Yue-Kai Huang is a Senior Researcher in the Optical Networking and Sensing Department at NEC Laboratories America in Princeton, NJ. He received his MS in Electro-Optical Engineering and his BS in Electrical and Electronics Engineering from National Taiwan University. He received his PhD in Electrical and Electronics Engineering from Princeton University, where his doctoral research focused on photonics and high-speed optical communication systems.
At NEC, Dr. Huang’s work advances the field of optical networking and fiber-based sensing systems. His research includes long-distance fiber transmission, optical/RF frontend designs for high-capacity systems, system design for distributed fiber sensing, and optical computation techniques using high-speed photonics. His work on intelligent optical sensor networks, in particular, uses fiber not only as a communication medium but also as a pervasive sensing platform. These innovations enable real-time monitoring of critical infrastructures such as transportation systems, utilities, and data centers. By combining fundamental photonics research with applied system development, Dr. Huang helps drive NEC’s mission to create more resilient, adaptive, and efficient network and sensing solutions.
His contributions result in many of NEC’s products in coherent 100G~400G and DAS sensing solutions and support the integration of advanced optical technologies into large-scale environments, bridging the gap between physical infrastructure and digital intelligence to improve safety, performance, and situational awareness.
For the first time, we demonstrate detection of vehicle speed, density, and road conditions using deployed fiber carrying high-speed data transmission, and prove carriers’ large-scale fiber infrastructures can also be used as ubiquitous sensing networks.
We demonstrate high spectral efficiency transmission over 549 km of field-deployed single-mode fiber using probabilistic-shaped 144QAM. We achieved 41.5 Tb/s over the C-band at a spectral efficiency of 9.02 b/s/Hz using 32-Gbaud channels at a channel spacing of 33.33 GHz, and 38.1 Tb/s at a spectral efficiency of 8.28 b/s/Hz using 48-Gbaud channels at a channel spacing of 50 GHz. To the best of our knowledge, these are the highest total capacities and spectral efficiencies reported in a metro field environment using C-band only. In high spectral efficiency transmission, it is necessary to optimize back-to-back performance in order to maximize the link loss margin. Our results are enabled by the joint optimization of constellation shaping and coding overhead to minimize the gap to Shannon’s capacity, transmitter- and receiver-side digital backpropagation, signal clipping optimization, and I/Q imbalance compensation.
We propose a single-ended Brillouin-based sensor in elliptical-core few-mode optical fiber for multi-parameter measurement using spontaneous Brillouin scattering. Distributed sensing of temperature and strain is demonstrated over 0.5 km elliptical-core few-mode fiber.
An ensemble learning algorithm is applied to enhance filtering tolerance of cascaded WSSs in open ROADM environment to demonstrate ~0.8dB Q-factor improvement over MLSE after transmitting over 3200km with 16 ROADMs.
We study digital signal processing techniques to optimize the back-to-back performance of large probabilistic shaped constellations. We cover joint optimization of LDPC and constellation shaping, CD pre-compensation, clipping and I/Q imbalance compensation.
41.5-Tb/s over 549 km of deployed SSMF in Verizon’s network is achieved using probabilistic-shaped 144QAM to optimize throughput at ultra-fine granularity. This is the highest C-band only capacity and spectral efficiency in metro field environment.
Quality of transmission prediction for real-time mixed line-rate systems is realized using artificial neural network based transfer learning with SDN orchestrating. 0.42 dB accuracy is achieved with a 1000 to 20 reduction in training samples.
