July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 1
doc.: IEEE 802.15-02/240SG3a
Submission
Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)
Submission Title: Empirically Based Statistical Ultra-Wideband Channel ModelDate Submitted: 24 June, 2002Source: Marcus Pendergrass, Time Domain Corporation 7057 Old Madison Pike, Huntsville, AL 35806Voice:256-428-6344 FAX: [256-922-0387], E-Mail: [email protected]
Re: Ultra-wideband Channel Models IEEE P802.15-02/208r0-SG3a, 17 April, 2002,
Abstract: An ultra-wideband (UWB) channel measurement and modeling effort, targeted towards the short-range, high data rate wireless personal area network (WPAN) application space, is described. Results of this project include a measurement database of 429 UWB channel soundings, including both line of sight and non line of sight channels, a statistical description of this database, and recommended models and modeling parameters for several UWB WPAN scenarios of interest.
Purpose: The information provided in this document is for consideration in the selection of a UWB channel model to be used for evaluating the performance of a high rate UWB PHY for WPANs.
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.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 2
doc.: IEEE 802.15-02/240SG3a
Submission
Marcus Pendergrass and William C. Beeler
24 June 2002
with thanks to Laurie Foss, Joy Kelly, James Mann, Alan Petroff, Alex Petroff, Mitchell Williams, and Scott Yano for assistance and support.
Empirically Based Statistical Ultra-Wideband (UWB) Channel Model
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 3
doc.: IEEE 802.15-02/240SG3a
Submission
Executive Summary• Important to characterize the Wireless Personal area
network (WPAN) environment.
• 429 channel soundings taken in residential and office environments.
• Statistical multipath models for 3 environments described: LOS 0-4 meters, NLOS 0-4 meters, NLOS 4 - 10 meters.
• Channel response modeled as a sum of scaled and delayed versions template waveform.
• Good fit to measurement data. Distortion <1dB.
• Recommendations offered
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 4
doc.: IEEE 802.15-02/240SG3a
Submission
Outline
• Introduction
• Measurement Campaign
• Data Analysis
• Statistical Environmental Models
• Analytical Models
• Conclusions/Recommendations
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 5
doc.: IEEE 802.15-02/240SG3a
Submission
• Introduction
• Measurement Campaign
• Data Analysis
• Statistical Environmental Models
• Analytical Models
• Conclusions/Recommendations
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 6
doc.: IEEE 802.15-02/240SG3a
Submission
Introduction
• Channel Impulse Response (CIR) modeling of radio-frequency channels necessary for system design, trades.
• Multipath channel effects will be a key determinant of system performance, reliability.
• Large literature on channel modeling available, including work on the UWB channel in particular.
• Important to characterize the wireless personal area network (WPAN) environment in both line of sight (LOS) and non line of sight (NLOS) cases.
• Models should be tuned to WPAN applications and environments.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 7
doc.: IEEE 802.15-02/240SG3a
Submission
Approach• Measurement Campaign
• Channel soundings taken in a variety of WPAN-type environments.
• Data Analysis• Deconvolution of channel impulse response (CIR) from
measurements. • Assessment of channel distortion. • Statistical analysis of UWB channel parameters as a
function of environment type.• Fit existing models to data
• IEEE 802.11 model.• The -K model.
• Assess goodness of fit• Recommend models, parameters
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 8
doc.: IEEE 802.15-02/240SG3a
Submission
Overview of Results
• 429 channels soundings taken from 11 different home and office environments.– Data will be made available to SG3a.
• Environmental signal distortion estimated.
• Multipath channel parameters described statistically:• RMS delay• Distribution of multipath arrival times.• Average power decay profile.
• Ability of existing models to capture the phenomenology of the data assessed.
• Recommendations made for models and parameters.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 9
doc.: IEEE 802.15-02/240SG3a
Submission
• Introduction
• Measurement Campaign
• Data Analysis
• Statistical Environmental Models
• Analytical Models
• Conclusions/Recommendations
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 10
doc.: IEEE 802.15-02/240SG3a
Submission
Purpose• Support statistical analysis WPAN propagation
environments by obtaining a well-documented set of diverse measurements of the UWB channel.
