Company
Tejas Networks Limited
8 contributions across 1 work items
8
Tdocs
1
Work items
Recent position changes
AI-synthesized from contributions · all text is paraphrased
New positions this meeting
- 9.1.1 — Proposes Associated ID in CSI-Report Config, weighted BAI calculation, Differential L1-RSRP with larger quantization, max beam count M=256, and extending Rel-17 TCI activation.
- 9.1.2 — Proposes specific parameter sets for sample-based measurements, requires redefining LoS/NLoS indication for Case-3a, and supports reusing existing Release-17/18 frameworks.
- 9.1.3 — Proposes using an associated ID, AI/ML model identification via Model ID in LCM mode, and prioritizing Type 1 performance monitoring with SGCS/NMSE.
Recent contributions
Specification support for beam management
Tejas Networks Limited presents 39 proposals and 6 observations addressing AI/ML beam management for NR Air Interface, focusing on consistency mechanisms for UE-sided models, performance monitoring metrics, and reporting configurations for…
Specification support for positioning accuracy enhancement
Tejas Networks Limited presents 24 proposals and 15 observations regarding AI/ML for NR positioning accuracy, focusing on sample-based and path-based measurement inputs, model output definitions for Case-3a, training data collection…
Specification support for CSI Prediction
Tejas Networks discusses AI/ML-based CSI prediction for Rel-19, focusing on consistency between training and inference, data collection mechanisms, and performance monitoring. The document presents 16 proposals and 3 observations…
Specification support for beam management
Tejas Networks Limited submits 36 proposals and 6 observations to address open issues for AI/ML-based beam management in NR, covering both UE-sided and NW-sided models. The document focuses on ensuring consistency between training and…
Specification support for positioning accuracy enhancement
Tejas Networks Limited submits a contribution discussing AI/ML for positioning accuracy enhancement, focusing on model input definitions, training data collection, and model performance monitoring. The document contains 23 proposals and 15…
Discussion on study for AI/ML CSI prediction
Tejas Networks discusses AI/ML for CSI prediction in Rel-19, focusing on ensuring consistency between training and inference, Life Cycle Management (LCM) modes, data collection mechanisms, and performance monitoring strategies. The…
Discussion on AI/ML for CSI Compression
Tejas Networks Limited presents 11 proposals and 5 observations regarding AI/ML-based CSI compression for NR Release 19, focusing on evaluation methodologies, inter-vendor collaboration, and monitoring frameworks. The document proposes…
Discussion on Other aspects of AI/ML model and data
Tejas Networks discusses model identification and data handling for AI/ML in NR, focusing on the consistency of NW-side additional conditions via 'associated IDs' and the mapping between these IDs, datasets, and model IDs. The document…