Learn to Coloring: Fast Response to Perturbation in UAV-Assisted Disaster Relief Networks

Wang, Bowen; Sun, Yanjing; Zhao, Nan; Gui, Guan

doi:10.1109/tvt.2020.2967124

Cited by 32 publications

(20 citation statements)

References 12 publications

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“…Other relevant tasks during SDAR activities could be monitoring the wireless channel conditions and adapting the communication system accordingly. In this case, BS can perform an initial spectrum sensing, while the spectrum awareness can be improved as other devices are deployed in the searching area [10]. 3GPP standardized bands are preferable, but other vacant bands, such as UHF or VHF, can also be used.…”

Section: A Critical Mission Requirements and Goalsmentioning

confidence: 99%

Artificial Intelligence for Enhanced Mobility and 5G Connectivity in UAV-Based Critical Missions

et al. 2021

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This work is supported by the MCTIC/CGI/FAPESP with the project entitled "SFI 2 -Slicing Future Internet Infrastructures", process number 2018/23097-3 and by the Brazilian National Council for Research and Development (CNPq). Ericsson employees do not access, use or contribute to any of the mentioned open source tools. Their contribution is related to theoretical, conceptual and architectural aspects.

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Section: A Critical Mission Requirements and Goalsmentioning

confidence: 99%

Artificial Intelligence for Enhanced Mobility and 5G Connectivity in UAV-Based Critical Missions

et al. 2021

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“…In the post-disaster areas where BSs are severely damaged, it is necessary to utilize the emerging technologies (e.g., UAV-assisted emergency networks) to restore the communicating services. erefore, some channel allocation methods for UAV-assisted cellular networks emerged [9,[26][27][28]. e authors of [26] aimed to achieve the energy efficiency by jointly optimizing subchannel selection and power control as well as UAV relays deployment, where UAVs just acted as a relay and the mobility of UAVs was not considered.…”

Section: Related Workmentioning

confidence: 99%

“…Although the FCFL can solve the constraint satisfaction problem in a decentralized way, it does not converge fast enough to respond to topology changes. e authors of [9] believed that the main challenges of channel allocation in stochastic and dynamic environments are how to obtain the desired decision results by utilizing the local information and make the convergence speed of channel allocation algorithm keep up with topology changes. erefore, they studied the integration of graph coloring and learning to address the above challenges, where a UAVassisted disaster relief network is modeled as a dynamic topology by using graph theory, and then a dynamic graph coloring algorithm was proposed to address the channel allocation problem of this dynamic topology in a decentralized way.…”

Section: Introductionmentioning

confidence: 99%

“…Although the work in [9] is the first study on UAVassisted emergency communications by introducing the dynamic graph coloring, it only focuses on sub-6 GHz UAVassisted disaster relief networks. e single hop communication in the traditional sub-6 GHz frequency band has long communication distance and good channel quality, but its spectrum resources are very limited.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Radio Channel Allocation in Integrated mmWave/Sub-6 GHz UAV-Assisted Disaster Relief Networks

Gui

Cai

2021

Mobile Information Systems

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The unmanned aerial vehicle- (UAV-) assisted sub-6 GHz disaster relief networks cannot meet high-speed transmission requirements. In this paper, the millimeter wave (mmWave) frequency band is combined with the sub-6 GHz frequency band to build a high-speed UAV-assisted disaster relief network. However, the high propagation path loss of mmWave signals usually needs to be compensated by beamforming, where the ground-facing beam of each UAV is the desired receiving beam of ground user information. The different channels need to be allocated to a single UAV so that this kind of beam can be used simultaneously by different ground users to communicate with this UAV. Also, the other UAVs should reuse these channels as much as possible to save spectrum resources. In this paper, the beamforming training (BFT) mechanism is firstly used to obtain the signal-to-noise ratio (SNR) values of all possible links between ground terminals and UAVs, which are used to estimate these links’ energy efficiency. Then, an interference graph construction algorithm is proposed to identify the links that cannot be used simultaneously in the same channel according to the system energy efficiency. Finally, an iterative channel allocation algorithm is designed to allocate new channels to eliminate the edges of the interference graph, so that the links obtained by the BFT process can be used simultaneously as much as possible under the constraint of the number of channels. The simulation results show that our proposed scheme can achieve the shorter average convergence time, the higher data rate (or the lower data loss rate), and the higher energy efficiency.

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“…The price range can vary between 20$-300$ for small battery-powered Radio Frequency (RF) drones such as the Parrot Bebop 2, to more than 3000$ for professional drones with advanced control systems and sensors such as the DJI Spreading Wings S1000. In the consumer market segment, drones are mainly used for taking aerial pictures and videos, while in the commercial segment the range of applications is more diverse: mapping of geographical areas, product delivery, and logistics, data collection, crop monitoring, and surveillance [10][11][12]. Drones are increasingly being used also in applications such as crime prevention, weather and meteorology, search and rescue operations, border and maritime patrol and forest fire monitoring.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of UAV-Enabled LoRa Networks for Disaster Management Applications

Saraereh

Alsaraira

Khan

et al. 2020

Sensors

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In hostile and remote environments, such as mountains, forests or suburban areas, traditional communications may not be available, especially after a disaster, such as a flood, a forest fire or an earthquake. In these situations, the wireless networks may become congested or completely disrupted and may not be adequate to support the traffic generated by rescuers. It is also considered as the key tool in Corona Virus (COVID-19) battle. Moreover, the conventional approaches with fixed gateways may not work either, and this might lead to decoding errors due to the large distance between mobile nodes and the gateway. To avoid the decoding errors and improve the reliability of the messages, we propose to use intermediate Unmanned Aerial Vehicles (UAVs) to transfer messages from ground-based Long Range (LoRa) nodes to the remote base station (BS). Specifically, this UAV-enabled LoRa architecture is based on the ad hoc WiFi network, wherein, UAVs act as relays for the traffic generated between LoRa nodes and BS. To make the architecture more efficient, a distributed topology control algorithm is also proposed for UAVs. The algorithm is based on virtual spring forces and movement prediction technique that periodically updates the UAV topology to adapt to the movement of the ground-based LoRa nodes that move on the surface. The simulation results show the feasibility of the proposed approach for packet reception rate and average delay quality of service (QoS) metrics. It is observed that the mechanisms implemented in a UAV-enabled LoRa network effectively help to improve the packet reception rate with nominal buffer delays.

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Learn to Coloring: Fast Response to Perturbation in UAV-Assisted Disaster Relief Networks

Cited by 32 publications

References 12 publications

Artificial Intelligence for Enhanced Mobility and 5G Connectivity in UAV-Based Critical Missions

Artificial Intelligence for Enhanced Mobility and 5G Connectivity in UAV-Based Critical Missions

Efficient Radio Channel Allocation in Integrated mmWave/Sub-6 GHz UAV-Assisted Disaster Relief Networks

Performance Evaluation of UAV-Enabled LoRa Networks for Disaster Management Applications

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