At&t Intellectual Property I, L.p.

Krystian Czapiga

Yaron Kanza

Velin Kounev

Arun Jotshi

Philip E Brown

Poornima Suresh

Gopalakrishnan Meempat

James Klosowski

Serkan Isci

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.

Machine-learning-based wireless planning using antenna radiation patterns

Aspects of the subject disclosure may include, for example, network deployment or radio-propagation computation based on a combination of photon mapping and machine learning including supporting near-real-time computation of the radio transmissions for different layouts of antennas and allowing examination of a large variety of antenna locations and layouts, changing configuration details, e.g., tilting antennas or optimally selecting the sector that each antenna covers, and so on. Other embodiments are disclosed.

Real-time ML-supported radio propagation computation for RAN planning

Architectures and techniques are presented that improve or enhance a network planning procedure such as by selecting a more efficient test buffer that is used to identify objects that might intersect a Fresnel zone between two transceivers. An improved test buffer (e.g., buffer region) can be one that is constructed from a plurality of rectangles situated along a line of sight of the two transceivers and that are oriented according to cardinal directions.

Adaptive buffer region for line-of-sight network planning

Aspects of the subject disclosure may include, for example, calculating a Fresnel zone about a line of sight (LoS) between a pair of antennas positioned on antenna mounts. The Fresnel zone is projected onto a geospatial grid of 3D cells, each having a height above a horizontal plane. Cells that intersect the Fresnel zone projection are selected to obtain a subset cells with constraint heights determined according to heights of the subset cells that are adjusted according to the Fresnel zone. The LoS is revised according to an algorithm to obtain a set of updated LoS. Those updated LoS that do not intersect the set of adjusted constraint heights are identified as solutions that include an optimal solution, should one exist. Other embodiments are disclosed.

System and method for geospatial planning of wireless backhaul links

Architectures and techniques are presented that improve or enhance a network planning procedure such as interactively planning suitable locations for transceiver sites that communicate with one another. Map data indicative of a 3D depiction of a physical space can be presented to a user interface device. Input indicative of a first transceiver site and a second transceiver site can be received. A Fresnel zone between the first transceiver site and the second transceiver site can be determined based on the map data. An interactive representation of the Fresnel zone can be presented to the user interface device.

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Hillsborough, NJ, United States of America

Krystian Czapiga