An OTFS Waveform-Based Delay-Doppler Domain Channel Measurement Method for High-Mobility Scenarios

[2510.19402] An OTFS Waveform-Based Delay-Doppler Domain Channel Measurement Method for High-Mobility Scenarios Skip to main content Search Submit Donate Log in Electrical Engineering and Systems Science > Signal Processing arXiv:2510.19402 (eess) [Submitted on 22 Oct 2025 ( v1 ), last revised 28 Aug 2026 (this version, v2)] Title: An OTFS Waveform-Based Delay-Doppler Domain Channel Measurement Method for High-Mobility Scenarios Authors: Kaifeng Bao , Tao Zhou , Chaoyi Li , Liu Liu , Bo Ai View PDF HTML (experimental) Abstract: Channel measurements are the prerequisite for applying emerging transmission technologies and designing communication systems. Conventional time or frequency domain channel measurement methods cannot directly obtain Doppler information induced by high-mobility scenarios. The channel spreading function (CSF) simultaneously captures delay and Doppler information while naturally characterizing the propagation environment in the delay-Doppler (DD) domain. However, DD domain channel measurement methods remain underexplored. This paper presents an orthogonal time frequency space (OTFS) waveform-based DD domain channel measurement method for high-mobility scenarios. A native OTFS waveform, employed as the sounding signal, is designed for the first time, and its sounding capability is comprehensively analyzed. Next, we detail the methodology of DD domain channel measurement, including synchronization and CSF estimation. To enhance measurement precision, a joint fractional delay and Doppler shift estimation algorithm is proposed, and the overall performance of the proposed method is evaluated. Subsequently, a practical DD domain channel measurement system is established, followed by system calibration and verification. Finally, DD domain channel measurements are conducted in vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) scenarios. Measurement results, including the CSF and other small-scale fading characteristics, confirm the effectiveness of the proposed method and offer valuable insights for advancing research on high-mobility communications. Comments: 16 pages, 20 figures Subjects: Signal Processing (eess.SP) Cite as: arXiv:2510.19402 [eess.SP] (or arXiv:2510.19402v2 [eess.SP] for this version) https://doi.org/10.48550/arXiv.2510.19402 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Kaifeng Bao [ view email ] [v1] Wed, 22 Oct 2025 09:21:56 UTC (28,885 KB) [v2] Fri, 28 Aug 2026 09:02:03 UTC (34,048 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Current browse context: eess.SP < prev | next > new | recent | 2025-10 Change to browse by: eess References & Citations SciX Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab)

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