Robust Power Allocation Scheme in Cognitive Radio Networks

Considering that the spectrum resources are becoming increasingly demand, maximum channel capacity is very crucial for future wireless communication systems, especially for cognitive radio networks (CRNs). However, most existing works usually assume that channel parameter estimation is perfect, which is often damped in practical systems. In this paper, we investigate the robust maximum channel capacity problem in the CRNs. Then assuming that channel parameter uncertainty is bounded, we consider that all channel parameter uncertainties are described by ellipsoid sets. From the perspective of worst-case optimization, we formulate it as a semi-infinite programming (SIP) problem. Furthermore, an optimal iterative algorithm based on the dual decomposition theory and Lagrange multiplier algorithm is applied. Simulation results validate that our robust scheme can achieve the channel capacity maximization considering the worst-case and strictly guarantee the power interference requirement of second users (SUs) under all parameters’ uncertainties.