Research on alleviating nonlinear problem by data feature extraction and fusion based on DFT-spread

Abstract

Coherent optical orthogonal frequency division multiplexing (CO-OFDM) system is susceptible to nonlinear effects because of its intrinsic high peak-to-average ratio (PAPR). In this paper, two methods based on discrete Fourier transform spread (DFT-S) are introduced to improve the nonlinear tolerance of CO-OFDM system by extracting and fusing data features, which extract the features of communication data and perform feature fusion to get the important significance of the data. The first one is based on the 2-ary amplitude shift keying (2-ASK) modulation and the Hermitian symmetry of DFT, and the other one is based on the advantages of selective mapping algorithm and characteristics of data subcarrier mapping mode which has a significant impact on PAPR. Simulation results show that compared with the traditional CO-OFDM and DFT-S CO-OFDM systems, the improved methods have better performance in terms of PAPR and BER.