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This paper demonstrates the use of machine learning to detect the presence ofintermodulation interference across several wireless carriers. We show asalient characteristic of intermodulation interference and propose a machinelearning based algorithm that detects the presence of intermodulationinterference through the use of supervised learning. This algorithm can use theradio access network intelligent controller or the sixth generation of wirelesscommunication (6G) edge node as a means of computation. Our proposed algorithmruns in linear time in the number of resource blocks, making it a suitableradio resource management application in 6G.

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