Robust Spectrum Sharing under Channel Uncertainty for Cognitive Radio Networks

In this paper, we study robust spectrum sharing under channel uncertainty in a cognitive radio network (CRN), where a great number of secondary users (SUs) and a primary user (PU) coexist with each other sharing the same frequency spectrum. Considering the practical challenge that the channel gain between SU transmitters (SU-Txs) and PU receiver (PU-Rx) is typically uncertain, a probabilistic interference constraint is introduced in this paper. Although the interference constraint can be transformed into a linear outage probability formation, the optimization problem is a non-convex and non-linear programming (NCNLP). To circumvent the difficulty of directly solving the problem, we convert the original objective function and the outage probability constraint into suitable forms by the mathematical transformation and apply the convex optimization theory to solving this intractable problem. Moreover, we employ the interior point method to design an efficient algorithm and acquire a near-optimal solution. Finally, numerical simulations are carried out under various parameter configurations, which demonstrate that the proposed robust spectrum sharing algorithm can achieve higher performance than the state-of-the-art schemes.