UCINet0: A Machine Learning based Receiver for 5G NR PUCCH Format 0

arXiv:2404.15243v1 Announce Type: cross
Abstract: Accurate decoding of Uplink Control Information (UCI) on the Physical Uplink Control Channel (PUCCH) is essential for enabling 5G wireless links. This paper explores an AI/ML-based receiver design for PUCCH Format 0. Format 0 signaling encodes the UCI content within the phase of a known base waveform and even supports multiplexing of up to 12 users within the same time-frequency resources. Our first-of-a-kind neural network classifier, which we term UCINet0, is capable of predicting when …

abstract arxiv control cs.ai cs.lg cs.ni decoding design eess.sp enabling format information machine machine learning paper type wireless