A Reduced Complexity Hybrid Precoding for mmWave Systems

Abstract

The emergence of millimeter wave (mmWave) communication signals leads a new era in wireless technology. High-bandwidth communication channels are available in the mmWave spectrum compared to the current commercial wireless systems. Wireless local and personal area networks in the unlicensed band, 5G cellular systems, as well as vehicle area networks, ad hoc networks, and wearables are just a few of the many uses for mmWave technology. The next generation of mmWave communication relies heavily on signal processing. Combined with radio frequency and mixed signal power limits, new multiple-input multiple-output (MIMO) communication signal processing techniques are necessary. Low-complexity transceiver techniques are required because of the large bandwidths. Compressed sensing techniques can be used for channel estimation and beamforming in the future. Channel matrix in mmWave MIMO systems has significant importance on the hybrid precoding systems. Most precoding techniques are working on processing the MIMO channel to find the optimum beamforming vectors. This article provides a significant study on reducing the MIMO channel complexity in order to find the optimum beamforming elements. The study shows that the spectral efficiency of the system can be slightly sacrificed to reduce the complexity of the system based on the MIMO channel matrix low rank decomposition. We show the derivation and simulation of the proposed system through MATLAB software after the mathematical modelling and verification of the system.