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harq-evaluation

Evaluate HARQ efficiency in 5G NTN using Monte Carlo simulations.

Updated Jun 10, 2026
Search Tags:#simulation#Monte Carlo#5G#NTN#HARQ
One-click install
npx skills add https://github.com/duonghoang2601/5g-ntn-harq --skill harq-evaluation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: harq-evaluation
Source: https://github.com/duonghoang2601/5g-ntn-harq/tree/main/report
Command: npx skills add https://github.com/duonghoang2601/5g-ntn-harq --skill harq-evaluation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, scipy, matplotlib, tqdm, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the evaluation of HARQ efficiency in 5G NTN, providing insights into link gain, orbit-SCS combinations, and energy efficiency through Monte Carlo simulations.

Core Features & Use Cases

  • Monte Carlo Simulations: Perform simulations to quantify HARQ performance across various dimensions.
  • Performance Metrics: Evaluate link gain, advantage over No-HARQ, and GEO pipeline utilization.
  • Use Case: Analyze the effectiveness of IR-HARQ in 5G NTN for LEO orbits, considering SCS and process limits.

Quick Start

Use the harq-evaluation skill to run the full simulation suite for 5G NTN HARQ evaluation.

Frequently Asked Questions about harq-evaluation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I evaluate HARQ efficiency in 5G Non-Terrestrial Networks?▼

HARQ efficiency in 5G NTN is evaluated using Monte Carlo simulations to analyze IR-HARQ performance over LEO orbits and Rician channels, providing insights into link gain and energy efficiency.

What is the advantage of IR-HARQ in 5G NTN over a No-HARQ approach?▼

IR-HARQ provides a quantifiable link gain and energy efficiency advantage over No-HARQ in 5G NTN, measured by simulating LEO orbits and Rician channels under specific SCS and process constraints.

Can I use Monte Carlo simulations to analyze 5G NTN link performance for LEO orbits?▼

Yes, Monte Carlo simulations analyze 5G NTN link performance for LEO orbits by evaluating IR-HARQ efficiency, measuring link gain, and calculating GEO pipeline utilization under specific SCS and process constraints.

What Python dependencies do I need to run 5G NTN HARQ simulations?▼

Running 5G NTN HARQ simulations requires numpy, scipy, matplotlib, and tqdm to execute Monte Carlo iterations, process Rician channel data, and visualize link gain and energy efficiency results.

How do I simulate Rician channels for IR-HARQ performance evaluation?▼

Simulating Rician channels for IR-HARQ evaluation involves running Monte Carlo simulations across 5G NTN LEO orbits, utilizing scipy and numpy to model channel characteristics and measure link gain.

Does HARQ efficiency in 5G NTN change with different orbit-SCS combinations?▼

HARQ efficiency in 5G NTN varies significantly across different orbit-SCS combinations, and Monte Carlo simulations quantify these differences by measuring link gain and energy efficiency for LEO orbits under specific SCS constraints.

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