Applied Optics
Enhancement of entropy-source signals from a Brillouin random fiber laser using linear predictive coding decorrelation preprocessing
Jiaxin Yu, Shaofei Wang, Xin Xue, Yi Liu, shuo su, Yicong Shi, Wenjun He, Yajun You, Kewu Li, Jian He, Xiujian Chou
Abstract
A decorrelation preprocessing method based on linear predictive coding (LPC) is proposed for enhancing entropy-source signals from a Brillouin random fiber laser (BRFL). Unlike structure-optimization-based approaches, the proposed algorithm directly suppresses predictable components in raw BRFL entropy-source signals by extracting prediction residuals from historical-sample-based linear prediction. Experimental results show that LPC preprocessing significantly reduces the autocorrelation sidelobe ratio of the BRFL sampling sequence from −0.044 to −28.917dB, increases the spectral flatness from 0.005 to 0.952, and improves the amplitude min-entropy from 5.454 to 6.190 bit/sample. After random-bit postprocessing, the generated bitstream exhibits good 0/1 balance and low residual correlation and successfully passes the NIST randomness tests. These results demonstrate the effectiveness of LPC-based decorrelation preprocessing in enhancing BRFL entropy-source signals, indicating its potential for fiber-laser-based physical random number generation and secure information processing.