Abstract:Deploying metasurfaces (MTSs) to eliminate wireless blind spots requires jointly determining the physical placement of MTSs and the meta-atom phase shifts. Existing methods typically rely on explicit channel estimation, which incurs prohibitive overhead and is often intractable in real-world networks. To sidestep this bottleneck, we propose RFZero, a channel-state-information (CSI)-free deployment paradigm. Instead of estimating channels, RFZero extracts macro-environmental features from visual photos to guide MTS placement, and leverages reference signal received power (RSRP) feedback for dynamic phase-shift optimization. Most importantly, RFZero operates independently of base stations, thereby enabling seamless plug-and-play implementation. Real-world field tests confirm that RFZero completely eliminates all blind spots in a $100\text{ m}^2$ indoor area using just a pair of $1.5\text{ m}\times 0.9\text{ m}$ MTSs.
| Comments: | 7 pages |
| Subjects: | Information Theory (cs.IT) |
| Cite as: | arXiv:2605.25140 [cs.IT] |
| (or arXiv:2605.25140v1 [cs.IT] for this version) | |
| https://doi.org/10.48550/arXiv.2605.25140 arXiv-issued DOI via DataCite (pending registration) |
From: Kaiming Shen [view email]
[v1]
Sun, 24 May 2026 15:39:27 UTC (11,765 KB)
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