Efficient UAV Placement Strategy for Guaranteed QoS Demand

Panda, Kirtan Gopal; Das, Shrayan

doi:10.1109/vtc2020-fall49728.2020.9348435

Cited by 11 publications

(1 citation statement)

References 14 publications

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“…Within this context, UAV placement algorithms have been proposed to determine the UAV positions that maximize the wireless coverage or the QoS and QoE offered to the users [25]. In particular, the solutions presented in [26,27] aim at maximizing the area and number of users served, whereas the ones in [28,29] focus on optimizing the QoS offered. The use of UAVs has also been envisioned under the Integrated Access and Backhaul (IAB) concept defined in 3GPP Release 16, which takes advantage of resources provided by BSs to establish backhaul networks [30].…”

Section: Related Workmentioning

confidence: 99%

Placement and Allocation of Communications Resources in Slicing-aware Flying Networks

Coelho¹,

Fontes²,

Campos³

et al. 2021

Preprint

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Network slicing emerged in 5G networks as a key component to enable the use of multiple services with different performance requirements on top of a shared physical network infrastructure. A major challenge lies on ensuring wireless coverage and enough communications resources to meet the target Quality of Service (QoS) levels demanded by these services, including throughput and delay guarantees. The challenge is exacerbated in temporary events, such as disaster management scenarios and outdoor festivities, where the existing wireless infrastructures may collapse, fail to provide sufficient wireless coverage, or lack the required communications resources. Flying networks, composed of Unmanned Aerial Vehicles (UAVs), emerged as a solution to provide on-demand wireless coverage and communications resources anywhere, anytime. However, existing solutions mostly rely on best-effort networks. The main contribution of this paper is SLICER, an algorithm enabling the placement and allocation of communications resources in slicing-aware flying networks. The evaluation carried out by means of ns-3 simulations shows SLICER can meet the targeted QoS levels, while using the minimum amount of communications resources.

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Section: Related Workmentioning

confidence: 99%

Placement and Allocation of Communications Resources in Slicing-aware Flying Networks

Coelho¹,

Fontes²,

Campos³

et al. 2021

Preprint

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5G network slicing with unmanned aerial vehicles: Taxonomy, survey, and future directions

Bouzid

Chaib

Bensaad

et al. 2022

Trans Emerging Tel Tech

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With the ever‐expanding rise of network demands and user expectations, the fifth generation (5G) of cellular networks was envisioned to support a plethora of use cases and conflicting user demands. Next to providing traditional connectivity like its previous generations, 5G also promises to be a heterogeneous network connecting humans, vehicles, unmanned aerial vehicles (UAVs), smart devices, and more. These challenging expectations proved to be overwhelming for traditional network infrastructures to handle. Network slicing has emerged as a promising solution that can achieve such diverse, taxing, and sometimes conflicting requirements in a dynamic and programmable way. There is no denying that UAVs have attained significant focus and research in recent years, and with 5G already being deployed, UAVs can now exploit the capabilities of the new networks. Extensive research is being taken to integrate UAVs into networks, assisting and improving aspects like latency, coverage, and capacity. Motivated by these facts, this survey distinguishes itself from other works by jointly exploring 5G, network slicing, and UAVs. The main contributions of this article are to showcase how UAVs can assist networks, provide a taxonomy of UAVs in the context of network slicing, and survey works that contribute to network slicing with UAVs. In this article, we present a comprehensive survey on UAVs in the context of network slicing, covering contributions, and state‐of‐the‐art literature. We discuss network slicing in‐depth, focusing especially on the three major slices: enhanced Mobile BroadBand, massive machine type communications, and ultra‐reliable low‐latency communications. We provide an overview of 5G enablers, including software‐defined networking and network function virtualization. We cover UAVs and identify their roles in networks as both users and assistants. Furthermore, this survey provides insight into open issues and future research directions related to network slicing and UAVs before concluding.

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3D Unmanned Aerial Vehicle Placement for Public Safety Communications

Kumbhar

Güvenç

2022

Intelligent Unmanned Air Vehicles Communications for Public Safety Networks

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Efficient UAV Placement Strategy for Guaranteed QoS Demand

Cited by 11 publications

References 14 publications

Placement and Allocation of Communications Resources in Slicing-aware Flying Networks

Placement and Allocation of Communications Resources in Slicing-aware Flying Networks

5G network slicing with unmanned aerial vehicles: Taxonomy, survey, and future directions

3D Unmanned Aerial Vehicle Placement for Public Safety Communications

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