# An E2E Simulator for 5G NR Networks

arXiv: https://arxiv.org/abs/1911.05534 · HTML: https://mlsanity.com/paper/1911.05534/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Nov 2019.

## Built on by (most cited first, 4 of 4)

- [A Synthetic Dataset for 5G UAV Attacks Based on Observable Network Parameters](https://mlsanity.com/paper/2211.09706/) (2022)
- [Agentic-V2X: Small Language Model Agents for Deadline-Aware V2X Scheduling in 5G/6G Networks](https://mlsanity.com/paper/2607.04290/) (2026)
- [NS3Learn: Transferring 5G NR Mode-2 Reception Realism from ns-3 to the Veins/SUMO Stack for Connected-Vehicle Safety Assessment](https://mlsanity.com/paper/2609.20578/) (2026)
- [Network-in-the-Loop at Scale: GPU-Batched 5G Simulation for Massively Parallel Robot Learning](https://mlsanity.com/paper/2610.02370/) (2026)

## Abstract (arXiv)

As the specification of the new 5G NR standard proceeds inside 3GPP, the availability of a versatile, full-stack, End-to-End (E2E), and open source simulator becomes a necessity to extract insights from the recently approved 3GPP specifications. This paper presents an extension to ns-3, a well-known discrete-event network simulator, to support the NR Radio Access Network. The present work describes the design and implementation choices at the MAC and PHY layers, and it discusses a technical solution for managing different bandwidth parts. Finally, we present calibration results, according to 3GPP procedures, and we show how to get E2E performance indicators in a realistic deployment scenario, with special emphasis on the E2E latency.