A SIC and ML approach for MIMO non-orthogonal multiple access signal detection

One of the top candidates for an enhanced radio architecture is Optical Non-Orthogonal Multiple Access (O-NOMA), which is based on Multiple inputs and Multiple Outputs (MIMO). The identification of signals at the receiver terminal is more difficult due to the employment of a lot of antennas. For the identification of signals in the 8 × 8, 16 × 16, 64 × 64 and 256 × 256 O-NOMA frameworks, we provide a Maximum Likelihood (ML) and Successive Interference cancellation (SIC) method in this paper. Additionally, the suggested algorithms are compared with traditional ML, SIC, Zero Forcing (ZF), and Minimum Mean Square Error (MMSE) approaches, and rigorous estimations are made of metrics like Bit Error Rate (BER) and Power Spectral Density (PSD). The outcomes of the simulation show that the suggested SIC and ML outperform the traditional methods. It should be added that the 64 × 64 O-NOMA effectively increased the structure’s throughput and spectral efficiency.