IP Library Granted Patent US 12665687
Granted Patent B2
US 12665687 · App. 18/548,117 · Granted Jun 23, 2026

Communication design support apparatus, communication design support method and program

Inventors: Minoru Inomata (Tokyo, JP); Wataru Yamada (Tokyo, JP); Nobuaki Kuno (Tokyo, JP); Motoharu Sasaki (Tokyo, JP)
Assignee: NTT, Inc.
H04B17/391H04B17/347
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Quick Facts
Patent No.
US 12665687
App. No.
18/548,117
Granted
Jun 23, 2026
Kind
B2
Abstract

A communication design support apparatus includes: a propagation model storage unit that stores a propagation model; an acquisition unit that acquires data in which structure data containing coordinate data is associated with data indicating propagation loss; and a selection unit that selects data indicating classification of a characteristic of a communication environment in a structure indicated by the structure data based on the acquired data.

Claims (27)

1 . A communication design support apparatus comprising:

a memory; and

a processor coupled to the memory and configured to:

store a propagation model in the memory;

acquire data in which structure data containing coordinate data is associated with data indicating propagation loss; and

select data indicating classification of a characteristic of a communication environment in a structure indicated by the structure data based on a feature extracted from the acquired data including the coordinate data and the propagation loss data.

2 . The communication design support apparatus according to claim 1 , wherein

the processor is configured to

acquire information indicating an antenna height of a base station, and

calculate occupancy of the structure and a statistical value of a height of the structure and select the data indicating the classification of the characteristic of the communication environment based on a result of comparison between a threshold determined in advance and the occupancy and a result of comparison between the antenna height and the statistical value.

3 . The communication design support apparatus according to claim 1 , wherein

the processor is configured to calculate occupancy of the structure and a statistical value of a height of the structure, input the calculated occupancy and statistical value to a classifier, and select the data indicating the classification of the characteristic of the communication environment.

4 . The communication design support apparatus according to claim 3 , wherein

the processor is further configured to learn the classifier by classification machine learning.

5 . A communication design support method performed by a computer storing a propagation model, the method comprising:

acquiring data in which structure data containing coordinate data is associated with data indicating propagation loss; and

selecting data indicating classification of a characteristic of a communication environment in a structure indicated by the structure data based on a feature extracted from the acquired data including the coordinate data and the propagation loss data.

6 . A non-transitory computer readable recording medium having a program embodied therein for causing a computer to perform the communication design support method of claim 5 .

7 . A communication design support apparatus comprising:

a memory; and

a processor coupled to the memory and configured to:

store a propagation model in the memory;

acquire data in which structure data containing coordinate data is associated with data indicating propagation loss; and

select data indicating classification of a characteristic of a communication environment in a structure indicated by the structure data based on the acquired data,

wherein the processor is configured to calculate occupancy of the structure and a statistical value of a height of the structure, input the calculated occupancy and statistical value to a classifier, and select the data indicating the classification of the characteristic of the communication environment.

8 . The communication design support apparatus according to claim 7 , wherein

the processor is further configured to learn the classifier by classification machine learning.