– Short range (0-4 meters), and medium range (4 - 10 meters)
– LOS and NLOS channels
– office and residential environments
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 11
doc.: IEEE 802.15-02/240SG3a
Submission
Measurement Plan
• NLOS and LOS measurements for WPAN multipath channel characterization.
• Metal stud and wooden stud environments.
– Metal studs typical of office environments; wooden studs more typical of residential environments.
– 11 different office and home locations
• Detailed documentation for each channel sounding
– X,Y,Z coordinates of transmit/receive antenna locations.
– Channel categorized as LOS or NLOS
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 12
doc.: IEEE 802.15-02/240SG3a
Submission
Test Setup Details
• Summary:
– Approximately omni-directional transmit/receive antennas (roughly 3 dBi gain)
– PCS and ISM band pass rejection filter
– Effective noise figure: 4.8 dB at receive antenna terminals
– Gain: 19.8 dB
– Radiated power at approximately -10 dBm in the 3 to 5 GHz spectrum (close to FCC UWB limit)
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 13
doc.: IEEE 802.15-02/240SG3a
Submission
Test Setup Details
• Data recorded:
– 100 ns channel record.
– 4096 data points per record.
– Effective sampling time is 24.14 ps (20 GHz Nyquist frequency).
– 350 averages per data point per channel record (for high SNR).
– Triggered sampling for accurate determination of effective LOS arrival time.
– Channel stimulus is UWB signal with 3 to 5 GHz 3 dB bandwidth, approximately 1.7 ns pulse duration.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 14
doc.: IEEE 802.15-02/240SG3a
Submission
Channel Measurement Test Setup
Miteq30 dB @ 4 GHz0.4 nsec delay
PreampNF = 2.2
+15 VdcP.S.
Calex CM1.15.400-115
Rcv Ant & Mount
BC1 50 ft.RG-223/U
21 dB @ 4 GHz78 nsec delay
22 nsec Delay LineHP54008A
2 dB @ 4 GHz
HP8449B1.5 nsec delay37 dB @ 4 GHz
PreampNF = 9
BC6 2 ft.RG-223/U
-1.3 dB @ 4 GHz3 nsec delay
HP8494B0-11 dB, 1 dB Step Variable Attenuator
HP8495B0-70 dB, 10 dB Step Variable Attenuator
4.5" of Semi Rigid
1.4 nsec delay-0.8 dB @ 4 GHz
at 0 dB step
High Pass Filter,ISM, & PCS Notch
f (GHz)
dB
3
2.44
1.88 -1.6 dB
Male to MaleSMA
1.0 nsec delay
Floppy
HP54750A
Ch.1
Ch.2
Trig
DSO
5.75
Transmit Ant
Channel
350 Averages10 ns/div
BC2 3 ft.RG-223/U
-2.0 dB @ 4 GHz nsec delay
Trigger Cable 50 ft.
RG-223/U21 dB @ 4 GHz78 nsec delay
TDC SG
BC5 2 ft.RG-223/U
-1.3 dB @ 4 GHz3 nsec delay
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 15
doc.: IEEE 802.15-02/240SG3a
Submission
Measurement Issues• Received pulse distortion
– Need accurate received pulse templates for deconvolution analysis.– Resolution: assessment of waveform distortion due to the angle
of arrival of the incoming signal.
• Determination of line of sight delay time in NLOS channels.– Accurate determination of multipath intensity profiles for NLOS
channels requires knowing where the line of sight path would have arrived, had it not been obstructed.
– Resolution: careful design and characterization of test setup and parameters (group delays, NF, antenna pattern, etc.), along with periodic excitation of the environment. Utilize known delays of test equipment, known transmit/receive locations, and periodic triggering to estimate what the direct path arrival time would have been for a NLOS channel.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 16
doc.: IEEE 802.15-02/240SG3a
Submission
Measurement Issue:Received Pulse Distortion
• Accurate received waveform template needed for effective deconvolution of channel impulse response.
• Sources of waveform distortion:– environment (non-linear group delay, frequency-selective
attenuation, etc.)
– interference (intermittent and steady state)
– antenna pattern
• Environmental distortion to be estimated in data analysis.
• Interference in minimized with appropriate filtering (PCS, ISM bands).
