公开(公告)号：US20220377844A1

公开(公告)日：2022-11-24

申请号：US17323242

申请日：2021-05-18

Applicant: QUALCOMM Incorporated

Inventor： Rajeev KUMAR ,  Eren BALEVI ,  Taesang YOO ,  Xipeng ZHU ,  Gavin Bernard HORN ,  Shankar KRISHNAN ,  Aziz GHOLMIEH

IPC: H04W88/08 ,  G06K9/62 ,  G06N20/00

Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for an ML model training procedure. A network entity may receive a trigger to activate an ML model training procedure based on at least one of an indication from an ML model repository or a protocol of the network entity. The network entity may transmit an ML model training request to activate the ML model training at one or more nodes. The one or more nodes may be associated with a RAN that may transmit, based on receiving the ML model training request, ML model training results indicative of a trained ML model. In aspects, an apparatus, such as a UE, may train the ML model based on an ML model training configuration received from the RAN, and transmit an ML model training report indicative of the trained ML model.

公开(公告)号：US20220030453A1

公开(公告)日：2022-01-27

申请号：US16947223

申请日：2020-07-23

Applicant: QUALCOMM Incorporated

Inventor： Rajeev KUMAR ,  Xipeng ZHU ,  Ozcan OZTURK ,  Shankar KRISHNAN ,  Linhai HE ,  Gavin Bernard HORN

IPC: H04W24/10 ,  H04W8/08 ,  H04W76/27 ,  H04W36/06

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may determine a mobility prediction for the UE. The UE may determine one or more radio resource management (RRM) measurement parameters based at least in part on the mobility prediction. The UE may perform one or more RRM measurements based at least in part on the one or more RRM measurement parameters. Numerous other aspects are provided.