Spatial diversity and optimization techniques for cognitive radio networks

The explosive growth of wireless applications and high demand for wireless resources have created spectruIIl crisis. Many spectrnm occupancy measurements have shown that most of the allocated spectrum experiences inefficient utilization. Hence radically new approaches arc required for better utilization of spectrum. This has motivated the concept of opportunistic spectrum access in the licensed bands namely cogni ti ve radio technology. This intelligent wireless system has the potential to improve the spectrum utilization by enabling unlicensed users to access the licensed bands without disturbing the licensed users. In this thesis, spatial multiplexing techniques are studied for underlay cognitive radio networks where transmit beamformers arc designed to satisfy quality of service and interference constraints using convex optimization techniques. Robust schemes arc also proposed in the presence of imperfect channel state information at the basestation. To overcome the infeasibility issues encountered in the beamformer design, a joint resource allocation and admission control technique is proposed using the branch and bound optimi7, ation method. Finally, signal-to-interference and noise ratio (SINR) balancing techniques are developed for different types of interference constraints on the primary users using a max-min fairness approach. These SINR balancing techniques also solve the problem of infeasibility. The performance of all these new schemes has been verified using MATLAB simulation results.