Adaptive and Intelligent Digital Signal Processing for Improved Optical Interconnection

doi:10.12142/ZTECOM.202002008

ZTE Communications ›› 2020, Vol. 18 ›› Issue (2): 57-73.DOI: 10.12142/ZTECOM.202002008

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Adaptive and Intelligent Digital Signal Processing for Improved Optical Interconnection

SUN Lin¹, DU Jiangbing¹(), HUA Feng², TANG Ningfeng², HE Zuyuan¹

^1.State Key Laboratory of Advanced Optical Communication Systems and Networks, Shanghai Jiao Tong University, Shanghai 200240, China
^2.State Key Laboratory of Mobile Network and Mobile Multimedia Technology, ZTE Corporation, Shenzhen, Guangdong 518055, China

Received:2019-03-04 Online:2020-06-25 Published:2020-08-07
About author:SUN Lin received the bachelor’s degree in electronic engineering from Sichuan University, China in 2014 and has developed great interest in optical fiber communication field. He is currently working toward the Ph.D. degree at Shanghai Jiao Tong University, China. His research activities and interests include fiber communications, optical signal processing and optical transmission and interconnection.|DU Jiangbing (dujiangbing@sjtu.edu.cn) received the bachelor’s degree and the master’s degree from the College of Physics and Institute of Modern Optics, Nankai University, China in 2005 and 2008, respectively, and the Ph.D. degree in electronic engineering from the Chinese University of Hong Kong, China, in 2011. He was with Huawei Technologies from 2011 to 2012. He joined Shanghai Jiao Tong University， China as an assistant professor since 2012, and became an associate professor since 2014. He is the author or coauthor of more than 140 journals and conference papers.|HUA Feng received the B.S. and M.S. degrees in optical instrument from Tianjin University, China in 1993 and 1996 respectively. She has worked with ZTE Corporation since 2000. Currently she is a senior engineer focusing on advanced research of cutting-edge optical communication technologies including silicon photonics, spatial division multiplexing and optical backplane. She has more than 10 patents.|TANG Ningfeng received the M.S. degree in testing engineering from Nanjing University of Aeronautics and Astronautics, China, in 1999. He has worked with ZTE Corporation since 1999. Currently he is an architecture engineer focusing on co-packaged optics and optical interconnection equipment. He has more than 10 patents.|HE Zuyuan received B.S. and M.S. degrees in electronic engineering from Shanghai Jiao Tong University, China in 1984 and 1987, respectively, and the Ph.D. degree in optoelectronics from the University of Tokyo, Japan, in 1999. He joined the Nanjing University of Science and Technology, China as a research associate in 1987, and became a lecturer in 1990. From 1995 to 1996, he was a research fellow in University of Tokyo. In 1999, he became a research associate with the University of Tokyo. In 2001, he joined CIENA Corporation, Maryland, USA, as a lead engineer leading the Optical Testing and Optical Process Development Group. He returned to the University of Tokyo as a lecturer in 2003, and became an associate professor in 2005 and a full professor in 2010. He is currently a chair professor of Shanghai Jiao Tong University. His reasearch focuses on optical fiber sensing.
Supported by:
National Natural Science Foundation of China (NSFC)(61935011)

Abstract

Abstract:

In recent years, explosively increasing data traffic has been boosting the continuous demand of high speed optical interconnection inside or among data centers, high performance computers and even consumer electronics. To pursue the improved interconnection performance of capacity, energy efficiency and simplicity, effective approaches are demonstrated including particularly advanced digital signal processing (DSP) methods. In this paper, we present a review about the enabling adaptive DSP methods for optical interconnection applications, and a detailed summary of our recent and ongoing works in this field. In brief, our works focus on dealing with the specific issues for short-reach interconnection scenarios with adaptive operation, including signal-to-noise-ratio (SNR) limitation, level nonlinearity distortion, energy efficiency consideration and the decision precision.

Key words: optical interconnection, digital signal processing, advanced modulation formats

SUN Lin, DU Jiangbing, HUA Feng, TANG Ningfeng, HE Zuyuan. Adaptive and Intelligent Digital Signal Processing for Improved Optical Interconnection[J]. ZTE Communications, 2020, 18(2): 57-73.

