| Title |
A Study on Multi-spectrum Channel Access Technology using Reinforcement Learning |
| Authors |
박종인(Jong In Park) ; 김건우(Gon Woo Kim) ; 김지수(Ji Su Kim) ; 최계원(Kae Won Choi) |
| DOI |
https://doi.org/10.5573/ieie.2022.59.1.87 |
| Keywords |
Reinforcement Learning; 802.11ax; Multispectral Channels; Media Access Control; CSMA/CA |
| Abstract |
In the 802.11 wireless communication environment, a CSMA/CA channel access technology is used to avoid collisions with other users. In the CSMA/CA method, loss of channel resources occurs in the process of avoiding collision, and in situations where users are concentrated and there are many, this loss becomes greater. However, since the available channel spectrum is fixed, it is important to reduce losses in limited channel resources. Therefore, this paper presents a channel approach technology using reinforcement learning to reduce the loss of channel resources generated to avoid collision in the existing channel approach. In addition, compared to the existing channel access technology, a direction in which performance can be checked and stable channel operation and limited channel resources can be efficiently used is proposed. |