Invention Publication
- Patent Title: MACHINE-LEARNING-BASED WIRELESS PLANNING USING ANTENNA RADIATION PATTERNS
-
Application No.: US18051622Application Date: 2022-11-01
-
Publication No.: US20240147251A1Publication Date: 2024-05-02
- Inventor: Serkan Isci , Krystian Czapiga , Yaron Kanza , Velin Kounev , James Klosowski , Gopalakrishnan Meempat
- Applicant: AT&T Intellectual Property I, L.P.
- Applicant Address: US GA Atlanta
- Assignee: AT&T Intellectual Property I, L.P.
- Current Assignee: AT&T Intellectual Property I, L.P.
- Current Assignee Address: US GA Atlanta
- Main IPC: H04W16/18
- IPC: H04W16/18 ; H04W16/28

Abstract:
In one example, a method performed by a processing system including at least one processor includes creating a geospatial model of an environment in which a cellular network is to be deployed, transforming, for each cellular antenna of a proposed antenna layout of the cellular network, a radiation pattern of the each cellular antenna into a signal strength array, to create a plurality of signal strength arrays, augmenting, for each signal strength array of the plurality of signal strength arrays, the each signal strength array with at least one parameter of a corresponding cellular antenna of the proposed antenna layout and at least one value describing the environment in which the cellular network is to be deployed, and estimating a coverage of the proposed antenna layout based on the signal strength array, as augmented, using a machine learning model.
Information query