Method and system for intelligent 3D aerial wireless transmission

Patent metadata

Field	Value
Publication number	US-11784691-B2
Application number	US-202217749903-A
Country	US
Kind code	B2
Filing date	May 20, 2022
Priority date	Nov 22, 2019
Publication date	Oct 10, 2023
Grant date	Oct 10, 2023

Abstract

A method and system for beamforming in a wireless communication system for intelligent three-dimensional aerial wireless transmission are disclosed. In an embodiment, the method includes: identifying at least one obstruction in at least one three-dimensional aerial view image of a current location of the at least one transmitting antenna; forming at least one set of virtual layers comprising of one or more virtual layers corresponding to the at least one obstruction; determining a collective attenuation value for the at least one set of virtual layers based on an attenuation value of the one or more virtual layers; and forming at least one first beam based on the collective attenuation value.

First claim

What is claimed is:

1. A method of beamforming for at least one transmitting antenna, the method comprising:
identifying at least one obstruction in at least one three-dimensional aerial view image of a current location of the at least one transmitting antenna;
forming at least one set of virtual layers comprising of one or more virtual layers corresponding to the at least one obstruction;
determining a collective attenuation value for the at least one set of virtual layers based on an attenuation value of the one or more virtual layers; and
forming at least one first beam based on the collective attenuation value.

2. The method as claimed in claim 1 , wherein the at least one obstruction is identified on a line-of-sight transmission between the at least one transmitting antenna and at least one receiving antenna, or
wherein the one or more virtual layers indicate one or more of an attenuation value of the at least one obstruction and plurality of obstructions parameters corresponding to the at least one obstruction, or
wherein forming the at least one beam comprises controlling at least one beam parameter of the at least one beam based on the collective attenuation value.

3. The method as claimed in claim 1 , wherein forming the set of virtual layers comprises:
obtaining a plurality of obstruction parameters corresponding to the at least one obstruction;
determining a plurality of virtual layer parameters based on one or more of the plurality of obstruction parameters, characteristics of the at least one transmitting antenna, the characteristics of at least one receiving antenna, and learned data;
forming the one or more virtual layers based on the plurality of virtual layer parameters; and
arranging the one or more virtual layers corresponding to the at least one obstruction in a stack to form the set of virtual layers, and
wherein forming the one or more virtual layers comprises at least one of:
determining a shape of the one or more virtual layers to be one of a two-dimensional shape and a three-dimensional shape based on the plurality of virtual layer parameters;
determining a shape of the one or more virtual layers is one of an identical shape, a substantially similar shape, and a distinct shape based on the plurality of virtual layer parameters; and
determining a dimension of the one or more virtual layers is one of an equal value and a distinct value based on the plurality of virtual layer parameters.

4. The method as claimed in claim 1 , wherein determining the collective attenuation value for the at least one set of virtual layers comprises:
determining the attenuation value of the one or more virtual layers based on a plurality of obstruction parameters corresponding to the at least one obstruction and one or more predefined attenuation models; and
deriving the collective attenuation value based on summation of the attenuation value of each of the one or more virtual layers, and
wherein determining the collective attenuation value for the at least one set of virtual layers comprises:
assigning a dynamically determined weight to each of the one or more virtual layers based on one or more of specified weighted attenuation models and dynamic parameters to obtain a weighted attenuation value; and
deriving the collective attenuation value based on summation of the weighted attenuation value of each of the one or more virtual layers, and
wherein the dynamically determined weight assigned to each of the one or more virtual layers is one of an equal value and a distinct value, or
wherein the dynamically determined weight is assigned to each of the one or more virtual layers at one of a same time instant and different time instants, or
wherein the weight is dynamically determined as learned data obtained by processing attenuation value of the one or more virtual layers, one or more of the plurality of virtual layer parameters, the dynamic parameters, and training data using one or more specified weighted attenuation models.

5. The method as claimed in claim 1 , further comprising:
categorizing the at least one set of virtual layers based on the collective attenuation value; and
forming at least one of the at least one first beam and at least one second beam based on the collective attenuation value and the categorization, and
wherein categorizing the set of virtual layers comprises:
categorizing, on the at least one three-dimensional aerial view image, the at least one set of virtual layers into one of an effective obstruction path and a nominal obstruction path based on a learned data and one or more threshold values, the threshold value being determined from one or more learned models, and wherein the effective obstruction path indicates the at least one set of virtual layer having a collective attenuation value higher than the threshold value and the nominal obstruction path indicates the at least one set of virtual layer having a collective attenuation value lower than the threshold value, or
wherein the forming at least one of the at least one first beam and the at least one second beam comprises controlling at least one beam parameter of the at least one first beam and the at least one second beam based on the collective attenuation value and the categorization, or
further comprising:
identifying a density percentage area of the at least one set of virtual layer based on the categorization of the at least one set of virtual layers and a categorization of the one or more virtual layers in the at least one set of virtual layers; and
forming at least one of the at least one first beam and the at least one second beam based on the collective attenuation value, the categorization, and the density percentage area, and threshold value, and wherein the forming at least one of the at least one first beam and the at least one second beam comprises controlling at least one beam parameter of the at least one first beam and the at least one second beam based on the collective attenuation value, the categorization, and the density percentage area.

6. The method as claimed in claim 1 , comprising dynamically performing, based on at least one of reflected signals obtained by emitting the at least one beam, a density percentage area of the one or more virtual layers, the at least one set of virtual layers, the one or more virtual layers, the collective attenuation value, and learned data, at least one of:
adjusting at least one of a plurality of virtual layer parameters of at least one virtual layer in the at least one set of virtual layers; and
merging the at least one set of virtual layers with at least one further set of virtual layers.

7. The method as claimed in claim 1 , further comprising:
determining at least one virtual hollow three-dimensional shape between the at least one set of virtual layers and at least one further virtual set of virtual layers;
selecting at least one three-dimensional obstruction free beam window within at least one virtual hollow three-dimensional shape; and
forming at least one of the at least one first beam and at least one second beam based on the collective attenuation value and the least one three-dimensional obstruction free beam window, and
wherein determining the at least one virtual hollow three-dimensional shape comprises:
detecting an open space distance between the at least one set of virtual layers and the at least one further virtual set of virtual layers; and
determining the at least one virtual hollow three-dimensional shape based on the open space distance and dimensions of the at least one set of virtual layers and at least one further virtual set of virtual layers, or
comprising dynamically performing, based on at least one of reflected signals obtained by emitting the at least one beam

Assignees

• Samsung Electronics Co Ltd
• Delhi Technological Univ

Inventors

• Agrawal Sachin Kumar
• Sharma Kapil

Classifications

• H04B7/0617 Primary

  for beam forming · CPC title

• G06V10/82

  using neural networks · CPC title

• G06V20/176

  Urban or other man-made structures · CPC title

• G06V10/764

  using classification, e.g. of video objects · CPC title

• H04B7/0413

  MIMO systems · CPC title