Figures/Tables 30

Figure 1 Advanced modulation formats for short-reach optical interconnections.

Figure 2 Modulation nonlinearity caused by: (a) nonlinear LI curve of vertically cavity surface emitting laser VCSEL; (b) nonlinear spectra of Si-MRM as well as wavelength drift.

Figure 3 Dyadic probability distributions of PAM-4, PAM-8, dyadic shaped PAM-4, dyadic shaped PAM-8(P’X) and dyadic shaped PAM-8(P’’X).

Figure 4 AIR curves for PAM-4 and PAM-8（a） with and （b） without dyadic PS （probabilistic shaping）.

Figure 5 Optical eye diagrams of 60 Gbit/s and 75 Gbit/s PAM-8 signals, with and without dyadic shaping.

Figure 6 Bit error ratio （BER） curves of 75 Gbit/s PAM-8 signals.

Figure 7 Bit loading metrologies of conventional DMT and proposed PS-DMT schemes.

Figure 8 Experimental bit loading results for DMT and PS-DMT in the optical B2B case: (a) bit-loading results for conventional DMT, PS-DMT and PS-DMT (dyadic); (b) shaped probability distributions of two typical subcarriers (22th and 66th subcarriers) for PS-DMT.

Figure 9 Constellations of 12th and 66th subcarriers for optical B2B case (3.5 dBm received power) and after 100 m OM3 fiber transmission (3.3 dBm received power).

Figure 10 Experimental GMI values and data rate of reliable communication under various received optical powers.

Figure 11 (a) The training model of SVM based on binary-tree structure; (b) a schematic diagram of the hyper plane generated by node SVM for the training processing of category 1.

Figure 12 Experimental setup of QAM decision based on SVM classification methods.

Table 1 Complexity comparison for different SVM-based decision schemes

Complexity	OvR	BE	CR	IQC
SVM number for training	2 294	2 177	2 177	804
Support vector number (×10⁵)	11.61	1.367	1.376	1.997
Average SVM number for testing	2 294	492	492	492

Figure 13 BER curves by using conventional hard decision and proposed CBT-SVM for (a) PAM-4; (b) PAM-8.

Figure 14 Optical power sensitivity versus different eye-linearity value by using conventional hard decision and proposed CBT-SVM.

Figure 15 Simulation setup of Si-MRM based optical interconnects system.

Figure 16 The level-deviation curve as a function of the wavelength drift. Inserted pictures are the eye diagrams at different wavelengths.

Figure 17 Sensitivity gain (solid curves) and receiver sensitivity power (dashed curves) for the machine learning detection at different LDs.

Figure 18 PAM-4 eye-diagram.

Figure 19 Long short-term memory.

Figure 20 BER curves.

Figure 22 LMS errors during interaction for optical B2B case.

Figure 23 Results of K-means equalization and SD for 90 Gbit/s and 100 Gbit/s PAM-4.

Figure 21 Proposed K-means receiver including equalization and soft decision.

Figure 24 Experimental setup of optical carrier-less amplitude phase modulation (CAP) transmission system (left) and principle of K-nearest neighbour algorithm (right)

Figure 25 (a) Electrical spectrum of 32 Gbit/s carrier-less optical amplitude phase (CAP) modulation signal; (b) constellation of 32 Gbit/s CAP in optical B2B case; (c) constellation of 32 Gbit/s CAP after 10 km transmission.

Figure 26 BER curves of 32 Gbit/s optical carrier-less amplitude phase modulation (CAP) by using conventional hard decision and K-NN decision.

Figure 27 SNR response and bit-allocation of multi-tone modulation (DMT) for back to back (B2B) and 100 m MMF.

Figure 28 Constellations of some typical subcarriers for multi-tone modulation (DMT) as well as SVM-based decision boundaries for (a) optical B2B case and (b) 100 m MMF transmission.

Figure 29 BER comparison between using SVM decision and conventional hard decision.

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