Intel corporation (20240205781). USER EQUIPMENT TRAJECTORY-ASSISTED HANDOVER simplified abstract

USER EQUIPMENT TRAJECTORY-ASSISTED HANDOVER

Organization Name

intel corporation

Inventor(s)

Ziyi Li of Beijing (CN)

Dawei Ying of Portland OR (US)

Qian Li of Portland OR (US)

Youn Hyoung Heo of Santa Clara CA (US)

Jaemin Han of Santa Clara CA (US)

Zongrui Ding of Portland OR (US)

Maruti Gupta Hyde of Santa Clara CA (US)

Yi Zhang of San Jose CA (US)

Sudeep Palat of Cheltenham (GB)

Yi Guo of Shanghai (CN)

USER EQUIPMENT TRAJECTORY-ASSISTED HANDOVER - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240205781 titled 'USER EQUIPMENT TRAJECTORY-ASSISTED HANDOVER

The patent application discusses systems, apparatuses, methods, and computer-readable media for user equipment (UE) trajectory-assisted handovers, with some embodiments incorporating artificial intelligence (AI) or machine learning (ML) to predict UE location information.

• Predicting UE location information using AI or ML
• Trajectory-assisted handovers for UE
• Incorporating artificial intelligence in predicting UE location
• Utilizing machine learning for UE trajectory-assisted handovers

Potential Applications: This technology could be applied in telecommunications, specifically in optimizing handovers between different network cells for mobile devices.

Problems Solved: This technology addresses the challenge of seamless handovers for user equipment moving between different network cells, ensuring uninterrupted connectivity.

Benefits: Improved user experience with seamless handovers Enhanced network efficiency with optimized trajectory-assisted handovers Reduced network congestion with predictive UE location information

Commercial Applications: Title: Enhanced Telecommunications Handover Optimization Technology This technology could be utilized by telecommunications companies to improve network efficiency and enhance user experience, leading to increased customer satisfaction and retention.

Prior Art: Readers can explore prior research on trajectory-assisted handovers in telecommunications and the use of AI/ML in predicting UE location for further insights into this technology.

Frequently Updated Research: Stay updated on the latest advancements in trajectory-assisted handovers and AI/ML applications in telecommunications to understand the evolving landscape of this technology.

Questions about UE Trajectory-Assisted Handovers: 1. How does AI contribute to predicting UE location information in trajectory-assisted handovers? 2. What are the key benefits of utilizing machine learning for UE handover optimization?

Original Abstract Submitted

systems, apparatuses, methods, and computer-readable media are provided for user equipment (ue) trajectory-assisted handovers. in particular, some embodiments may include artificial intelligence (ai) or machine learning (ml) to predict ue location information. other embodiments may be described and/or claimed.