Titlebook: Intelligent Unmanned Air Vehicles Communications for Public Safety Networks; Zeeshan Kaleem,Ishtiaq Ahmad,Trung Quang Duong Book 2022 The

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Intelligent Unmanned Air Vehicles Communications for Public Safety Networks

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UAV Placement and Resource Management in Public Safety Networks: An Overview, the UAVs. This chapter has focused the details on the UAV-supported public safety networks and state of the artwork related to UAV placement, resource allocation, and UAV-related security concerns in PSN.

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3D Unmanned Aerial Vehicle Placement for Public Safety Communications,he performance of designed Aerial-HetNet with optimally placed UAVs is evaluated in the coverage probability and fifth-percentile spectral efficiency (5pSE), using various heuristics algorithms and a brute-force. The Aerial-HetNet’s system-wide coverage probability and 5pSE are computed and compared

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Location Prediction and Trajectory Optimization in Multi-UAV Application Missions,h avoidance of obstacles or sudden landing) within application missions. In this chapter, we explain a diverse set of techniques involved in drone location prediction, position and velocity estimation and trajectory optimization involving: (i) Kalman Filtering techniques, and (ii) Machine Learning m

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,UAV Trajectory Optimization and Choice for UAV Placement for Data Collection in Beyond 5G Networks,hich will ultimately reduce the overall AoI. We use three different kinds of trajectories namely, ., .-based trajectory, and .. Simulations show that the proposed trajectory outperforms in the scenario, where disaster-points are less. Additionally, unsupervised learning-based UAVs distribution helps

IRS

Enhancing UAV-Based Public Safety Networks with Reconfigurable Intelligent Surfaces,onment in order to operate securely, at extended ranges, and with reduced communication and energy costs. Consequently, the integration of RIS with UAV networks is advocated as a key enabler for critical public safety services, where highly resilient, reliable, secure, and low latency communications

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UAVs Path Planning by Particle Swarm Optimization Based on Visual-SLAM Algorithm,l path. Moreover, the dynamic fitness function (DFF) is developed to evaluate path planning performance while considering various optimization parameters such as flight risk estimation, energy consumption, and operation completion time. This system achieves high fitness value and safely arrives at t