Phase-Shifted DMRS-Aided Automatic Modulation Classification for PDSCH in 5G New Radio

In this letter, a novel automatic modulation classification (AMC) scheme is developed for physical downlink shared channel (PDSCH) in 5G New Radio (NR). We design a convolutional neural network (CNN) to classify modulation types of the received PDSCH. To improve the classification accuracy, an enhanced demodulation reference signal (DMRS) structure is proposed where the phase of the DMRS is shifted depending on the modulation types. Simulation results verify that the proposed AMC scheme achieves 31.5% gain compared to the legacy scheme in terms of classification accuracy.