Distributed allocation and dynamic reassignment of channels in UAV networks for wireless coverage

Patra, Amar Nath; Regis, Paulo Alexandre; Sengupta, Shamik

doi:10.1016/j.pmcj.2019.02.005

Cited by 11 publications

(7 citation statements)

References 8 publications

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“…At the early stage of deployment and operation for the shorter distance, centralized sharing performs more efficiently. However, when it comes to longer distances and later part of the operations, it will be much more complicated to reposition or control the device [ 38 ].…”

Section: Taxonomy Of Iodmentioning

confidence: 99%

The Internet of Drones: Requirements, Taxonomy, Recent Advances, and Challenges of Research Trends

Abdelmaboud

2021

Sensors

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The use of unmanned aerial vehicles or drones are a valuable technique in coping with issues related to life in the general public’s daily routines. Given the growing number of drones in low-altitude airspace, linking drones to form the Internet of drones (IoD) is a highly desirable trend to improve the safety as well as the quality of flight. However, there remain security, privacy, and communication issues related to IoD. In this paper, we discuss the key requirements of security, privacy, and communication and we present a taxonomy of IoD based on the most relevant considerations. Furthermore, we present the most commonly used commercial case studies and address the latest advancements and solutions proposed for the IoD environments. Lastly, we discuss the challenges and future research directions of IoD.

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Section: Taxonomy Of Iodmentioning

confidence: 99%

The Internet of Drones: Requirements, Taxonomy, Recent Advances, and Challenges of Research Trends

Abdelmaboud

2021

Sensors

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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%

“…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. Considering that the movement of UAVs and channel reallocation generate cochannel inferences among different communication links, the authors of [27] proposed channel reallocation methods that dynamically reassign channels to reduce the ripple effect. In [28], the authors introduced nonorthogonal multiple-access to a UAV wireless network architecture and proposed a two-sided matching and swapping algorithm to deal with the problem of limited spectrum resources.…”

Section: Related Workmentioning

confidence: 99%

“…Based on local information in decision-making, the authors of [9] studied the integration of graph coloring and learning to adapt to channel allocation under dynamic topology. Although the work in [9] improved the convergence speed, along with those in [7,8,[24][25][26][27][28], it did not apply to channel allocation in integrated mmWave/sub-6 GHz UAV-assisted disaster relief networks.…”

Section: Related Workmentioning

confidence: 99%

“…If there is any element in X' that has a value of c then (27) Update the value of the corresponding element in X as c (28) End if (29) If there is any element in X that has a value of 0 then (30) If c < C then (31) c � c + 1 and go to 2 ( 32 Mobile Information Systems (4) e MUAV sends the BFT information of every GSTA to SUAVs through "MUAV FB" frames. (5) Finally, one SUAV will be chosen based on the BFT information to send a "FB" frame to each GSTA.…”

Section: Convergence Performance Analysismentioning

confidence: 99%

See 2 more Smart Citations

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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NOMA-Based Statistical Signal Transmission for Beyond 5G Communications

Zhang

Zhou

et al. 2022

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Distributed allocation and dynamic reassignment of channels in UAV networks for wireless coverage

Cited by 11 publications

References 8 publications

The Internet of Drones: Requirements, Taxonomy, Recent Advances, and Challenges of Research Trends

The Internet of Drones: Requirements, Taxonomy, Recent Advances, and Challenges of Research Trends

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

NOMA-Based Statistical Signal Transmission for Beyond 5G Communications

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