Multiple drone-cell deployment analyses and optimization in drone assisted radio access networks

In this paper, we propose a drone assisted radio access networks architecture in which drone-cells are leveraged to relay data between base stations and users. Based on the state-of-the-art drone-to-user and drone-to-base station (D2B) channel models, we first analyze the user coverage and the D2B backhaul connection features of drone-cells. We then formulate the 3-D drone-cell deployment problem with the objective of maximizing the user coverage while maintaining D2B link qualities, for a given number of drone cells being deployed. To solve the problem, the particle swarm optimization (PSO) algorithm is leveraged for its low computational cost and unique features suiting the spatial deployment of drone-cells. We propose a per-drone iterated PSO (DI-PSO) algorithm that optimizes drone-cell deployments for different drone-cell numbers, and prevents the drawbacks of the pure PSO-based algorithm derived from related works. Simulations show that the DI-PSO algorithm can achieve higher coverage ratio with less complexity comparing to the pure PSO-based algorithm.