Cognitive radio access in femto-cell networks using game theory

• Main Author: Lai, Jurgen Qixin
• Other Authors: A S Madhukumar
• Format: Final Year Project
• Language: English
• Published: 2012
• Subjects: DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks
• Online Access: http://hdl.handle.net/10356/49108
• Institution: Nanyang Technological University

Game theory is a field of applied mathematics that describes and analyses interactive decision situations. It consists of a set analytical tool that predict the outcome of complex interactions among rational entities, where rationality demands a strict adherence to a strategy based on perceived or measured results. In the early to mid- 1990’s, game theory was applied to the networking problems including flow control, congestion control, routing and pricing of internet services. Recently, there has been growing interest in adopting game-theoretic methods today’s leading communications and networking issues, including power control and resource sharing in wireless and peer-to-peer networks. The application of mathematical analysis to wireless networks has met with limited success, due to the complexity of mobility and traffic models, coupled with the dynamic topology and the unpredictability of link quality that characterize such networks. The ability to model individual, independent decision makers whose actions potentially affect all other decision makers makes game theory particularly attractive to analyze the performance of ad hoc networks. Wireless systems become more complicated with respect to network size, protocol heterogeneity, multimedia service variations, dynamics interactions, and unknown attacks. These challenges have made it difficult to model, analyze, predict, and optimize wireless network performance. With the increasing number of wireless access terminals, resource scarcity and hence competition among mobile users becomes severe. With the help of game theory, it will be able to significantly help better understand the complex interactions, and design more efficient, scalable, and robust protocols.