Aggregated Renewal Markov Processes With Applications in Simulating Mobile Broadcast Systems

Abstract

For purposes of simulating contemporary communication systems, it is, in many cases, useful to apply error models for specific levels of abstraction. Such models should approximate the packet error behavior of a given system at a specific protocol layer, thus incorporating the possible detrimental effects of lower protocol layers. Packet error models can efficiently be realized using finite-state models; for example, there exists a wide range of studies on using Markov models to simulate communication channels. In this paper, we consider aggregated Markov processes, which are a subclass of hidden Markov models (HMMs). Artificial limitations are set on the state transition probabilities of the models to find efficient methods of parameter estimation. We apply these models to the simulation of the performance of digital video broadcasting-handheld (DVB-H). The parameters of the packet error models are approximated as functions of the time-variant received signal strength and speed of a mobile vehicular DVB-H receiver, and it is shown that useful results may be achieved with the described packet error models, particularly when simulating mobile reception in field conditions.