Cognitive Radio (CR) paradigm represents an innovative solution to mitigate the spectrum scarcity problem by enabling Dynamic Spectrum Access (DSA), defined in order to conciliate the existing conflicts between the ever-increasing spectrum demand growth and the currently inefficient spectrum utilization. The basic idea of DSA is to provide proper solutions that allow sharing radio spectrum among several radio communication systems with sake of optimizing the overall spectrum utilization. This dissertation addressed the problem of modelling cognitive management frameworks that provide innovative strategies for spectrum management suitable to different scenarios and use cases in the context of DSA/CR Networks (CRNs). The first solution presented in this dissertation initially addressed the development of a framework that provides spectrum management strategies for Opportunistic Networks (ONs) defined as extended infrastructures created temporarily to serve specific regions following the policies dictated by the operator. The development of systems based on the CR paradigm to support the ONs is considered a key aspect to allow autonomous decisions and reconfiguration ability mechanisms because of the temporarily nature of these networks and the highly dynamic nature of the radio environment. Then, in order to expand the design of cognitive management frameworks providing spectrum management solutions that have applicability in a number of different scenarios and use cases, a cognitive management framework that exploits the Partially Observable Markov Decision Process (POMDP) concept has been proposed to combine the CR capabilities of radio environment awareness with a statistical characterization of the system dynamic. Finally, the framework based on POMDPs has been further extended with new functionalities able to characterize the environment dynamic through long-term predictions carried out exploiting the so-called belief vector. These frameworks as a whole aimed at demonstrating that a reliable characterization of the radio environment that combines awareness of its surrounding with a statistical evaluation of the system dynamics is able to guarantee an effcient utilization of the available spectrum resources. From a methodological point of view, the development and assessment of the proposed cognitive management frameworks and the corresponding spectrum management solutions involved analytical studies, system-level simulations and a real-time platform implementation. Overall, the research conducted in the context of this dissertation has revealed that proper cognitive management functionalities can be extremely beneficial to support spectrum management in a wide variety of scenarios and use cases.
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