Optimal-sampling Active Interference Cancellation under the Minimax Criterion

In industry and academia, researchers have given more and more attention to Cognitive Radio (CR). The key idea of CR is to make it possible for a wireless system to find the vacant spectrum and transfer data without interfering with licensed users (LUs). Then, OFDM is proposed as a candidate signaling technology for such applications. However, the sidelobe interference of subcarriers has become a problem. In this letter, a method for sidelobe suppressing in OFDM systems is proposed and investigated. The proposed method is based on sampling in optimal locations with optimal weights in Active Interference Cancellation (AIC). By means of this technique, the maximum interference of the target spectrum is minimized. The proposed method can be used to minimize the maximum interference to licensed users in OFDM-based cognitive radio systems. Additionally, this method can be combined with other algorithms, such as Cancellation Carriers (CCs) and Subcarrier Weighting (SW), to enhance their performance under the minimax criterion.