Radio Resource Management In Cognitive Radio Using Evolutionary Techniques

This thesis addresses radio resource management (RRM) in cognitive radio (CR) for optimal utilization of radio and hardware resources. We explore evolutionary optimization techniques for RRM in CR as well as to implement advance transmission techniques to enhance efficiency of CR at affordable cost and complexity.The first contribution of the thesis address CR parameter adaptation problem in multicarrier environment to determine the optimal set of transmission parameters for a given situation. A set of transmission and environmental parameters are defined and fitness functions that cover relationships between these parameters are developed to implement cognitive control method. Different communication objectives are defined and used in combination with these fitness functions to direct CR to a solution. We applied different evolutionary methods to optimize multiple CR objectives for different modes. Simulation results reveal that swarm optimization algorithms provide higher fitness values and trade off multiple objectives more efficiently, compared with other evolutionary methods.As a second contribution in this work, we address resource allocation in multiuser OFDM-based CR system and apply evolutionary techniques to CR scheduling problem. Simulations results show that proposed algorithms provide an efficient solution for radio resource management in OFDMA-based cognitive radio network. They maximize the system capacity while adhering to the interference and power constraints.Utilization of multiple antenna transmission technique is a potential solution to co-channel interference problems in coexisting environments. However, additional system cost and complexities associated with multiple antennas limit their application in CR Systems. Third contribution of the dissertation introduces antenna selection in cognitive MIMO systems and proposes low complexity antenna selection algorithms. Wherein, using only a subset of available antennas to transmit or receive signal greatly reduce hardware cost and complexities of the CR transceivers, while keeping much of the benefits of multiple antennas.This research work on the whole is expected to contribute in the efforts towards realization of cognitive radios and networks.