Scalable Photonic Neurons for High-speed Automatic Modulation Classification

Publication Date: 11/9/2025

Event: IEEE Photonics Conference (IPC 2025)

Reference: pp. 1-3, 2025

Authors: Yuxin Wang, Princeton University; Weipeng Zhang, Princeton University; Eric C. Blow, Princeton University, NEC Laboratories America, Inc.; Joshua C. Lederman, Princeton University; Bhavin J. Shastri, Queen’s University; Paul R. Prucnal, Princeton University

Abstract: Automatic modulation classification (AMC) is becoming increasingly critical in the context of growing demands for ultra-wideband, low-latency signal intelligence in 5G/6G systems, with photonics addressing the bandwidth and real-time adaptability limitations faced by traditional radio-frequency (RF) electronics. This paper presents the first experimental photonicimplementation of AMC, achieved through a fully functional photonic neural network built from scalable microring resonators that co-integrate electro-optic modulation and weighting. This work also represents a system-level deployment of such compact photonic neurons in a real photonic neural network, demonstrating the significant potential of photonic computing for large-scale, complex RF intelligence in next-generation wireless communication systems.

Publication Link: https://ieeexplore.ieee.org/document/11282391