Green Communication Techniques for AI-Enhanced Resource Allocation in Future 6G Network

This paper presents how integrating AI-driven algorithms for energy-efficient resource allocation in 6G networks can be one solution to meet the ever-growing demand for high-performance and sustainable wireless systems, focusing on green communication strategies. This proposed framework makes sure that the minimum energy consumption and maximum resource utilization through state-of-the-art machine learning techniques. It builds a mathematical model that suits the demands of the 6G network and involves tradeoffs between power efficiency, latency, and throughput. The different network situations include changes in traffic loads and environmental factors, which are modeled through MATLAB simulations to validate this approach. The results show very significant gains in energy efficiency, with up to 30% power use compared to traditional techniques at the same or even improved quality of communication. Several key findings show that AI can enable green communication without deteriorating system performance or user experience. This research also provides valuable recommendations for network operators and regulators on achieving carbon neutrality in the telecommunications industry and contributes to developing sustainable 6G technology.