Deep-Reinforcement Learning Multiple Access for Heterogeneous Wireless Networks
Deep-Reinforcement Learning Multiple Access for Heterogeneous Wireless Networks
This paper investigates a deep reinforcement learning (DRL)-based MAC protocol for heterogeneous wireless networking, referred to as a Deep-reinforcement Learning Multiple Access (DLMA). Specifically, we consider the scenario of a number of networks operating different MAC protocols trying to access the time slots of a common wireless medium. A key …