Analysis of a Dynamic Queuing Model for Secondary Users in Cognitive Radio Networks

In recent years, the increased demand for wireless multimedia services has led to huge bandwidth crisis. The concept of Cognitive Radio Networks (CRN) has been proposed as a solution. In CRN, higher Primary User Activity leads to an increased number of Pre-empted Secondary Users (PSU). Since the PSUs are given priority over New Secondary Users (NSU), the NSUs might get starved. Due to this priority of PSUs less number low priority users can be served. The advent of the Internet of Things, the traffic pattern has become unpredictable. All this reasons required a Dynamic Cognitive Channel Allocation (DCCA) algorithm which has been proposed in this work which balances the service among the PSUs and NSUs as per priority of SU as well as avoiding starvation. Analysis of the proposed algorithm using Continuous Time Markov Chain Model shows an improvement over existing literature of 44.44% in NSU dropping probability and 22.8% improvement in NSU blocking probability with respect to arrival of PUs. Varying the arrival of SUs has resulted in an improvement of 58% and 45.75% in the dropping and blocking probabilities of NSUs respectively. The starvation of SUs has lowered by 32.52% with varying arrival rate of PU and 41.38% with varying arrival rate of SUs