A Survey on Spectrum Management for Unmanned Aerial Vehicles (UAVs)

Jasim, Mohammed; Shakhatreh, Hazim; Siasi, Nazli; Sawalmeh, Ahmad; Aldalbahi, Adel; Al-Fuqaha, Ala

doi:10.1109/access.2021.3138048

Cited by 44 publications

(38 citation statements)

References 321 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, the Figures 4b to 4e show the users' locations during their mobility from time slot t2 to t5, respectively. For safety reasons, in this work , we set the minimum UAV height to 100m [41], [42].…”

Section: Simulation Resultsmentioning

confidence: 99%

Mobile-IRS Assisted Next Generation UAV Communication Networks

Shakhatreh¹,

Sawalmeh²,

Alenezi³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Prior research on intelligent reflection surface (IRS)assisted unmanned aerial vehicle (UAV) communications has focused on a fixed location for the IRS or mounted on a UAV.The assumption that the IRS is located at a fixed position will prohibit mobile users from maximizing many wireless network benefits, such as data rate and coverage. Furthermore, assuming that the IRS is placed on a UAV is impractical for various reasons, including the IRS's weight and size and the speed of wind in severe weather. Unlike previous studies, this study assumes a single UAV and an IRS mounted on a mobile ground vehicle (M-IRS) to be deployed in an Internet-of-Things (IoT) 6G wireless network to maximize the average data rate. Such a methodology for providing wireless coverage using an M-IRS assisted UAV system is expected in smart cities. In this paper, we formulate an optimization problem to find an efficient trajectory for the UAV, an efficient path for the M-IRS, and users' power allocation coefficients that maximize the average data rate for mobile ground users. Due to its intractability, we propose efficient techniques that can help in finding the solution to the optimization problem. First, we show that our dynamic power allocation technique outperforms the fixed power allocation technique in terms of network average sum rate. Then we employ the individual movement model (Random Waypoint Model) in order to represent the users' movements inside the coverage area. Finally, we propose an efficient approach using a Genetic Algorithm (GA) for finding an efficient trajectory for the UAV, and an efficient path for the M-IRS to provide wireless connectivity for mobile users during their movement. We demonstrate through simulations that our methodology can enhance the average data rate by 15% on average compared with the static IRS and by 25% on average compared without the IRS system.

show abstract

Section: Simulation Resultsmentioning

confidence: 99%

Mobile-IRS Assisted Next Generation UAV Communication Networks

Shakhatreh¹,

Sawalmeh²,

Alenezi³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Increasing use of drones for civil and commercial applications will eventually impose a variety of challenges on management of the radio frequency spectrum. Thus, to ensure efficient utilization of spectrum, safe operation of UAVs, and coexistence of drones with existing wireless networks, spectrum management challenges need to be addressed [324]. Unfortunately, current spectrum allocation techniques cannot be used for UAV networks.…”

Section: Spectrum Managementmentioning

confidence: 99%

“…However, currently used spectrum management techniques and solutions are not very effective when they are applied to UAV networks. In particular, the dynamic nature of UAVs such as their lifetime and speed require the use of cell shapes that change dynamically, i.e., associated with number of subscribers, bandwidth demands and various services [324]. Dependable and secure operation of UAVs within a wireless network is significantly relied on valuable spectrum management techniques that can obtain spectrum efficiency gain at minimized interference, increased capacity, maximum coverage, and high quality of service (QoS).…”

Section: Spectrum Managementmentioning

confidence: 99%

“…They must be able to handle rapid fluctuations of channels, and varying network topologies. The new spectrum management methods will greatly affect the physical and medium access control (MAC) layers of networks, RF circuitry (e.g., antenna), network capacity, communication coverage and cost [324]. Jasim et al in [324] provided a comprehensive review on spectrum management techniques for UAV networks.…”

Section: Spectrum Managementmentioning

confidence: 99%

“…The new spectrum management methods will greatly affect the physical and medium access control (MAC) layers of networks, RF circuitry (e.g., antenna), network capacity, communication coverage and cost [324]. Jasim et al in [324] provided a comprehensive review on spectrum management techniques for UAV networks. Jasim et al listed appropriate management techniques that align with drones' requirements and characteristics to ensure efficient usage of the radio spectrum.…”

Section: Spectrum Managementmentioning

confidence: 99%

See 2 more Smart Citations

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

et al. 2022

View full text Add to dashboard Cite

The use of drones, formally known as unmanned aerial vehicles (UAVs), has significantly increased across a variety of applications over the past few years. This is due to the rapid advancement towards the design and production of inexpensive and dependable UAVs and the growing request for the utilization of such platforms particularly in civil applications. With their intrinsic attributes such as high mobility, rapid deployment and flexible altitude, UAVs have the potential to be utilized in many wireless system applications. On the one hand, UAVs are able to operate as flying mobile terminals within wireless/cellular networks to support a variety of missions such as goods delivery, search and rescue, precision agriculture monitoring, and remote sensing. On the other hand, UAVs can be utilized as aerial base stations to increase wireless communication coverage, reliability, and the capacity of wireless systems without additional investment in wireless systems infrastructure. The aim of this article is to review the current applications of UAVs for civil and commercial purposes. The focus of this paper is on the challenges and communication requirements associated with UAV-based communication systems. This article initially classifies UAVs in terms of various parameters, some of which can impact UAVs' communication performance. It then provides an overview of aerial networking and investigates UAVs routing protocols specifically, which are considered as one of the challenges in UAV communication. This article later investigates the use of UAV networks in a variety of civil applications and considers many challenges and communication demands of these applications. Subsequently, different types of simulation platforms are investigated from a communication and networking viewpoint. Finally, it identifies areas of future research.

show abstract

Network simulation tools for unmanned aerial vehicle communications: A survey

Jiang,

Han,

et al. 2024

Int J Communication

View full text Add to dashboard Cite

SummaryUnmanned aerial vehicle (UAV) communication has been proposed as an effective solution in both military and civilian scenarios, with low cost, high efficiency, high flexibility, and on‐demand deployment. Network simulation is an economically efficient method for validating new ideas in UAV communication. While some simulation tools have been proposed for UAV communications, there is a lack of a state‐of‐the‐art review to guide newcomers in this research field. In existing surveys, the discussion of network simulators is not comprehensive and the content discussed is outdated. There has also been no discussion of open‐source UAV simulation tools. To fill these research gaps, this survey presents an updated and comprehensive survey of UAV network simulation tools, including a unique collection of open‐source tools. Research challenges and opportunities have been proposed to inspire follow‐up studies.

show abstract

A Survey on Spectrum Management for Unmanned Aerial Vehicles (UAVs)

Cited by 44 publications

References 321 publications

Mobile-IRS Assisted Next Generation UAV Communication Networks

Mobile-IRS Assisted Next Generation UAV Communication Networks

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

Network simulation tools for unmanned aerial vehicle communications: A survey

Contact Info

Product

Resources

About