Emerging applications for public safety communications are further strengthened by integrating unmanned aerial vehicles (UAVs) into an existing terrestrial network infrastructure. UAV-based communications and networking can enhance wireless connectivity by integrating UAVs as aerial base stations and aerial user equipment into an existing 5G terrestrial heterogeneous network (HetNet). This chapter designs a public safety 3-tier aerial HetNet (Aerial-HetNet) composed of macrocells and picocells on the ground and small cells carried by UAVs. In particular, this chapter proposes an Aerial-HetNet with optimally placed UAVs for guaranteed quality-of-service. This proposed Aerial-HetNet also considers range expansion bias at small cells, various inter-cell interference coordination (ICIC) for interference mitigation, 3D beamforming for antennas, and 3D channel modeling for UAVs. Furthermore, the 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 when the unmanned aerial base stations (UABS) are deployed on fixed hexagonal locations using computer-based Matlab simulations. UABS locations are optimized using an elitist harmony search genetic algorithm (eHSGA) and genetic algorithm (GA). The simulation results show that the heuristic algorithms (eHSGA and GA) outperform the brute-force approach and achieved higher peak values of 5pSE and coverage probability. Furthermore, simulation results reveal that the Aerial-HetNet performance of the low-altitude UABSs at 25 m is sparsely better than medium-altitude UABSs (50 m and 36 m). Finally, a trade-off is encountered between achieving the peak Aerial-HetNet performance and the computation time, while applying different heuristic algorithms.
3D Unmanned Aerial Vehicle Placement for Public Safety Communications
Unmanned Syst. Tech.
Intelligent Unmanned Air Vehicles Communications for Public Safety Networks ; Chapter : 3 ; 51-89
2022-05-07
39 pages
Article/Chapter (Book)
Electronic Resource
English
Aerial base-stations , Brute force , Range expansion , Coverage , eICIC , FeICIC , Genetic algorithm , Harmonic search , Interference management , Location optimization , Public safety , Unmanned aerial vehicles Engineering , Communications Engineering, Networks , Mechanical Engineering , Artificial Intelligence