Robust adaptive power control for cognitive radio networks

Abstract

In this study, the problem of robust adaptive power control (PC) in an underlay cognitive radio network with multiple secondary users (SUs) and primary users (PUs) is considered. Due to the effects of uncertainties (i.e. estimation errors, delays), the optimal PC (resource allocation) cannot guarantee the quality of service of SUs and PUs under imperfect channel state information and interference power of PUs. A robust resource allocation problem is formulated to maximise sum throughput of SUs under individual power constraints and signal-to-interference-and-noise ratio constraints of SUs as well as interference temperature constraints of PUs, whereas channel uncertainties and interference uncertainties induced into the secondary system are modelled by multiplicative uncertainties. Under the worst-case approach, the problem is transformed into a geometric programming problem solved by Lagrange dual methods. The performance of the different algorithms and the impact of uncertainties are discussed according to several simulation results.