• Distortion due to non-ideal antenna pattern was assessed empirically.– distortion as a function of elevation angle.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 17
doc.: IEEE 802.15-02/240SG3a
Submission
Typical Normalized Antenna Azimuth and Elevation Patterns (omni-
directional antennas)0
TDC SG
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 18
doc.: IEEE 802.15-02/240SG3a
Submission
Received Pulse Distortion Test Setup
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 19
doc.: IEEE 802.15-02/240SG3a
Submission
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
0.0E+00 5.0E-10 1.0E-09 1.5E-09 2.0E-09 2.5E-09
TX 90 Deg Above Boresight Facing TX 60 Deg Above TX 30 Deg Below
– For angles of elevation between -70 degrees and +70 degrees, waveform distortion was found to be minimal.
– Significant distortion near 90 degrees elevation; however, signal is severely attenuated in this region.
– Use of a single received pulse template was judged acceptable for deconvolution analysis.
Pulse Distortion Test Results
Normalized amplitudesNormalized amplitudes
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 20
doc.: IEEE 802.15-02/240SG3a
Submission
• In our test set-up, periodic excitation of the environment (non time-hopped) allowed for more accurate calculation of LOS delays.
• With periodic excitation the channel ring-down from previous pulse can add to the recorded response data if the record length is shorter than the ring-down time of the channel.
• Random excitation decorrelates the previous pulse’s ring-down from the recorded response through the DSO averaging process.
• Effect is most pronounced in channels with high RMS delay spread.
Measurement Issue:Determination of LOS Delay
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 21
doc.: IEEE 802.15-02/240SG3a
Submission
Periodic Channel Stimulus Example
0 5 10 15 20 25 30 35 40 45 50-4
-3
-2
-1
0
1
2
3
4x 10
-3 6m, Periodic, NLOS
Am
plitu
de
Time (ns)
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 22
doc.: IEEE 802.15-02/240SG3a
Submission
Random Channel Stimulus Example
0 5 10 15 20 25 30 35 40 45 50-4
-3
-2
-1
0
1
2
3
4x 10
-3 6m, Psuedo Random, NLOS
Am
plitu
de
Time (ns)
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 23
doc.: IEEE 802.15-02/240SG3a
Submission
Minimal Effect on RMS Delay
– Ability to accurately determine LOS delay was judged important enough to utilize periodic (non time-hopped) pulse trains.
0 5 10 15 20 25 30 35-4
-3
-2
-1
0
1
2
3
4x 10
-3 6m, NLOS, Periodic (Black) and Psuedo Random (Red)
Am
plitu
de
Time (ns)
CIR RMS Delay=16.3
CIR RMS Delay=15.5
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 24
doc.: IEEE 802.15-02/240SG3a
Submission
Channel Measurement Environments
• 11 different office and home environments
• Metal and wood stud constructions
• Distances less than or equal to 10 meters.
• 471 channel soundings taken in total.
• Complete documentation of measurement locations and environments.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 25
doc.: IEEE 802.15-02/240SG3a
Submission
Example Measurement Locations
A Typical Office Environment13'-9"
10'-3
"
6'-9
"17
.7
36" door
file cabinet16.5"x28"
desk27'x47.5"
bookcase12"x30"
bookcase12"x30"
desk
27.5
"x47
"
desk27.5"x47"
shelf40"x12"
lampz =
185.4
z = 74.9
z = 125.7
Chairz= 48
Chairz 19
Chairz = 48
z =81.3
49
z =124.4
z =71
z =71
trash
tras
h
10"x15"z = 38
10"x
15"
z =
38
chair
z = 52
z=47
z =
48
14"x
35"
z = 166.4
z = 74.9
z = 74.9z =
125.7
1
3
17
11
19
15
13
7
9
5
23
74.9
z = 74.9
80.9
z = 166.4199.6
z = 74.9
z = 166.4
292.
8
103.4
z = 74.9
268.
3
z = 86.3
269
z = 74.9
252.9
z = 52
250.8
z = 52
114126
z = 86
67.87"
31
2.5
419.2
205.
