CSI-tuples-based 3D Channel Fingerprints Construction Assisted by MultiModal Learning
Low-altitude communications can promote the integration of aerial and terrestrial wireless resources, expand network coverage, and enhance transmission quality, thereby empowering the development of sixth-generation (6G) mobile communications. As an enabler for low-altitude transmission, 3D channel fingerprints (3D-CF), also referred to as the 3D radio map or 3D channel knowledge map, are expected to enhance the understanding of communication environments and assist in the acquisition of channel state information (CSI), thereby avoiding repeated estimations and reducing computational complexity. In this paper, we propose a modularized multimodal framework to construct 3D-CF. Specifically,...
| Authors | Chenjie Xie, Li You, Ruirong Chen et al. |
|---|---|
| Primary category | cs.IT |
| Published | 26 March 2026 |
| Last updated at source | 26 March 2026 |
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