Delay performance analysis and access strategy design for a multichannel cognitive radio network

Abstract

For a hierarchical cognitive radio network (CRN), the secondary users (SUs) may access the licensed spectrum opportunistically, whenever it is not occupied by the primary users (PUs). An important issue for this kind of CRN is the achievable qualityof-service (QoS) performance, such as traffic transmission delay, which is critical to the SUs' traffic experience. In this paper, we focus on the delay performance analysis of the SU system and the design of the corresponding optimal access strategy for the case of SUs sharing multiple licensed channels. In our analysis, the transmission of PU and SU traffic is modeled as M/G/1 queues. By merging the PU and SU traffic, we propose the model of a priority virtual queue on the licensed channels. Based on this model, we obtain the expected system delay expression for SU traffic through M/G/1 preemptive repeat priority queuing analysis. For the case of multiple licensed channel access, the access strategy is further investigated with respect to the expected system delay for SU traffic. By minimizing the expected transmission delay, the optimal access strategy is modeled as a nonlinear programming problem, which can be resolved by means of the classic Genetic Algorithm (GA). Numerical results validate our analysis and design of an optimal access strategy. Meanwhile, by considering the time taken by the GA approach, we can also adopt the inverse proportional access strategy to obtain near-optimal results in practice.cognitive radio network, preemptive repeat priority queuing, nonlinear programming, optimal access strategy Citation:Li X, Wang J, Li H S, et al. Delay performance analysis and access strategy design for a multichannel cognitive radio network.

In the development of wireless cognitive science

“…Furthermore, a novel concept of resource flow has been introduced for an intelligent and autonomous cognitive resource management under various types of resource [4]. Besides, other key technologies and applications have also been discussed in this special topic, such as the cognitive engine design [5], delay performance analysis [6], reconfiguration decision making [7], bio-inspired approaches and applications [8] and energy-efficient spectrum-aware clustering for cognitive radio sensor networks [9]. Therefore, this special topic will provide a comprehensive introduction to cognitive wireless network theory and technology, reduce the gap between science and engineering communities and promote innovations for future wireless network evolution.…”