Application of MVDR and MUSIC spectrum sensing techniques with implementation of node's prototype for cognitive radio AD hoc networks

In this paper, radio spectrum management is discussed in a multi-hop distributed network architecture scenario, dedicated for Internet of Things (IoT) applications, that aims to transform everyday objects to smart objects. In this sense, important features of Cognitive Radio Ad Hoc Networks (CRAHNs) are presented. The main interest is given to spectrum sensing functionality. Thus, the Multiple Signal Classification (MUSIC) technique and the Minimum Variance Distortionless Response (MVDR) technique are implemented. Obtained result exhibits good performance and high accuracy in Bluetooth spectrum signals detection using MUSIC technique. To reduce the gap between the simulations and real implementation, we propose a low cost node prototype for CRAHNs experiment, which consists of a radio platform and a host cognitive engine. It is carried out using 'USRP (Universal Software Radio Peripheral) and GNU-Radio' Software Defined Radio (SDR) platform, implemented on a single board computer. It ensures the development of CR functions undertaken locally by the users seamlessly work in an end-to-end multi-hop scenario.