Patents by Inventor Nirav Gohel

Nirav Gohel 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).

  • System and method for improving machine learning model performance in a communications network
    Patent number: 11575583
    Abstract: A system, method and non-transitory computer readable media for optimizing input data for an ML model associated with a communications network. In one implementation, example ML model(s) may be trained using a modified dataset obtained for a plurality of cellular aggregation units (CAUs) of the RAN infrastructure(s), wherein the modified dataset is derived from data collected for individual CAUs over a data collection period with respect to a plurality of KPI variables. The modified data set is optimized by replacement of null values of variables with corresponding modal values of the variables. The trained ML model may be used for predicting one or more KPIs based on a set of test data associated with the RAN infrastructure(s).
    Type: Grant
    Filed: November 13, 2019
    Date of Patent: February 7, 2023
    Assignee: Telefonaktiebolaget LM Ericsson (Publ)
    Inventors: Mayuresh Hooli, Miroslav Budic, Pulin Chhatbar, Nirav Gohel, Narendra Tilwani
  • SYSTEM AND METHOD FOR IMPROVING MACHINE LEARNING MODEL PERFORMANCE IN A COMMUNICATIONS NETWORK
    Publication number: 20220029892
    Abstract: A system, method and non-transitory computer readable media for optimizing input data for an ML model associated with a communications network. In one implementation, example ML model(s) may be trained using a modified dataset obtained for a plurality of cellular aggregation units (CAUs) of the RAN infrastructure(s), wherein the modified dataset is derived from data collected for individual CAUs over a data collection period with respect to a plurality of KPI variables. The modified data set is optimized by replacement of null values of variables with corresponding modal values of the variables. The trained ML model may be used for predicting one or more KPIs based on a set of test data associated with the RAN infrastructure(s).
    Type: Application
    Filed: November 13, 2019
    Publication date: January 27, 2022
    Inventors: Mayuresh Hooli, Miroslav Budic, Pulin Chhatbar, Nirav Gohel, Narendra Tilwani