Patents by Inventor FOAD SOHRABI

FOAD SOHRABI has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • DEEP-LEARNING FOR DISTRIBUTED CHANNEL FEEDBACK AND PRECODING
    Publication number: 20240163880
    Abstract: Some embodiments of the present disclosure provide a deep-learning-based framework for designing components of a downlink precoding system. The components of such a system include downlink training pilots and channel estimation based on receipt of the downlink training pilots. Another component involves channel measurement and feedback strategy at the user equipment. The components include a precoding scheme designed at the base station based on the feedback from the user equipment.
    Type: Application
    Filed: November 9, 2023
    Publication date: May 16, 2024
    Applicants: HUAWEI TECHNOLOGIES CANADA CO., LTD., THE GOVERNING COUNCIL OF THE UNIVERSITY OF TORONTO
    Inventors: WEI YU, FOAD SOHRABI, KAREEM ATTIAH ALBORAIE, MOHAMMADHADI BALIGH
  • Deep-learning for distributed channel feedback and precoding
    Patent number: 11832259
    Abstract: Some embodiments of the present disclosure provide a deep-learning-based framework for designing components of a downlink precoding system. The components of such a system include downlink training pilots and channel estimation based on receipt of the downlink training pilots. Another component involves channel measurement and feedback strategy at the user equipment. The components include a precoding scheme designed at the base station based on the feedback from the user equipment.
    Type: Grant
    Filed: June 26, 2020
    Date of Patent: November 28, 2023
    Assignees: HUAWEI TECHNOLOGIES CANADA CO., LTD., THE GOVERNING COUNCIL OF THE UNIVERSITY OF TORONTO
    Inventors: Wei Yu, Foad Sohrabi, Kareem Attiah Alboraie, Mohammadhadi Baligh
  • Flexible Downlink Control Channel Monitoring for Downlink Repetitions
    Publication number: 20230344580
    Abstract: A wireless device receives configuration parameters indicating: transmission of an uplink (UL) signal in a set of symbols, and a plurality of physical downlink control channel (PDCCH) monitoring occasions (MOs) for repetitions of a downlink control information (DCI). At least one PDCCH MO of the plurality of PDCCH MOs overlaps in time with the set of symbols. Based on a quantity of the at least one PDCCH MO, the wireless device cancels the transmission of the UL signal in a subset of symbols from the set of symbols or not monitor (e.g., skip monitoring) the at least one PDCCH MO.
    Type: Application
    Filed: April 18, 2023
    Publication date: October 26, 2023
    Applicant: Ofinno, LLC
    Inventors: Foad Sohrabi, Mohammad Ghadir Khoshkholgh Dashtaki, Esmael Hejazi Dinan, Ali Cagatay Cirik, Hua Zhou
  • DEEP-LEARNING FOR DISTRIBUTED CHANNEL FEEDBACK AND PRECODING
    Publication number: 20210410135
    Abstract: Some embodiments of the present disclosure provide a deep-learning-based framework for designing components of a downlink precoding system. The components of such a system include downlink training pilots and channel estimation based on receipt of the downlink training pilots. Another component involves channel measurement and feedback strategy at the user equipment. The components include a precoding scheme designed at the base station based on the feedback from the user equipment.
    Type: Application
    Filed: June 26, 2020
    Publication date: December 30, 2021
    Applicants: HUAWEI TECHNOLOGIES CANADA CO., LTD., THE GOVERNING COUNCIL OF THE UNIVERSITY OF TORONTO
    Inventors: WEI YU, FOAD SOHRABI, KAREEM ATTIAH ALBORAIE, MOHAMMADHADI BALIGH