Abstract
Real-time spectrum sensing (RT-SS) is an essential technology for the upcoming sixth-generation (6G) networks, enabling dynamic spectrum management to support emerging integrated sensing and communication (ISAC) applications. However, conventional electronic and photonic RT-SS solutions face challenges in achieving ultrawide measurement range, compact size, and low latency, simultaneously. Here, we demonstrate an integrated photonic RT-SS system covering microwave to sub-terahertz bands on a thin-film lithium niobate (TFLN) platform. The TFLN chip integrates a broadband electro-optic (EO) modulator for signal loading, an EO microring filter bank for high-speed parallel frequency-to-time mapping, and an EO comb for channel referencing. The system achieves an analysis bandwidth of 57.5 GHz and measurable frequency up to 120 GHz, at a low latency of < 110 ns. The RT-SS system is further validated through a proof-of-concept ISAC demonstration, where a radar adaptively accesses underutilized spectral regions for high-quality ranging under dynamic communication interferences. Our work provides a compact solution for high-efficiency spectrum management in 6G ISAC networks.
Similar content being viewed by others
Data availability
The data generated in this study has been deposited in the Zenodo at (https://doi.org/10.5281/zenodo.18731695).
References
Jornet, J. M., Knightly, E. W. & Mittleman, D. M. Wireless communications sensing and security above 100 GHz. Nat. Commun. 14, 841 (2023).
Griffiths, H. et al. Radar spectrum engineering and management: Technical and regulatory issues. Proc. IEEE 103, 85–102 (2014).
Liu, F. et al. Integrated sensing and communications: Toward dual-functional wireless networks for 6g and beyond. IEEE J. Sel. areas Commun. 40, 1728–1767 (2022).
Chen, X. Q. et al. Integrated sensing and communication based on space-time-coding metasurfaces. Nat. Commun. 16, 1836 (2025).
Qian, N. et al. Analog parallel processor for broadband multifunctional integrated system based on silicon photonic platform. Light.: Sci. Appl. 14, 71 (2025).
Zhang, W. et al. Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation. Nat. Commun. 14, 1107 (2023).
Lu, S. et al. Integrated sensing and communications: Recent advances and ten open challenges. IEEE Internet Things J. 11, 19094–19120 (2024).
Alsaedi, W. K., Ahmadi, H., Khan, Z. & Grace, D. Spectrum options and allocations for 6G: a regulatory and standardization review. IEEE Open J. Commun. Soc. 4, 1787–1812 (2023).
Davis III, R., Chen, Z., Hamerly, R. & Englund, D. Rf-photonic deep learning processor with Shannon-limited data movement. Sci. Adv. 11, eadt3558 (2025).
Haykin, S., Thomson, D. J. & Reed, J. H. Spectrum sensing for cognitive radio. Proc. IEEE 97, 849–877 (2009).
Polese, M. et al. Coexistence and spectrum sharing above 100 GHz. Proc. IEEE 111, 928–954 (2023).
Dang, S., Amin, O., Shihada, B. & Alouini, M.-S. What should 6g be? Nat. Electron. 3, 20–29 (2020).
Wang, W. et al. On-chip topological beamformer for multi-link terahertz 6g to xg wireless. Nature 632, 522–527 (2024).
Zhu, S. et al. Integrated lithium niobate photonic millimetre-wave radar. Nat. Photonics 19, 204–211 (2025).
Wang, Z. et al. Vision, application scenarios, and key technology trends for 6 G mobile communications. Sci. China Inf. Sci. 65, 151301 (2022).
Entesari, K. & Sepidband, P. Spectrum sensing: Analog (or partially analog) CMOS real-time spectrum sensing techniques. IEEE Microw. Mag. 20, 51–73 (2019).
Ma, Y. et al. Sparsity independent sub-nyquist rate wideband spectrum sensing on real-time TV white space. IEEE Trans. Vehicular Technol. 66, 8784–8794 (2017).
Kim, N.-S. & Rabaey, J. M. A dual-resolution wavelet-based energy detection spectrum sensing for UWB-based cognitive radios. IEEE Trans. Circuits Syst. I: Regul. Pap. 65, 2279–2292 (2017).
Zhong, L., Abbasi, M., Uddin, S. M. A. & Lee, W. Broadband frequency-domain analog processor for spectrum sensing with20 GHz scan range. IEEE Trans. Circuits Syst. II: Express Briefs 70, 1759–1763 (2023).
Sepidband, P. & Entesari, K. A CMOS real-time spectrum sensor based on phasers for cognitive radios. IEEE Trans. Microw. theory Tech. 66, 1440–1451 (2017).
Romero Cortés, L., Onori, D., Guillet de Chatellus, H., Burla, M. & Azaña, J. Towards on-chip photonic-assisted radio-frequency spectral measurement and monitoring. Optica 7, 434–447 (2020).
