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---
license: apache-2.0
language:
- en
pretty_name: satcom_qa
tags:
- satellite
- communications
size_categories:
- n<1K
---
# 🛰️ SATCOM Question-Answer Dataset
## Dataset Summary
**SATCOM-QA** is a **human-generated evaluation dataset** designed for testing LLM reasoning in Satellite Communications (SatCom).
It contains around 1,000 open-ended questions, of which about 30% involve mathematical or quantitative SatCom reasoning (e.g., link budget calculations, path loss, beamforming, SNR, orbital geometry).
The dataset is designed for evaluation purpose.
---
## Key Features
* **Human-written** questions & answers
* **Open-ended** free-form responses
* **Covers core SatCom/NTN domains**, including:
* Link Budget
* Propagation & Path Loss
* Frequency bands
* Beamforming & antennas
* Multi-layer NTNs (satellites, HAPS, UAVs)
* 6G integration
* Localization with NTNs
* 30% math-focused problems
* Includes **reference links** to the answers provided
* No synthetic content, no model-generated text
---
## Intended Use
* Benchmarking LLMs on **technical SatCom reasoning**
* Testing domain-specific expertise for
* NTN/6G research
* Satellite engineering
* Telecommunications academia/industry
* Evaluating mathematical reasoning in real-world SatCom tasks
---
## Data Structure
### Fields
* **question** *(string)*
* **answer** *(string, human-written)*
* **topic** *(string: e.g., Link Budget, Beamforming, NTNs, etc.)*
* **sources** *(list of URLs — academic references)*
* **math_required** *(bool)*
---
## Source Material
Questions are based on **public academic literature**, including (examples):
* Multi-layer NTN architectures (ResearchGate)
* Integrated 6G TN/NTN (ResearchGate)
* NTN localization (arXiv)
* Link budget fundamentals (open-access journals)
## Example
```python
from datasets import load_dataset
ds = load_dataset("esa-sceva/satcom-qa")
test_ds = ds["train"]
print(test_ds[0]["question"])
print(test_ds[0]["answer"]) |