Sensing-Native Over-the-Air Federated Learning
2026-06-17T08:51:44Z•2b9b9f16233b062135cf555bd599d922c386b3134eef7f6e3c36a91b476160b8
Bayesian Fisher informationMIMO sensingMMSE deconvolutionNLOS trackingNOMAbackscatter positioningbeamforming optimizationeavesdroppingfederated learningindoor localizationintegrated sensing and communication (ISAC)jammingmatched filteringover-the-air federated learningphysical-layer securitypilot-aided channel estimationprecoding sequence designprivacyrobust beamformingsemidefinite relaxation (SDR)signal-dependent interferencesuccessive convex approximation (SCA)trilaterationtunable liquid lensvisible light communication (VLC)
What happened
This document aggregates recent arXiv papers (June 17, 2026) focused on integrated sensing/communication, wireless localization, and signal-processing techniques: sensing-native over-the-air federated learning (leveraging gradient signals for target ranging while doing FL aggregation), MIMO sensing/precoding with scatterers, robust beamforming for secure uplink NOMA-ISAC (jamming/sensing to mitigate an uncertain eavesdropper), tunable liquid-lens assisted VLC under random receiver orientation, pilot-aided MIMO channel identification and deconvolution, and several works on backscatter-based NLo
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_eess_sp
- Record identifier
- 2b9b9f16233b062135cf555bd599d922c386b3134eef7f6e3c36a91b476160b8
- Enrichment time
- 2026-06-17T08:51:44Z
- AI-assisted enrichment
- Yes
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