AI-Based Wireless Communication Systems Enabling Innovative Smart Systems Design
Abstract
This chapter explores how Artificial Intelligence (AI) will support the future of wireless communication systems through advances in 6G networks, IoT ecosystems, and edge computing technologies. Technologies that enhance machine learning (ML), deep learning (DL), and reinforcement learning (RL) algorithms to improve network functions, including resource allocation, spectrum assignment, and traffic distribution. This chapter demonstrates that ML models improve latency and energy efficiency in low-density networks. It presents RL as substantially better at handling dynamic, high-traffic situations, achieving up to 30% latency reduction and a 25% improvement in spectral efficiency compared with standard network optimization methods. With a projected 120% increase in AI technology adoption from 2023 to 2035, AI-embedded wireless systems demonstrate enhanced operational efficiency in digital security, smart cities, healthcare, transportation, and industrial automation, but also pose potential negative impacts on energy consumption and security, as well as on future adoption.
