We focus on the problem of managing the energy consumption of a cellular network tailored to cover rural and low-income areas. The considered architecture exploits Unmanned Aerial Vehicles (UAVs) to ensure wireless coverage, as well as Solar Panels (SPs) and batteries installed in a set of ground sites, which provides the energy required to recharge the UAVs. We then target the maximization of the energy stored in the UAVs and in the ground sites, by ensuring the coverage of the territory through the scheduling of the UAV missions over space and time. After providing the problem formulation, we face its complexity by proposing a decomposition-based approach and by designing a brand-new genetic algorithm. The results, obtained over a set of representative case studies, reveal that there exists a trade-off between the UAVs battery level, the ground sites battery level, and the level of coverage. In addition, both the decomposed version and the genetic algorithm perform sufficiently close to the integrated model, with a strong improvement in the computation times.INDEX TERMS Energy management, mixed integer linear programming, renewable energy sources, Unmanned Aerial Vehicles, UAV mission scheduling, cellular networks.
The installation of base station (BS) sites is regulated by a variety of laws at international, national, and local levels. While international regulations are already severe, the national and local laws applied in many countries and regions follow precautionary principles and enforce electromagnetic field (EMF) constraints that are even more restrictive. This legal environment results in substantial constraints affecting the planning of cellular networks, as requests for new BS site installation are easily denied by national or local authorities. In this paper, we consider the problem of cellular planning under restrictive EMF limits from the user equipment (UE) viewpoint. We focus on outdoor urban areas and first evaluate the impact of the current, non-optimal network planning at the UE side through a quantitative measurement-driven analysis of the quality of service (QoS) observed by users in heterogeneous, large-scale urban scenarios. We then perform a qualitative assessment of the perceived QoS and generated EMF levels at one UE transferring data from/to a BS based on its position with respect to the serving BS. Finally, we run a what-if analysis by comparing the existing planning with the one where new BS sites can be installed, thanks to a relaxation of the restrictive EMF constraints. Our results clearly show that a cellular planning driven by restrictive EMF constraints forces UE to experience large distances from the serving BS, frequent non-lineof-sight conditions, and poor received signal. In turn, this entails a very negative combination of high electric field activity (EFA) levels generated by the UE and low QoS perceived by the user. We show that, by relaxing the restrictive EMF constraints, the problem could be sensibly mitigated with a positive impact on the UE channel conditions and consequently on the perceived QoS and the UE EFA. INDEX TERMS Cellular network planning, EMF limits, impact on QoS, user equipment measurements.
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