Marpaung, D., Yao, J. & Capmany, J. Integrated microwave photonics. Nat. photonics 13, 80–90 (2019).
Konatham, S. R. et al. Real-time gap-free dynamic waveform spectral analysis with nanosecond resolutions through analog signal processing. Nat. Commun. 11, 3309 (2020).
Wang, Y., Yang, S., Yang, B., Gao, Y. & Chi, H. Photonic real-time Fourier transform via optical phase conjugation. Opt. Lett. 50, 3632–3635 (2025).
Azaña, J. & Zhu, X. Optical time-mapped spectrograms (i): from the time-lens fourier transformer to the Talbot-based design. J. Lightwave Technol. 41, 4609–4623 (2023).
Azaña, J., Zhu, X., Rowe, C. & Crockett, B. Optical time-mapped spectrograms (ii): fractional Talbot designs. J. Lightwave Technol. 41, 5284–5295 (2023).
Ding, J., Zhu, D., Yang, Y., Pan, Z. & Pan, S. Photonics-based multidomain features extraction for radio frequency signals. IEEE Trans. Microw. Theory Tech. 72, 3692–3700 (2023).
Zhu, X., Crockett, B., Rowe, C. M., Sun, H. & Azaña, J. Agile manipulation of the time-frequency distribution of high-speed electromagnetic waves. Nat. Commun. 15, 8942 (2024).
Li, J. et al. Low-latency short-time Fourier transform of microwave photonics processing. J. Lightwave Technol. 41, 6149–6156 (2023).
Guillet de Chatellus, H., Cortés, L. R. & Azaña, J. Optical real-time fourier transformation with kilohertz resolutions. Optica 3, 1–8 (2016).
Wang, H. & Dong, Y. Real-time and high-accuracy microwave frequency identification based on ultra-wideband optical chirp chain transient SBS effect. Laser Photonics Rev. 17, 2200239 (2023).
Zuo, P., Ma, D. & Chen, Y. Short-time fourier transform based on stimulated brillouin scattering. J. Lightwave Technol. 40, 5052–5061 (2022).
Dong, W. et al. Compact photonics-assisted short-time Fourier transform for real-time spectral analysis. J. Lightwave Technol. 42, 194–200 (2023).
He, H. et al. Ultrawideband dynamic microwave frequency–amplitude measurement. Sci. Adv. 11, eadu5130 (2025).
Wang, X. et al. Wideband adaptive microwave frequency identification using an integrated silicon photonic scanning filter. Photonics Res. 7, 172–181 (2019).
Zhang, W., Liu, H., Cheng, Y., Hong, X. & Wang, B. High-resolution photonic-assisted microwave frequency identification based on an ultrahigh-q hybrid optical filter. Opt. Express 31, 42651–42666 (2023).
Yao, Y. et al. Highly integrated dual-modality microwave frequency identification system. Laser Photonics Rev. 16, 2200006 (2022).
Tao, Y. et al. Fully on-chip microwave photonic instantaneous frequency measurement system. Laser Photonics Rev. 16, 2200158 (2022).
Wang, C. et al. Integrated lithium niobate electro-optic modulators operating at CMOS-compatible voltages. Nature 562, 101–104 (2018).
Kharel, P., Reimer, C., Luke, K., He, L. & Zhang, M. Breaking voltage–bandwidth limits in integrated lithium niobate modulators using micro-structured electrodes. Optica 8, 357–363 (2021).
Feng, H. et al. On-chip optical vector analysis based on thin-film lithium niobate single-sideband modulators. Adv. Photonics 6, 066006–066006 (2024).
Yu, M. et al. Integrated femtosecond pulse generator on thin-film lithium niobate. Nature 612, 252–258 (2022).
Hu, Y. et al. High-efficiency and broadband on-chip electro-optic frequency comb generators. Nat. photonics 16, 679–685 (2022).
Xu, M., He, M., Zhu, Y., Yu, S. & Cai, X. Flat optical frequency comb generator based on integrated lithium niobate modulators. J. Lightwave Technol. 40, 339–345 (2022).
Zhang, M., Wang, C., Cheng, R., Shams-Ansari, A. & Lončar, M. Monolithic ultra-high-q lithium niobate microring resonator. Optica 4, 1536–1537 (2017).
Hu, Y. et al. On-chip electro-optic frequency shifters and beam splitters. Nature 599, 587–593 (2021).
Feng, H. et al. Integrated lithium niobate microwave photonic processing engine. Nature 627, 80–87 (2024).
López-Risueño, G., Grajal, J. & Sanz-Osorio, A. Digital channelized receiver based on time-frequency analysis for signal interception. IEEE Trans. Aerosp. Electron. Syst. 41, 879–898 (2005).
