Exploring Hybrid Beamforming Techniques in 5G Massive MIMO Networks

A significant event in the evolution of wireless communication technology is the introduction of the fifth generation (5G) network. Massive MIMO (Multiple Input Multiple Output) technology makes use of numerous antennas at the base station to enable simultaneous connection with numerous users. It is very essential for 5G and beyond systems to meet the increased demand, with the potential to significantly outperform conventional MIMO systems in terms of spectral efficiency. Due to the complexity of the channel estimation several algorithms are proposed by the researchers. This work provides the comparative analysis of ANM (Atomic norm minimization), NOMP (Newtonized Orthogonal Matching Pursuit), and ML (Maximum likelihood) algorithms. The simulation results are verified in Xilinx 14.5 and MATLAB, bit error rate (BER) and mean squared (MSE) are analyzed.