Spectrum Management in Cognitive Radio Ad Hoc Networks (CRAHNs) Using Bio-inspired Optimization Algorithms
Abstract: Cognitive Radio Network (CRN) has an important role in next generation wireless networks; it can potentially provide higher performance of wireless communication networks in terms of reliability, scalability, stability and spectrum efficiency. Cognitive radio networks are on the basis of radio nodes equipped with a cognitive engine (CE); it can manage spectrum and change transmission parameters using artificial intelligence methods in particular bio-inspired optimization methods. This study investigates spectrum management problem in cognitive ad hoc network in particular mobile ad hoc network with cognitive nodes. The spectrum management problem can be summarized as channel allocation and cluster formation problems that are both multi-objective combinatorial optimization problems, which can be addressed with bio-inspired optimization algorithms, i.e., genetic algorithms and swarm intelligence methods. In this thesis the focus are on the convergence characteristics and multi-objective functions.
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