7
Lampz=185
Lampz=185
Receiverz = 0cm
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 26
doc.: IEEE 802.15-02/240SG3a
Submission
13'-9.5"
21'-4.5"
1'-0
"
5'-1"
13'-8.5"
14'-4
"
1'-8
"
conference table4' x 12'
69.5" 54.5"
59.5
"
57.5
"
table
15" x 45"
36"
14x1450"
14.5"
trash
18" 49" 70"28" 93"
18"
21"
24"
Conference Room 245
Example Measurement Locations
Conference Room
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 27
doc.: IEEE 802.15-02/240SG3a
Submission
Bill Beeler Living Room5/22/02 1:50p
1/4"=1'0"
11'-3"
3'-9"
10'-0"
1'-0"
1'-8 9/16"
10'-2"6'-3"
4'-6 5
/8"
7'-3"
2'-3 1/8"
6'-8"
19
19
19
15
34
34
3
4
34
20 20
28
28 28
44
25
frontdoor
endtable17x23
endtable17x23
coffee table19x47.5
tv/s
tere
o
wall
unit
24x 5
4
36"
34"
38" x 88"
38"
x 6
5"
38" x 65"
metalbarbells
meta
l
bucket
12"
x
17"
cart
metal fan12" x 24"
33.
5" hallway
kitchenarea
diningarea
endtable17x2320
metalstairstepexcerisemachine
under table
firepla
ce
openning in wall tokitchen 72"
hallw
ay
books
12" 1
2"
window98"12" 12"
sto
ne surfa
ce
Example Measurement LocationsResidential Living Room
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 28
doc.: IEEE 802.15-02/240SG3a
Submission
Measurement Database• 471 channel soundings taken in total.• Database consists of a subset of 429 of these
channels:– All measurements vertically polarized.– Includes received waveform scans and extracted channel
impulse responses.– Includes calculated channel parameters, including RMS
delay and path loss.– Also includes various measurement meta-data, including
• locations of transmitter and receiver• channel categorized as LOS or NLOS.• calculated line of sight delay time• environment type (wood stud, metal stud)• polarization• number of intervening walls between transmitter and receiver.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 29
doc.: IEEE 802.15-02/240SG3a
Submission
• Introduction
• Measurement Campaign
• Data Analysis
• Statistical Environmental Models
• Analytical Models
• Conclusions/Recommendations
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 30
doc.: IEEE 802.15-02/240SG3a
Submission
Analysis Goals
• Extract a description of the channel that is independent of the channel stimulus.
• Estimate “distortion” caused by the propagation environments.
• Produce a statistical description of channel parameters as a function of environment type.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 31
doc.: IEEE 802.15-02/240SG3a
Submission
Major Analysis Assumptions
• Channel modeled as a linear time-invariant (LTI) filter.– assume that there are negligible changes to the channel on the
time scale of a communications packet.
• Impulse response for the channel is assumed to be of the form
– channel’s effect on signal is modeled as a series of amplitude scalings ak and time delays k.
N
kkk tath
0
)( (1)
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 32
doc.: IEEE 802.15-02/240SG3a
Submission
20 40 60 80 100 120 140 160 180-2000
-1000
0
1000
2000
Am
plitu
de
Received Reconstructed
20 40 60 80 100 120 140 160 180-0.05
-0.025
0
0.025
0.05
Time (nS)
CIR
20 dB Threshold
CLEAN is a variation of
a serial correlation
algorithm Uses a template
received waveform to
sift through an arbitrary
received waveform Cross-correlation with
template suppresses
non-coherent signals
and noise Result is k’s and k’s
of CIR independent of
measurement system
CLEAN Algorithmused to deconvolve CIR from channel
record
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 33
doc.: IEEE 802.15-02/240SG3a
Submission
CLEAN AlgorithmCompared to Frequency Domain De-
Convolution
0 5 10 15 20 25 30 35 40 45 50
-1000
0
1000
Channel Record (Signal + noise)
Am
plitu
de
0 5 10 15 20 25 30 35 40 45 500
0.02
0.04
0.06
0.08
0.1
Time (nS)
CLEAN Template Correlation vs Frequency Domain De-Convolution
norm
aliz
ed h
(t)
Frequency De-Convolution CIR
CLEAN CIR
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 34
doc.: IEEE 802.15-02/240SG3a
Submission
CLEAN Algorithmgeometric interpretation
s
r
s-r
Original scan Error vector
Linear space of all possible reconstructed scans
CLEAN approximation to original scan (reconstructed scan)
2
2
s
r
Energy Capture Ratio:
Relative Error:
2
2
s
rs
Least Squares Condition:
12
2
2
2
s
rs
s
r(2)
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 35
doc.: IEEE 802.15-02/240SG3a
Submission
CLEAN Algorithmestimation of signal distortion
• CLEAN returns the CIR in precisely the desired form (1).
