Gaussian Mixture Model for Millimeter-Wave Cellular Communication Networks

As compared to the microwave communication networks, the theoretical analyses of system performances such as the cell coverage and the cell average data rate are more difficult due to the unique propagation path loss model for mmWave cellular communication networks. In this paper, based on the unique transmission states of the distance-dependent piecewise propagation probability functions, the analytical six-state analytical mixture distribution of the propagation loss including the distance-dependent path loss, shadowing and small-scale fading is obtained. For each state, a novel Kullback-Leibler divergence based Gaussian approximation method is proposed to model the distribution of the propagation loss. The distribution of the propagation loss including the large-scale fading and small-scale fading is approximated via a six-state Gaussian mixture model, then the closed-form expression for the signal-to-noise ratio can be easily obtained. The cell coverage is expressed as the weighted sum of the error functions, and the cell average data rate is expressed as the weighted sum of the moments of the propagation loss for the six different states. Numerical results show that the cell coverage mainly depends on the none line-of-sight transmission and the cell average data rate mainly depends on the line-of-sight transmission.