Skip to Main Content
Two-dimensional (2D) and three-dimensional (3D) steady state Markov chains are widely used to analyze the traffic performance of communications networks. When the characteristics of the network changes with time, such steady state Markov chain is unable to determine different probability states. Markov Modulated Poisson Process (MMPP) is a special case of Markov Arrival Process (MAP) where arrival rate depends on probability states. In this paper, a traffic model of micro-macro cellular network of time dependent traffic load is modeled and its probability states are evaluated using MMPP varying load condition of the network under different parts of observation time.
Date of Conference: 21-23 Dec. 2009