Drone-Enabled Load Management for Solar Small Cell Networks in Next-Gen Communications Optimization for Solar Small Cells
Daksh Dave, Dhruv Khut, Sahil Nawale, Pushkar Aggrawal, Disha Rastogi, Kailas Devadkar
TL;DR
The paper addresses energy constraints in next-generation cellular networks by enabling load management through drone-carried airborne base stations that redistribute energy across solar-powered small cell base stations within a green micro-grid. It proposes a drone-based energy redistribution algorithm that minimizes drone movement while optimizing energy transfer, supported by the Solar-Weighted Charging Algorithm (SWCA) and the Energy Buffer Algorithm (EBA) and formalized through a transfer model using $L(i,j)$ and a cost metric $Cost(i,j,h)$ on a BS graph. Key contributions include real-world testing in campus environments, substantial reductions in BS power outages (up to ~90%), and insights on cost, adaptability, and latency relative to static solar/storage alternatives. This work advances resilient, energy-efficient expansion of solar-powered small cells for NGN deployments by leveraging energy-aware drone mobility and backhaul decisions.
Abstract
In recent years, the cellular industry has witnessed a major evolution in communication technologies. It is evident that the Next Generation of cellular networks(NGN) will play a pivotal role in the acceptance of emerging IoT applications supporting high data rates, better Quality of Service(QoS), and reduced latency. However, the deployment of NGN will introduce a power overhead on the communication infrastructure. Addressing the critical energy constraints in 5G and beyond, this study introduces an innovative load transfer method using drone-carried airborne base stations (BSs) for stable and secure power reallocation within a green micro-grid network. This method effectively manages energy deficit by transferring aerial BSs from high to low-energy cells, depending on user density and the availability of aerial BSs, optimizing power distribution in advanced cellular networks. The complexity of the proposed system is significantly lower as compared to existing power cable transmission systems currently employed in powering the BSs. Furthermore, our proposed algorithm has been shown to reduce BS power outages while requiring a minimum number of drone exchanges. We have conducted a thorough review on real-world dataset to prove the efficacy of our proposed approach to support BS during high load demand times