Cubic metric reduction in OFDM systems by iterative descendent clipping and filtering

Abstract

Cubic metric (CM) is being regarded as a more accurate metric for envelope fluctuations of orthogonal frequency division multiplexing (OFDM) signals than peak-to-average power ratio (PAPR). Iterative clipping and filtering (ICF) is a simple and efficient technique for PAPR reduction. However, our analysis shows that this technique can not actually achieve sufficient CM reduction due to the difference between the two metrics. In this paper, based on the definition of CM, a new clipping method called descendent clipping is proposed, which can achieve more CM reduction by introducing a new parameter called descent factor. Further, we combine descendent clipping with filtering and develop two iterative descendent clipping and filtering (IDCF) algorithms: adaptive IDCF and fixed IDCF. Simulation results show that these two algorithms offer better performance and much faster convergence than the conventional ICF technique when used to reduce CM.