Investigation and mitigation of Spatially Correlated Fading in Massive MIMO

Abstract

Massive MIMO (Multiple Input Multiple Output) systems, characterized by the use of a large number of antennas at the base station, offer significant improvements in capacity and spectral efficiency. However, the benefits of massive MIMO can be hindered by spatial correlation fad- ing. Spatial correlation fading refers to the phenomenon where the fading characteristics of multiple antenna channels in a MIMO system are correlated. This correlation arises due to insufficient spatial separation between antennas, limited scattering environments, or specific propagation conditions. In order to mitigate these issues, this thesis explores channel estimator for accurate estimation of the fading channel to improve spectrum efficiency of massive MIMO. The study begin with provides statistical properties for the minimum mean squared error (MMSE), element-wise (EW-MMSE), and least-squares (LS) channel estimations in this model. Additionally, analyze rigorous closed-form uplink (UL) and downlink (DL) spectral efficiency (SE) expressions. Comprehensive simulations on MATLAB and an analysis comparing the LS, MMSE and EW-MMSE under different precoder in order to estimate accurate channel state information, the MMSE demonstrate its better performance. The simulation results show that the SE is higher with different values of SNR, NMSE, coherence block length, number of BS antennas and number of Ues when using MMSE channel estimator and lower when using LS channel estimator.