Gelecek nesil heterojen ağlar için bilişsel iletişim teknikleri

Recently, cognitive radio emerged as a promising solution to spectrum scarcity problem. Cognitive radio introduces appealing features such as improved spectrum utilization and increased communication quality by making use of opportunistic and dynamic spectrum access. However, these capabilities impose additional tasks like spectrum sensing and spectrum management. In the following years, cognitive radio technology will inevitably be used in various network platforms, such as wireless sensor networks, smart grid, machine-to-machine communications, public protection and disaster relief networks, and vehicular networks. In each of the areas where cognitive radio is to be introduced, optimal techniques that address the trade-off between additional capabilities and requirements of cognitive radio must be developed. The aim of this thesis is to intelligently exploit the characteristic of various network platforms to develop cognitive communication solutions tailored specifically to each of them. For the areas mentioned earlier, we provide a comprehensive discussion of how cognitive radio technology may be applied to alleviate the problems, mainly related to spectrum scarcity. Then we present solutions related to spectrum sensing, throughput maximization and achievable reliability for cognitive radio sensor networks as applied to some of these communication systems. Specifically, we present our solutions for a two-stage spectrum sensing technique developed for resource constrained cognitive radio sensor networks. The first stage is to determine roughly a set of channels which are more likely to be available. In the second stage, a more accurate fine sensing scheme is used to locate vacant channels with higher precision. We also present our analysis on throughput maximization for electromagnetic energy harvesting cognitive radio networks, as well as an analysis of achievable reliability under opportunistic spectrum access for cognitive sensor-actor networks in smart grid. We target smart grid specifically for the later analysis, since reliability is a key requirement in both securing expansive backbone smart grid equipment and adaptive pricing using up-to-date demand response information. We discuss the viability of using cognitive radio technology in public protection and disaster relief networks, and propose a network architecture based on cognitive radio. We present comparisons of our architecture with the state-of-the-art and give simulation results to emphasize the importance of cognitive radio when used properly in such systems. Finally, we investigate the routing problem in cognitive vehicular networks. We list the challenges for routing in this network type, mainly due to its highly dynamic nature. We also lay out the advantages that are specific to vehicular networks. We present the state-of-the-art on both routing for vehicular and cognitive vehicular networks and discuss open research areas.