Learning Compact Terrain-Context Representations for Feasibility-Aware Offline Reinforcement Learning in UAV Relaying Networks
2026-04-02T08:51:43Z•d49f5c638cd8b4754ef64d52854bd07e736d2de0a77050d26f92d3ee5668c1d3
3GPP6G-imagingISACIsing-machineRF-signal-processingRISUAV-securityVAEadversarial-MLdatasetjamming-planninglocalizationoffline-RLprivacy-surveillancequantum-annealingradio-mapsreconfigurable-intelligent-surfacerepresentation-learningsignal-separationspectrum-monitoringwireless-security
What happened
This collection of papers presents advances in wireless communications, sensing, and learning that have dual-use security implications. Highlights: RFSS — a publicly released 103 GB 3GPP-compliant multi-source RF signal separation dataset (GSM/UMTS/LTE/5G NR) with benchmarks, which can accelerate development of powerful source-separation and interception tools; 6G BI-SAR/BI-ISAR imaging methods that perform high-resolution imaging using Doppler-only processing (privacy/surveillance risk); multiple ISAC, antenna and RIS advances (SWAN pinching-antenna CRLB optimization, scalable fluid-antenna S
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_eess_sp
- Record identifier
- d49f5c638cd8b4754ef64d52854bd07e736d2de0a77050d26f92d3ee5668c1d3
- Enrichment time
- 2026-04-02T08:51:43Z
- AI-assisted enrichment
- Yes
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.