6G Radio Channel Sounding: Challenges and Potential Solutions
The success of forthcoming 6G wireless systems will rely on the implementation of new radio technologies, such as the utilization of extremely large-scale antenna arrays (ELAAs), exploration of existing and new frequency spectrum, adoption of machine-learning and digital twin concepts, and so on. Radio channel modeling, based on channel data collected by high-fidelity channel sounders in various deployment scenarios, is essential for developing and designing future wireless systems. However, channel sounders that can support 6G research and development have been confronted with significant challenges due to the adoption of new antenna configurations, new frequency bands, new deployment scenarios, and new radio technologies. In this article, we discuss challenges for the 6G channel sounder. Following that, we present three novel channel sounders designed to address some of the challenges in 6G research: virtual array channel sounder up to 330 GHz, which can support scalable antenna and frequency configuration as requested by 6G; long-range radio-over-fiber (RoF) enabled channel sounder for spatial radio map measurements, which can collect massive channel data in frequency, time and spatial domains to support machine-learning powered 6G applications; and passive channel sounder for 5G live network, which is essential for realizing the concept of a digital twin of electromagnetic radio environment.
Authors
- Yejian Lyu (ORCID: https://orcid.org/0000-0002-5420-7731)
- Hao Sun (ORCID: https://orcid.org/0000-0002-0514-5765)
- Benoît Derat (ORCID: https://orcid.org/0000-0003-4583-2292)
- Wei Fan (ORCID: https://orcid.org/0000-0002-9835-4485)
- Xiang Zhang (ORCID: https://orcid.org/0000-0002-5568-1806)
- Fengchun Zhang (ORCID: https://orcid.org/0000-0003-0957-1232)
- Jonathan Borrill
- Jianhua Zhang
Institutions
- Beijing University of Posts and Telecommunications (CN)
- Shanghai Jiao Tong University (CN)
- Rohde & Schwarz (Germany) (DE)
- China Academy of Information and Communications Technology (CN)
- Purple Mountain Laboratories (CN)
- Southeast University (CN)
- Aalborg University (DK)
Publication Details
- Journal
- IEEE Wireless Communications
- Published
- 2025-02-01
- DOI
- https://doi.org/10.1109/mwc.001.2400057
- Citations
- 3
- Primary Topic
- Advanced MIMO Systems Optimization
- Type
- article
- Field-Weighted Citation Impact
- 2.19
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Beijing Municipality
- Southeast University