№ files_lp_4_process_3_124832
File format: docx Character count: 3202 File size: 48 KB
Year: 2026
Region / City: Gothenburg, Sweden
Topic: AI/ML-based Mobility, Multi-hop UE Trajectory
Document Type: pCR
Organization: 3GPP TSG-RAN WG3
Author: Ericsson, Jio Platform, ZTE, Huawei, NEC, Qualcomm, Samsung, China Telecom, CATT, FiberCop, Nokia, LG Electronics
Target Audience: Telecommunications professionals, network engineers, AI/ML researchers
Period of validity: February 2026
Approval Date: February 2026
Date of Changes: February 2026
Contextual Description: A technical document that outlines the multi-hop UE trajectory prediction solutions using AI/ML models for mobile network optimization.
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TP for TR 38.745 Conclusion on Study on AI/ML for NG-RAN Phase 3
Year: 2026
Region / City: Goteborg, Sweden
Topic: AI/ML for NG-RAN Phase 3
Document Type: Meeting Document
Organization: 3GPP TSG-RAN WG3
Author: ZTE Corporation (Rapporteur), NEC, Nokia, Ofinno, Qualcomm, Lenovo, Samsung, Ericsson, CATT, China Telecom, Huawei, LG Electronics, CMCC, China Unicom, FiberCop
Target Audience: 3GPP members, RAN3 participants, telecommunication engineers
Period of Action: Rel-20 normative phase
Approval Date: 13 February 2026
Date of Changes: 13 February 2026
Further Discussion on AI/ML Assisted Intra-CU LTM — pCR to TR 38.745, RAN3#131 (9–13 February 2026)
Year: 2026
Location: Gothenburg Metropolitan Area, Sweden
Event: 3GPP TSG-RAN WG3 Meeting #131
Agenda Item: 12.2.2
Organization: 3rd Generation Partnership Project (3GPP)
Working Group: TSG-RAN WG3
Source Organization: Huawei
Document Type: pCR (proposed Change Request)
Target Specification: TR 38.745
Specification Version Base: TR 38.745 V1.1.0 (2026-02)
Technical Domain: Telecommunications Engineering
Technology Context: 5G New Radio
Topic: AI/ML-assisted intra-CU LTM optimization
Key Concepts: Artificial Intelligence, Machine Learning, intra-CU LTM, mobility management, beam selection, uplink synchronization
Input Data Sources: local node measurements, UE measurement reports, mobility history, radio resource status, UE trajectory prediction
Output Data Elements: predicted candidate cell and beam, target cell and beam selection, predicted TA values, predicted timing for cell switch and early UL synchronization
Feedback Data: LTM target cell and beam per switch event, measured TA values, SON reports, actual timing of cell switch and early synchronization
Approval Context: Agreements reached at RAN3#131
Request for exceptional extension of a PhD trajectory that was delayed due to COVID-19
Year: 2021
Region / city: Ghent, Belgium
Theme: COVID-19 impact on PhD trajectories
Document type: Funding request
Institution: Ghent University
Author: Ghent University Research Administration
Target audience: PhD students, promoters
Period of validity: Until funding is granted
Approval date: N/A
Date of amendments: N/A
Topics: Multi-hop 38745 trajectory