A flexible-bandwidth model with channel reservation and channel aggregation for three-layered Cognitive Radio Networks
Abstract The Fifth Generation (5G) of wireless communication systems is expected to meet a large demand for mobile traffic and provide higher data rates, supporting bandwidth-hungry applications. In this respect, Cognitive Radio and Channel Aggregation (CA) are envisioned as key 5G enablers providing additional spectrum resources through the Dynamic Spectrum Access, and higher data rates through multiple contiguous or non-contiguous spectrum aggregation. Moreover, since 5G networks should comprise heterogeneous applications that may have different Quality of Service (QoS), Quality of Experience (QoE) and security requirements, multiple service class support becomes a must, and thus multiple priorities have been assigned for different flow types in current wireless standards. Previous works have studied Cognitive Radio Networks (CRN) as homogeneous two-priority queueing systems, composed of primary (PUs) and secondary (SUs) users, however, those are usually not capable of analyzing SUs with different QoS requirements. In addition, most authors are concerned about proving the efficiency of QoS provisioning approaches such as channel reservation or channel aggregation, frequently using separate models in unloaded scenarios. This paper proposes and analyzes an M/M/N/N three-layered system in which the unlicensed traffic is detached in two priority classes (i.e., high and low), encompassing all possible bandwidth arrangements, a multi-level reservation feature and multiple aggregation strategies. Previous works on CA have shown that, regardless the network state, this technique should always boost the overall performance, differently from the reservation process that presents high inefficiency in overloaded networks. For this reason, CA was enabled to mitigate the reservation's drawbacks while scaling the benefits of both techniques, in a single model.