Performance Evaluation of Cognitive Radio Networks with Parallel Channels

The cognitive radio (CR) is a newly proposed wireless communication technology to improve the spectrum utilization. Through channel sensing and learning, cognitive radio systems exploit the unused spectrums and occupy it so that the network can allocate the spectrum dynamically and improve the utilization of available spectrum. There are a number of research focusing on the single-channel cognitive radio systems, however the CR system with parallel channels is an unexplored area because of its complexity. In this paper, we conduct performance evaluation of the CR system with parallel channels was conduct by using stochastic network calculus (SNC). The data arrival process for all primary/secondary users and the service process of parallel channels are characterized by Markov modulated deterministic processes (MMDP). Then we formulate the data arrival process and service process as arrival curve and service curve in the SNC theory. The closed form solutions of stochastic performance boundary of the delay and backlog are obtained using the delay bound theorem and backlog theorem in SNC theory. Finally, we make extensive simulations to evaluate the correctness of the proposed model, and conduct performance analysis of the CR system with parallel channels with various parameter settings. The results show that our proposed framework can effectively model and analyze the CR system with parallel channels.