Cross-Layer Optimization on Access Delay in Channel-Hopping Based Cognitive Radio Networks

摘要

In this paper, we propose an optimization approach on access delay by jointly modeling imperfect spectrum sensing and multi-channel multi-secondary user (SU) access contention, from a cross-layer perspective, for channel-hopping (CH) based cognitive radio networks (CRNs). Specifically, we first employ an absorbing Markov chain to model the multi-SU access contention process by combining the impacts of spectrum sensing and rendezvous; furthermore, we propose a methodology to derive the enclosed expression of rendezvous probability by analyzing the regularity and the periodicity of a CH rendezvous algorithm. We further analyze the access delay model and compute the optimal parameter combination (e.g., sensing duration and access contention duration) to build a communication link within minimum time duration Theoretical analysis and simulation results validate the proposed optimization approach and show that the optimization of cross-layer parameters can significantly decrease SUs' access delay. Moreover, the impact of the numbers of SUs and channels is also analyzed to study the relationship between CRN size and SUs' minimum access delay.