Simultaneous User Association and Placement in Multi-UAV Enabled Wireless Networks (original) (raw)

UAV-relay Placement with Unknown User Locations and Channel Parameters

2018 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

This work investigates the problem of optimal placement of an UAV that provides communication services by acting as a flying wireless relay between a fixed base station (BS) and ground users. The proposed approach builds on the knowledge of the terrain topology where the network is deployed and aims at finding the optimal position of the UAV that maximizes the throughput in the max-min sense. Different from prior works, we do not assume any prior knowledge on user locations and the underlying wireless channel pathloss parameters. We first jointly estimate the user location and the pathloss parameters from the measurements collected by the UAV, and then use them to find the optimal relay position. When it comes to the optimal placement, an iterative algorithm is provided which iterates between the planar UAV placement and altitude optimization by exploiting the 3D city map information.

Joint Mobility-Aware UAV Placement and Routing in Multi-Hop UAV Relaying Systems

Ad Hoc Networks, 2021

Unmanned Aerial Vehicles (UAVs) have been extensively utilized to provide wireless connectivity in rural and underdeveloped areas, enhance network capacity and provide support for peaks or unexpected surges in user demand, mainly due to their fast deployment, cost-efficiency and superior communication performance resulting from Line of Sight (LoS)-dominated wireless channels. In order to exploit the benefits of UAVs as base stations or relays in a mobile network, a major challenge is to determine the optimal UAV placement and relocation strategy with respect to the mobility and traffic patterns of the ground network nodes. Moreover, considering that the UAVs form a multi-hop aerial network, capacity and connectivity constraints have significant impacts on the end-to-end network performance. To this end, we formulate the joint UAV placement and routing problem as a Mixed Integer Linear Program (MILP) and propose an approximation that leads to a LP rounding algorithm and achieves a balance between time-complexity and optimality.

3-D Placement Schemes of Multiple UAVs in NFP-based Wireless Networks

2018 5th International Conference on Information and Communication Technologies for Disaster Management (ICT-DM), 2018

In this paper, we propose two placement strategies of multiple unmanned aerial vehicles (UAVs) in network flying platform (NFP)-based wireless networks. The first strategy is based on a proposed distributed placement algorithm (DPA) that can be executed by the collaboration of the users and a high altitude controlling NFP (mother UAV). The second strategy uses a proposed centric placement algorithm (CPA) at the mother UAV to define the number and optimal placement of the needed UAVs. For the system model, a Matérn Cluster Process (MCP) is used to describe the users' location in realistic scenarios. Based on that, we detail the proposed algorithms, and we derive the corresponding number expressions of the needed UAVs. Numerical results are used to confirm the derived expression and to evaluate the proposed 3-D placement strategies.

UAV placement for enhanced connectivity in wireless ad-hoc networks

2004

In this paper we address the problem of providing full connectivity in large (wide area) ad hoc networks by placing advantaged nodes like UAVs (as relay nodes) in appropriate places. We provide a formulation where we can treat the connectivity problem as a clustering problem with a summation-form distortion function. We then adapt the Deterministic Annealing clustering algorithm to our formulation and using that we find the minimum number of UAVs required to provide connectivity and their locations. Furthermore, we describe enhancements that can be used to extend the basic connectivity problem to support notions of reliable connectivity that can lead to improved network performance. We establish the validity of our algorithm and compare its performance with optimal (exhaustive search) as well as non-opitmal (hard clustering) algorithms. We show that our algorithm is nearoptimal both for the basic connectivity problem as well as extended notions of connectivity.

The Optimal and the Greedy: Drone Association and Positioning Schemes for Internet of UAVs

IEEE Internet of Things Journal, 2021

This work considers the deployment of unmanned aerial vehicles (UAVs) over a pre-defined area to serve a number of ground users. Due to the heterogeneous nature of the network, the UAVs may cause severe interference to the transmissions of each other. Hence, a judicious design of the user-UAV association and UAV locations is desired. A potential game is defined where the players are the UAVs. The potential function is the total sum rate of the users. The agents' utility in the potential games is their marginal contribution to the global welfare or their socalled wonderful life utility. A game-theoretic learning algorithm, binary log-linear learning (BLLL), is then applied to the problem. Given the potential game structure, a consequence of our utility design, the stochastically stable states using BLLL are guaranteed to be the potential maximizers. Hence, we optimally solve the user-UAV association and 3D-location problem. Next, we exploit the submodular features of the sum rate function for a given configuration of UAVs to design an efficient greedy algorithm. Despite the simplicity of the greedy algorithm, it comes with a performance guarantee of 1 − 1/e of the optimal solution. To further reduce the number of iterations, we propose another heuristic greedy algorithm that provides very good results. Our simulations show that, in practice, the proposed greedy approaches achieve significant performance in a few number of iterations.

