@inproceedings{5891f3dce5fb4d1b91227cf57b32f38e,
title = "Reinforcement Learning Based Interference Control Scheme in Heterogeneous Networks",
abstract = "Heterogeneous networks (HetNet) guarantee higher throughput and lower latency than traditional homogeneous network environments. In order to guarantee such performance, interference control between the macro base station (MBS) and the small cell base station (SBS) have to be effectively performed. However, the existing interference control scheme has limitations in controlling interference for rapidly increasing SBS and UEs. In order to solve this problem, we introduce interference control and handover scheme with reinforcement learning in HetNet. Each BS learns transmission power, activation pattern and bias values for optimal network performance in HetNet. We introduce HetNet technologies incorporating various reinforcement learning models and introduce research areas that will be conducted in the future.",
keywords = "component, formatting, insert, style, styling",
author = "Yunseong Lee and Laihyuk Park and Wonjong Noh and Sungrae Cho",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 34th International Conference on Information Networking, ICOIN 2020 ; Conference date: 07-01-2020 Through 10-01-2020",
year = "2020",
month = jan,
doi = "10.1109/ICOIN48656.2020.9016463",
language = "English",
series = "International Conference on Information Networking",
publisher = "IEEE Computer Society",
pages = "83--85",
booktitle = "34th International Conference on Information Networking, ICOIN 2020",
}