학술논문
Deep Learning-based Multi-Connectivity Optimization in Cellular Networks
Document Type
Conference
Source
2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring) Vehicular Technology Conference (VTC2022-Spring), 2022 IEEE 95th. :1-5 Jun, 2022
Subject
Language
ISSN
2577-2465
Abstract
Multi-connectivity emerges as a useful feature to handle the traffic in heterogeneous cellular scenarios and fulfill the demanding requirements in terms of data rate and reliability. It allows a device to be simultaneously connected to multiple cells belonging to different radio access network nodes from a single or multiple radio access technologies. This paper addresses the problem of optimally splitting the traffic among cells when multi-connectivity is used. For this purpose, it proposes the use of deep learning to determine the optimum amount of traffic of a device that needs to be sent through one or another cell depending on the current traffic and radio conditions. Obtained results reveal a promising capability of the proposed Deep Q Network solution to select quasi optimum traffic splits in the considered scenario.