公开(公告)号：US20230123472A1

公开(公告)日：2023-04-20

申请号：US17906198

申请日：2021-03-15

Applicant: ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY

Inventor： Ahmed ALKHATEEB ,  Muhammed ALRABEIAH ,  Andrew HREDZAK

IPC: H04B7/06 ,  H04W36/32 ,  H04W64/00 ,  G01S13/86

Abstract: Vision-aided wireless communications systems are provided. Embodiments disclosed herein leverage visual data sensors (such as red-blue-green (RGB)/depth cameras) to adapt communications (e.g., predict beamforming directions) in large-scale antenna arrays, such as used in millimeter wave (mmWave) and massive multiple-input multiple-output (MIMO) systems. These systems face two important challenges: (i) a large training overhead associated with selecting an optimal beam and (ii) a reliability challenge due to high sensitivity of mmWave and similar signals to link blockages. Interestingly, most devices that employ mmWave antenna arrays, such as 5G phones, self-driving vehicles, and virtual/augmented reality headsets, will likely also use cameras. Therefore, an efficient olution is presented which uses cameras at base stations and/or handsets to help overcome the beam selection and blockage prediction challenges.