ISAC Imaging by Channel State Information using Ray Tracing for Next Generation 6G
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Abstract (arXiv)
Integrated sensing and communications (ISAC) is emerging as a cornerstone technology for sixth generation (6G) wireless systems, unifying connectivity and environmental mapping through shared hardware, spectrum, and waveforms. The following paper presents an ISAC imaging framework utilizing channel state information (CSI) per-path components, transmitter (TX) positions, and receiver (RX) positions obtained from the calibrated NYURay ray tracer at 6.75 GHz in the upper mid-band. Our work shows how each resolvable multipath component can be extracted from CSI estimation and cast into an equivalent three-dimensional reflection point by fusing its angle and delay information, which is useful and challenging for multi-bounce reflections. The primary contribution of the paper is the two-segment reflection point optimization algorithm, which independently estimates the path lengths from the TX position and RX position to an equivalent reflection point (ERP) on the object surface, thus enabling precise geometric reconstruction. Subsequently, we aggregate the ERPs derived from multiple pairs of TX and RX positions, generating dense three dimensional point clouds representing the objects in the channel. Experimental results validate that the proposed ISAC imaging framework accurately reconstructs object surfaces, edges, and curved features. To the best of our knowledge, this paper provides the first demonstration of multi bounce ISAC imaging using wireless ray tracing at 6.75 GHz.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Sep 2025.
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Citing papers per year: 2026: 4.
4 papers.
- 2026Bridging Visual and Wireless Sensing via a Unified Radiation Field for 3D Radio Map Constructioncited by 4
- 2026Intelligent Base Station Deployment in Urban Wireless Networks: A Geographic Data-Informed Digital Twin Approachcited by 1
- 2026LOCUS-DT: Localization via Observation-Conditioned Uncertainty Scoring with Digital Twinscited by 0
- 2026TRACE: Learning to Self-Calibrate Wireless Digital Twins from ISAC Measurementscited by 0
- 2026TRACE: Learning to Self-Calibrate Wireless Digital Twins from ISAC Measurements26 Sep 2026
- 2026LOCUS-DT: Localization via Observation-Conditioned Uncertainty Scoring with Digital Twins1 Aug 2026
- 2026Intelligent Base Station Deployment in Urban Wireless Networks: A Geographic Data-Informed Digital Twin Approach30 Jun 2026
- 2026Bridging Visual and Wireless Sensing via a Unified Radiation Field for 3D Radio Map Construction27 Jan 2026