An optimized general target channel sequence for prioritized cognitive radio networks

Abstract

Cognitive radio networks serve different secondary user applications which have distinct delay requirements. In order to better support the delay-sensitive applications, we consider secondary user traffic to be classified into M prioritized classes based on delay requirements. The priority of a secondary user increases within the same class after each interruption to reduce the cumulative handoff delay. A mixed preemptive/non-preemptive resume priority M/G/1 queueing model is assumed to analyze multiple spectrum handoffs. Closed form expressions are derived for both the extended data delivery time and dropping probability for each secondary user class. The analysis assumes a general target channel sequence, where a secondary user can select either to stay at his current channel or change it after each interruption. This general target channel sequence is optimized using a genetic algorithm in order to minimize the average extended data delivery time of all secondary user classes. Numerical results show that the proposed interruption-based priority mechanism outperforms the existing priority mechanisms in terms of average handoff delay and extended data delivery time in case of changing the target channel while preserves the extended data delivery time in case of always stay. Moreover, the optimized general target channel sequence gives better performance compared to the target channel sequences mentioned in the IEEE 802.22 wireless regional area networks standard for different network cases.