Modeling and Performance Analysis of Cognitive Radio Networks Using Stochastic Timed Colored Petri Nets

Cognitive radio (CR) is currently one of the most promising information transmission technologies to deal with the problem of spectrum scarcity and spectrum underutilization in wireless communications. CR networks aim to enhance spectrum efficiency to meet the ever-increasing demands of end users. The principle is to provide the opportunity for unlicensed users (secondary users, SUs) to temporarily and dynamically access the unused or sparsely used bandwidth while ensuring that it never interferes or degrades the performance of the incumbent license holders, commonly called primary users (PUs). This raises several challenges to be addressed in CR networks and performance of secondary users is one of the critical issues tackled in this paper. That is, we propose to devise CR networks as a retrial queueing system where PUs have preemptive priority over SUs. To calculate performance measures of the devised model under quite general assumptions about the model parameters, analytical methods are known to require hard calculations and the obtained results are generally not exploitable. For this reason, simulation modeling becomes the last resort to assess the dependability indicators. To this extend, we build the simulation model of the queueing system using Timed Stochastic Colored Petri Nets. Various useful results will be hence drawn while varying network conditions. Both exponential and Erlang distributions are considered for modeling service time of SUs. The obtained results with restrictive assumptions fit the analytical outcomes experienced for quite similar queuing models, which demonstrate the effectiveness of the proposed STCPN simulation model.

     

A stochastic model to study the impact of the transmission frequency of hello messages on the connectivity of ad hoc networks

In this paper, we exploit the utility of Hello messages in the Ad hoc networks to study the impact of their transmission frequencies on the connectivity of the network. Assuming that the Hello messages arrive at a given node according to a Poisson process, we model a cluster-head motion (respectively an ordinary node motion) using a random process. This model allows us to find the critical value of the transmission frequency of Hello messages. We also have investigate a fundamental property of an Ad hoc network: its connectivity. We then analyze the number of neighbors of a given node, the isolation probability, the handoff probability and the probability that the considered network is connected, i.e. each node can communicate with an other node via the network.