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The enormous increase in cellular users requires novel advancements in the existing cellular infrastructure. Therefore, small cell networks (SCNs) are a promising solution to meet the ever-growing demands of cellular users as they are beneficial in terms of coverage and providing higher data rates. However, one of the challenging parts is the deployment of small cell base stations (SBs) and their connectivity with the backhaul network. In this paper, we use the scalable idea of replacing the terrestrial backhaul network with an aerial network to provide fronthaul connectivity to SBs. In particular, we address the optimum placement of unmanned aerial vehicles (UAVs) to associate the SBs such that the sum-rate of the overall network is maximized. We achieve such an objective by proposing a two-layer framework, i.e., unsupervised learning and iterative algorithm (defined as UAV equalizer), and we call this twolayer framework as a hybrid approach. Simulation results show that the proposed hybrid approach outperforms the traditional approaches in terms of maximizing the sum-rate, minimum bandwidth consumption, moreover, maximizing link utilization and energy efficiency. CCS CONCEPTS • Networks → Unmanned aerial vehicles; Small cell networks.

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