Ahmed, MashrukhRabiul Alam, Md. Golam2026-08-192026-08-192023-01-01M. Ahmed and M. G. Rabiul Alam, "A Convolution Neural Network based QPSK and 16QAM Modulations Simulator for a Multiuser MIMO-OFDM Transmission Simulation over a Nakagami-m Fading Channel," 2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI), Dhaka, Bangladesh, 2023, pp. 1-6, doi: 10.1109/STI59863.2023.10465002.97983503942902-s2.0-85190287680https://hdl.handle.net/10361/29311Wireless communication has been a widespread method of data transfer in the modern era. Various modulation techniques have been found and among them 16QAM has proven to be the most efficient. This study provides a Convolutional Neural Network (CNN) approach for simulating 16QAM and QPSK modulation schemes over a multiuser MIMO-OFDM using the Keras library over Nakagami-m fading. It then examines the two modulation schemes to determine if QPSK might be a viable alternative to 16QAM. In this paper two analysis have been done, a realistic MIMO OFDM system simulation and weighted belief propagation decoding.6 pagesen-USfalse16QAMCNNKerasMIMONakagami-m fadingOFDMQPSKWireless communication systems.Computer communication systems.Conference Proceeding10.1109/STI59863.2023.10465002