1. Date Submitted: [24 June 2005]
1 December 2018
Project: IEEE P Working Group for Wireless Personal Area Networks (WPANs)
Submission Title: [Non-coherent ranging results with a-priori knowledge of noise variance]
Date Submitted: [24 June 2005]
Source: [Ismail Guvenc, Zafer Sahinoglu, Andy Molisch, Philip Orlik, Mitsubishi Electric]
Contact: Zafer Sahinoglu
Voice:[ ,
Abstract: [This document provides performance results of non-coherent ranging receivers, under the assumption that noise variance is accurately estimated and available a-priori]
Purpose: [To help objectively evaluate ranging proposals under consideration]
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. Option-III (Ternary Sequences)
Proposed System Parameters (With Same # Pulses per unit time) (by MERL)
Option-I (Burst PPM)
The Other Bit
One Bit
Always Empty
Always Empty
Always Empty
4-pulses
4 pulses
Option-III (Ternary Sequences)
………………………… 1 2 3 31 4 5 6 7 8 30
Pulse Repetition Interval ~ 62.5ns
Option-IV (Pulse PPM)
Tp = 4ns
Tf = ~125ns
PRP ± TH

3. Energy Detection Receiver Architectures
"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
BPF
( )2
LPF /
2-4ns
integrator
ADC
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

4. Simulations Observation window = 512ns TOA Ambiguity = 256ns
1 December 2018
Observation window = 512ns
TOA Ambiguity = 256ns
Ts3 = 2048ns*
Option 3
(16 pulses per 2us)
Option 1 **
(16 pulses per 2us)
Option 4 (16 pulses per 2us)
In our simulations, a base signal in each option is considered to be 2us long. TOA ambiguity of 256 ns is assumed. In other words, the delay is uniformly distributed within the first 256ns. Observation window is equal to the symbol duration in option-1 and option-4. It corresponds to 1 quarter of the symbol duration in option-3. Therefore, we expect the performance of ternary signaling to degrade to some extent when half a symbol duration TOA ambiguity is assumed.
Ts1 = Ts4 = 512ns
* Since option-3 uses 31 chip sequences, 1984ns symbol duration is used for option-3 to have multiples of 4ns sampling duration. However, total energy used within 4ms duration are identical for all cases.
** A training sequence of all 1’s are used. Random training sequence will introduce self interference that will degrade the performance.
Saturday, December 01, 2018

5. Threshold Selection
Assume that µn and σn2 mean and the variance of the noise respectively
Probability that a noise only sample greater than a threshold ε is
Probability of threshold crossing within K consecutive noise only samples
The corresponding threshold is
PFA ε

6. Results
PFA = 0.1, TB = 4ns

7. Results
PFA = 0.05, TB = 4ns

8. Results
PFA = 0.01, TB = 4ns

9. Results
PFA = 0.005, TB = 4ns

10. Results
PFA = 0.001, TB = 4ns

11. Results
PFA = 0.1, TB = 2ns

12. Results
PFA = 0.05, TB = 2ns

13. Results
PFA = 0.01, TB = 2ns

14. Results
PFA = 0.005, TB = 2ns

15. A-priori knowledge of noise variance improved ranging performance
Conclusion
A-priori knowledge of noise variance improved ranging performance
Threshold is set according to the noise variance and probability of missing a block, not according to the percentage of the highest signal energy block
This made option-4 suffered.
Option-1 (after processing gain) performed the best both in terms of 3ns confidence level and mean absolute error (MAE).
3ns confidence level can be 90% around 15dB, at 4ns sampling interval, and around 13dB at 2ns sampling interval
MAE is around 2ns at 15dB at 4ns sampling interval, and at 13dB at 2ns sampling interval

16. Transmitted Time-hopping Sequence ACF of the Transmitted Time-hopping
Zero Correlation Zone
Multipath
components
Peak
Leading
Edge
Received energy
samples (after
processed with the
time-hopping code)
Search-back the
leading edge
Saturday, December 01, 2018

17. When the signal energy increases, the leading edge energy increases
Peak SB
When the signal energy increases, the leading edge energy increases
However, energy of the sidelobes increases as well
It becomes more likely to pick multipath components from the ACF’s sidelobe when searching back the leading edge
Therefore, increasing the Eb/No may hurt after some point