Heterogeneous Dynamic Spectrum Access in Cognitive Radio enabled Vehicular Networks Using Network Softwarization

Dynamic spectrum access (DSA) in cognitive radio networks (CRNs) is regarded as an emerging technology to solve the spectrum scarcity problem created by static spectrum allocation. In DSA, unlicensed users access idle channels opportunistically, without creating any harmful interference to licensed users. This method will also help to incorporate billions of wireless devices for different applications such as Internet-of-Things, cyber-physical systems, smart grids, etc. Vehicular networks for intelligent transportation cyber-physical systems is emerging concept to improve transportation security and reliability. IEEE 802.11p standard comprising of 7 channels is dedicated for vehicular communications. These channels could be highly congested and may not be able to provide reliable communications in urban areas. Thus, vehicular networks are expected to utilize heterogeneous wireless channels for reliable communications. In this thesis, real-time opportunistic spectrum access in cloud based cognitive radio network (ROAR) architecture is used for energy efficiency and dynamic spectrum access in vehicular networks where geolocation of vehicles is used to find idle channels. Furthermore, a three step mechanism to detect geolocation falsification attacks is presented. Performance is evaluated using simulation results

Design, Analysis, Implementation and Evaluation of Real-time Opportunistic Spectrum Access in Cloud-based Cognitive Radio Networks

Opportunistic spectrum access in cognitive radio network is proposed for remediation of spectrum under-utilization caused by exclusive licensing for service providers that are intermittently utilizing spectrum at any given geolocation and time. The unlicensed secondary users (SUs) rely on opportunistic spectrum access to maximize spectrum utilization by sensing/identifying the idle bands without causing harmful interference to licensed primary users (PUs). In this thesis, Real-time Opportunistic Spectrum Access in Cloud-based Cognitive Radio Networks (ROAR) architecture is presented where cloud computing is used for processing and storage of idle channels. Software-defined radios (SDRs) are used as SUs and PUs that identify, report, analyze and utilize the available idle channels. The SUs in ROAR architecture query the spectrum geolocation database for idle channels and use them opportunistically. The testbed for ROAR architecture is designed, analyzed, implemented and evaluated for efficient and plausible opportunistic communication between SUs