Directional antennas modelling and coverage analysis for UAV networks with blockage effects in urban environment

Zhang, Hongtao; Li, Xueyuan

doi:10.1002/ett.4737

Cited by 3 publications

(1 citation statement)

References 20 publications

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“…in 5G communications. To provide a network infrastructure for a large number of mobile users and Internet of Things (IoT) devices and to extend the coverage of terrestrial base stations specially to remote areas, the architectures, requirements and corresponding issues of integrating UAVs with such networks have been widely discussed in 2,3,4,5 .…”

Section: Introductionmentioning

confidence: 99%

Placement and Power Assignment for Hierarchical UAV Networks under Hovering Fluctuations in mmWave Communications

Abdollahi

Azarhava

Niya

2023

Preprint

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In this paper, we investigate the successful transmission probability of an aerial cellular network in which an unmanned aerial vehicle (UAV) as a Macrocell Base Station (UAV-BS) serves other UAVs as aerial users. The beamforming capable antennas are mounted on the UAVs, to increase the throughput of the network. The random effects of inner forces such as controlling errors or outer forces like the air conditions result in the random fluctuations. We assume Rician fading distribution over the links between the UAVs, then, we calculate the distribution of the channels under hovering fluctuations. Also, we derive the closed form expressions for successful transmission probability. Defining an optimization problem on the average successful transmission probability of the network, we obtain the best placement of UAV-BS along with the resource allocation. The problem turns out to be a non-convex problem and time consuming via numerical exhaustive search methods. Instead, we solve the optimization problem for its lower bound. Maximization problem for the achieved lower bound is equivalent to maximize the main problem. Then, we use some approximations to convert it to a low complex problem to find the solution. We use the entity of the low complex problem to obtain the allocated power for each UAV and in the following, the problem becomes convex which is solved by KKT conditions to obtain the location of UAV-BS. The theoretical results show that optimizing the lower bound probability achieves the suboptimal solution for power assignment and placement problem, which is verified by simulation results.

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Section: Introductionmentioning

confidence: 99%

Placement and Power Assignment for Hierarchical UAV Networks under Hovering Fluctuations in mmWave Communications

Abdollahi

Azarhava

Niya

2023

Preprint

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Triboelectricity Based Self‐Powered Digital Displacement Sensor for Aircraft Flight Actuation

Zhou,

Xu,

Cao

et al. 2023

Adv Funct Materials

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The utilization of unmanned aerial vehicles (UAVs) is on the rise across various industries. In such a scenario, the issue of flight safety for these UAVs becomes increasingly paramount. Currently, UAVs exhibit shortcomings in flight attitude perception compared to more mature manned aircraft, especially concerning the position sensing of flight actuation, which poses significant safety risks. Mature position monitoring solutions for flight actuation used in manned aircraft cannot be directly integrated into systems of UAV due to compatibility issues. This necessitates the development of new position sensing technologies to address this challenge. Triboelectric nanogenerators, with their advantages of miniaturization, self‐powering capabilities, and the ability to generate voltage‐level electrical signals, are chosen to form a part of the position detection system for sensors in UAVs. In this study, a self‐powered displacement sensor is developed that utilizes frictional charge separation signals. This sensor is specifically designed to monitor the position status of the flight actuators in UAV. With a compact volume of <11.1 cm3 and a weight of <9.5 g, this sensor is lightweight efficient and adaptable for practical applications.

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Placement and Power Assignment for Hierarchical UAV Networks Under Hovering Fluctuations in mmWave Communications

Azarhava,

Abdollahi,

Musevi Niya

2024

Trans Emerging Tel Tech

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In this article, we investigate the successful transmission probability of an aerial cellular network in which an unmanned aerial vehicle (UAV), as a macrocell base station (UAV‐BS) serves other UAVs as aerial users. The antennas with beamforming capability are mounted on the UAVs, to increase the throughput of the network. The random effects of inner forces such as controlling errors or outer forces like the air conditions, result in the random fluctuations in the hovering UAVs. We assume Rician fading distribution over the links between the UAV‐BS and other UAVs. Then, we calculate the distribution of the corresponding channel gain under hovering fluctuations and we derive the closed form expressions for successful transmission probability for each user. Defining an optimization problem on the average successful transmission probability of the network, we obtain the best placement of UAV‐BS along with the resource allocation. The problem turns out to be a non‐convex problem and time consuming via numerical exhaustive search methods. We obtain a lower bound for the average successful transmission probability and we solve the optimization problem for this lower bound. Maximization problem for the achieved lower bound is equivalent to maximize the main problem. Using some approximations, we convert the problem to a low complex one, then, the problem becomes convex which is solved by KKT conditions and yields the location of UAV‐BS. The theoretical results reveal the influence of fluctuations on the throughput of the network and show that optimizing the lower bound probability achieves the suboptimal solution for power assignment and placement problem, which is verified by simulation results.

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Directional antennas modelling and coverage analysis for UAV networks with blockage effects in urban environment

Cited by 3 publications

References 20 publications

Placement and Power Assignment for Hierarchical UAV Networks under Hovering Fluctuations in mmWave Communications

Placement and Power Assignment for Hierarchical UAV Networks under Hovering Fluctuations in mmWave Communications

Triboelectricity Based Self‐Powered Digital Displacement Sensor for Aircraft Flight Actuation

Placement and Power Assignment for Hierarchical UAV Networks Under Hovering Fluctuations in mmWave Communications

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