WinProp is a complete suite of tools in the domain of wireless propagation and radio network planning. With applications
ranging from satellite to terrestrial, from rural via urban to indoor radio links, WinProp’s innovative wave propagation models combine accuracy with short computation time.
View the typical workflows when working with propagation simulations in specific scenarios, how to add a network planning
to a propagation simulation, include a receiver pattern, set up a time-variant scenario, include multiple-input multiple-output
(MIMO) at both the base station and the mobile station, connectivity analysis of sensor networks and optimization.
Use AMan to generate, edit and analyze a single antenna. Superimpose multiple antennas radiating similar signals to determine
the actual antenna pattern while taking into consideration the local environment.
Predict path loss between transmitter and receiver with ProMan. Perform network planning including the wireless standards (the air interfaces) and including multiple transmitters/receivers
(multiple base stations).
The traffic simulation report in ProMan based on the Monte Carlo approach that evaluates the numbers of served, blocked and not assigned mobiles (users)
for each application and for each cell.
Additional channel characteristics like channel impulse responses, spatial channel impulse responses and angular profiles
can be displayed for user-defined locations in separate graphs.
The most important criterion to measure the performance of a prediction model is the accuracy. The accuracy of a prediction
models can be analyzed by comparing simulation results with measurements.
WinProp includes empirical and semi-empirical models (calibration with measurements possible), rigorous 3D ray-tracing models
as well as the unique dominant path model (DPM).
In WinProp various air interfaces and applications are pre-defined: broadcasting, cellular, wireless access, WiFi, sensor networks,
ICNIRP and EM compliance.
ProMan offers the possibility to determine the probability
density function for each type of simulation result, click Analysis > Display PDF (Probab. Density Fct) of Values, where you can select whether the PDF is determined for one of the
following:
all prediction planes and all horizontal layers
all horizontal prediction planes
prediction planes and surfaces only
currently active horizontal prediction plane
zoomed area of the currently active horizontal plane
After selecting the area to be evaluated, you have to specify the quantization
interval, which is used to discretize the result data.
Note: Unpredicted result pixels (result values which are set to “not
computed”) are not considered for the generation of the PDF.
Figure 1. Example of a probability density function of a received power prediction.