The need for high data rates has been one of the driving factors for the evolution of the wireless systems from Single Input Single Output (SISO) systems to Multiple Input Multiple Output (MIMO) systems. For MIMO systems, the channel is in the form of a matrix; hence the characterization of random matrices plays an indispensable role in studying MIMO channel metrics. Recently, there has been a focus on generalized fading models, namely κ - μ and η - μ, which model the small scale variations in the line of sight and non-line of sight conditions, respectively. These generalized fading distributions include the well-studied Rayleigh, Rician, Nakagami, one-sided Gaussian distributions as special cases. However, given the complicated pdf structure of these generalized fading distributions, it is challenging to develop the matrix distribution for these fading channels. Hence, in this talk, we focus on developing an approximate matrix model for these fading channels in terms of the Wishart distribution, through minimizing the Kullback-Leibler (KL) divergence. We also demonstrate the utility of the results by determining the ergodic rate expressions for a zero-forcing (ZF) receiver in a massive MIMO scenario with low-resolution analog-to-digital converters (ADCs) in the antennas.