A Virtual Control Layer Resource Allocation Framework for Heterogeneous Cognitive Radio Network

To make best use of the various radio resources in the heterogeneous network enabled by the software defined network or cognitive radio (CR) technology, a resource allocation framework with flexibility and quick reconfigurability in the network control layer is an important issue. In this paper, the authors propose a channel allocation framework with configurable objectives and high computing efficiency in the complicated context of a multi-user multi-channel CR network cell. First, a channel allocation protocol named the distribution probability matrix (DPM) is applied to model the channel allocation scenarios quantitatively. Then, a queueing analytical framework using DPM is built to model the CR system and comprehensive performance evaluations of every individual secondary user are obtained separately. An overall performance evaluation of the CR system is carried out using the concept of weighted throughput, which is introduced to represent the importance of the users and the feature to distinguish different types of users. Then, a parameter named overtime probability (OP) is introduced to describe the measure of delay approximately with high computing efficiency. Thereby, an optimization of the system is formulated to maximize the overall weighted throughput under delay constraints represented by OP and a hill climbing algorithm is developed to find the solution in terms of DPM. The numerical results reveal how to allocate the resources to achieve the optimization objective under various system settings and prove the computing efficiency of the framework.