5G NR & 6G Network Simulation

gNB · UE · 5G Core · MIMO · Beamforming · Slicing

NetSim is a system-level simulator for modeling 5G/6G networks end to end. Build network digital twins, design and test new protocols, and plan deployments that account for real wireless propagation. Protocol source code is provided in C, with an external interface to Python.

AI/ML in the RAN MIMO & beamforming Network slicing SA / NSA HARQ & link adaptation

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NetSim · 5G NR design window

NetSim's 5G NR design window showing a gNB serving multiple UEs

Who uses NetSim 5G

The industry's leading system-level simulator for 5G/6G lets users create digital twins to optimise protocol and application performance, design new technologies, and plan deployments with accurate propagation impairments.

Mobile operators & CSPs

Use off-the-shelf models and analysis tools to investigate network capacity, peak throughput, and end-to-end latency.

Equipment manufacturers

Test and demonstrate designs in realistic scenarios before production
Generate synthetic data to train AI/ML models

Universities & research

Accelerate R & D on new protocols and algorithms
Write your own algorithms by modifying the NetSim source code

End-to-end 5G simulation

Full-stack, packet-level simulation with link-level abstractions, an intuitive interface, and source code included.

Full-stack packet level

End-to-end simulation of 5G networks across every layer, with system-level modelling and link-level abstractions.

Devices

UE, gNB (omni and sector), 5G Core (SMF, AMF, UPF), plus router, switch, and server.

Interactive UI

Drag-and-drop network design, a results dashboard, and an interactive plots window.

Traffic generation

FTP, HTTP, Voice, Video, Email, Gaming, and custom traffic, with configurable data rate, packet size, and inter-arrival times.

Telemetry

Radio measurements, radio resource allocation, and per-packet trace files for deep analysis.

Protocol source in C

Every layer ships with C source code, so you can modify the stack and build custom protocols.

Python interface

An external interface to Python supports automation, AI/ML workflows, and run-time control.

AI/ML in the RAN

Couple NetSim with machine learning, for example AI/ML in the RAN and online slicing algorithms.

NetSim 5G results dashboard and plots window

The NetSim results dashboard and plots window shown after a 5G NR run.

The 5G NR protocol stack

Specifications modelled from the 5G Core down to the radio, aligned to the relevant 3GPP series. Every band, numerology, and timer below is configurable.

Core

5G Core

Functions and interfaces based on TS 23.501 and TS 23.502
Interfaces: N1/N2, N3, N4, N6, N11, XN
Core devices: SMF, AMF, UPF

Deployment

SA and NSA modes

5G SA (standalone) architecture
5G NSA for LTE–5G dual connectivity, leveraging existing LTE RAN/EPC
NSA options 4, 4a, 7, and 7a

RLC

Radio Link Control (38.322)

TM (transparent), UM (unacknowledged), AM (acknowledged) modes
Segmentation and reassembly of RLC SDUs
t-reassembly and t-pollRetransmit timers

PDCP

Packet Data Convergence (38.323)

Maintenance of PDCP sequence numbers
Discard timer and t-Reordering timer
Transmit and receive buffer maintenance

MAC

Medium Access Control

Multiplexing and de-multiplexing of MAC SDUs onto transport blocks
Schedulers: Round Robin, Proportional Fair, Max C/I, and PFS with rate guarantee (how the scheduler works)
Link adaptation:
- Inner loop (ILLA): sets MCS from CQI
- Outer loop (OLLA): adjusts MCS from HARQ ACK/NACK to meet target BLER
Handover: inter- and intra-frequency, A3-event based, with configurable interruption time, margin, time to trigger, and cell individual offset (CIO)

Slicing

Network slicing

Slice types: BE, eMBB, URLLC, MIoT, V2X
Static resource sharing by percentage of resources allocated
Dynamic resource sharing via an online machine-learning algorithm

PHY

Frame structure & numerology

Uplink and downlink physical channels, frame structure, and physical resources
Flexible sub-carrier spacing using multiple numerologies:
- FR1: µ = 0, 1, 2
- FR2: µ = 2, 3
Carrier aggregation: intra-band and inter-band
PHY modulations: BPSK, QPSK, 16QAM, 64QAM, 256QAM

PHY

Frequency bands

FR1 TDD: n34, n38, n39, n40, n41, n50, n51, n77, n78, n79
FR1 FDD: n1, n2, n3, n5, n7, n8, n12, n20, n25, n28, n66, n70, n71, n74
FR2 TDD: n257, n258, n259, n260, n261, n262, n263

PHY

MIMO & beamforming

gNB antennas: 1, 2, 4, 8, 16, 32, 64, 128; UE antennas: 1, 2, 4, 8, 16
Spatial channel model (SCM): channel matrix H per Tx/Rx antenna pair
Gaussian channel with Rayleigh fast fading, i.i.d. Complex Normal (0, 1) per coherence time
Digital beamforming gain from the eigenvalues of the Gram (Wishart) matrix
2D parabolic sector antenna modelling (3GPP TR 37.840)

PHY

HARQ, BLER & coding

HARQ with soft combining
User-set target BLER, looked up from SINR–BLER data tables
SINR–BLER data for all MCS (1–28), base graphs (1, 2), and tables (1, 2, 3), generated by an in-house link-level simulator and validated against literature
Code block segmentation into code blocks (CB) and code block groups (CBG)

PHY

Interference & measurements

Downlink interference: exact geometric, interference over thermal
Uplink interference: interference over thermal
Per-TTI radio measurements: SINR, SNR, Rx signal level, pathloss, shadow-fading loss, beamforming gain, CQI, MCS
Per-gNB pathloss files importable from third-party tools such as MATLAB

RF propagation (38.900)

Log-distance mean pathloss, log-normal shadowing, Rayleigh fading
Environments: Rural Macrocell, Urban Macrocell, Urban Microcell, Indoor Office (mixed and open)
UE position indoor or outdoor; LOS and NLOS states
Outdoor-to-indoor: high-loss and low-loss models