Project Information
- Award Number: NSF #2549359
- Project Duration: 2026/10–2029/09
- Program: NSF VINES (Use-Inspired NextG) Track 1, CISE/CNS
- Principal Investigator: Prof. Tingjun Chen (Duke University)
- Collaborators: Prof. Ali Niknejad, Prof. Jun-Chau Chien, and Prof. Zaijun Chen (UC Berkeley)
- Graduate Students: To be added.
- Undergraduate Students: To be added.
Project Overview
The rapid growth of wireless traffic and the scaling of massive multiple-input multiple-output (MIMO) radios have pushed existing fronthaul technologies to their limits. Today’s mobile fronthaul, based on digital radio-over-fiber (DRoF), requires extensive analog/digital conversion at the radio unit (RU) and high-bandwidth digital data transfer. This results in significant energy overhead, costly high-speed electronics, and scalability bottlenecks that hinder dense, energy-efficient, and cost-effective RU deployments.
This collaborative project between Duke University and UC Berkeley develops a new approach that replaces conventional massive MIMO RUs and DRoF-based mobile fronthaul with photonics-enabled massive MIMO RUs connected over a wavelength-division multiplexing (WDM) fronthaul, through the co-design of network architecture, RF/photonic circuits, and signal processing.
The research is organized around three interrelated thrusts: (i) Development of a unified modeling and calibration framework for electrical-optical-electrical (E/O/E) signal transmission over the RF-photonic WDM fronthaul, enabling accurate characterization and compensation of impairments across the photonic and wireless domains; (ii) Investigation of novel integrated photonic and RF circuits based on microring modulators (MRMs) and photodetectors, including techniques for efficient modulation, demodulation, and local oscillator distribution across WDM channels; (iii) Design of in-line analog signal processing architectures that perform matrix-vector multiplication directly within the RF-photonic fronthaul, transforming it from a communication medium into a computing substrate.
Key Results and Outcomes
Coming soon.
Broader Impacts
This project advances knowledge at the intersection of wireless communications, signal processing, integrated photonic and RF circuits, and optical networking. The developed technologies will help reduce the energy footprint of next-generation (NextG) networks, improve the utilization of existing fiber-optic infrastructure, and facilitate the use of RF-photonics for both the transport and processing of massive MIMO signals. The project also provides a platform to engage graduate, undergraduate, and high-school students through research experiences and outreach activities.