Heterogeneous Wireless Network

Heterogeneous wireless networks (HetNets), comprising diverse technologies and devices, aim to optimize resource allocation and enhance overall network performance. Current research heavily focuses on leveraging artificial intelligence, particularly machine learning techniques like federated learning and reinforcement learning, along with graph neural networks, to address challenges in resource management (e.g., channel and power allocation) and distributed model training. These advancements are crucial for improving energy efficiency, reducing latency, and ensuring robust operation in increasingly complex and data-intensive 6G networks, impacting both theoretical understanding and practical deployment of next-generation wireless systems.