ADDRESSING ENERGY EFFICIENCY CHALLENGES IN TELECOM NETWORKS WITH AI-OPTIMIZED BASE STATIONS

Аннотация

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% QoScompliance, demonstrating themodel's effectiveness infuture green telecom networks. Keywords: 5G, Energy Efficiency, Base Stations, AI Optimization, Reinforcement Learning, Green Telecom