Real-Time Video Streaming and Control of Cellular-Connected UAV System: Prototype and Performance Evaluation

Zhou, Hui; Hu, Fenghe; Juras, Michal; Mehta, Asish B.; Deng, Yansha

doi:10.1109/lwc.2021.3076415

Cited by 24 publications

(10 citation statements)

References 10 publications

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“…In addition, the network structure frequently changes due to the high movement speed, leading to low performance, so the optimization and prediction of movement trajectory problems also need to be studied [52]. In [53], the authors designed a real-time video communication system based on UAVs and Cellular networks.…”

Section: ) Aerial Communication Networkmentioning

confidence: 99%

Innovative Trends in the 6G Era: A Comprehensive Survey of Architecture, Applications, Technologies, and Challenges

et al. 2023

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While the fifth-generation mobile network is being commercialized worldwide, researchers have recently started looking towards the next generation, called the 6G network. Unlike 5G and previous generations of wireless technologies designed to improve network performance for greater bandwidth, lower latency and greater reliability, 6G ecosystems is considered a platform conducive to innovations in the fields of computing, artificial intelligence, connectivity and sensors, virtualization and more. It is designed to meet the requirements of higher global coverage, greater spectral efficiency, a reduced carbon footprint, with an emphasis on sustainability, equity, trust and security through unprecedented architectural evolutions and technology. 6G will be an integrated network system that includes a traditional terrestrial mobile network, space network, and underwater network to provide ubiquitous network access. Even if there are studies on vision of 6G network that have already been published, there is still a significant amount of ground to cover. There is no decision made yet regarding anything and nothing has been ruled out. The focus of this study is to identify a complete picture of changes in architectures, technologies, and challenges that will shape the 6G network. We hope the research results will provide indications for further studies on 6G ecosystems.

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Section: ) Aerial Communication Networkmentioning

confidence: 99%

Innovative Trends in the 6G Era: A Comprehensive Survey of Architecture, Applications, Technologies, and Challenges

et al. 2023

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“…Wireless transmission of large volumes of data is energy consuming and can deplete the on-board energy of UAVs very quickly [25]. Higher resolution video is of larger data size and requires more network bandwidth for transmission [26]. Streaming high bitrate (high resolution) video leads to increased energy consumption in transmission [27].…”

Section: Related Workmentioning

confidence: 99%

ECMS: Energy-Efficient Collaborative Multi-UAV Surveillance System for Inaccessible Regions

Singhal

Barick

2022

IEEE Access

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The evolution and popular adaptation of drone technology in diverse applications has necessitated advancement of UAV communication framework. UAVs inherently support features like mobility, flexibility, adaptive altitude, which make them a preferable option for dynamic surveillance of remote locations. Multiple UAVs can cooperatively work to accomplish surveillance missions more efficiently. However, the intermittent network connectivity and the limited onboard energy storage impose a great challenge on UAV-assisted remote surveillance. This paper presents an Energy-efficient Collaborative Multi-UAV Surveillance (ECMS) system for surveillance of inaccessible regions. The system employs an optimal Multi-UAV Collaborative Monocular Vision (MCMV) topology to facilitate the surveillance with zero blind spot using minimum number of drones. We also propose an application-aware Multi-Path Weighted Load-balancing (MWL) routing protocol for handling congestion by distributing traffic among all available resources in UAV network and adaptively selecting the of source datarate (i.e. switching video resolution). The simulation results demonstrate that the proposed surveillance system achieves coverage with lesser number of UAVs compared to the existing systems. It also achieves higher throughput, higher packet-delivery ratio, higher residual energy of UAVs, and lower end-to-end delay.INDEX TERMS Unmanned aerial vehicle, remote surveillance, UAV network topology, multi-path routing, load balancing.

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“…Cellular-connected UAV (C-UAV) swarm network has been regarded as a promising solution to tackle various complicated tasks, including cargo delivery, aerial imaging, and traffic control [2]- [4]. This is because the cellular technology provides the following advantages: 1) due to the almost ubiquitous accessibility of cellular networks, cellular-connected UAVs provide the pilot with beyond line-of-sight control [5]; 2) based on the ultra-reliable low latency communications (URLLC) and massive machine type communications (mMTC) services, cellular-connected UAVs achieve significant performance improvements over conventional UAV communication technologies (such as WiFi and Bluetooth) regarding reliability, security, and data throughput [6]; and 3) positioning service in the cellular network provides UAVs with an extra dimension of localization.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Cellular-Connected UAV Swarm Control Optimization

Shao‐Horn¹,

Zhou²,

Deng³

et al. 2023

Preprint

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Cellular-connected unmanned aerial vehicle (UAV) swarm is a promising solution for diverse applications, including cargo delivery and traffic control. However, it is still challenging to communicate with and control the UAV swarm with high reliability, low latency, and high energy efficiency. In this paper, we propose a two-phase command and control (C&C) transmission scheme in a cellular-connected UAV swarm network, where the ground base station (GBS) broadcasts the common C&C message in Phase I. In Phase II, the UAVs that have successfully decoded the C&C message will relay the message to the rest of UAVs via device-to-device (D2D) communications in either broadcast or unicast mode, under latency and energy constraints. To maximize the number of UAVs that receive the message successfully within the latency and energy constraints, we formulate the problem as a Constrained Markov Decision Process to find the optimal policy. To address this problem, we propose a decentralized constrained graph attention multi-agent Deep-Q-network (DCGA-MADQN) algorithm based on Lagrangian primaldual policy optimization, where a PID-controller algorithm is utilized to update the Lagrange Multiplier.Simulation results show that our algorithm could maximize the number of UAVs that successfully receive the common C&C under energy constraints.

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Real-Time Video Streaming and Control of Cellular-Connected UAV System: Prototype and Performance Evaluation

Cited by 24 publications

References 10 publications

Innovative Trends in the 6G Era: A Comprehensive Survey of Architecture, Applications, Technologies, and Challenges

Innovative Trends in the 6G Era: A Comprehensive Survey of Architecture, Applications, Technologies, and Challenges

ECMS: Energy-Efficient Collaborative Multi-UAV Surveillance System for Inaccessible Regions

Energy-Efficient Cellular-Connected UAV Swarm Control Optimization

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