Wang, L. et al. Integrated ultra-wideband dynamic microwave frequency identification system in lithium niobate on insulator. Laser Photonics Rev. 18, 2400332 (2024).
Yan, H. et al. Thin-film-lithium-niobate photonic chip for ultra-wideband and high-precision microwave frequency measurement. Laser Photonics Rev. 19, 2401273 (2025).
Li, Z., Bennett, R. & Stedman, G. Swept-frequency induced optical cavity ringing. Opt. Commun. 86, 51–57 (1991).
Savchenkov, A. A., Matsko, A. B., Ilchenko, V. S. & Maleki, L. Optical resonators with ten million finesse. Opt. Express 15, 6768–6773 (2007).
Liu, H. et al. Integrated sensing and communication signal processing based on compressed sensing over unlicensed spectrum bands. IEEE Trans. Cogn. Commun. Netw. 10, 1801–1816 (2024).
Zhang, Y. et al. Systematic investigation of millimeter-wave optic modulation performance in thin-film lithium niobate. Photonics Res. 10, 2380–2387 (2022).
Zhu, X. et al. Twenty-nine million intrinsic q-factor monolithic microresonators on thin-film lithium niobate. Photonics Res. 12, A63–A68 (2024).
Han, H., Ruan, S. & Xiang, B. Heterogeneously integrated photonics based on thin film lithium niobate platform. Laser Photonics Rev. 19, 2400649 (2025).
Xie, X. et al. A 3.584 tbps coherent receiver chip on inp-linbo3 wafer-level integration platform. Light.: Sci. Appl. 14, 172 (2025).
Wang, W. et al. Low loss 16-channel photodetector array receiving module with fine tuning ability. IEEE Photonics J. 14, 1–6 (2022).
Liu, Z. et al. 25 × 50 gbps wavelength division multiplexing silicon photonics receiver chip based on a silicon nanowire-arrayed waveguide grating. Photonics Res. 7, 659–663 (2019).
Blaicher, M. et al. Hybrid multi-chip assembly of optical communication engines by in situ 3d nano-lithography. Light.: Sci. Appl. 9, 71 (2020).
Eichenberger, J., Yetisir, E. & Ghalichechian, N. High-gain antipodal Vivaldi antenna with pseudoelement and notched tapered slot operating at (2.5 to 57) GHz. IEEE Trans. Antennas Propag. 67, 4357–4366 (2019).
Moller de Freitas, M. et al. Monolithically integrated ultra-wideband photonic receiver on thin film lithium niobate. Commun. Eng. 4, 55 (2025).
Tao, Z. et al. Ultrabroadband on-chip photonics for full-spectrum wireless communications. Nature 645, 80–87 (2025).
Acknowledgements
This work is supported by the Research Grants Council, University Grants Committee (STG3_E-104-25-N, C.W., CityU 11204022, C.W., CityU 11204523, C.W., C1002-22Y, C.W., STG3/E-704/23-N, C.W., CityU 11212721, C.W., CityU 11213125, C.W., and JRFS2526-1S01, H.F.), Croucher Foundation (9509005, C.W.), City University of Hong Kong (9610682, C.W.). We thank W.-H. Wong and K. Shum at CityU for their help in device fabrication and measurement. We thank the technical support of C. F. Yeung, S. Y. Lao, C. W. Lai and L. Ho at HKUST, Nanosystem Fabrication Facility (NFF), for the stepper lithography and PECVD process.
Author information
Authors and Affiliations
Contributions
Y.T., H.F. and C.W. conceived the idea, with the discussions from H.S. and X.W. Y.T. proposed the system architecture and designed the devices. H.F., Y.W. and Z.C. fabricated the devices. Y.T. and H.F. carried out the experimental measurements and data analysis, with the assistance of X.X., Y.S.Z., Y.W.Z., T.G., and Z.T. The adaptive spectrum allocation algorithm was proposed by Y.F., X.Y. and J.X. The spectrogram data analysis and the imaging simulation of the ISAC demonstration was implemented by Y.F., with the guidance from X.Y. The paper was prepared by Y.T. and H.F., with contributions from all authors. C.W. supervised the project.
Corresponding authors
Ethics declarations
Competing interests
H.F., Z.C. and C.W. are involved in developing lithium niobate technologies at RhinoptiX Technology Ltd. The remaining authors declare no competing interests.
Peer review
Peer review information
Nature Communications thanks Jose Azana, who co-reviewed with Xinyi Zhu; and the other, anonymous, reviewers for their contribution to the peer review of this work. A peer review file is available.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Tao, Y., Feng, H., Fang, Y. et al. Integrated photonic ultrawideband real-time spectrum sensing for 6G wireless networks. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70389-0
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41467-026-70389-0


