Home
AMan
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.
Introduction
Radio network planning tools rely on accurate wave propagation models to predict the path loss between two arbitrary points.
Antenna Pattern Basics
The radiation pattern of an antenna is a graphical representation or mathematical function that indicates the angular dependence of radiation from the antenna.
Conversion of 2x2D Patterns (Horizontal & Vertical) to 3D Patterns
Weighted Bilinear Interpolation (WBI) Algorithm

Welcome
Release Notes
See what's new in the latest release.
Get Started
The WinProp Getting Started Guide contains step-by-step instructions on how to get started with WinProp.
Examples
The Altair installation directory contains a collection of examples that shows you WinProp concepts and essentials.
Introduction to WinProp
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.
Typical Workflow in WinProp
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.
WallMan
The WallMan component offers a convenient facility to generate and edit vector building databases.
TuMan
The TuMan tool enables you to generate and modify tunnel scenarios.
AMan
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.
- Introduction
  Radio network planning tools rely on accurate wave propagation models to predict the path loss between two arbitrary points.
  - Antenna Pattern Basics
    The radiation pattern of an antenna is a graphical representation or mathematical function that indicates the angular dependence of radiation from the antenna.
    - Isotropic Radiator
      An isotropic radiator is an ideal (theoretical) antenna operating without losses and having equal radiation in all directions.
    - Directional Characteristic of Antennas
      Commercial antennas do not radiate the same power density in all directions (in contrast to the isotropic radiator). There are always directions with higher power density and others with smaller power density.
    - Gain, Directivity and Other Parameters
      Antenna patterns are described by parameters such as gain, directivity, pattern lobes, half-widths, equivalent radiation angle, and effective area.
    - Mathematical Description of Antenna Patterns
    - Conversion of 2x2D Patterns (Horizontal & Vertical) to 3D Patterns
- Multiple Antenna Scenario Configuration (MASC)
- Using AMan
- Default Shortcut Keys
  View the default shortcut keys available for AMan for faster and easier operation.
ProMan
The ProMan component includes wave propagation models for different scenarios and network planning simulators for various air interfaces.
Methods
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).
Main Applications
In WinProp various air interfaces and applications are pre-defined: broadcasting, cellular, wireless access, WiFi, sensor networks, ICNIRP and EM compliance.
WinProp Utilities
The WinProp utilities consist of the Launcher utility and the Updater.
Appendix
Reference information is provided in the appendix.

Weighted Bilinear Interpolation (WBI) Algorithm

This algorithm¹ is almost identical to the arithmetic mean (AM) algorithm. The gains and angle distances are also read from the vertical and horizontal pattern and are weighted according to their distances.

In contrast to the bilinear interpolation (BI) algorithm, the vertical angles are additionally weighted with the factor $(1 - \sin ϑ)$ . Therefore, the gain values read from the vertical pattern are no longer relevant in the horizontal plane (for $ϑ$ = 90°), and the horizontal pattern is, therefore, more accurate.

The mathematical equation for the computation of the weighted bilinear interpolation is:

G (φ, ϑ) = \frac{(φ_{1} G_{φ 2} + φ_{2} G_{φ 1}) \frac{ϑ_{1} ϑ_{2}}{{(ϑ_{1} + ϑ_{2})}^{2}} + (ϑ_{1} G_{ϑ 2} + ϑ_{2} G_{ϑ 1}) \frac{φ_{1} φ_{2}}{{(φ_{1} + φ_{2})}^{2}}}{(φ_{1} + φ_{2}) \frac{ϑ_{1} ϑ_{2}}{{(ϑ_{1} + ϑ_{2})}^{2}} + (ϑ_{1} + ϑ_{2}) \frac{φ_{1} φ_{2}}{{(φ_{1} + φ_{2})}^{2}}}

An alternative method to describe the interpolation is given below:

Figure 1. Angles and gains used for the weighted bilinear interpolation.

G (ϑ, φ) = \frac{d_{t i l t 1} \cdot G_{t i l t 2} + d_{t i l t 2} \cdot G_{t i l t 1} + d_{r o t 1} \cdot (1 - \sin ϑ) \cdot G_{r o t 2} + d_{r o t 2} \cdot (1 - \sin ϑ) \cdot G_{r o t 1}}{d_{t i l t 1} + d_{t i l t 2} + d_{r o t 1} \cdot (1 - \sin ϑ) + d_{r o t 2} \cdot (1 - \sin ϑ)}

The weighted bilinear interpolation leads to more accurate results compared to bilinear interpolation (BI) algorithm. The mean error is approximate 1.3 dB and the standard deviation is 0.6 dB for a $\frac{λ}{2}$ - dipole.

The most accurate results can be obtained with this algorithm if the main radiation of the antenna is in the horizontal plane.

¹ A 3D Interpolation Method for Base-Station-Antenna Radiation Patterns in IEEE Antennas and Propagation Magazine, F. Gil, A. Claro, J. Ferriera, C. Pardelinha, and L. Correia, Vol. 43, No.2, April 2001.