Monte Carlo Simulation Results for THz UAV Communication Networks

100 Monte Carlo trials provide statistical reporting for simulation parameters in Terahertz UAV communication networks. The dataset contains key results from a study on Reconfigurable Intelligent Surface-assisted UAV positioning and optimization. It was authored by M. Rudra Kumar and published on figshare in March 2026.

Use Cases

• Analyze statistical distributions of Achievable Data Rate across 100 Monte Carlo trials to assess network performance.
• Validate simulation parameters for UAV Positioning Within and UAV Deployment strategies under Severe Path Loss conditions.
• Model High Sensitivity and propagation conditions for High Data Rates in Reconfigurable Intelligent Surface-enabled networks.
• Benchmark the performance of the Combines Modified K algorithm for UAV Coordination and optimization.

Strengths

• Contains results from 100 Monte Carlo trials, providing a basis for statistical analysis.
• Focuses on a specific, advanced research area: Terahertz communications with UAVs and Reconfigurable Intelligent Surfaces.
• Released under the permissive CC BY 4.0 license for broad reuse.

Limitations

• The dataset is very small at 77.4 KB, indicating limited scope and likely summary statistics rather than raw trial data.
• Specific columns, sample data, and row counts are unknown, limiting immediate analytical utility.
• Data is generated from simulations, not real-world measurements, which may not capture all practical environmental factors.

Provenance

Source

figshare, authored by M. Rudra Kumar.

Collection Method

Generated from Monte Carlo simulations based on defined parameters.

Freshness

Last updated March 2026.