Service Completion Probability Enhancement and Fairness for SUs using Hybrid Mode CRNs

TLDR: This paper investigates SSCP enhancement by utilizing hybrid underlay-interweave mode of CRNs and propose a dynamic channel reservation algorithm to support interrupted users and proposes a multi-attributes based fairness-driven channel determination (MFD) algorithm for channel interruption, which ensures fairness among SUs in availing network services.

Abstract: Cognitive radio networks (CRNs) promise to accommodate billions of Internet of Things (IoT) devices within scarce spectrum by allowing secondary users (SUs) to use licensed spectrum. However, the devices need uninterruptible communication, which the conventional CRNs cannot fulfill. This necessitates successful service completion probability (SSCP) enhancement in CRNs. Further, maintaining fairness among SUs, in terms of availing network services, is a matter of consideration for ensuring the network services to be fairly available to all SUs. In this paper, we propose a hybrid CRN (HCRN) scheme to analyze two problems. Firstly, we investigate SSCP enhancement by utilizing hybrid underlay-interweave mode of CRNs and propose a dynamic channel reservation algorithm to support interrupted users. Secondly, we propose a multi-attributes based fairness-driven channel determination (MFD) algorithm for channel interruption, which ensures fairness among SUs in availing network services. Furthermore, continuous-time Markov chain is used for modelling, and mathematical formulations are derived for SSCP. The proposed scheme is evaluated under various network traffic loads and channel failure rates. Numerical results show significant improvement in SSCP and reduction in forced termination rate as compared to the benchmark. Similarly, the MFD algorithm brings a prominent improvement in fairness.