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RadioModRec-1 is a simulated dataset for Automatic Modulation Recognition (AMR) comprising fifteen digital modulation schemes, including 4QAM, 16QAM, 64QAM, 256QAM, 8PSK, 16PSK, 32PSK, 64PSK, 128PSK, 256PSK, CPFSK, DBPSK, DQPSK, GFSK and GMSK, which are widely used in modern wireless communication systems. The dataset supports Rayleigh and Rician channel models and additive white Gaussian noise (AWGN) conditions ranging from –20 dB to +20 dB in 5 dB steps. It was curated by Emmanuel Adetiba and Jamiu R. Olasina, with partial funding from Google’s TensorFlow Outreaches in Colleges program.
