Robust Ranging Algorithm for UWB Radio: Proposal and Evaluation

1. Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) Submission Title: [Robust Ranging Algorithm for UWB radio] Date Submitted: [19 July, 2005] Source: [Cheolhyo Lee (1), Jae Young Kim (1), Eun Chang Choi (1), Chong Hyun Lee (2)] Company[(1) Electronics and Telecommunications Research Institute (ETRI) (2) Seokyeong University] Address[(1) 161 Gajeong-dong, Yuseong-gu, Daejeon, Republic of Korea (2) 16-1 Jungneung-Dong, Sungbuk-Ku, Seoul, Republic of Korea] Voice:[(1) +82 42 860 5577, (2) +82 2 940 7472], FAX: [(1) +82 42 860 5218 (2) +82 2 919 0345] E-Mail: [(1) clee7@etri.re.kr, (2) chonglee@skuniv.ac.kr] Abstract: [The robust ranging algorithm is proposed for the alternative PHY for 802.15.4a] Purpose: [This submission is in response to the committee’s request to submit the proposal enabled by an alternate 802.15 TG4a PHY] Notice: This document has been prepared to assist the IEEE P802.15. It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein. Release: The contributor acknowledges and accepts that this contribution becomes the property of IEEE and may be made publicly available by P802.15.

2. Robust Ranging Algorithm for UWB Radio Electronics and Telecommunications Research Institute (ETRI) Seokyeong University Republic of Korea

3. Outline • Proposed Algorithm • Proposed algorithm flow & summary • Comparisons of complexities with MERL and I2R • Simulations for CM1 • Simulations for CM8 • Conclusions

4. SNR Increase Compute Energy Convert Time to Frequency FFT High Resolution Algorithm Add few Frames & Compute Energy BPF ( )2 LPF / 1-4ns integrator ADC Proposed Algorithm TOA Estimator

5. Filtering + Assumption/path selection Time base 1-2ns accuracy Energy image generation Removes interference Assumption path synchronization Matrix Analog comparator Time stamping "Path-arrival dates" table 1D to 2D Conversion Length-3 Vertical Median or Minimum Filtering 2D to 1D Conversion with Energy Combining 1D to 2D Conversion BPF ( )2 LPF / 2-4ns integrator interference suppression Energy image generation Energy combining across symbols 1D-2D Conversion Sliding Correlator 2D-1D Conversion ADC Bipolar template Other Architectures for Comparison FT R&D TOA Estimator I2R MERL

6. Proposed Algorithm Flow • Algorithm based High Resolution TOA Finding the Subspace Finding Spectrum Finding TOA

7. Proposed Algorithm Summary • Required Operation: • Correlation • FFT • Comparison • Complexity (N: No. of Energy Block) • R: N point Correlation • FFT: N point FFT • Noise Subspace: N point scalar and vector multiplication • Peak Finding: N point comparison

8. Complexity of the Proposed Algorithms

9. Complexity of Algorithm by MERL - Complexity Ratio = Proposed/MERL = 8863/4064 = 218% -> Two times * Sorting (3 point Median Filtering) = 32 rearrange operations = (Compare & allocation) = 9

10. Complexity of Algorithm by I2R - Complexity Ratio = Proposed/I2R = 8863/32209 = 27.4% -> less than I2R

11. Simulation Parameters for CM1 • CM1 Channel considered • Ts = 1ns • SNR 8~22dB • 10 Frames are accumulated. • Three High Resolution Algorithms • Compare with MERL • True TOA = 10

12. Simulation Results True TOA • SNR 8dB True TOA

13. Simulation Results True TOA True TOA • SNR 8dB • High Resolution TOA VS MERL

14. Simulation Results True TOA • SNR 9dB True TOA

15. Simulation Results True TOA • SNR 9dB True TOA • High Resolution TOA VS MERL

16. Simulation Results True TOA • SNR 14dB True TOA

17. Simulation Results True TOA • SNR 14dB True TOA • High Resolution TOA VS MERL

18. Simulation Results True TOA • SNR 17dB True TOA

19. Simulation Results True TOA • SNR 17dB True TOA • High Resolution TOA VS MERL

20. Simulation Results True TOA • SNR 22dB True TOA

21. Simulation Results True TOA • SNR 22dB True TOA • High Resolution TOA VS MERL

22. Simulation Parameters for CM8 • CM8 Channel considered • Window length = 64 • Ts = 1ns • SNR 10~22dB • 5 Frames are accumulated. • High Resolution Algorithms • Compare with MERL • True TOA = 10

23. Simulation Results True TOA • SNR 10dB

24. Simulation Results True TOA • SNR 10 dB True TOA • High Resolution TOA VS MERL

25. Simulation Results True TOA • SNR 11dB

26. Simulation Results True TOA • SNR 11 dB True TOA • High Resolution TOA VS MERL

27. Simulation Results • SNR 13dB

28. Simulation Results • SNR 13dB • High Resolution TOA VS MERL

29. Simulation Results • SNR 17dB

30. Simulation Results • SNR 17dB • High Resolution TOA VS MERL

31. Key Issue • Complexity • FFT is just the order of O(Nlog2(N))=> O(N) • What is the complexity of correlator? -> equal or greater than O(N2) • It depends on how many correlation operation is required • Order of complexity • Proposed algorithm = MERL < I2R

32. Conclusions • Advantages • Low complexity and high performance • Small memory size • High performance for low SNR and SINR • Can be applied to Coherent system • Small TOA estimation error (by CM8 simulation) • Independent to signal waveform • Future works • Need comprehensive simulation • Consider the SOP environment