ADAPTIVELINK: SMART ARCHITECTURES FOR FUTURE WIRELESS COMMUNICATION

Abstract

The rapid evolution of wireless communication technologies has introduced complex network architectures with diverse quality-of-service requirements and highly dynamic operating environments. Traditional communication frameworks struggle to efficiently manage spectrum, interference, and resource allocation in next-generation wireless networks. This paper presents an intelligent adaptive communication architecture that leverages artificial intelligence to enhance network performance and adaptability. Machine learning and optimization techniques are integrated to enable real-time decision-making for spectrum management, modulation selection, and power control. The proposed architecture dynamically adapts to varying traffic loads and channel conditions, ensuring reliable and efficient communication. Simulation-based evaluation demonstrates improvements in throughput, latency, and energy efficiency compared to conventional static architectures. The results highlight the potential of AI-driven adaptive communication systems for future wireless networks, including 5G and beyond