Finite-state Markov Model for Lognormal, Chi-square (Central), Chi-square (Non-central), and K-distributions

This paper formulates a finite-state Markov channel model to represent received signal-to-noise (SNR) ratios having lognormal, K-distribution, chi-square (central) and chi-square (non-central) distributions in a slow fading channel. The range of the SNRs is partitioned into a finite number of states following earlier works in literature. Performance measures like level crossing rates, steadystate probabilities, transition probabilities, and state-time durations are derived, and numerical results are plotted and discussed for the FSMC models for all the distributions.