Estimating the medium access probability in large cognitive radio networks

Abstract

During the last decade we have seen an explosive development of wireless technologies. Consequently the demand for electromagnetic spectrum has been growing dramatically resulting in the spectrum scarcity problem. In spite of this, spectrum utilization measurements have shown that licensed bands are vastly underutilized while unlicensed bands are too crowded. In this context, Cognitive Radio Network emerges as an auspicious paradigm in order to solve those problems. The main question that motivates this work is: what are the possibilities offered by cognitive radio to improve the effectiveness of spectrum utilization? With this in mind, we propose a methodology, based on configuration models for random graphs, to estimate the medium access probability of secondary users. We perform simulations to illustrate the accuracy of our results and we also make a performance comparison between our estimation and one obtained by a stochastic geometry approach.