A system-on-chip microwave photonic processor solves dynamic RF interference in real-time with femtosecond latency

/in /by

Publication Date: 1/15/2024

Event: Nature Light

Reference: 13(14):1-12, 2024

Authors: Weipeng Zhang, Princeton University; Joshua C. Lederman, Princeton University; Thomas Ferreira de Lima, NEC Laboratories America, Inc.; Jiawei Zhang, Princeton University; Simon Bilodeau, Princeton University; Leila Hudson, Princeton University; Alexander Tait, Queen’s University; Bhavin J. Shastri, Queen’s University; Paul R. Prucnal, Princeton University

Abstract: Radio-frequency interference is a growing concern as wireless technology advances, with potentially life-threatening consequences like interference between radar altimeters and 5?G cellular networks. Mobile transceivers mix signals with varying ratios over time, posing challenges for conventional digital signal processing (DSP) due to its high latency. These challenges will worsen as future wireless technologies adopt higher carrier frequencies and data rates. However, conventional DSPs, already on the brink of their clock frequency limit, are expected to offer only marginal speed advancements. This paper introduces a photonic processor to address dynamic interference through blind source separation (BSS). Our system-on-chip processor employs a fully integrated photonic signal pathway in the analogue domain, enabling rapid demixing of received mixtures and recovering the signal-of-interest in under 15 picoseconds. This reduction in latency surpasses electronic counterparts by more than three orders of magnitude. To complement the photonic processor, electronic peripherals based on field-programmable gate array (FPGA) assess the effectiveness of demixing and continuously update demixing weights at a rate of up to 305?Hz. This compact setup features precise dithering weight control, impedance-controlled circuit board and optical fibre packaging, suitable for handheld and mobile scenarios. We experimentally demonstrate the processor’s ability to suppress transmission errors and maintain signal-to-noise ratios in two scenarios, radar altimeters and mobile communications. This work pioneers the real-time adaptability of integrated silicon photonics, enabling online learning and weight adjustments, and showcasing practical operational applications for photonic processing.

Publication Link: https://www.nature.com/articles/s41377-023-01362-5