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

This letter demonstrates the use of machine learning to detect the presence of intermodulation interference across several wireless carriers. We propose an algorithm that detects the presence of intermodulation interference through the use of linear regression as a supervised machine learning technique. 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 real-time radio resource management application in 6G.