Combining AI/ML and PHY Layer Rule Based Inference - Some First Results
Brenda Vilas Boas, Wolfgang Zirwas, Martin Haardt · 2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC) · 2022
In 3GPP New Radio (NR) Release 18 we see the first study item starting in May 2022, which will evaluate the potential of artificial intelligence and machine learning (AI/ML) methods for Radio Access Network (RAN) 1, i.e., for mobile radio PHY and MAC layer applications. We use the profiling method for an accurate iterative estimation of the parameters of the dominant multipath components, as it promises a large channel prediction horizon. We investigate options to partly or fully replace some functionalities of rule based PHY layer algorithms by AI/ML inferences, with the goal to achieve either a higher performance, lower latency, or reduced processing complexity. We provide first results for noise reduction, then a combined scheme for model order selection, compare options to infer multipath component start parameters, and provide an outlook on a possible channel prediction framework.