name: ML
full_form: Machine Learning
context: training dataset; - The distribution of UE location for generating the training dataset may be one of the following: - Option 1: grid distribution, i.e., one training data is collected at the center of one small square grid, where, for example, the width of the square grid can be 0.25/0.5/1.0 m. - Option 2: uniform distribution, i.e., the UE location is randomly and uniformly distributed in the evaluation area. Sub-use case specific: For AI/ML-assisted positioning, companies report which construction is applied in their evaluation: a) Single-TRP construction: the input of the ML model is the channel measurement between the target UE and a single TRP, and the output of the ML model is for the same pair of UE and TRP. b) Multi-TRP construction: the input of the ML model contains N sets of channel measurements between the target UE and N (N>1) TRPs, and the output of the ML model contains N sets of values, one for each of the N TRPs. Notes: For a measurement (e.g., RSTD) which is a
description: Machine Learning (ML) is a subset of artificial intelligence that uses algorithms and statistical models to enable machines to perform tasks without explicit instructions. It relies on patterns and inference to learn from data. In 3GPP TS 38.843, ML is used in AI/ML-assisted positioning to evaluate the performance of positioning techniques.
explanation: The text describes Machine Learning as a technology applied within the context of 3GPP TS 38.843 for evaluating positioning techniques. This clearly places it within the category of Technology.
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