Energy and Spectral Efficiency Analysis for Downlink Massive MIMO Systems

Abstract

Massive multiple-input multiple-output (MIMO) refers to the use of a huge number of antennas at the base station to transmit and receive signals that fully utilize spatial resources, improving wireless network energy efficiency and spectral efficiency. There are many radio frequency chain components corresponding to each antenna which results in higher power consumption in massive MIMO system. From these radio frequency chains components, digital-to-analog converters (DACs) are one of the most power consuming in downlink massive MIMO. The power consumption of DAC can be minimized by reducing its resolution. Massive MIMO systems combined with beamforming play an important role in 5G wireless communication systems. Digital beamforming having dedicated (Radio Frequency) RF chain for each antenna is complex and costly while hybrid beamforming with reduced number of RF chain is less complex and achieve better energy efficiency by lowering the power consumption. In this thesis low resolution DACs are used, considering threshold capacity to lower power consumption and enhance energy efficiency of the system. Modulation is also the other technique used to enhance the capacity and spectral efficiency of the system when DAC capacity is below the threshold. Low resolution DAC and Modulation techniques applied for hybrid and digital beamforming and their performances analyzed. The simulation results show that using low resolution DACs enhance energy efficiency compared to without DAC resolution. For hybrid beamforming, better energy efficiency is achieved compared to digital beamforming using low resolution DAC. Digital beamforming achieve better spectral efficiency through modulation compared to hybrid beamforming.The trade-off between energy and spectral efficiency is also analysed considering low resolution DAC.