Three-Dimensional Geometry-Based UAV-MIMO Channel Modeling for A2G Communication Environments

Jiang, Hao; Zhang, Zaichen; Wu, Liang; Dang, Jian

doi:10.1109/lcomm.2018.2828110

Cited by 108 publications

(84 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The authors of [55] studied the spacetime correlation function of a 3D mobile MIMO-based UAV, where only the NLoS channel was considered. In [56], a 3D geometric MIMO channel model was developed for the aBS-gUE link, where the elliptic cylinder model was adopted to describe the distribution of scatters around the aBS and gUE.…”

Section: B Channel Models For Aerial Communicationmentioning

confidence: 99%

Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting

Jaafar

Naser

Muhaidat

et al. 2020

IEEE Open J. Veh. Technol.

View full text Add to dashboard Cite

Recently, interest on the utilization of unmanned aerial vehicles (UAVs) has aroused. Specifically, UAVs can be used in cellular networks as aerial users for delivery, surveillance, rescue search, or as an aerial base station (aBS) for communication with ground users in remote uncovered areas or in dense environments requiring prompt high capacity. Aiming to satisfy the high requirements of wireless aerial networks, several multiple access techniques have been investigated. In particular, space-division multiple access (SDMA) and power-domain non-orthogonal multiple access (NOMA) present promising multiplexing gains for aerial downlink and uplink. Nevertheless, these gains are limited as they depend on the conditions of the environment. Hence, a generalized scheme has been recently proposed, called rate-splitting multiple access (RSMA), which is capable of achieving better spectral efficiency gains compared to SDMA and NOMA. In this paper, we present a comprehensive survey of key multiple access technologies adopted for aerial networks, where aBSs are deployed to serve ground users. Since there have been only sporadic results reported on the use of RSMA in aerial systems, we aim to extend the discussion on this topic by modelling and analyzing the weighted sum-rate performance of a two-user network served by an RSMA-based aBS. Finally, related open issues and future research directions are exposed. Index Terms-Orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA), rate-splitting multiple access (RSMA), unmanned aerial vehicle (UAV), survey. I. INTRODUCTION D UE to the unprecedented growth of mobile data traffic and stringent quality-of-service (QoS) requirements, recent research efforts have focused on several key enabling technologies for 5G networks and beyond [1], such as millimeter waves (mmWave), terahertz (THz) communications, multiple-input multiple-output (MIMO), massive MIMO, multiple access techniques, relaying, cognitive radio, and unmanned aerial networks [2]. In particular, unmanned aerial vehicles (UAVs) have demonstrated great potential in enabling new applications. For instance, UAVs can be used for aerial security inspection, traffic monitoring, smart agriculture, aerial delivery, etc. [3], [4] (and references therein). Furthermore, UAVs can be deployed as aerial base stations (aBSs) to provide wireless access to ground and aerial devices/users, in several scenarios such as temporary events, disasters when a terrestrial cellular network is not fully operational, and congestion due to unpredictable traffic surges, as well as aerial devices/users (e.g., cargo drones) [5], [6].

show abstract

Section: B Channel Models For Aerial Communicationmentioning

confidence: 99%

Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting

Jaafar

Naser

Muhaidat

et al. 2020

IEEE Open J. Veh. Technol.

View full text Add to dashboard Cite

show abstract

“…The authors in [9] provided an analytical method for optimizing the altitude of a UAV to offer better coverage for users. The horizontal positions of UAVs are optimized in [14] by fixing the altitude to reduce the number of required UAV BSs for covering a set of ground users [15]- [17]. A UAV-enabled cell employment optimization problem is examined in [18] to exploit the users which can cover in three-dimensional (3D) space.…”

Section: Introductionmentioning

confidence: 99%

Employing Unmanned Aerial Vehicles for Improving Handoff Using Cooperative Game Theory

Goudarzi

Anisi

Ciuonzo

et al. 2021

IEEE Trans. Aerosp. Electron. Syst.

View full text Add to dashboard Cite

Heterogeneous wireless networks that are used for seamless mobility are expected to face prominent problems in future 5G cellular networks. Due to their proper flexibility and adaptable preparation, remote-controlled Unmanned Aerial Vehicles (UAVs) could assist heterogeneous wireless communication. However, the key challenges of current UAV-assisted communications consist in having appropriate accessibility over wireless networks via mobile devices with an acceptable Quality of Service (QoS) grounded on the users' preferences. To this end, we propose a novel method based on cooperative game theory to select the best UAV during handover process and optimize handover among UAVs by decreasing the (i) end-to-end delay, (ii) handover latency and (iii) signaling overheads. Moreover, the standard design of Software Defined Network (SDN) with Media Independent Handover (MIH) is used as forwarding switches in order to obtain seamless mobility. Numerical results derived from the real data are provided to illustrate the effectiveness of the proposed approach in terms of number of handovers, cost and delay.

show abstract

“…With the rapid technological advances made in electronics, interest is shifting toward collaborative UAV systems [1]. Although single-UAV systems are already in use, a single-UAV system cannot complete multi-faceted missions properly across large areas, due to battery constraints, self-provisioning, and other restrictions [2,3]. A multi-UAV system can cover a wider area than a single UAV because the drones work in cooperation with each other.…”

Section: Introductionmentioning

confidence: 99%

“…However, in addition to the advantages of running multiple drones, there exist numerous challenges and prominent design problems to be overcome before operation of a group of UAVs can be realized. Comparing multi-UAV systems with single-UAV systems, we find that one of the unique challenges of a multi-UAV system is communication [2][3][4]. Single-UAV systems use ground-based and satellite communication infrastructures but can also establish communication links between the drone and airborne control systems.…”

Section: Introductionmentioning

confidence: 99%

“…Single-UAV systems use ground-based and satellite communication infrastructures but can also establish communication links between the drone and airborne control systems. In all cases, UAV communications are built between the UAV and the infrastructure [2,3]. As the number of UAVs increases, effective network architecture design becomes a critical issue in preventing issues, such as broadcasting storms.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mathematical modeling for flocking flight of autonomous multi-UAV system, including environmental factors

2020

KSII TIIS

View full text Add to dashboard Cite

In this study, we propose a decentralized mathematical model for predictive control of a system of multi-autonomous unmanned aerial vehicles (UAVs), also known as drones. Being decentralized and autonomous implies that all members make their own decisions and fly depending on the dynamic information received from other unmanned aircraft in the area. We consider a variety of realistic characteristics, including time delay and communication locality. For this flocking flight, we do not possess control for central data processing or control over each UAV, as each UAV runs its collision avoidance algorithm by itself. The main contribution of this work is a mathematical model for stable group flight even in adverse weather conditions (e.g., heavy wind, rain, etc.) by adding Gaussian noise. Two of our proposed variance control algorithms are presented in this work. One is based on a simple biological imitation from statistical physical modeling, which mimics animal group behavior; the other is an algorithm for cooperatively tracking an object, which aligns the velocities of neighboring agents corresponding to each other. We demonstrate the stability of the control algorithm and its applicability in autonomous multi-drone systems using numerical simulations.

show abstract

Three-Dimensional Geometry-Based UAV-MIMO Channel Modeling for A2G Communication Environments

Cited by 108 publications

References 10 publications

Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting

Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting

Employing Unmanned Aerial Vehicles for Improving Handoff Using Cooperative Game Theory

Mathematical modeling for flocking flight of autonomous multi-UAV system, including environmental factors

Contact Info

Product

Resources

About