QoS Provisioning in Heterogeneous Cognitive Radio Networks through Dynamic Resource Allocation

Cognitive radio networks (CRN) has been depicted as one of the most important driving forces in achieving next generation wireless communication capabilities. To this end, several works are being done in describing and designing this new wireless communication paradigm. In this work, a study on how dynamic resource allocation can be used in achieving the desired quality of service (QoS) in a heterogeneous CRN environment is carried out. An underlay CRN model is developed where, in the resource allocation formulation, the demands of secondary users differ but must be met concomitantly. The objective is to maximize the weighted data rate of the different categories of users in the CRN, and by so doing, achieve some required QoS. The developed problem is both non-linear and also non-deterministic polynomial-time (NP) hard. However, the problem is smartly re-formulated as an integer linear programming problem and the branch-and-bound approach is employed in obtaining optimal solutions. The QoS metrics evaluated are average data rate, throughput and outage probability. The results obtained show that optimal solutions with QoS satisfaction are achievable for the heterogeneous CRN.