1. Submission Title: [Resolving the Ambiguity in IMST Measurements]
<month year>
doc: IEEE c
May 2006
Project: IEEE P Working Group for Wireless Personal Area Networks (WPANs)
Submission Title: [Resolving the Ambiguity in IMST Measurements]
Date Submitted: [May 2006]
Source: [Alexei Davydov, Alexander Maltsev, Ali Sadri ]
Company: [Intel Corporation]
Address: [Intel Corporation, Evening Creek Drive, San Diego , CA , USA]
Abstract: [Proposed the procedure for resolving the ambiguity in IMST measurements]
Purpose: [Contribution to TG3c at May 2006 meeting in Jacksonville, USA]
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
Alexei Davydov (Intel Corporation)
<author>, <company>

2. Agenda IMST measurement scenarios review
May 2006
Agenda
IMST measurement scenarios review
Comparison of results for angle measurements with and without ambiguity
Description of simplified three-dimensional ray-tracing model
Cluster identification methodology
Inter-cluster time of arrival statistics
Summary
Alexei Davydov (Intel Corporation)

3. Measurement scenarios plan
<month year>
doc: IEEE c
May 2006
Measurement scenarios plan
LOS
NLOS
Edge
Alexei Davydov (Intel Corporation)
<author>, <company>

4. Measurements Scenarios
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doc: IEEE c
May 2006
Measurements Scenarios
Library environment with tables, chairs and metal bookshelves with books
3 main types of measurement scenarios
LOS: unobstructed line of sight conditions
Edge: partially obstructed line of sight by the edge of a metal bookshelf
NLOS: non line of sight obstructed by a densely filled bookshelf
3 types of RX antennas (horn, wideband dipole array antenna, biconical)
Fixed TX lens antenna position at the suspended ceiling, RX measurements range ~2-5m
Time resolution is 1/960MHz ≈ 1ns
Two types of virtual uniform antenna arrays for direction of arrival analysis
501x1 uniform linear array with 1mm antenna spacing (los scenarios)
301x51 uniform planar antenna array with 1mm antenna spacing (edge scenario)
Alexei Davydov (Intel Corporation)
<author>, <company>

5. Direction of arrival measurements (Edge scenario)
May 2006
Direction of arrival measurements (Edge scenario)
Planar array: non-ambiguous azimuth angle measurements
Linear array: ambiguous azimuth angle measurements 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12
Black dots represent the rays positions reconstructed from the simplified geometry-based tracing model. Low order reflected rays are only shown. Note: rays #1,5,9 are appearing from another angles in the right figure.
Alexei Davydov (Intel Corporation)

6. May 2006
Illustration of simplified three-dimensional geometry-based ray-tracing model 1 2 3 4 5 6 7 8 9 10 11 12
Note: rays #1,5,9 (for scenarios cx,cy,cz) and rays #1,2,3,4 (for scenarios ew,ex,ey,ez) are only the rays which are arrived from the backside of the linear antenna array
Alexei Davydov (Intel Corporation)

7. Direction of arrival measurements (LOS scenario)
May 2006
Direction of arrival measurements (LOS scenario)
Linear array: ambiguous azimuth angle measurements
Reconstructed non-ambiguous rays positions from the simplified geometry-based tracing model 1 2 3 4 5 6 7 8 9 10 11 12
Note: rays #1,5,9 incident from the backside of the linear antenna array may be easily recognized in the left figure by the using the rays positions from the simplified geometry-based tracing model shown in the right figure.
Alexei Davydov (Intel Corporation)

8. Cluster identification procedure (1)
May 2006
Cluster identification procedure (1)
2D Gaussian Kernel Density Estimation (KDE) for rays time-angle of arrivals was used for assisting the cluster identification process by visual inspection
Alexei Davydov (Intel Corporation)

9. Cluster identification procedure (2)
May 2006
Cluster identification procedure (2)
Projections of the identified cluster positions on the time-angular channel power profiles
Alexei Davydov (Intel Corporation)

10. Inter-clusters time of arrival statistics
May 2006
Inter-clusters time of arrival statistics
Note: Exponential distribution of inter-arrival delays indicates that Poisson process can be used for modeling of clusters time of arrival
Alexei Davydov (Intel Corporation)

11. May 2006
Summary
For all IMST measurement scenarios the cluster angle of arrival ambiguity can be successfully overcome with help of simplified geometry-based ray-tracing model
In most of the situations the ambiguity doesn’t affect intra-cluster multi-path components angle of arrival distribution
Alexei Davydov (Intel Corporation)

12. May 2006
Backup
Alexei Davydov (Intel Corporation)

13. Power Delay Profile (biconical antenna, aver. over all scenarios)
May 2006
Power Delay Profile (biconical antenna, aver. over all scenarios)
Experimental average PDP
Delay breakpoint K Δ τ γ
Model PDP
K, [dB]
τ, [ns]
Δ, [dB]
γ, [ns]
Λflat [ns-1]
Λexp [ns-1] 8 30 6 10
0.3 1
Alexei Davydov (Intel Corporation)

14. Power Delay Profile (biconical antenna, alternative approximation)
May 2006
Power Delay Profile (biconical antenna, alternative approximation)
Model PDP
Alexei Davydov (Intel Corporation)

15. May 2006
Direction of arrival / Time of arrival observations (biconical antenna)
~Rician fading
~Rayleigh fading
Alexei Davydov (Intel Corporation)

16. May 2006
Direction of arrival / Time of arrival observations (biconical antenna)
near rough reflector
~ Rayleigh distribution
Alexei Davydov (Intel Corporation)