ML Detection and PAPR Reduction of NC-OFDM Signals Based on Clipping Noise Suppression for Cognitive Radio

Abstract

We propose a new scheme based on clipping noise suppression to effectively reduce the peak-to-average power ratio (PAPR) of non-contiguous orthogonal frequency division multiplexing (NC-OFDM) signals that are used in dynamic spectrum access networks such as cognitive radio. Applying the conventional clipping method to NC-OFDM presents a problem in that not only the subcarriers used by secondary users (SUs) are affected, but the subcarriers of primary users (PUs) are also affected. This paper proposes a method for improving PAPR reduction performance by dividing the subcarriers, depending on the use of subcarriers by the SU, and applying suppression of different types of clipping noise to the subcarriers used by the SU and other subcarriers. Simulation results show that the lower the suppression of the clipping noise for subcarriers not used by the SU, the lower the PAPR of the NC-OFDM signal becomes.