Resource Allocation for Machine-to-Machine Communications with Unmanned Aerial Vehicles

Kasgari

IEEE Trans. Wireless Commun.

et al. 2019

Self Cite

390

231

In this paper, a novel concept of three-dimensional (3D) cellular networks, that integrate drone base stations (drone-BS) and cellular-connected drone users (drone-UEs), is introduced. For this new 3D cellular architecture, a novel framework for network planning for drone-BSs as well as latency-minimal cell association for drone-UEs is proposed. For network planning, a tractable method for drone-BSs' deployment based on the notion of truncated octahedron shapes is proposed that ensures full coverage for a given space with minimum number of drone-BSs. In addition, to characterize frequency planning in such 3D wireless networks, an analytical expression for the feasible integer frequency reuse factors is derived. Subsequently, an optimal 3D cell association scheme is developed for which the drone-UEs' latency, considering transmission, computation, and backhaul delays, is minimized. To this end, first, the spatial distribution of the drone-UEs is estimated using a kernel density estimation method, and the parameters of the estimator are obtained using a cross-validation method. Then, according to the spatial distribution of drone-UEs and the locations of drone-BSs, the latency-minimal 3D cell association for drone-UEs is derived by exploiting tools from optimal transport theory. Simulation results show that the proposed approach reduces the latency of drone-UEs compared to the classical cell association approach that uses a signal-to-interference-plus-noise ratio (SINR) criterion. In particular, the proposed approach yields a reduction of up to 46% in the average latency compared to the SINR-based association. The A preliminary conference version of this work appears in [1].Recent reports from the federal aviation administration (FAA) shows that the number of unmanned aerial vehicles (UAVs), also known as drones, will exceed 7 million in 2020 [2]. Such a massive use of drones will have significant impacts on wireless networking. From a wireless perspective, the two key roles of drones include: aerial base station (BS), and user equipment (UE) [3]-[5]. Due to their flexibility and inherent ability for line-of-sight (LoS) communications, drone-BSs can provide broadband, wide-scale, and reliable wireless connectivity during disasters and temporary events [4]-[11]. Moreover, drone-BSs offer a promising solution for ultra-flexible deployment and cost-effective wireless services, without the prohibitive costs of terrestrial BSs.Meanwhile, drones can also act as UEs (i.e., cellular-connected drone-UEs) that must connect to a wireless network so as to operate. In particular, cellular-connected drone-UEs can be used for wide range of applications such as package delivery [12], surveillance, remote sensing, and virtual reality. The key feature of drone-UEs is their ability to intelligently move in three dimensions and optimize their trajectory in order to efficiently complete their missions. Therefore, drone-UEs are widely used for delivery purposes such as in Amazon's prime air drone delivery service and drug delivery in me...

Section: Estimation Of the Spatial Distribution Of Drone-uesmentioning

confidence: 87%

“…However, none of these previous works [4]- [8], [13]- [16], [18]- [22], [25], studied a 3D wireless network of co-existing aerial base stations and users (i.e., drone-BSs and drone-UEs) while addressing network planning, deployment, and latency-aware cell association problems.…”

Section: Introductionmentioning

confidence: 99%

Beyond 5G With UAVs: Foundations of a 3D Wireless Cellular Network

Kasgari

IEEE Trans. Wireless Commun.

et al. 2019

Self Cite

390

231

“…In this regard, the use of mobile UAVs is a promising solu-tion to a number of challenges associated with IoT networks. In IoT-centric scenarios, UAVs can be deployed as flying base stations to provide reliable and energy-efficient uplink IoT communications (e.g., see [7], [10], [83], and [84]). In fact, due to the aerial nature of the UAVs and their high altitude, they can be effectively deployed to reduce the shadowing and blockage effects as the major cause of signal attenuation in wireless links.…”

