RAIL-5G: A Challenging Real-World Dataset and Benchmark for AI-Based 5G Indoor Localization

arXiv:2610.25201 · eess.SP, cs.LG · Submitted 2026-10-18 · Read on arXiv

eess.SP, cs.LG

Submitted: 2026-10-18

Updated: 2026-10-18

Comments: To be published in the proceedings of the 16th International Conference on Indoor Positioning and Indoor Navigation (IPIN)

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 1× in this paper · explained in 2 episodes

Related papers

• What If They Took the Shot? A Hierarchical Bayesian Framework for Counterfactual Expected Goals
• Runtime Assurance Under Measurement Attack: Necessary and Sufficient Observability Conditions for Learned Control in Radio Access Networks
• Physics-Constrained Deep Learning Model for Contactless Blood Pressure Monitoring from Triaxial Bodyseismography
• SpellerSSL: Self-Supervised Learning with P300 Aggregation for Speller BCIs
• Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review
• Continuous Orthogonal Mode Decomposition: Haptic Signal Prediction in Tactile Internet