Queueing Analysis of Performance Measures Under a New Configurable Channel Allocation in Cognitive Radio

Abstract

To help achieve optimal channel allocation for a cognitive radio network with multiple channels and multiple users, the authors propose a queueing analytical framework for implementing a configurable channel allocation method. Various allocation scenarios can be captured by the allocation method under different parameters. The influence of the parameters under different environmental parameters and system settings on the performance measures is investigated by the proposed framework. System settings such as imperfect spectrum sensing, adaptive modulation and coding scheme, automatic repeat and request, various primary user activity patterns, and finite secondary user buffer size are considered to make the proposed model practical. The procedures to derive performance measures, such as average queue length, packet loss rate, throughput, and average packet delay, are presented. Numerical results that reveal the relationship between various performance measures and the channel allocation method parameters under different channel conditions and secondary user system settings are shown. The allocation method and the analytical framework would be useful to help achieve optimal performance and evaluate different allocation methods.