公开(公告)号：US20240113795A1

公开(公告)日：2024-04-04

申请号：US17935006

申请日：2022-09-23

Applicant: QUALCOMM Incorporated

Inventor： Tribhuvanesh OREKONDY ,  Arash BEHBOODI ,  Hao YE ,  Joseph Binamira SORIAGA

IPC: H04B17/391

CPC classification number: H04B17/391

Abstract: Certain aspects of the present disclosure provide techniques and apparatuses for training and using machine learning models to estimate a representation of a channel between a transmitter and a receiver in a spatial environment. An example method generally includes estimating a representation of a channel using a machine learning model trained to generate the estimated representation of the channel based on a location of a transmitter in a spatial environment, a location of a receiver in the spatial environment, and information about the spatial environment. One or more actions are taken based on the estimated representation of the channel.

公开(公告)号：US20240144087A1

公开(公告)日：2024-05-02

申请号：US18340671

申请日：2023-06-23

Applicant: QUALCOMM Incorporated

Inventor： Fabio Valerio MASSOLI ,  Ang LI ,  Shreya KADAMBI ,  Hao YE ,  Arash BEHBOODI ,  Joseph Binamira SORIAGA ,  Bence MAJOR ,  Maximilian Wolfgang Martin ARNOLD

IPC: G06N20/00 ,  H04B7/06

CPC classification number: G06N20/00 ,  H04B7/0695

Abstract: Certain aspects of the present disclosure provide techniques and apparatus for beam selection using machine learning. A plurality of data samples corresponding to a plurality of data modalities is accessed. A plurality of features is generated by, for each respective data sample of the plurality of data samples, performing feature extraction based at least in part on a respective modality of the respective data sample. The plurality of features is fused using one or more attention-based models, and a wireless communication configuration is generated based on processing the fused plurality of features using a machine learning model.