5G Ship-to-Satellite Communication
Final Year Project — 28 GHz 5G Communication
Deep Neural Network for real-time phased array beam steering.
Enabling reliable ship-to-satellite communication at millimeter-wave.
Project Showcase
Watch how our DNN-powered beam steering system works — from MATLAB simulation to real hardware deployment on TMYTEK BBox.
* In video data are dummy,scroll down and contact us for real data
Architecture
Simulate 4-element ULA with mutual coupling at 28 GHz using MATLAB Phased Array Toolbox. Generate 121 training samples across ±60°.
Train custom neural network (1→64→128→64→8) with sin/cos phase encoding. Backpropagation from scratch, no Deep Learning Toolbox needed.
Three-way comparison: Mathematical model vs DNN vs Optimal. DNN achieves 1.38° MAE with mutual coupling compensation. Verified on TMYTEK TMXLABKIT hardware.
Predict phase shifts, voltages, and power in <1ms. Hardware-ready outputs for 6-bit phase shifter with 0–5V control.
Closed-loop Python script connects to TMYTEK BBox via Ethernet. Automatically sweeps beam to lock onto the strongest LTC5596 power signal.
Neural Network
Interactive
Adjust the steering angle to see predicted phase shifts, voltages, and radiation pattern for the 4-element array. Power values are from real TMYTEK hardware measurements.
Hardware Integration
Connect to TMYTEK BBox N257 via the local bridge server. Control phase shifts and perform automatic beam tracking in real-time.
Performance
Over fixed antenna (no beam steering)
vs 50% without steering during LEO pass
Improvement over no-steering baseline
Pointing error despite ship roll ±8°
| Metric | No Steering | Mathematical | AEP-DNN |
|---|---|---|---|
| Link Availability | ~50% | ~75% | ~90% |
| Avg Channel Capacity | ~100 Mbps | ~200 Mbps | ~250 Mbps |
| Pointing Error | Large | ~5° | <1° |
| Coupling Compensated | No | No | Yes |
Technical