Radio resource management for cognitive radio networks

• Main Author: Pirmoradian, Mahdi
• Published: Kingston University 2012
• Subjects: 621.384; Computer science and informatics
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.592756

Cognitive radio concept is a promising technology to cope with the spectrum scarcity issue in the emerging wireless technology. Practical cognitive radio as an intelligent radio is on the horizon, in which the system is able to observe radio environment, understanding its situation, and adapt its transceiver parameters without disruption to the licensed service. The main given functionality of the cognitive radio is dynamic spectrum management using underlay or overlay spectrum-sharing mechanisms. This thesis studies several objectives in cognitive radio networks namely; cumulative interference in multi-user overlay networks, effective capacity optimisation in time varying imperfect fading channels, and diverse spectrum decision schemes (i.e. Maximum Entropy Channel Access, MECA, and Adaptive Spectrum Opportunity Access, ASOA, schemes) in overlay networks. Also Green Cognitive Radio concept is introduced for enhancing energy efficiency in overlay networks. The cumulative interference at a cell-edge active primary receiver is estimated based on the two scenarios, the broadcast of receiver beacon signal and the broadcast of licensed transmitter beacon signal. In the proposed system topology, the cognitive users are distributed within and outside of the licensed coverage area with constant density. The results indicate that cumulative interference significantly gets low level through the broadcast of receiver beacon signal scenario in comparison with the licensed transmitter scenario. Additionally, optimising effective capacity of a secondary user subject to the interference constraint and transmission power constraint factors, in imperfect fading channels is studied. In this case, cross channel state information is a key factor in adapting transmission power and channel capacity accordingly. The numerical results show that effective capacity is influenced upon increasing cross channel error (secondary transmitter-primary receiver link), and QoS delay items. Moreover, the study is completed by proposing power control policy upon minimising interference level at the licensed receiver subject to the desired effective capacity level and transmission power constraint. Hence, performance of the proposed spectrum decision schemes (MECA, ASOA) is examined and explained by comparison with Random Channel Access (RCA), Minimum Channel Rate (MCR), and First Opportunity Channel Access (FOCA) schemes in the period of simulation time. MECA scheme uses weighted entropy function to assess usefulness of the remaining available idle channels, and so selects appropriate spectrum opportunity for secondary data delivery. The performance reveals that MECA and ASOA can potentially be considered as viable approaches in spectrum selection schemes. Additionally, in the case of GCR aspect an opportunistic power control policy using the remaining idle channel lifetime is proposed to mitigate interference power at the primary receiver. Overall, we develop and propose a unique technique in decreasing total interference in overlay networks; effective capacity optimisation in underlay networks, feasible spectrum selection schemes, and also green cognitive radio concept in the field of dynamic spectrum access networks.