Коригування параметрів фізичного рівня мобільних мереж

Abstract

Intelligent technologies for adjusting the physical layer of mobile networks, which are used to optimize and improve the operation of wireless communication systems, are investigated. Such technologies allow to improve the efficiency of data transmission, increase throughput and reduce transmission errors. In particular, we consider the structure of the end-to-end physical layer based on reinforcement learning, which studies how an agent should make decisions in a certain environment to maximize some reward or expected benefit. In the context of the physical layer of a network, reinforcement learning can be used to optimize the behavior of an agent that affects data transmission and control of channel parameters.