Green Cooperative Communication Based Cognitive Radio Sensor Networks for IoT Applications

Abstract

Green communication with emerging future technologies like the Internet of things (IoT), Industry 4.0, and Industrial IoT (IIoT) pushes modern society towards a smarter paradigm. Thus, for its deployment and implementation in the society, the involving Wireless Sensor Networks (WSNs) and its computing technologies should be designed in an energy-efficient way. In this paper, we propose an energy-efficient cooperative technique for Cognitive Radio Sensor Networks (CRSNs) for IoT applications. In this type of applications, there is a constant need for inter and intra-cluster WSNs communication. Also, the active nodes need power based on the application rather than and uniform distributing power to all the nodes or randomly distribution (conventional). The work addresses the issue by proposing a hybrid approach of using Vector Quantization (VQ) and Hierarchical Maximum Likelihood (HML) to allocate power only for the active Secondary User (SU) nodes. The proposed work illustrates a fast computation towards cluster formation and Cluster Head (CH) communication between two clusters for IoT applications with CRSNs. The work is presented with mathematical analysis and simulation results along with the comparison of existing techniques.