Erlang Capacity Performance Evaluation of Spectrum Adaptation Strategies in Cognitive Radio Networks

Interruption of ongoing calls of secondary users (SUs) due to the arrival of primary users (PUs) is one of the most relevant factors that degrade both quality of service and system throughput in cognitive radio networks (CRNs). In this paper, the Erlang capacity achieved by different resource management mechanisms previously proposed in the literature to mitigate the effects of call interruptions is evaluated and compared when they are employed separately in cognitive radio networks (CRNs) with heterogeneous traffic. This evaluation is done to identify the most relevant mechanisms to improve the performance of these networks. Also, strategies that jointly employ different resource management techniques and spectrum adaptation to exploit the synergy of the different mechanisms are proposed and evaluated. The aim of the proposed spectrum allocation strategy is to take advantage of the flexibility and delay tolerance features of elastic traffic. Additionally, a mathematical model for the performance analysis of the proposed strategies in CRNs with heterogeneous traffic is developed. Numerical results demonstrate that call buffering and adaptive spectrum mechanisms in heterogeneous traffic CRNs can significantly improve overall system performance by efficiently exploiting the elasticity of delay-tolerant traffic.