Digital Twin Enabled Site Specific Channel Precoding: Over the Air CIR Inference
This paper investigates the significance of designing a reliable, intelligent, and true physical environment-aware precoding scheme by leveraging an accurately designed channel twin model to obtain realistic channel state information (CSI) for cellular communication systems. Specifically, we propose a fine-tuned multi-step channel twin design process that can render CSI very close to the CSI of the actual environment. After generating a precise CSI, we execute precoding using the obtained CSI at the transmitter end. We demonstrate a two-step parameters’ tuning approach to design channel twin by ray tracing (RT) emulation, then further fine-tuning of CSI by employing an artificial intelligence (AI) based algorithm can significantly reduce the gap between actual CSI and the fine-tuned digital twin (DT) rendered CSI. The simulation results show the effectiveness of the proposed novel approach in designing a true physical environment-aware channel twin model.
Authors
- Lingjia Liu (ORCID: https://orcid.org/0000-0003-1915-1784)
- Danda B. Rawat
- Imtiaz Ahmed (ORCID: https://orcid.org/0000-0001-6465-532X)
- Md. Zoheb Hassan (ORCID: https://orcid.org/0000-0003-0037-5382)
- Majumder Haider (ORCID: https://orcid.org/0000-0002-7809-7805)
- Timothy J. O’Shea (ORCID: https://orcid.org/0000-0003-2467-220X)
Institutions
- Howard University (US)
- Université Laval (CA)
- Virginia Tech (US)
Publication Details
- Journal
- IEEE Communications Letters
- Published
- 2025-05-07
- DOI
- https://doi.org/10.1109/lcomm.2025.3567850
- Citations
- 4
- Primary Topic
- Industrial Vision Systems and Defect Detection
- Type
- article
- Field-Weighted Citation Impact
- 4.97
Funders
- National Science Foundation