Evaluation of Beamsteering Performance in MultiuserMIMO Unmanned Aerial Base Stations Networks

Castellanos, German; Colpaert, Achiel; Deruyck, Margot; Tanghe, Emmeric; Vinogradov, Evgenii; Martens, Luc; Pollin, Sofie; Joseph, Wout

doi:10.1109/access.2022.3182120

Cited by 3 publications

(2 citation statements)

References 53 publications

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“…• Access: As specified in 3GPP TR 22.829, UxNB is able to connect to the 5G core network and operate as a BS, via a wireless backhaul link, and can bootstrap as a BS, from the core network's perspective. To do so, we assume that the UxNB is equipped with multiple antennas enabling directional patterns towards users [11].…”

Section: A System Componentsmentioning

confidence: 99%

“…• Backhaul: The backhaul can be provided by a wireless gateway (e.g., a nearby TBS, TUAV, or satellite) or through an associated anchor, if it provides backhauling services. In the case of a wireless backhaul, integrated access and backhaul (IAB) can be leveraged [10], [11]. Since 3GPP does not enforce any particular IAB implementation, radio access and backhauling can use different frequency bands or the same spectrum.…”

Section: A System Componentsmentioning

confidence: 99%

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iTUAVs: Intermittently Tethered UAVs for Future Wireless Networks

Cherif¹,

Jaafar²,

Vinogradov³

et al. 2023

IEEE Wireless Commun.

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We propose the intermittently tethered unmanned aerial vehicle (iTUAV) as a tradeoff between the power availability of a tethered UAV (TUAV) and flexibility of an untethered UAV. An iTUAV can provide cellular connectivity while being temporarily tethered to the most adequate ground anchor. Also, it can flexibly detach from one anchor, travel, then attach to another one to maintain/improve the coverage quality for mobile users. Hence, we discuss here the existing UAV-based cellular networking technologies, followed by a detailed description of the iTUAV system, its components, and mode of operation. Subsequently, we present a comparative study of the existing and proposed systems highlighting the differences of key features such as mobility and energy. To emphasize the potential of iTUAV systems, we conduct a case study, evaluate the iTUAV performance, and compare it to benchmarks. Obtained results show that with only 10 anchors in the area, the iTUAV system can serve up to 90% of the users covered by the untethered UAV swapping system. Moreover, results for a small case study prove that the iTUAV allows to balance performance/cost and can be implemented realistically. For instance, when user locations are clustered, with only 2 active iTUAVs and 4 anchors, achieved performance is superior to that of the system with 3 TUAVs, while when considering a single UAV on a 100 minutes event, a system with only 6 anchors outperforms the untethered UAV as it combines location flexibility with increased mission time.

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Section: A System Componentsmentioning

confidence: 99%

Section: A System Componentsmentioning

confidence: 99%

iTUAVs: Intermittently Tethered UAVs for Future Wireless Networks

Cherif¹,

Jaafar²,

Vinogradov³

et al. 2023

IEEE Wireless Commun.

View full text Add to dashboard Cite

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Digital twin based DDPG reinforcement learning for sum-rate maximization of AI-UAV communications

Lee,

Park,

Sung

2024

J Wireless Com Network

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Construction of wireless infrastructure using unmanned aerial vehicle (UAV) can effectively expand the coverage and support high-density traffic of next-generation communication systems. Designing wireless systems including UAVs as aerial base stations (ABSs) is a challenging task, due to the mobility of ABSs causing time-varying nature of environmental surroundings and relative propagation paths to user equipment (UE) devices. Therefore, it is essential to have an accurate estimate of the channel for varying positioning of the UAVs. In this paper, we propose to adopt a digital twin based performance evaluation procedure for wireless systems including ABSs, providing enhanced accuracy of channel modeling for specific target deployment areas. Using ray-tracing channel models reflecting detailed building and terrain information of the transmission environment, an UAV position optimization algorithm based on reinforcement learning is presented. By utilizing deep deterministic policy gradient (DDPG), the proposed algorithm calculates the overall throughput in the digital twin and determines the desired states of the UAV. Performance evaluation results demonstrate the trajectory training ability of the algorithm and the performance advantage of the system with a reduced amount of shadow area compared to those with ground base stations (GBSs).

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Evaluating 60 GHz FWA Deployments for Urban and Rural Environments in Belgium

Castellanos

Beelde

David

et al. 2023

Sensors

Self Cite

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Fixed wireless access (FWA) provides a solution to compete with fiber deployment while offering reduced costs by using the mmWave bands, including the unlicensed 60 GHz one. This paper evaluates the deployment of FWA networks in the 60 GHz band in realistic urban and rural environment in Belgium. We developed a network planning tool that includes novel backhaul based on the IEEE 802.11ay standard with multi-objective capabilities to maximise the user coverage, providing at least 1 Gbps of bit rate while minimising the required network infrastructure. We evaluate diverse serving node locations, called edge nodes (EN), and the impact of environmental factors such as rain and vegetation on the network design. Extensive simulation results show that defining a proper EN’s location is essential to achieve viable user coverage higher than 95%, particularly in urban scenarios where street canyons affect propagation. Rural scenarios require nearly 75 ENs per km2 while urban scenarios require four times (300 ENs per km2) this infrastructure. Finally, vegetation can reduce the coverage by 3% or increment infrastructure up to 7%, while heavy rain can reduce coverage by 5% or increment infrastructure by 15%, depending on the node deployment strategy implemented.

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Evaluation of Beamsteering Performance in MultiuserMIMO Unmanned Aerial Base Stations Networks

Cited by 3 publications

References 53 publications

iTUAVs: Intermittently Tethered UAVs for Future Wireless Networks

iTUAVs: Intermittently Tethered UAVs for Future Wireless Networks

Digital twin based DDPG reinforcement learning for sum-rate maximization of AI-UAV communications

Evaluating 60 GHz FWA Deployments for Urban and Rural Environments in Belgium

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