Developing A New Scheduling Algorithm for Wi-Fi 6 Technology Based on Machine Learning

Authors : İbrahim MASRİ, Erdal ERDAL

Pages : 322-337

Doi:10.29137/umagd.1075903

View : 12 | Download : 7

Publication Date : 2022-01-31

Article Type : Research Paper

Abstract :Wireless mobile communications have experienced tremendous growth in the number of users, data rate requirements, and coverage in recent years. As the data rate and system throughput requirements increase, researchers and system designers need to develop efficient methods to meet these requirements with reasonable effort and cost. In this paper, we discuss an efficient approach to deal with diminishing the overhead of Downlink insert ignore into journalissuearticles values(DL); and feedback using Machine Learning insert ignore into journalissuearticles values(ML); for 802.11ax. In particular, the antennas that are related to the router were divided into two gatherings. We used good samples of Channel State Information insert ignore into journalissuearticles values(CSI); that were taken from an open-access dataset and used it to train our linear regression model. The first group of antennas was used as input to our model and the second group was used as the output of the model. In the online mode, we need to estimate only one group of antennas and for the second group, we can predict it using the trained linear regression model by using the estimated CSI group as input to the model. Therefore, the output of the model using as the CSI for the second group. In this way, we can reduce the overhead of the DL in the router as shown in the result table so the router will work more efficiently compared to the existing systems. From the results table in the last section, the average sum rate has increased between 20% and 30%.
Keywords : 802 11ax Standard, Wireless Network, Wi Fi 6, Leaner Regression, Machine Leaning, Scheduling Algorithm