Real-time complex-valued RF blind source separation via in-physics computing.

Authors

Jiajia Wang, Shuran Zhang, Haoran Zhang, Yifu Xu, Shifan Chen, Peiming Yan, Zhihui Liu, Xiaotian Zhu, Shuying Li, Yuyang Liu, Sha Zhu, Chao Wang, Yunping Bai, Chaoran Huang, Sai T Chu, David J Moss, Xingyuan Xu, Kun Xu

Published in

Science advances. Volume 12. Issue 46. Pages eaeg1515. Nov 13, 2026. Epub Nov 11, 2026.

Abstract

The rise of edge-centric 6G networks demands real-time intelligent processing of heterogeneous radio-frequency (RF) signals. Complex-valued blind source separation (CV-BSS) provides a physical-layer capability, enabling the blind extraction of source components from overlapping RF signals. Here, we demonstrate an integrated photonic vector processor (IPVP) that implements real-time CV-BSS via in-physics computation directly on raw RF signals. The IPVP operates across multiple RF bands up to 24 GHz and achieves blind, in-hardware adaptation to unknown sources and channels via in situ learning. Experiments demonstrate the efficacy of IPVP in multiple-input multiple-output (MIMO) communications and multi-band radar interference suppression. The IPVP reduces the EVMs of the two recovered signals from over 50% to 6.18% and 5.3%, respectively, while enhancing the SIR by up to 26 dB. This work demonstrates, to our knowledge, the first photonic processor capable of real-time CV-BSS at RF, highlighting the potential of integrated photonic hardware for ultralow-latency, edge-intelligent signal processing.

PMID:
43013664
Bibliographic data and abstract were imported from PubMed on 12 Nov 2026.

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