Set Transformer-Based Beamforming Design for Cell-Free Integrated Sensing and Communication
2026-03-26T08:51:45Z•0f07c363d3213d7e1324473c84b97f380d39e5939a72322fb9ce109a6ecb16a3
38 GHz6DMAAIM imagingDeep Q-ensembleFDA-MIMO-GPRJONSWAPMie scatteringSiPMTHzUAVarray optimizationbeam squintbeamformingcell-free ISACclutter covariancedispersive-medium uncertaintymovable antennasmultimodal priorsphase noise (PN)ray tracingsensing-assisted beam probingset transformeruncertainty-aware schedulingunsupervised learningwater-to-air optical
What happened
Collection of recent arXiv submissions (Mar 26, 2026) across wireless sensing, communications, and machine learning for radio/optical channels. Highlights: a Set-Transformer framework (STCIB) for cell-free ISAC beamforming providing unsupervised, permutation-invariant modeling and runtime gains; an end-to-end water-to-air optical propagation model using Monte Carlo ray-tracing with Mie scattering and JONSWAP sea-surface models (targeting LED→SiPM links and UAV instability); array layout optimization for 38 GHz active incoherent millimeter-wave imaging (AIM) showing improved reconstruction with
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_eess_sp
- Record identifier
- 0f07c363d3213d7e1324473c84b97f380d39e5939a72322fb9ce109a6ecb16a3
- Enrichment time
- 2026-03-26T08:51:45Z
- AI-assisted enrichment
- Yes
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