JISE

Fifth-generation (5G) and beyond fifth-generation (B5G) wireless communication systems use advanced radio technologies like massive multiple-input multiple-output (M-MIMO) and non-orthogonal multiple access (NOMA) to speed up data transfer and reduce latency. Three different M-MIMO setups, namely 64x64, 128x128, and 256x256, have used hybrid algorithms in the presence of a tapped delay line type C (TDL-C) fading channel model. The authors specifically developed this model to accurately represent both line-of-sight (LOS) and non-line-of-sight (N-LOS) channels across the entire frequency range from 0.5 to 100 gigahertz (GHz). An orthonormal matrix (Q) and an upper triangular matrix (R) are used in these hybrid algorithms. Simulations include QR decomposition with M-algorithm maximum likelihood detection (QRM-MLD), QR decomposition with minimum mean square error (QR-MMSE), QR decomposition with beamforming (QR-BF), and QR decomposition with zero forcing (QR-ZF). The channel becomes time-selective due to node mobility, and the fading channel coefficient follows a Nakagami-m distribution. The research shows that a conventional MMSE multiuser detection approach is ineffective in time-selective fading settings. However, when it comes to bit error rate (BER) and average sum rate, successive interference cancellation (SIC) minimum mean square error (MMSE) multiuser detections surpass other traditional systems. The QRM-MLD MMSE technique decreases the computational cost in comparison to traditional systems. The hybrid algorithms achieve a nearly 3 dB increase in signal-to-noise ratio (SNR) at BER while still maintaining minimal complexity. The QR-MLD algorithm greatly improves the increase in sum rate and achieves the maximum level of performance. The simulation findings closely correspond to the analytical results.