High-Speed Optical Chaotic Data Selection Logic Operations with the Performance of Error Detection and Correction

Author:

Xu Geliang1ORCID,Wang Kun2,Xu Liang1,Deng Jiaqi1

Affiliation:

1. School of Electronic Engineering, Chaohu University, Hefei 238024, China

2. School of Computer Science and Artificial Intelligence, Chaohu University, Hefei 238024, China

Abstract

Based on the chaotic polarization system of optically injected cascaded vertical-cavity surface-emitting lasers (VCSELs), we propose a novel implementation scheme for high-speed optical chaotic data selection logic operations. Under the condition where the slave VCSEL (S-VCSEL) outputs a chaotic laser signal, we calculate the range of the applied electric field and the optical injection amplitude. We also investigate the evolution of the correlation characteristics between the polarized light output from the periodic poled LiNbO3 (PPLN) and the S-VCSEL as a function of the optical injection amplitude under different applied electric fields. Furthermore, we analyze the polarization bistability of the polarized light from the PPLN and S-VCSEL. Based on these results, we modulate the optical injection amplitude as the logic input and the applied electric field as the control logic signal. Using a mean comparison mechanism, we demodulate the polarized light from the PPLN and S-VCSEL to obtain two identical logic outputs, achieving optical chaotic data selection logic operations with an operation speed of approximately 114 Gb/s. Finally, we investigate the influence of noise on the logic outputs and find that both logic outputs do not show any error symbols under the noise strength as high as 180 dBw. The anti-noise performance of logic output O1 is superior to that of optical chaotic logic output O2. For noise strengths up to 185 dBw, error symbols in O2 can be detected and corrected by comparison with O1.

Funder

Natural Science Research Project of Anhui Educational Committee

University-Level General Projects of Chaohu University

National Undergraduate Innovation and Entrepreneurship Training Program

Publisher

MDPI AG

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