game is a non-cooperative potential game where the players (UAVs) can maximize the limited-interference sumrate by only optimizing a local utility function. Therefore, we adopt the best response dynamics to reach a Nash equilibrium of the game which is also a local optimum of the social welfare function. Our simulation results show that, using the proposed approach, the network's sum rate of the studied scenario is improved by 200% as compared with the trivial case where the classical version of K-means is adopted and users are assigned, at each iteration, to the closest UAV.

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“…Some initialization procedures can however be used to improve the convergence results of K-means [14]. 10 PSfrag replacements…”

Section: A Simulation Setupmentioning

confidence: 99%

Learn-As-You-Fly: A Distributed Algorithm for Joint 3D Placement and User Association in Multi-UAVs Networks

Hammouti

Benjillali

Shihada

et al. 2019

IEEE Trans. Wireless Commun.

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“…In [18], the authors proposed a computational method to find the optimal and fast drone deployment in order to enhance the coverage performance in the case of public safety communications. In [19], Kalantari et al studied the backhaul resource allocation, user association, and 3D placement of drones. The authors proposed a novel delaysensitive approach by associating the delay-sensitive users to the macro BS and the other users to either the macro BS or DBSs.…”

Section: A Related Workmentioning

confidence: 99%

Spatial and Temporal Management of Cellular HetNets with Multiple Solar Powered Drones

Alsharoa

Ghazzai

Kadri

et al. 2020

IEEE Trans. on Mobile Comput.

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This paper proposes an energy management framework for cellular heterogeneous networks (HetNets) supported by dynamic solar powered drones. A HetNet composed of a macrocell base station (BS), micro cell BSs, and drone small cell BSs are deployed to serve the networks' subscribers. The drones can land at pre-planned locations defined by the mobile operator and at the macrocell BS site where they can charge their batteries. The objective of the framework is to jointly determine the optimal trips of the drones and the MBSs that can be safely turned off in order to minimize the total energy consumption of the network. This is done while considering the cells' capacities and the minimum receiving power guaranteeing successful communications. To do so, an integer linear programming problem is formulated and optimally solved for three cases based on the knowledge level about future renewable energy statistics of the drones. A low complex relaxed solution is also developed. Its performances are shown to be close to those of the optimal solutions. However, the gap increases as the network becomes more congested. Numerical results investigate the performance of the proposed drone-based approach and show notable improvements in terms of energy saving and network capacity.Index Terms-Drone-based communications, dynamic drone small cells, energy harvesting, energy management, heterogeneous networks.

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“…In both [3] and [14], the backhaul link was assumed to be ideal. The authors of [15] considered the impact of the positioning of the UAV on both the access and the backhaul links. However, in [15], despite the potentially higher data rates of FSO links, an RF link was considered for backhauling and the position of the UAV and the RF bandwidth shared between the access and backhaul links was optimized.…”

Section: Introductionmentioning

confidence: 99%

Ergodic Sum Rate Analysis of UAV-Based Relay Networks With Mixed RF-FSO Channels

Ajam

Najafi

Jamali

et al. 2020

IEEE Open J. Commun. Soc.

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Unmanned aerial vehicle (UAV)-based communications is a promising new technology that can add a wide range of new capabilities to the current network infrastructure. Given the flexibility, costefficiency, and convenient use of UAVs, they can be deployed as temporary base stations (BSs) for ondemand situations like BS overloading or natural disasters. In this work, a UAV-based communication system with radio frequency (RF) access links to the mobile users (MUs) and a free-space optical (FSO) backhaul link to the ground station (GS) is considered. In particular, the RF and FSO channels in this network depend on the UAV's positioning and (in)stability. The relative position of the UAV with respect to the MUs impacts the likelihood of a line-of-sight (LOS) connection in the RF link and the instability of the hovering UAV affects the quality of the FSO channel. Thus, taking these effects into account, we analyze the end-to-end system performance of networks employing UAVs as buffer-aided (BA) and non-buffer-aided (non-BA) relays in terms of the ergodic sum rate. Simulation results validate the accuracy of the proposed analytical derivations and reveal the benefits of buffering for compensation of the random fluctuations caused by the UAV's instability. Our simulations also show that the ergodic sum rate of both BA and non-BA UAV-based relays can be enhanced considerably by optimizing the positioning of the UAV. We further study the impact of the MU density and the weather conditions on the end-to-end system performance.

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User association and bandwidth allocation for terrestrial and aerial base stations with backhaul considerations

Cited by 102 publications

References 20 publications

Learn-As-You-Fly: A Distributed Algorithm for Joint 3D Placement and User Association in Multi-UAVs Networks

Learn-As-You-Fly: A Distributed Algorithm for Joint 3D Placement and User Association in Multi-UAVs Networks

Spatial and Temporal Management of Cellular HetNets with Multiple Solar Powered Drones

Ergodic Sum Rate Analysis of UAV-Based Relay Networks With Mixed RF-FSO Channels

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