3-D Placement of UAVs Based on SIR-Measured PSO Algorithm

2019 IEEE Globecom Workshops (GC Wkshps)(2019)

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Abstract
This work studies the deployment of unmanned aerial vehicles (UAVs) as emergency access points to provide wireless services to users in a green field. Specifically, three fundamental design issues are explored under practical 3D air-to-ground (ATG) channel models, namely the minimum number of UAVs, their optimal deployment locations and the optimal transmit power allocation. To decouple these design goals, a particle swarm optimization (PSO)-based scheme in conjunction with the balanced Signal to Interference plus Noise Ratio (SINR) transmit power allocation is proposed. Exploiting the closed-form expressions of the SINR-balanced optimal power allocation and the resulting SINR, the proposed PSO-based scheme optimizes the UAV location generation by generation. Furthermore, a K-means clustering-based initialization scheme is developed to improve the performance of the proposed PSO-based scheme. Finally, a power fine-tuning scheme is devised to further reduce the total transmit power. Extensive simulation is performed to confirm the good performance of the proposed scheme.
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Key words
noise ratio transmit power allocation,power fine-tuning scheme,initialization scheme,UAV location generation,PSO-based scheme,SINR-balanced optimal power allocation,closed-form expressions,balanced Signal,particle swarm optimization-based scheme,optimal transmit power allocation,optimal deployment locations,channel models,3D air-to-ground,green field,wireless services,emergency access points,unmanned aerial vehicles,SIR-measured PSO algorithm,UAV
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