Mobility Control of Unmanned Aerial Vehicle as Communication Relay to Optimize Ground-to-Air Uplinks

Wu, Guannan; Gao, Xiaoguang; Wan, Kaifang

doi:10.3390/s20082332

Cited by 11 publications

(10 citation statements)

References 40 publications

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“…The development of the general control law continues by computing ̄ ∈ ℝ similarly to (7), namely through…”

Section: Subsequently Settingmentioning

confidence: 99%

“…In addition, new research has shown that drones are able to effectively be employed as communication relays 5,6 between ground units, allowing them to overcome communication difficulties caused by obstacles or terrain features, such as buildings or mountainous terrain. The approach in these works often assumes a centralized level of coordination 7 , known locations of ground units 8,9 , or focuses on a small finite subset of connectivity topologies within decentralized frameworks 10,11 .…”

Section: Introductionmentioning

confidence: 99%

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Bearing-based Autonomous Communication Relay Positioning under Field-of-View Constraints

Fabris,

Zelazo

2022

Preprint

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This paper investigates the problem of communication relay establishment for multiple agent-based mobile units using a relay vehicle. The objective is to drive autonomously the relay vehicle to attain a position for communication relay establishment while maintaining the other vehicles inside of its field-of-view. A bearingbased control law is proposed for the relay drone and designed for both single and multiple agents. We also provide a collision avoidance scheme that ensures no collisions between the relay and other agents. Numerical simulations and experimental results are reported as well to show the efficacy of the proposed approach.

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“…The development of the general control law continues by computing ̄ ∈ ℝ similarly to (7), namely through…”

Section: Subsequently Settingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bearing-based Autonomous Communication Relay Positioning under Field-of-View Constraints

Fabris,

Zelazo

2022

Preprint

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show abstract

“…Moreover, they did not study dense urban areas. Wu et al 37 studies UAV mobility control issues as a communication relay on multiagents' on-demand service. It takes mobile agents and entirely unknown wireless channel properties, using only online measured data on collected agent location information and received signal strength (RSS).…”

Section: Cellular-to-uav Path Loss For Uavmentioning

confidence: 99%

Unmanned aerial vehicle‐enabled layered architecture based solution for disaster management

Khan

Gupta

2021

Trans Emerging Tel Tech

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Unmanned aerial vehicle (UAV) has become a priority in the industrial and academic research community for the last few years. With the fast development of wireless networking technologies, it is widely used in many applications such as surveillance, search and rescue (SAR) operation, disaster management, remote monitoring, and so forth. Emergency communication for victims and first responders is one of the critical requirements during natural and human-made disasters. Airborne Base Stations (BS) or UAV-mounted BS has been used to provide high-speed internet services and rescue responses in natural disasters and emergencies in recent years. Most of the previous research on UAV-mounted BS (UAVmBS) only considers outdoor users. It assumes their coordinate position in a two-dimensional (2D) plane, taking only Euclidean pathloss-based distance into account.Though, in man-made or urban natural disaster situations such as floods, cyclones, building fires, and so forth, users are stuck in single or multistory high-rise buildings situated in a three-dimensional (3D) plane. In such cases, it is possible to interact and rescue reliably if pathloss features are known a priori, both for UAVmBS to users (downlink) and vice versa (uplink). As pathloss in the above situations is a mixture of outdoor and indoor elements, adopting a compatible model can be challenging for communications. This article proposes a layered architecture and studies the path loss models best suited for the disaster management system (DMS), which considers both indoor and outdoor parameters. Further, the main goal is to effectively implement a layered architecture employing UAVmBS in urban disasters for better capacity and coverage improvement. Simulation outputs display the progress in transmission delays, throughput, and effective packet delivery for disaster management.

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“…The smart service-centric domain includes aerial delivery [3], smart healthcare, smart homes, Internet of vehicles [4], UAV simulation [5], pollution monitoring, smart agriculture, disaster management [6], industrial Internet of Things, and green mobility [7]. It has emerged as a prominent development area to revolutionize UAV-assisted IoT in daily day life [8]. In sensor-enabled UAV-assisted applications, for transmitting and viewing data immediately, the Internet is utilized to connect actuators and sensors inside the aerial vehicles.…”

Section: Introductionmentioning

confidence: 99%

Internet of Unmanned Aerial Vehicles: QoS Provisioning in Aerial Ad-Hoc Networks

Kumar

Kaiwartya

et al. 2020

Sensors

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Aerial ad-hoc networks have the potential to enable smart services while maintaining communication between the ground system and unmanned aerial vehicles (UAV). Previous research has focused on enabling aerial data-centric smart services while integrating the benefits of aerial objects such as UAVs in hostile and non-hostile environments. Quality of service (QoS) provisioning in UAV-assisted communication is a challenging research theme in aerial ad-hoc networks environments. Literature on aerial ad hoc networks lacks cooperative service-oriented modeling for distributed network environments, relying on costly static base station-oriented centralized network environments. Towards this end, this paper proposes a quality of service provisioning framework for a UAV-assisted aerial ad hoc network environment (QSPU) focusing on reliable aerial communication. The UAV’s aerial mobility and service parameters are modelled considering highly dynamic aerial ad-hoc environments. UAV-centric mobility models are utilized to develop a complete aerial routing framework. A comparative performance evaluation demonstrates the benefits of the proposed aerial communication framework. It is evident that QSPU outperforms the state-of-the-art techniques in terms of a number of service-oriented performance metrics in a UAV-assisted aerial ad-hoc network environment.

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Mobility Control of Unmanned Aerial Vehicle as Communication Relay to Optimize Ground-to-Air Uplinks

Cited by 11 publications

References 40 publications

Bearing-based Autonomous Communication Relay Positioning under Field-of-View Constraints

Bearing-based Autonomous Communication Relay Positioning under Field-of-View Constraints

Unmanned aerial vehicle‐enabled layered architecture based solution for disaster management

Internet of Unmanned Aerial Vehicles: QoS Provisioning in Aerial Ad-Hoc Networks

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