Wireless communications in time variant ad-hoc networks is very challenging. The increasing demand for mobile multimedia and safety applications in time-variant environments requires new concepts for the development of such wireless systems. Time variant scenarios can be found in several environments:
- Car-to-car (or car-to-infrastructure) communication scenarios
- MESH and sensor networks in time-variant scenarios
- Wi-Fi hotspots in railway stations, airports or city centers
- Stations and underground mines with moving trains
- Airports with moving airplanes
- Elevators inside buildings
The main difference in such applications compared to the classical network planning is the time variance of these scenarios. The locations of transmitters, receivers, and obstacles are time-variant (i.e. moving). These effects influence the propagation and lead to time variant channel impulse responses. Doppler shifts and the directional channel impulse response are mandatory results when simulating such time-variant scenarios.
Definition of Time Variant Scenarios
The tool WallMan
of the WinProp suite can be used to define the movement of the objects in the time variant scenarios. Time variant behavior can be assigned individually to each element in the vector database or to groups of objects. Further information about the definition of the time-variant behavior is available on the database page.
Propagation Model for Time Variant Scenarios
For the time-variant scenarios all propagation models of the indoor scenarios
can be used. Besides the indoor propagation models also a new ray-optical model is available to predict additionally the Doppler shift for each propagation path (see figure).
The following images show some computation results of WinProp. Please click on the images to enlarge them:
|Application: Car-to-Car Scenario
Application: Adaptive Cruise Control
||Application: Railway Station
Computed propagation paths in a car-to-car scenario.
The development of ad-hoc networks used for car-to-car and car-to-infrastructure communications requires an analysis of the radio channel between the cars. Thus it is evident to understand this radio link and to model it with accurate propagation models.
Computed propagation paths in an ACC scenario
The development of adaptive cruise control (ACC) relies on a deep understanding of the radar channel between the car and its environment. Simulations of this radio channel help to improve the algorithms for angle and distance estimation.
Main station with trains
The planning of radio coverage in areas with significant time-variance is more reliable if the time-variance is included in the simulations. So drop-outs can be seen and analyzed easily. Especially for train stations (also underground stations) and airports the models for the time variant scenarios are important.