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Experience · Wireless Centre of Excellence

BT Group

Wireless Digital Twin & 5G Channel Modelling

Wireless Centre of Excellence · Digital Twins · RF Propagation · 5G

Developed a Python-based wireless digital-twin workflow using NVIDIA Sionna RT, OpenAirInterface and OAIBOX hardware to model radio propagation, generate time-varying channels and reproduce them through a hardware channel emulator for repeatable 5G testing.

PythonNVIDIA Sionna RT5G NRRay TracingBeamformingChannel ModellingDigital TwinsOpenAirInterfaceHardware-in-the-Loop
01 — The Problem

Field trials are hard to reproduce

Real wireless field trials are expensive, time-consuming, hard to reproduce and sensitive to changing conditions. The aim: a digital-twin workflow where realistic propagation environments can be simulated, reproduced and measured repeatedly.

Real environment
Digital propagation model
Channel representation
Hardware channel emulator
5G hardware
Measured KPIs
02 — Digital Twin Pipeline

Simulation wired to real hardware

The core of the work connects a physics-based propagation model to actual 5G hardware emulation — it does not stop at plots from a propagation model.

3D Scene / Geometry
NVIDIA Sionna RT
Ray-Traced Propagation
CIR / CFR / TDL
DEE / Set-Loss Channel Profile
Spirent Vertex Channel Emulator
OAIBOX + OpenAirInterface
SINR · RSRP · BLER · Throughput · MCS
03 — Scene & Propagation

Ray-traced radio environments in Sionna RT

I built the simulation workflow in Python with NVIDIA Sionna RT — one transmitter and multiple indoor / outdoor receiver positions in a reproducible scenario.

Handled
  • 3D scene configuration
  • Transmitter / receiver placement
  • Carrier frequency
  • Bandwidth
  • Antenna configuration
  • Ray tracing
  • Radio maps
Bands / bandwidth
  • 3.5 GHz
  • 7.05 GHz
  • 100 MHz bandwidth

The framework supported the 3.5 / 7.05 GHz comparison, but broader 7.05 GHz hardware sweeps were limited by time and equipment access — not all were completed.

04 — Antenna Arrays

Uniform planar arrays, aperture-preserving scaling

Transmitters were modelled as Uniform Planar Arrays rather than point sources. Moving from 3.5 GHz to 7.05 GHz, element count could increase while keeping a comparable physical aperture — so the comparison of lower-frequency coverage vs higher-frequency spatial / array gain stays meaningful.

Isotropic elements3GPP TR 38.901 patternsλ/2 spacingArray steering vectorsPhysical aperture
05 — Beamforming

Conventional · Zero-Forcing · MMSE

UE positionsSteering vectorsChannel matrixBF / ZF / MMSE precoderSignal + interferenceSINR
Array responseSteering vectorsComplex linear algebraRegularisationInter-user interferencePower normalisation
06 — Radio KPIs

Engineering metrics, not just rays

SINRRSRPBLERThroughputMCSCoverage RatioEmpirical CDFs

Throughput estimates came from SINR with a capped spectral-efficiency model; hardware runs provided actual 5G link KPIs.

07 — Ray Tracing

Stochastic launching + deterministic paths

Monte Carlo ray launching

Rays sampled and launched from the transmitter, scored on whether they reached a capture region around a receiver — efficient orientation-dependent statistics.

Rays launchedRays capturedCapture probability

Deterministic path tracing

Sionna RT's path solver for physically valid paths, up to five interactions.

Line of sightReflectionsRefractionsMultipath
08 — Rays → Channels

From geometry to channel representations

Ray pathsDelay + complex amplitudeCIRCFR / TDL
CIR
  • Path gains + propagation delays
CFR
  • Channel behaviour across frequency
TDL
  • Discrete channel for baseband sim / emulation
09 — Mobility & Doppler

Time-varying channels

Kinematic recomputation

Re-run ray tracing as positions change.

Doppler-only evolution

Reuse a ray solution and evolve its complex path coefficients using Doppler shifts.

The time-dependent channel H(f, t) was evaluated across an OFDM grid (1024 subcarriers, 30 kHz spacing): delay–Doppler spectra, subcarrier and CFR evolution, average gain vs time and frequency.

Doppler-only evolution closely tracked full kinematic recomputation for small per-step displacements. When geometry changes significantly (new occlusions or reflection points), full ray re-tracing is still required.

10 — Hardware-in-the-Loop

Reproducing channels on real RF

Simulated channel behaviour was taken beyond software and reproduced on hardware, so controlled channels could be measured without relying on uncontrolled over-the-air propagation.

Sionna RT
Time-varying CIR / path-loss
DEE files / Set-Loss values
Spirent Vertex
Fading / attenuation on RF ports
OAIBOX · OAI 5G NR
Real link KPIs
11 — Baseline Scenario

A reproducible golden baseline

A UE moves around a transmitter on a circular trajectory at 3.5 GHz, establishing a stable baseline before more complex interference and mobility scenarios.

Distance-based path lossAntenna patternSmooth lognormal shadowingMultipath fadingDoppler
12 — Results

Measured hardware baseline

Median SINR≈ 23.5 dB
Mean RSRP≈ −96 dBm
Mean DL throughput≈ 359 Mbps
Mean BLER≈ 1%
In-sync ratio≈ 1.0
Capture duration≈ 96 min

Stable SINR, RSRP, throughput and BLER showed the simulation-to-hardware chain produced a controlled, repeatable baseline suitable for further experimentation — not full validation of every 5G scenario.

13 — What I Developed

Across the whole stack

Simulation

Python simulation framework3D scene setupRadio mapsAntenna arraysFrequency-band configuration

Signal Processing

BeamformingZero ForcingMMSEComplex channel matricesSINR analysis

Propagation

Ray TracingMultipathCIRCFRTDLDoppler

Hardware

OAIBOXOpenAirInterfaceSpirent VertexChannel EmulationKPI Measurement
14 — Skills Developed

What the internship built up

Wireless Modelling

Radio-Propagation ModellingMultipath AnalysisChannel Impulse ResponsesFrequency-Selective ChannelsTime-Varying ChannelsDoppler Modelling

Antennas & Beamforming

Uniform Planar ArraysArray SteeringBeamformingZero-Forcing PrecodingMMSE PrecodingAperture Scaling

Numerical / Software

PythonNumPyComplex Linear AlgebraSimulation AutomationData ProcessingScientific Visualisation

Digital Twins

Scene ModellingPhysics-Based SimulationSimulation-to-Hardware PipelinesReproducible TestingModel Validation

5G / RF Systems

5G NRSINRRSRPBLERMCSThroughputOAI

Hardware Integration

OAIBOXChannel EmulationHardware-in-the-LoopRF Test Workflows
15 — Engineering Honesty

Potential extensions, not completed results

The completed hardware results establish a controlled single-cell, single-UE, 3.5 GHz baseline. Due to internship time and intermittent equipment access, these broader experiments were not fully executed:

Multi-cell interferenceFull beam-sweep hardware comparisons7.05 GHz hardware campaignRicher fading / Doppler modelsMulti-UE scheduling
Recommendation

Supervisor recommendation

Recommendation from Dr. Ryan HusbandsWireless Research Manager, Adastral Park · BT Group