DUGC-VRNet: Joint VR Recognition and Channel Estimation for Spatially Non-Stationary XL-MIMO
2026-03-30T08:51:47Z•9bbb0c6f820eeca2a709df012d658e90050c784fdb7f571284a05d0fe5f9449c
3GPP6GE‑FASGalois‑ringsIoTLDPCSTAR‑RISTR_38.901XL‑MIMOchannel‑estimationcodingdeep‑learninggraph‑neural-networkslanguage‑modelsphysical‑layer‑securitypoint‑cloudquantum‑error‑correctionrotatable‑antennasemantic‑communicationtimelinesswireless
What happened
Batch of arXiv papers (announcements) covering advanced communications and coding research: deep-learning-based near-field/XL‑MIMO channel estimation with visibility-region recognition (DUGC‑VRNet); multi-dimensional spatially-coupled LDPC design via gradient descent; 3GPP Release‑19 measurement campaigns/datasets for TR 38.901 (7–24 GHz); physical‑layer secrecy analysis for Enormous Fluid Antenna Systems (E‑FAS) with correlated surface‑wave leakage; Cross‑Layer Semantic Error Correction (CL‑SEC) combining language models with physical‑layer information; adaptive 3D point‑cloud transmission (s
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_math_it
- Record identifier
- 9bbb0c6f820eeca2a709df012d658e90050c784fdb7f571284a05d0fe5f9449c
- Enrichment time
- 2026-03-30T08:51:47Z
- AI-assisted enrichment
- Yes
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