Validation of Radio Channel Models using an Anechoic Chamber

1. Validation of Radio Channel Models using an Anechoic Chamber Yuhao Zheng, David M. Nicol University of Illinois at Urbana-Champaign

2. Outline Introduction & anechoic chamber Experimental framework Radio channel models Experiment results Conclusions & future works

3. Introduction • Wireless network simulation is popular • Fidelity is a problem • Especially for radio channel model • Higher layers depend on physical layer • Tradeoff: accuracy ↔ computational cost • Simple models: free space, two ray • Complex models: raytracing, Transmission Line Matrix (TLM)

4. Our Focus Tx Rx • Complex models: Raytracing, TLM • Received signal strength • Sensitivity experiments • Small changes in environment • How does a model reflect this? • Problems • Need accurate measured value for validation • Anechoic chamber

5. Anechoic Chamber • Illinois Wireless Wind Tunnel (iWWT) • Characteristics • No outside interferences • No inside reflections • Ideal wireless testbed • “Free space” inside

6. Experimental Framework chamber wall experiment measured model predicted compare & validate reflector (material varies) 11 ft wireless node Soekris Engineering net4521 transmit pkts record RSS attenuator (directional) 20 ft

7. Simple Raytracing Model  a series of points n points Contribution of this single reflection path: de di ai ae N • Wireless node  single point • Assumption: omnidirectional antenna • Attenuator  fixed pathloss coefficient • Depends on direction • Reflector  line • Material-dependent reflection rate, tuned offline

8. Advanced Raytracing Model Im direct path reflected path n points • More general radio model • Single point  point matrix de di ai ae Re N • Consider path loss & path delay • Revision to single reflection path • Complex number addition

9. Transmission Line Matrix Model • Even-based Transmission Line Matrix [Nutaro’06] • Space  cells displacement  state • A cell can change state when • External event: from adjacent cells • Internal event: when not at equilibrium position • Implementation details • Grid size = λ/D, D is tunable • Source: sinusoidal • RSS: average over time

10. Experimental Results small-scale movement large-scale movement 11 ft direction A direction B 20 ft

11. Results – Large-scale Movement direction A  can capture the peakbut not exact shape ~2dB error direction B 

12. Results – Small-scale Movement direction A  cannot capture the shape ~2dB error direction B 

13. Results – Radio Beamform wireless box @rotating table spectrum analyzer

14. Results – Radio Beamform up to 10dB variation!

15. Results – Resolution of Raytracing converged, n=9 is good

16. Results – Resolution of TLM not converged, D=8 is the best

17. Conclusions & Future Works • Conclusions • 2dB error of both raytracing & TLM • Model uncertainty > error eliminated by chamber • Validation outside the chamber may be okay • Future works • Quantify the speed of different models • Consider the beamform of antenna

18. Backup Slides

19. Result – Antenna Shape

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