Simulation Results for RIS-Assisted UAV THz Communication Framework

Figshare hosts simulation results for a proposed RIS-assisted UAV positioning framework to enhance Terahertz communication. The dataset, authored by M. Rudra Kumar, contains files in a 78.0 KB ZIP archive. It supports analysis of link robustness, achievable data rate, and user connectivity gains from coordinated UAV and Reconfigurable Intelligent Surface optimization.

Use Cases

• Analyze gains in achievable data rate from RIS configuration and UAV deployment optimization.
• Compare link robustness and user connectivity metrics across different simulated network configurations.
• Validate the performance of the reinforcement learning-based strategy for user grouping and phase-shift adaptation.

Strengths

• Dataset is openly licensed under CC BY 4.0, permitting sharing and adaptation.
• Results are focused on a specific, novel framework integrating RIS and UAVs for THz networks.
• Findings are recent, with a last update timestamp of March 2026.

Limitations

• The dataset is very small at 78.0 KB, indicating limited scope and likely a summary of results rather than raw simulation logs.
• No tabular data, column definitions, or sample data are provided, limiting direct analytical use.
• Content is specific to a single proposed framework, reducing generalizability to other communication systems.

Provenance

Source

M. Rudra Kumar via figshare

Collection Method

Simulation results from a proposed reinforcement learning-based optimization framework.

Freshness

Last updated March 2026.