On cognitive processes in cognitive radio networks

Abstract

In this article we model the cognitive processes and evaluate their impact on the performance of cognitive radio networks (CRN). Operation of the cognitive radio nodes, can be characterized by two types of processes: communication processes such as packets transmission, and cognitive processes such as estimation of the network state and decision-making for dynamic resource allocation. We propose a continuous time Markov chain model of CRN that couples these processes into unified queueing framework and analyze it by means of the matrix-geometric approach. From the obtained results, we derive the performance measures of CRN such as average delay and throughput, and establish their dependencies on the underlying cognitive processes. Additionally, we design an efficient policy for accessing the vacant channels and managing the transmission-sensing trade-off, which arises when transmissions and sensing are mutually exclusive. The policy search is carried out by the stochastic optimization method of cross-entropy. The optimized policy leads to significantly enhanced performance of CRN.