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3D Indoor Databases
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In indoor scenarios an accurate description of the walls and objects
inside the buildings is very important. WinProp supports different types
of 2D or 3D indoor databases:
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Vector databases lead obviously to more accurate
prediction results - but it might take a longer time to process the data and to check
if everything is described correctly.
Pixel databases can be used to
define the scenario within a shorter time frame. Drawings of the building floors can
be scanned and imported within a few minutes leading to a very efficient propagation
analysis.
Of course WinProp allows also a combination of pixel and vector data to provide
the most flexible interface to the user. In the combined databases, 3D vector objects
can be inserted in pixel databases to model the scenario accurately.
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3D vector data of a typical office building
with multiple floors
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The pixel databases are generated with individual
(scanned) bitmaps of the drawings of each floor. Different material properties
and heights (of the objects) can be assigned to the various colors in the bitmaps.
WinProp's indoor vector databases are based on
- planar objects with polygonal shape
- arbitrary number of corners in polygons
- individual characterization of material properties for each object
- Multiple subdivisions (e.g. doors, windows,... ) in objects possible.
- Each subdivision with individual material properties
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Non-deterministic Objects
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Obviously furniture and persons inside buildings have a significant impact on the wave propagation and
should therefore be considered in the propagation analysis - but their locations are non-deterministic,
i.e. the user does not know where these objects are located exactly (furniture) or they are even
non-stationary (persons).
Therefore the effects of furniture, persons, etc. in indoor databases cannot be described with
deterministic 3D objects (polygons) in vector and pixel databases.
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Without furniture and persons
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Deterministic modeling
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Non-deterministic modeling
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WallMan offers the possibility to define areas with non-deterministic objects in the database.
These areas can be defined to describe the shadowing in a statistical sense. The propagation
paths inside these areas (polygonal cylinders) get a higher attenuation depending on the
length of the path inside the object (and the type of object). Mobile stations located inside
these objects will also get a higher path loss assigned (depending on the type of the object).
Accordingly the above mentioned non-deterministic objects in indoor environments can now be
considered in the propagation analysis, leading to a higher accuracy.
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