公开(公告)号：US20240107597A1

公开(公告)日：2024-03-28

申请号：US18469492

申请日：2023-09-18

Applicant: MEDIATEK INC.

Inventor： Abhishek Roy ,  Hao Bi ,  CHIA-CHUN HSU

IPC: H04W76/10 ,  H04W76/20

CPC classification number: H04W76/10 ,  H04W76/20

Abstract: This invention presents methods leveraging artificial intelligence and machine learning (AI/ML) models to enhance wireless communications efficiency in 5G/6G networks. The processes involve storing, configuring, and transferring AI/ML models within base stations and user equipment devices (UE), allowing for localized decision-making and improved network performance. Features include dynamic model activation/deactivation, model compression/decompression, and encoding/decoding method negotiation. Periodic or condition-driven model updates ensure responsiveness to network changes, while model replacements enable upgrades and iterations. The system facilitates seamless handovers between base stations, with information sharing about model capabilities and UE specifics. Model storage and configuration can also occur in the UE, empowering it for local decision-making in variable or challenging network conditions. The techniques contribute to significant performance, efficiency, and reliability improvements in 5G/6G wireless networks.

公开(公告)号：US20240106510A1

公开(公告)日：2024-03-28

申请号：US18369488

申请日：2023-09-18

Applicant: MEDIATEK INC.

Inventor： Abhishek Roy ,  Vaibhav Pradeep Bhosale ,  Gyu Bum Kyung ,  Chia-Chun Hsu

IPC: H04B7/06

CPC classification number: H04B7/0639 ,  H04B7/06958

Abstract: In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be wireless equipment. The wireless equipment selects a first subset of beams to be utilized for beam management. The beams are from a set of first type of beams used for communication with a base station or a UE. The wireless equipment measures signals transmitted on a second subset of beams. The beams are from the set of first type of beams or from a set of second type of beams. The wireless equipment measures the signals over a time window. The wireless equipment inputs the measurements to a computational model. The wireless equipment receives predictions of channel measurements on the first subset of beams from the computational model.