Effects of urban microcellular environments on ray-tracing-based coverage predictions

Area of Science:

• Electromagnetics and Wave Propagation
• Computational Physics
• Telecommunications Engineering

Background:

• Ray-tracing (RT) is a deterministic method for studying wave propagation, crucial for urban microcellular environments.
• RT model accuracy heavily relies on detailed environmental information, including geometric and electrical parameters.
• Balancing database costs with prediction accuracy is essential for practical RT applications.

Purpose of the Study:

• To investigate the impact of environmental information inaccuracies on RT-based wave propagation predictions.
• To guide the selection of appropriate database accuracy levels for cost-effective RT modeling.
• To analyze the trade-offs between database costs and prediction accuracy in urban microcellular environments.

Main Methods:

• Generated artificial erroneous digital maps to simulate inaccuracies in geometric (building layout) information.
• Systematically compared RT predictions using original and erroneous maps against measurements.
• Investigated the influence of random errors on Root Mean Square (RMS) delay spread.
• Simulated path loss and RMS delay spread by varying dielectric constant and conductivity of building materials.

Main Results:

• Inaccuracies in geometric environmental data significantly affect RT-based coverage predictions.
• Random errors in geometry impact RMS delay spread results.
• Variations in electrical parameters (dielectric constant, conductivity) influence path loss and RMS delay spread predictions.

Conclusions:

• Environmental data accuracy is critical for reliable RT wave propagation predictions in urban settings.
• Database accuracy requirements should be carefully considered to achieve optimal cost-prediction accuracy trade-offs.
• The study provides insights for building accurate and cost-efficient environmental databases for RT models.