Understanding UAV-Based WPCN-Aided Capabilities for Offshore Monitoring Applications

Carrillo, Dick; Mikhaylov, Konstantin; Nardelli, Pedro H. J.; Andreev, Sergey; Costa, Daniel Benevides da

doi:10.1109/mwc.001.2000218

Cited by 8 publications

(5 citation statements)

References 12 publications

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“…The integration of various technologies in modern MCNs, such as sensing equipment and advanced power supply infrastructure, necessitates a holistic performance evaluation that takes into account the role of various actors in the MCN ecosystem [99]. Network lifetime maximization is a significant technical challenge that on one hand can reduce outage probability and on the other hand ensure the provision of end to end high data rate applications.…”

Section: Network Lifetime Maximizationmentioning

confidence: 99%

A Survey on UAV-Aided Maritime Communications: Deployment Considerations, Applications, and Future Challenges

Νομικός

Gkonis

Bithas

et al. 2023

IEEE Open J. Commun. Soc.

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Maritime activities represent a major domain of economic growth with several emerging maritime Internet of Things use cases, such as smart ports, autonomous navigation, and ocean monitoring systems. The major enabler for this exciting ecosystem is the provision of broadband, low-delay, and reliable wireless coverage to the ever-increasing number of vessels, buoys, platforms, sensors, and actuators. Towards this end, the integration of unmanned aerial vehicles (UAVs) in maritime communications introduces an aerial dimension to wireless connectivity going above and beyond current deployments, which are mainly relying on shore-based base stations with limited coverage and satellite links with high latency. Considering the potential of UAV-aided wireless communications, this survey presents the state-of-the-art in UAV-aided maritime communications, which, in general, are based on both conventional optimization and machine-learning-aided approaches. More specifically, relevant UAV-based network architectures are discussed together with the role of their building blocks. Then, physical-layer, resource management, and cloud/edge computing and caching UAV-aided solutions in maritime environments are discussed and grouped based on their performance targets. Moreover, as UAVs are characterized by flexible deployment with high re-positioning capabilities, studies on UAV trajectory optimization for maritime applications are thoroughly discussed. In addition, aiming at shedding light on the current status of real-world deployments, experimental studies on UAV-aided maritime communications are presented and implementation details are given. Finally, several important open issues in the area of UAV-aided maritime communications are given, related to the integration of sixth generation (6G) advancements. These future challenges include physical-layer aspects, non-orthogonal multiple access schemes, radical learning paradigms for swarms of UAVs and unmanned surface and underwater vehicles, as well as UAV-aided edge computing and caching.

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Section: Network Lifetime Maximizationmentioning

confidence: 99%

A Survey on UAV-Aided Maritime Communications: Deployment Considerations, Applications, and Future Challenges

Νομικός

Gkonis

Bithas

et al. 2023

IEEE Open J. Commun. Soc.

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“…(1) Data transmission: Real-time monitoring data collected by drones need to be efficiently transmitted to shore-based mobile monitoring vehicles or ground-based base stations via a control data chain. In medium to long-range sea monitoring, the collected data can be transmitted to unmanned vessels or maritime law enforcement vessels, which can establish communication with the rear using shipboard satellite equipment [131]. Within this context, new solutions to improving data transmission during UAV surveillance are wanted to ensure the reliability and security of the transmitted data, especially in adverse weather conditions and remote areas [132].…”

Section: Marine Safety and Surveillancementioning

confidence: 99%

Applications, Evolutions, and Challenges of Drones in Maritime Transport

Wang,

Zhou,

Xing

et al. 2023

JMSE

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The widespread interest in using drones in maritime transport has rapidly grown alongside the development of unmanned ships and drones. To stimulate growth and address the associated technical challenges, this paper systematically reviews the relevant research progress, classification, applications, technical challenges, and possible solutions related to the use of drones in the maritime sector. The findings provide an overview of the state of the art of the applications of drones in the maritime industry over the past 20 years and identify the existing problems and bottlenecks in this field. A new classification scheme is established based on their flight characteristics to aid in distinguishing drones’ applications in maritime transport. Further, this paper discusses the specific use cases and technical aspects of drones in maritime rescue, safety, navigation, environment, communication, and other aspects, providing in-depth guidance on the future development of different mainstream applications. Lastly, the challenges facing drones in these applications are identified, and the corresponding solutions are proposed to address them. This research offers pivotal insights and pertinent knowledge beneficial to various entities such as maritime regulatory bodies, shipping firms, academic institutions, and enterprises engaged in drone production. This paper makes new contributions in terms of the comprehensive analysis and discussion of the application of drones in maritime transport and the provision of guidance and support for promoting their further development and integration with intelligent transport.

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“…In [13], a medical health monitoring scenario was studied to guarantee effective coverage by deploying UAVs to cover health monitoring equipment in the region, enabling the collection of health monitoring data and providing real-time computational processing to guarantee timely rescue services in case of accidents. In [14], the UAV-assisted maritime monitoring scenario was studied, in which the UAV acts as a mobile base station to achieve energy transmission, and the monitoring nodes are based on obtaining energy upload data information, and the energy efficiency is obtained as a measure of the ratio between the amount of data uploaded by the nodes and the energy consumption of the UAV, and the impact of the UAV hovering point on the network performance is investigated. For the remote ocean monitoring scenario [15], the data of underwater monitoring points are obtained through the surface convergence point, and the data collection work is completed by UAVs, and the optimization goal is to maximize the network lifetime by jointly allocating the UAV deployment, subchannel matching, and joint allocation optimization of power matters, time, and other resources to maximize the remaining energy of underwater nodes while guaranteeing the delay requirements.…”

Section: Related Workmentioning

confidence: 99%

Resource Allocation in UAV-Assisted Wireless Powered Communication Networks for Urban Monitoring

Lyu

Zhang

2022

Wireless Communications and Mobile Computing

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In this paper, we studied the unmanned aerial vehicle-assisted urban monitoring network, in which unmanned aerial vehicle (UAV) with wireless power transmission provides energy transmission and data collection services for the network. Considering the density of the urban monitoring network, we use the k -means algorithm to cluster the monitoring nodes and reduce the complexity of the UAV services. The UAVs are serviced using a fly-hover-communication protocol. During hovering, the UAV works in the full-duplex mode, collecting data from cluster head nodes on one side and recharging nodes in coverage on the other side. We propose a multiobjective joint optimization problem that considers maximizing the amount of data collection and energy transfer and minimizing the energy consumption of the UAV during the service period. In the optimization process, there is a partial conflict between the three objectives. For this reason, the importance of the optimization objectives is considered and described by weighting parameters. A multiobjective joint deep deterministic policy gradient algorithm is proposed for the multiobjective control policy of UAVs. Numerical results show that the proposed algorithm can achieve the joint optimization of multiple objectives and is compared with other algorithms to verify the superiority of the proposed algorithm.

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Understanding UAV-Based WPCN-Aided Capabilities for Offshore Monitoring Applications

Cited by 8 publications

References 12 publications

A Survey on UAV-Aided Maritime Communications: Deployment Considerations, Applications, and Future Challenges

A Survey on UAV-Aided Maritime Communications: Deployment Considerations, Applications, and Future Challenges

Applications, Evolutions, and Challenges of Drones in Maritime Transport

Resource Allocation in UAV-Assisted Wireless Powered Communication Networks for Urban Monitoring

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