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) , (2) ], FAX: [(1) (2) ]
[(1) (2)
Abstract: [The robust ranging algorithm is proposed for the alternative PHY for a]
Purpose: [This submission is in response to the committee’s request to submit the proposal enabled by an alternate TG4a PHY]
Notice: This document has been prepared to assist the IEEE P 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 P

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

5. Other Architectures for Comparison
BPF
( )2
LPF /
2-4ns
integrator
ADC
"Path-arrival dates" table
1D to 2D Conversion
Assumption path synchronization Matrix
Filtering + Assumption/path selection
Time base 1-2ns accuracy
Time stamping
Analog comparator
FT R&D
TOA Estimator
Sliding Correlator
Energy combining across symbols
interference suppression
1D-2D Conversion
2D-1D Conversion
Energy image
generation
Bipolar template
I2R
1D to 2D Conversion
Length-3 Vertical Median or Minimum Filtering
Removes interference
2D to 1D Conversion with Energy Combining
Energy image generation
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
N = 32
Accumulation of signals
(Preamble symbols-1) x 31 chip sequences adds.
992 op. (= 32 x 31, assuming preamble symbols is 31)
N point FFT
(Two FFTs)
2x(N/2)log2N complex mults.
2xNlog2N complex additions
960 op. (=2x80 complex mults= 2x4x80 real mults. + 2x2x80 real adds.)
640 op. (= 2x160 complex adds. = 2x320 real adds.)
Correlation
(3 times)
3xN*N real multiplication
3xN*(N-1) real addition
3072 op. (=3x1024 real mults.)
2976 op. (= 3x992 real adds.)
Noise Subspace
N complex multiplication
192 op.
(=128 real mults real adds.)
Finding Peaks
N-1 Comparison
31 comparisons
Total Operations
8863 op.
Memory size N 32

9. Complexity of Algorithm by MERL
N = 32
N x N image*
(N-2 x N-2) x 32
rearrange operations
8100 op. (= 30 x 30 x 32)
2D to 1D conversion
(Preamble symbols-1) x 31 chip sequences adds.
992 op. (= 31 x 32)
Total operation
9092 op.
Memory size
N x N = N2
1024
- Complexity Ratio = Proposed/MERL = 8863/9092 = 97.5%
-> Almost same
* Sorting (3 point Median Filtering)
= 32 rearrange operations = (Compare & allocation) = 9

10. Complexity of Algorithm by I2R
N = 32
Sliding Correlation
N*N real adds.
1024 real adds.
N/2 x N image
sliding correlation x 31 chip sequences
31744 op. (= 1024 x 31)
2D to 1D conversion
(Preamble symbols-1) x 31 chip sequences adds.
465 op. (= 15 x 31)
Total operation
32209 op. (= )
Memory size
Preamble symbols x 31 chip sequences
496 (= 16 x 31)
- 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
SNR 8dB
True TOA
True TOA

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

14. Simulation Results
SNR 9dB
True TOA
True TOA

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

16. Simulation Results
SNR 14dB
True TOA
True TOA

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

18. Simulation Results
SNR 17dB
True TOA
True TOA

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

20. Simulation Results
SNR 22dB
True TOA
True TOA

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

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
SNR 10dB
True TOA

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

25. Simulation Results
SNR 11dB
True TOA

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

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. Conclusions Advantages Future work Low complexity and high performance
Low memo
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 work
Need comprehensive simulation
Consider the SOP environment