Section: Uav Networkmentioning

confidence: 99%

A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems

IEEE Commun. Surv. Tutorials

Bennis

et al. 2019

Self Cite

2,068

1,175

The use of flying platforms such as unmanned aerial vehicles (UAVs), popularly known as drones, is rapidly growing. In particular, with their inherent attributes such as mobility, flexibility, and adaptive altitude, UAVs admit several key potential applications in wireless systems. On the one hand, UAVs can be used as aerial base stations to enhance coverage, capacity, reliability, and energy efficiency of wireless networks. On the other hand, UAVs can operate as flying mobile terminals within a cellular network. Such cellular-connected UAVs can enable several applications ranging from real-time video streaming to item delivery. In this paper, a comprehensive tutorial on the potential benefits and applications of UAVs in wireless communications is presented. Moreover, the important challenges and the fundamental tradeoffs in UAV-enabled wireless networks are thoroughly investigated. In particular, the key UAV challenges such as three-dimensional deployment, performance analysis, channel modeling, and energy efficiency are explored along with representative results. Then, open problems and potential research directions pertaining to UAV communications are introduced. Finally, various analytical frameworks and mathematical tools such as optimization theory, machine learning, stochastic geometry, transport theory, and game theory are described. The use of such tools for addressing unique UAV problems is also presented. In a nutshell, this tutorial provides key guidelines on how to analyze, optimize, and design UAV-based wireless communication systems. arXiv:1803.00680v2 [cs.IT] 17 Mar 2019 particular, the work in [45] discussed the applications of flying ad-hoc networks, design considerations, communication protocols, and privacy aspects. In [46], a comprehensive review of UAV-based flying ad hoc networks (FANETs) and their challenges are provided. Moreover, several FANET design challenges in terms of mobility, node density, topology change, radio propagation model, and power consumption are investigated. The survey in [47] discussed the design challenges pertaining to the use of UAVs as relay nodes in flying adhoc networks. The work in [48] provided a comprehensive survey on the potential use of UAVs for supporting IoT services. In particular, key challenges and requirements for designing UAV-assisted IoT networks are discussed in [48]. In [49], the authors surveyed different mechanisms and protocols for developing airborne communication networks while considering low-altitude-platform communications, high-altitudeplatform communications, and integrated airborne communication systems. The survey in [50] studied the use of HAPs for broadband communications. Moreover, it described key advantages of HAPs compared to terrestrial and satellite networks, suitable HAP airships, frequency bands, and possible HAP-based network architectures. The authors in [51] studied the challenges and advantages associated with a multi-tier drone network architecture. Moreover, this work investigated the performance of a multi-tier drone...

“…Furthermore, this work does not analyze the control aspect of drones which is essential in designing drone-based MIMO systems. In fact, none of the previous works on drone communications, such as in [2]- [4], [6]- [19], has studied the use of a drone-based antenna array system for service time minimization.…”

Section: A Related Work On Uav Communicationsmentioning

confidence: 99%

Communications and Control for Wireless Drone-Based Antenna Array

Bennis

et al. 2019

IEEE Trans. Commun.

Self Cite

In this paper, the effective use of multiple quadrotor drones as an aerial antenna array that provides wireless service to ground users is investigated. In particular, under the goal of minimizing the airborne service time needed for communicating with ground users, a novel framework for deploying and operating a drone-based antenna array system whose elements are single-antenna drones is proposed. In the considered model, the service time is minimized by minimizing the wireless transmission time as well as the control time that is needed for movement and stabilization of the drones. To minimize the transmission time, first, the antenna array gain is maximized by optimizing the drone spacing within the array. In this case, using perturbation techniques, the drone spacing optimization problem is addressed by solving successive, perturbed convex optimization problems. Then, according to the location of each ground user, the optimal locations of the drones around the array's center are derived such that the transmission time for the user is minimized. Given the determined optimal locations of drones, the drones must spend a control time to adjust their positions dynamically so as to serve multiple users. To minimize this control time of the quadrotor drones, the speed of rotors is optimally adjusted based on both the destinations of the drones and external forces (e.g., wind and gravity). In particular, using bang-bang control theory, the optimal rotors' speeds as well as the minimum control time are derived in closed-form. Simulation results show that the proposed approach can significantly reduce the service time to ground users compared to a fixed-array case in which the same number of drones form a fixed uniform antenna array. The results also show that, in comparison with the fixed-array case, the network's spectral efficiency can be improved by 32% while leveraging the drone antenna array system. Finally, the results reveal an inherent tradeoff between the control time and transmission time while varying the number of drones in the array.