Tag Archive for: eric c blow

Eric Blow is a Researcher in the Optical Communications & Computing Department at NEC Laboratories America in Princeton, NJ. He received his Bachelor’s degree in Electrical and Computer Engineering from The College of New Jersey, while conducting research focused on nonlinear photonic effects within organic chromophores. He received his MA and PhD in Electrical Engineering from Princeton University. His PhD research focused on developing novel integrated photonic systems for microwave signal processing. With a background in photonics engineering, he contributes to the development of next-generation high-speed real-time optical artificial intelligent computing. Dr. Blow’s work includes design, testing, and prototyping of new photonic integrated circuits, collaborating across teams to ensure that NEC’s hardware meets the demanding requirements of next-generation computation. His efforts help bring experimental technologies from the lab to production, improving reliability and scalability in optical systems.

Posts

Real-Time Photonic Blind Interference Cancellation

December 1, 2023/in Publications/by NEC Labs America

mmWave devices can broadcast multiple spatially-separated data streams simultaneously in order to increase data transfer rates. Data transfer can, however, be compromised by interference. Photonic blind interference cancellation systems offer a power-efficient means of mitigating interference, but previous demonstrations of such systems have been limited by high latencies and the need for regular calibration. Here, we demonstrate real-time photonic blind interference cancellation using an FPGA-photonic system executing a zero-calibration control algorithm. Our system offers a greater than 200-fold reduction in latency compared to previous work, enabling sub-second cancellation weight identification. We further investigate key trade-offs between system latency, power consumption, and success rate, and we validate sub-Nyquist sampling for blind interference cancellation. We estimate that photonic interference cancellation can reduce the power required for digitization and signal recovery by greater than 74 times compared to the digital electronic alternative.

Real-Time Blind Source Separation with Integrated Photonics for Wireless Signals

May 7, 2023/in Publications/by NEC Labs America

We demonstrate, for the first time, real-time blind source separation of interfering GHz transmitters using photonic weights controlled by an RF-System-on-Chip FPGA. This analog system achieves multi-antenna signal separation with millisecond execution latency.

Time Series Prediction and Classification using Silicon Photonic Neuron with Self-Connection

May 15, 2022/in Publications/by NEC Labs America

We experimentally demonstrated the real-time operation of a photonic neuron with a self-connection, a prerequisite for integrated recurrent neural networks (RNNs). After studying two applications, we propose a photonics-assisted platform for time series prediction and classification.

A Silicon Photonic-Electronic Neural Network for Fiber Nonlinearity Compensation

October 1, 2021/in Publications/by NEC Labs America

In optical communication systems, fibre nonlinearity is the major obstacle in increasing the transmission capacity. Typically, digital signal processing techniques and hardware are used to deal with optical communication signals, but increasing speed and computational complexity create challenges for such approaches. Highly parallel, ultrafast neural networks using photonic devices have the potential to ease the requirements placed on digital signal processing circuits by processing the optical signals in the analogue domain. Here we report a silicon photonic–electronic neural network for solving fibre nonlinearity compensation in submarine optical-fibre transmission systems. Our approach uses a photonic neural network based on wavelength-division multiplexing built on a silicon photonic platform compatible with complementary metal–oxide–semiconductor technology. We show that the platform can be used to compensate for optical fibre nonlinearities and improve the quality factor of the signal in a 10,080 km submarine fibre communication system. The Q-factor improvement is comparable to that of a software-based neural network implemented on a workstation assisted with a 32-bit graphic processing unit.

Demonstration of photonic neural network for fiber nonlinearity compensation in long-haul transmission systems

March 8, 2020/in Publications/by NEC Labs America

We demonstrate the experimental implementation of photonic neural network for fiber nonlinearity compensation over a 10,080 km trans-pacific transmission link. Q-factor improvement of 0.51 dB is achieved with only 0.06 dB lower than numerical simulations.