Spectrum sensing and resource allocation strategies for cognitive radio

Cognitive radio is a promising technique for efficient spectrum utilization. It must dynamically monitors activity in the primary spectrum and adapts its transmission to available spectral resources. The blind spectrum sensing and resource allocation in cognitive radio are being addressed in this thesis. The aim of the first part of this research has been to investigate whether model selection or signal space dimension estimation and information theoretic distance measures could be used to improve spectrum detection performance in a blind way and low signal to noise region. Through a thorough research effort, two novel spectrum sensing algorithms based on distribution analysis and dimension estimation of the primary user received signal were proposed and analyzed. The second part of this thesis presents and analyzes two user selection strategies based on outage probability. One explored the idea of combining multi-user diversity gains with spectral sharing techniques to maximize the secondary users sum rate while maintaining the outage probability of the primary user not degraded with a distributed manner, the other treat the beamforming problem in the context of cognitive radio using multiuser MIMO secondary user system and proposes a user selection strategy based on outage probability.