A Priority Based Adaptive Channel Reservation Algorithm for Improved System Capacity in Cognitive Radio Networks

Cognitive Radio Network (CRN) aims to solve the problem of spectrum congestion by allowing opportunistic use of idle spectrum bands by secondary users (SUs) in the absence of primary users (PUs). Channel reservation policies have been proposed in this regard to ensure maximum throughput for these SUs, while minimizing their interference with PUs. However, these algorithms always reserve a fixed number of channels for PU, leading to under-utilization of idle channels in times of low PU activity. This paper addresses this problem by introducing a novel Priority based Adaptive Channel Reservation (PACR) algorithm that adaptively reserves channels based on PU activity and further performs priority based channel allocation to both real-time and non real-time users. Mathematical models are designed for PACR based CRN, that depict increase in system capacity and system heterogeneity with respect to hosting both Voice over IP (VoIP) and data applications. Extensive performance analysis obtains trade-off among critical system parameters and ensures maximum Quality of Service for the VoIP users. Finally, analysis in real-life like simulation models validates the inferences drawn from the mathematical models, recording over 100% improvement in SU throughput for PACR algorithm as compared to static channel reservation policy.