A Business Framework for Dynamic Spectrum Access in Cognitive Networks

• Main Author: Kelkar, Nikhil Satish
• Other Authors: Electrical and Computer Engineering
• Format: Others
• Published: Virginia Tech 2014
• Subjects: Cognitive Networks; Dynamic Spectrum Access; Business Model
• Online Access: http://hdl.handle.net/10919/42383; http://scholar.lib.vt.edu/theses/available/etd-05022008-111653/

Traditionally, networking technology has been limited because of the networks inability to adapt resulting in sub-optimal performance. Limited in state, scope and response mechanisms, network elements consisting of nodes, protocol layers and policies have been unable to make intelligent decisions. Modern networks often operate in environments where network resources (e.g. node energy, link quality, bandwidth, etc.), application data (e.g. location of user) and user behaviors (e.g. user mobility and user request pattern) experience changes over time. These changes degrade the network performance and cause service interruption. In recent years, the words â cognitiveâ and â smartâ have become the buzzwords and have been applied to many different networking and communication systems. Cognitive networks are being touted as the next generation network services which will perceive the current network conditions and dynamically adjust their parameters to achieve better productivity. Cognitive radios will provide the end-user intelligence needed for cognitive networks and provide dynamic spectrum access for better spectrum efficiency.<p> We are interested in assessing the practical impact of Cognitive Networks on the Wireless Communication industry. Our goal is to propose a formal business model that will help assess the implications of this new technology in the real world and the practical feasibility of its implementation.<p> We use the layered business model proposed by Ballon [8] which follows a multi-parameter approach by defining four levels on which business models operate and by identifying three critical design parameters on each layer. The Value Network layer identifies the important entities which come into the picture in the light of the new technology. The Functional layer addresses the issue of different architectural implementations of the Cognitive Networks. At the Financial layer, we propose a NPV model which highlights the cost/revenue implications of the technology in the real world and contrasts the different Dynamic Spectrum Access (DSA) schemes from a financial perspective. Finally, the Value Proposition layer seeks to explain the end-user flexibility and efficient spectrum management provided by the use of Cognitive radios and Cognitive networks. === Master of Science