Iterative Clipping-Noise Compression Scheme for PAPR Reduction in OFDM Systems

Abstract

The application of orthogonal frequency division multiplexing (OFDM) has become more and more widespread in recent years. However, the high peak-to-average power ratio (PAPR) problem is still one of the critical issues in the implementation of OFDM systems. Among the techniques of PAPR reduction, iterative clipping and filtering (ICF) is widely used due to its easy implement, and many ICF-based methods have been proposed recently. The optimized ICF (OICF) further has been designed with an optimized filter and achieves faster convergence rate. And the simplified OICF (SOICF) applies Lagrange multiplier method to simplify the problem solving as compared to OICF. The approach saves SOICF from using complicated convex optimization methods. Most recently the clipping-noise compression (CNC) method is proposed to reduce the required number of Fourier transforms by compressing the clipping noise in the time domain. Based on SOICF, this paper adopts clipping and noise compression to replace the calculation of PAPR-reduction vector in each iteration. Analysis shows that the computational complexity of the proposed scheme is lower than SOICF. In addition, we have improved the CNC technique and introduced a compression threshold in the proposed scheme. In each iteration, only the components whose amplitude exceeds the compression threshold are compressed, while the others remain unchanged. To this end, this reduces the amount of information lost, resulting in better BER performance. The simulation results show that the proposed scheme has better BER performance than SOICF, and better PAPR reduction than CNC. When equal amounts of PAPR reduction by the evaluated methods are actually achieved, the BER performance of the proposed scheme is better than SOICF and CNC, especially with high-order modulation or lower clipping ratio.