ADDRESSING ENERGY EFFICIENCY CHALLENGES IN TELECOM NETWORKS WITH AI-OPTIMIZED BASE STATIONS
DOI:
https://doi.org/10.55640/Keywords:
5G, Energy Efficiency, Base Stations, AI Optimization, Reinforcement Learning, Green TelecomAbstract
The increasing energy consumption of telecom infrastructure, particularly 5G base stations, poses significant sustainability and cost challenges. This paper proposes an AI-driven optimization framework to reduce energy usage in base stations without degrading network performance. By integrating deep reinforcement learning (DRL) with real-time traffic analysis, the system dynamically manages transceiver states, beamforming patterns, and power levels. Simulation results show a 38% improvement in energy efficiency while maintaining over 95% QoS compliance, demonstrating the model's effectiveness in future green telecom networks.
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