This paper provides a comprehensive review of AI/ML-based direct positioning
within 5G systems, focusing on its potential in challenging scenarios and
conditions where conventional methods often fall short. Building upon the
insights from the technical report TR38.843, we examine the Life Cycle
Management (LCM) with a focus on to the aspects associated direct positioning
process. We highlight significant simulation results and key observations from
the report on the direct positioning under the various challenging conditions.
Additionally, we discuss selected solutions that address measurement reporting,
data collection, and model management, emphasizing their importance for
advancing direct positioning.

该研究综述了基于人工智能 / 机器学习的直接定位在 5G 系统中的应用，重点研究了其在常规方法难以应对的挑战性场景和条件下的潜力。结合技术报告 TR38.843 的见解，我们对与直接定位过程相关的生命周期管理进行了进一步研究。我们强调了在各种具有挑战性条件下的直接定位的重要模拟结果和关键观察结果。此外，我们还讨论了解决测量报告、数据收集和模型管理的选定解决方案，并强调它们对于推进直接定位的重要性。