RF Chain Selection Using Hybrid Optimization with Precoding in mm-Wave Massive MIMO Systems

Energy efficiency is considered the prominent metric in data communication systems and has a greater impact on designing Millimetre-wave (mm-wave) multiple input multiple output (MIMO) systems. As the recent mm-wave system relies upon the number of radiofrequency (RF) chains, effective RF chains are preferred to maximize overall system performance, energy and spectral efficiency. Degraded system efficiency and increased path loss are the major limitations faced in MIMO systems. This harms the data rate transmission between transmitter and receiver antennas. Hence, an effectual mm-wave with a massive MIMO model is presented in this research by adopting standard techniques. The chief objective of this research is to maximize energy and spectral efficiency with an appropriate selection of RF chains. The optimal RF chains are selected through a hybrid optimization model called the differential evolution firefly selection model (DEA + FOA). After selecting optimal RF chains, an appropriate precoding scheme is used to route the transmitted data over the preferred direction by overcoming the path-loss issues. In the precoding step, the successive interference cancellation based technique is employed to optimize the RF chain's sub-capacity and increase the system efficiency. The performance of a proposed model is analyzed by evaluating the energy and spectral efficiency by varying the number of RF chains at low and high signal-to-noise ratio rates. The proposed optimization and precoding techniques are compared with existing approaches to analyze the efficacy of a proposed MIMO system. The proposed model has proven extremely effective in transforming data from transmitter to receiver with increased system efficiency.