Applications of Deep Learning and Deep Reinforcement Learning in 6G Networks
An overview of the applications and advancements of DL and DRL in 6G networks is provided and the latest research is discussed to identify areas for further exploration in this field.
Abstract
As the demand for data-driven applications and emerging technologies such as extended reality, autonomous vehicles, and the Internet of Things (IoT) continues to grow, the development of a next-generation wireless communication system, 6G, becomes necessary. To fulfill the stringent requirements of 6G networks, new enabling technologies are necessary. Deep learning (DL) and deep reinforcement learning (DRL) are two promising technologies that have gained significant attention in recent years. In this paper, we provide an overview of the applications and advancements of DL and DRL in 6G networks. We discuss the latest research and identify areas for further exploration in this field.