Intermodulation Interference Detection in 6G Networks: A Machine Learning Approach

Autor:	Mismar, Faris B.
Rok vydání:	2021
Předmět:	Computer Science - Networking and Internet Architecture
Druh dokumentu:	Working Paper
DOI:	10.1109/VTC2022-Spring54318.2022.9860900
Popis:	This paper demonstrates the use of machine learning to detect the presence of intermodulation interference across several wireless carriers. We show a salient characteristic of intermodulation interference and propose a machine learning based algorithm that detects the presence of intermodulation interference through the use of supervised learning. This algorithm can use the radio access network intelligent controller or the sixth generation of wireless communication (6G) edge node as a means of computation. Our proposed algorithm runs in linear time in the number of resource blocks, making it a suitable radio resource management application in 6G. Comment: 6 pages, 5 figures. Invited paper to IEEE 95th Vehicular Technology Conference Workshops (VTC2022-Spring), to appear
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2111.00524 Zobrazit plný text záznamu View this record from Arxiv