Propagation and channel modeling are
crucial for optimized design of advanced wireless
communications systems which have been evolving at a
dramatic speed in the last decade. The ever smaller cell
sizes, wider bandwidth, and higher data rate constitute
challenges for the design of wireless systems. The recent
introduction of multiple antenna systems requires channel
information in angular domains in order to exploit the
multipaths to enhance the data rate and system reliability.
The cognitive radio concept prescribes even greater
challenges on propagation modeling in which real time
capabilities are needed.
To meet these challenges and provide accurate propagation
predictions, numerical simulations should be able to tackle
the complex propagation environments such as urban areas,
indoor environments, and indoor/outdoor interfaces with
satisfactory computational speed and accuracy. Although
traditional propagation models such as Hata model are easy
to use and are fast in terms of simulation, they are not
applicable to small cells where individual structures such
as buildings in urban areas and rooms in indoor environments
affect the propagation characteristics significantly and
have to be taken into account to achieve realistic
propagation modeling. It is now well known that ray-tracing
is the best numerical tool to provide satisfying propagation
prediction results.
Our group has developed sophisticated
ray-tracing algorithms and software packages which provide
path loss, angle of arrival/departure, and delay
profile/spread for indoor and outdoor propagation
environments. To further improve the accuracy of our
ray-tracing tool, we developed complex wall models (such as
the metal framed windows) which fit the ray tracing engine
and can be integrated with it. Sample result from the "Site
Planning Software" package developed at the University of
Hawaii is shown in Fig. 1 [12].
Recently, as the geospatial data are
accumulating explosively in the cyberspace, we developed
methods to reconstruct three-dimensional (3D) building
structures based on high resolution images and
visualizations available in Google Earth. This unique
capability extends the application of our ray-tracing
software to an ever wider scenario [9]. We are approaching
the ultimate goal of viewing the radio propagation
prediction on a typical image of the urban environment of
interest.
Also, we are continuously doing researches to improve the
computational speed and accuracy of the ray-tracing tool to
achieve the real time capability. We are proposing an
intelligent ray-tracing scheme which exploits the spatial
coherence of the rays to accelerate the computational speed.
Significant speedup is expected in the near future.
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Fig. 1. Added capabilities to our
site-planning software: the radiation patterns of
transmit and receive antennas can be loaded into the
software for simulation of realistic antennas. The
software can provide path loss, delay spread, angle
of arrival/departure, and others. |
All these capabilities and research topics are tightly
related to the industries and many of our research
activities are actually motivated and sponsored by the
industry partners and their needs. For example, via the NSF
Center (Connection One), we have worked with Kyocera for
providing angular propagation information such as angle of
arrival/departure; with BAE Systems and L-3 Communications,
we investigated real time capabilities and 3D reconstruction
of building structures by exploiting available geospatial
resources in Cyberspace. Some results under the industrial
sponsorship are illustrated in Figs. 2 and 3.
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Fig. 2. Comparison between
original (top) and reconstructed (bottom) 3D
building structures in Cape Town, South Africa.
Based on 60 building structures we reconstructed, it
is found that for more than 95% cases the footprint
and height errors are less than 0.5 meters which is
excellent in terms of terms of propagation
prediction. Our simulation results show that the
reconstruction errors/inaccuracies will cause an
average standard deviation of 5.1 dB compared with a
reference one. |
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Fig. 3. Received power along five
routes in Rosslyn, VA, using the 3D reconstructed
model. The simulation results were compared with the
published ones and good agreement between them is
observed. |
We also reconstructed part of Rosslyn
City, VA, based on Google Earth visualization, built the 3D
building models, and simulated the path gains along five
measurement routes. The results were compared with the
published ones and good match between them was observed. The
path gain can be rendered back in Google Earth together with
the 3D buildings as shown in Fig. 3.
Objectives
:
Develop algorithms for the automatic extraction of 3D models
from images and/or visualizations available in cyberspace;
develop intelligent ray-tracing schemes with real-time
capabilities; add new functions or capabilities such as the
time variant channel characterization including Doppler
effect calculations; investigate the application of genetic
algorithms for the optimal site planning such as the
determination of best base station locations for a given
propagation environment.
Deliverables
: Software
modules that can be used stand alone or integrated into
sponsors’ legacy product.
Business or industry needs:
Automation is highly sought by the industries and customized
modular software will best fit their need. We understand
that cost is a key component for industrial development and
commercialization. By directly working with the industry
sponsors we are able to address their concerns and meet
their needs in an cost effective manner.
