Interference Analysis and Management with Applications in Heterogeneous Small-cell Cognitive Radio Networks

This thesis examines interference modeling and management in small cell cognitive radio networks. A generalized unified model is presented for the heterogeneous next generation network interference at a target receiver located at the centre of the cell. The derived model is then applied in devising a simple distributed power allocation algorithm for the next generation network nodes. Cooperative communication has been proved to improve the outage performance and capacity of wireless links under certain channel conditions, but is not efficient under favorable conditions. We propose a hybrid cooperation technique suited for cognitive radio networks that can reap the diversity benefits of cooperative communication without sacrificing the capacity. Next, a formulation of the power allocation problem in the cognitive interference channel is presented whereby the interference margin at the primary receivers are seen as resources to be shared optimally. A relative rate utility based power allocation algorithm that is shown to achieve favorable sum throughput is then proposed. Finally, the thesis investigates various interference coordination techniques for multi-antenna cognitive radio users coexisting with multiple primary users under a restricted interference temperature constraint. Knowledge of the zero forcing beamforming techniques and the interference alignment schemes are applied to satisfy the restricted interference temperature constraint at the primary receivers while supported significant sum rate at the secondary system.