An Efficient 3-D Positioning Approach to Minimize Required UAVs for IoT Network Coverage

IEEE Internet of Things Journal, 2021

Using Unmanned Aerial Vehicles (UAVs) to cover users in wireless networks has increased in recent years. Deploying UAVs in appropriate positions is important to cover users and nodes properly. In this paper, we propose an efficient approach to determine the minimum number of required UAVs and their optimal positions. To this end, we use an iterative algorithm that updates the number of required UAVs at each iteration. To determine the optimal position for the UAVs, we present a mathematical model and solve it accurately after linearizing. One of the inputs of the mathematical model is a set of candidate points for UAV deployments in 2D space. The mathematical model selects a set of points among candidate points and determines the altitude of each UAV. To provide a suitable set of candidate points, we also propose a candidate point selection method: the MergeCells method. The simulation results show that the proposed approach performs better than the 3D P-median approach introduced in the literature. We also compare different candidate point selection approaches, and we show that the MergeCells method outperforms other methods in terms of the number of UAVs, user data rates, and simulation time.

Joint 3-D Positioning and Power Allocation for UAV Relay Aided by Geographic Information

2021

In this paper, we study to employ geographic information to address the blockage problem of air-to-ground links between UAV and terrestrial nodes. In particular, a UAV relay is deployed to establish communication links from a ground base station to multiple ground users. To improve communication capacity, we fifirst model the blockage effect caused by buildings according to the three-dimensional (3-D) geographic information. Then, an optimization problem is formulated to maximize the minimum capacity among users by jointly optimizing the 3-D position and power allocation of the UAV relay, under the constraints of link capacity, maximum transmit power, and blockage. To solve this complex non-convex problem, a two-loop optimization framework is developed based on Lagrangian relaxation. The outer-loop aims to obtain proper Lagrangian multipliers to ensure the solution of the Lagrangian problem converge to the tightest upper bound on the original problem. The inner-loop solves the Lagra...

On the Optimal 3D Placement of a UAV Base Station for Maximal Coverage of UAV Users

2020

Unmanned aerial vehicles (UAVs) can be users that support new applications, or be communication access points that serve terrestrial and/or aerial users. In this paper, we focus on the connectivity problem of aerial users when they are exclusively served by aerial base stations (BS), i.e., UAVBSs. Specifically, the 3D placement problem of a directionalantenna equipped UAV-BS, aiming to maximize the number of covered aerial users under a spectrum sharing policy with terrestrial networks, is investigated. Given a known spectrum sharing policy between the aerial and terrestrial networks, we propose a 3D placement algorithm that achieves optimality. Simulation results show the performance of our approach, in terms of number of covered aerial users for different configurations and parameters, such as the spectrum sharing policy, antenna beamwidth, transmit power, and aerial users density. These results represent novel guidelines for exclusive aerial networks deployment and applications, ...

UAV Base Station Location Optimization for Next Generation Wireless Networks: Overview and Future Research Directions

2019 1st International Conference on Unmanned Vehicle Systems-Oman (UVS), 2019

Unmanned aerial vehicles mounted base stations (UAV-BSs) are expected to become one of the significant components of the Next Generation Wireless Networks (NGWNs). Rapid deployment, mobility, higher chances of unobstructed propagation path, and flexibility features of UAV-BSs have attracted significant attention. Despite, potentially, high gains brought by UAV-BSs in NGWNs, many challenges are also introduced by them. Optimal location assignment to UAV-BSs, arguably, is the most widely investigated problem in the literature on UAV-BSs in NGWNs. This paper presents a comprehensive survey of the literature on the location optimization of UAV-BSs in NGWNs. A generic optimization framework through a universal Mixed Integer Non-Linear Programming (MINLP) formulation is constructed and the specifications of its constituents are elaborated. The generic problem is classified into a novel taxonomy. Due to the highly challenging nature of the optimization problem a range of solutions are adopted in the literature which are also covered under the aforementioned classification. Furthermore, future research directions on UAV-BS location optimization in 5G and beyond non-terrestrial aerial communication systems are discussed.

Optimizing Number, Placement, and Backhaul Connectivity of Multi-UAV Networks

ArXiv, 2021

Multi-Unmanned Aerial Vehicle (UAV) Networks is a promising solution to providing wireless coverage to ground users in challenging rural areas (such as Internet of Things (IoT) devices in farmlands), where the traditional cellular networks are sparse or unavailable. A key challenge in such networks is the 3D placement of all UAV base stations such that the formed Multi-UAV Network (i) utilizes a minimum number of UAVs while ensuring – (ii) backhaul connectivity directly (or via other UAVs) to the nearby terrestrial base station, and (iii) wireless coverage to all ground users in the area of operation. This joint Backhaul-and-coverage-aware Drone Deployment (BoaRD) problem is largely unaddressed in the literature, and, thus, is the focus of the paper. We first formulate the BoaRD problem as Integer Linear Programming (ILP). However, the problem is NP-hard, and therefore, we propose a low complexity algorithm with a provable performance guarantee to solve the problem efficiently. Our ...