3D On-Demand Flying Mobile Communication for Millimeter-Wave Heterogeneous Networks

Feng, Kai-Ten; Shen, Li-Hsiang; Li, Chi‐Yu; Huang, Po-Tsang; Wang, Lichun; Lin, Yi‐Bing; Chang, M.F.

doi:10.1109/mnet.011.1900600

Cited by 16 publications

(6 citation statements)

References 13 publications

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“…Technically speaking, LFAUAVs equipped with 5G/5GB communication abilities, intelligence data analytics capabilities and wireless power transfer (WPT) technologies is integrated with SC to meet the ultra-high reliability, ultrahigh availability, and ultra-low latency requirements of SC applications using visual LoS (VLoS) links. UAV base stations (BSs) can detect the communication coverage holes [55] in the urban areas and position themselves [56], [57] appropriately to provide uninterrupted communication services over a city. In this direction, several LFAUAVs as the SC aerial MEC platform can close the coverage constraints in an urban environment with respect to the size of the city, which, in turn, help maintain the link reliability for mobile FA-SDVs.…”

Section: ) Smart City Digital Twins and Cloud Platformmentioning

confidence: 99%

Conceptualisation of Human-on-the-Loop Haptic Teleoperation With Fully Autonomous Self-Driving Vehicles in the Urban Environment

Kuru¹

2021

IEEE Open J. Intell. Transp. Syst.

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The automotive industry aims to deploy commercial level-5 fully autonomous self-driving vehicles (FA-SDVs) in a diverse range of benefit-driven concepts on city roads in the years to come. In all future visions of operating networks of FA-SDVs, humans are expected to intervene with some kind of remote supervisory role. Recent advances in cyber-physical systems (CPS) within the concept of Internet of Everything (IoE) using tactile internet (TI) teleport us to teleoperate remote objects within the cyber-world. Human-on-the-loop (HOTL) haptic teleoperation with an extension of human control and sensing capability by coupling with artificial sensors and actuators with an increased sense of real-time driving in the remote vehicle can help overcome the challenging tasks when the new driver -artificial intelligence (AI) agent -encounters an unorthodox situation that can't be addressed by the autonomous capabilities. This paper analyses HOTL real-time haptic delay-sensitive teleoperation with FA-SDVs, in the aspects of human-vehicle teamwork by establishing two similar remote parallel worlds -real-world vehicle time-varying environment and cyber-world emulation of this environment, i.e., digital twins (DTs) -in which a human telesupervisor (HTS), as a biological agent, can be immersed with no cybersickness enabling omnipresence through a timely bidirectional flow of energy and information. The experiments conducted as a proof of concept of HOTL haptic teleoperation regarding learning with human-vehicle collaboration show promising results and the potential of benefiting from the proposed framework.

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Section: ) Smart City Digital Twins and Cloud Platformmentioning

confidence: 99%

Conceptualisation of Human-on-the-Loop Haptic Teleoperation With Fully Autonomous Self-Driving Vehicles in the Urban Environment

Kuru¹

2021

IEEE Open J. Intell. Transp. Syst.

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“…The authors in [17]- [21] have pre-sented the work based on the autonomous navigation of UAVs but not considered to use UAV as a user to detect the mobile signal strength. Additionally, the authors in [22]- [29] have discussed about the efficient 3D aerial BS placement while considering several UAVs, backhaul, an optical link, users' mobility, millimeter wave (mmWave) and energy constraints with or without machine learning algorithm. Despite all these recent research, UAVs have not been utilised with RL for coverage hole detection.…”

Section: A Backgroundmentioning

confidence: 99%

Optimal 3D UAV base station placement by considering autonomous coverage hole detection, wireless backhaul and user demand

2020

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The rising number of technological advanced devices making network coverage planning very challenging tasks for network operators. The transmission quality between the transmitter and the end users has to be optimum for the best performance out of any device. Besides, the presence of coverage hole is also an ongoing issue for operators which cannot be ignored throughout the whole operational stage. Any coverage hole in network operators' coverage region will hamper the communication applications and degrade the reputation of the operator's services. Presently, there are techniques to detect coverage holes such as drive test or minimization of drive test. However, these approaches have many limitations. The extreme costs, outdated information about the radio environment and high time consumption do not allow to meet the requirement competently. To overcome these problems, we take advantage of Unmanned aerial vehicle (UAV) and Q-learning to autonomously detect coverage hole in a given area and then deploy UAV based base station (UAV-BS) by considering wireless backhaul with the core network and users demand. This machine learning mechanism will help the UAV to eliminate human-in-the-loop (HiTL) model. Later, we formulate an optimisation problem for 3D UAV-BS placement at various angular positions to maximise the number of users associated with the UAV-BS. In summary, we have illustrated a cost-effective as well as time saving approach of detecting coverage hole and providing on-demand coverage in this article.

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“…Now if we set all the binary variables {ρ i, j } equal to 0, all the binary variables {ρ i,G } will be equal to 1 according to (27). Since the SINR functions γ i, j and γ i,G are positive (see (7) and ( 13), respectively), the solution satisfies all the constraints. Such a placement result means that all the UEs are served by the GBS.…”

Section: Feasibilitymentioning

confidence: 99%

“…Such a result can make each DBS serve almost the same number of UEs. In fact, the data rate of a UE is not proportion to distance squared according to (7) and ( 8) and the co-channel interference from different nearby DBSs is not considered in this stage. Balanced k-means clustering cannot find the optimal result for the considered problem (P4).…”

Section: User Association Clusteringmentioning

confidence: 99%

The Coverage Overlapping Problem of Serving Arbitrary Crowds in 3D Drone Cellular Networks

Lai,

Wang,

Han

2020

Preprint

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Providing coverage for flash crowds is an important application for drone base stations (DBSs). However, any arbitrary crowd is likely to be distributed at a high density. Under the condition for each DBS to serve the same number of ground users, multiple DBSs may be placed at the same horizontal location but different altitudes and will cause severe co-channel interference, to which we refer as the coverage overlapping problem. To solve this problem, we then proposed the data-driven 3D placement (DDP) and the enhanced DDP (eDDP) algorithms. The proposed DDP and eDDP can effectively find the appropriate number, altitude, location, and coverage of DBSs in the serving area in polynomial time to maximize the system sum rate and guarantee the minimum data rate requirement of the user equipment. The simulation results show that, compared with the balanced k-means approach, the proposed eDDP can increase the system sum rate by 200% and reduce the computation time by 50%. In particular, eDDP can effectively reduce the occurrence of the coverage overlapping problem and then outperform DDP by about 100% in terms of system sum rate.

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3D On-Demand Flying Mobile Communication for Millimeter-Wave Heterogeneous Networks

Cited by 16 publications

References 13 publications

Conceptualisation of Human-on-the-Loop Haptic Teleoperation With Fully Autonomous Self-Driving Vehicles in the Urban Environment

Conceptualisation of Human-on-the-Loop Haptic Teleoperation With Fully Autonomous Self-Driving Vehicles in the Urban Environment

Optimal 3D UAV base station placement by considering autonomous coverage hole detection, wireless backhaul and user demand

The Coverage Overlapping Problem of Serving Arbitrary Crowds in 3D Drone Cellular Networks

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