Cross-Layer Based Resource Management Frameworks for Mobile Cognitive Radio Networks

Resource management has been one of the most important aspects of Mobile Cognitive Radio Networks (MCRNs) since their inception. It engulfs fundamental network operations such as spectrum management, bandwidth allocation, channel access, data routing, transmission power assignment and energy management. All such mechanisms are necessary for achieving the delay/throughput requirements desired by modern network services and users. Compared to traditional wireless mobile networks, the MCRN environment poses additional challenges and complicated requirements to the above functions and resource management in general, which eventually lead to an urgent need for reconsideration of the employed wireless protocol stack. The objective in MCRNs would be to apply more efficient protocol hierarchies and achieve better management of the common available resources for both secondary and primary users, at the minimum possible cost and by leaving the minimum possible resource footprint, as required for all modern communications systems. The cross-layer design approach has been proven extremely useful towards this direction, especially for network types such as sensor, mesh and cognitive radios. It allowed exploiting the most appropriate network mechanisms, while bypassing monolithic and outdated requirements when possible. In this chapter, we focus exactly on this aspect of protocol architectures and network management, and present state-of-the-art cross-layer based resource management approaches for MCRNs. Initially, we present three important resource management frameworks, and then we provide directions for developing generic and adaptive resource management protocol architectures for MCRNs, based on cross-layer and component-based design principles emerging from the previously presented approaches. This is the first attempt to highlight the suitability of combining cross-layer with component-based network design, and this work will also sketch qualitatively the potential benefits of such approach. Finally, some practical considerations for the proposed architecture, along with directions for future research conclude the chapter.