• Convolution of CIR with pulse template p(t) produces the “reconstructed” channel record r(t):
• When the least squares condition (2) holds, the residual difference between the CLEAN reconstruction and original channel record is a measure of the distortion introduced by the channel (i.e. the amount of signal energy that is not of the form (1)).
N
kkk tpatphtr
0
)()(
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 36
doc.: IEEE 802.15-02/240SG3a
Submission
CLEAN Residual Estimates of Signal Distortion
• Least squares condition met at 85% energy capture ratio, on average.
• Estimated signal distortion:
– NLOS, 0 to 4 meters, metal stud case: 15.5% (0.7 dB)
– LOS, 0 to 4 meters, metal stud case: 16.6% (0.7 dB)
– NLOS, 4 to 10 meters, metal stud case: 17.0% (0.8 dB)
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 37
doc.: IEEE 802.15-02/240SG3a
Submission
• Introduction
• Measurement Campaign
• Data Analysis
• Statistical Environmental Models
• Analytical Models
• Conclusions/Recommendations
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 38
doc.: IEEE 802.15-02/240SG3a
Submission
Data Used for the Analysis• 429 of the 471 channel records
– all vertically polarized measurements.
– duplicate measurements removed.
Number of Measurement Locations vs Distance
130137
69 6863
4
27.60%
56.69%
71.34%
85.77%
99.15% 100.00%
0
20
40
60
80
100
120
140
160
2 4 6 8 10 MoreBin (m)
Numb
er o
f Tra
nsmi
t and
Rec
eive
Ant
enna
Pos
ition
s
.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
Number of Measurement Positions per Bin Cumulative %
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 39
doc.: IEEE 802.15-02/240SG3a
Submission
General Remarks on the Data
• Data collection SNRs varied from about 40 dB for 1-meter boresight scans to about 15 dB for some 10-meter NLOS scans.
• LOS and NLOS channels exhibit wide variations in path loss and RMS delay spread. Some NLOS channels have lower delay spreads than some LOS channels.
– The variations can be explained by grazing angles and destructive interference for LOS channels , and low attenuation through materials for NLOS channels.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 40
doc.: IEEE 802.15-02/240SG3a
Submission
Scan #1: LOS 1m distance, Antenna Boresight
1/r2 Path Loss
5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20-0.06
-0.04
-0.02
0
0.02
0.04
0.06A
mpl
itude
Time (ns)
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 41
doc.: IEEE 802.15-02/240SG3a
Submission
Scan #57: LOS 3.1m distance, office environment,
approximately 1/r5.28 Path Loss
0 5 10 15 20 25 30 35 40-5
-4
-3
-2
-1
0
1
2
3
4
5x 10
-3
Am
plitu
de
Time (ns)
Check this one!Check this one!
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 42
doc.: IEEE 802.15-02/240SG3a
Submission
Scan #6: NLOS 1.3m distance, office environment,
approximately 1/r26.5 path loss
0 5 10 15 20 25 30 35
-2
-1
0
1
2
3
x 10-3
Am
plitu
de
Time (ns)
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 43
doc.: IEEE 802.15-02/240SG3a
Submission
Scan #15: NLOS2.7m distance, office environment
approximately 1/r2.07 Path Loss
0 2 4 6 8 10 12 14 16 18 20
-0.02
-0.015
-0.01
-0.005
0
0.005
0.01
0.015
0.02
Am
plitu
de
Time (ns)
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 44
doc.: IEEE 802.15-02/240SG3a
Submission
Descriptive Statistics of the Data
• CIRs and channel parameters extracted for all 429 records.
• Statistical analysis and model fitting done only for metal stud measurements.– 369 metal stud measurements.– 60 wood stud measurements not enough for statistical
breakdown.– Three scenarios considered:
• I. NLOS, 0 to 4 meters, metal stud.• II. LOS, 0 to 4 meters, metal stud.• III. NLOS, 4 to 10 meters, metal stud.
– Not enough LOS, 4 to 10 meter channels for analysis.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 45
doc.: IEEE 802.15-02/240SG3a
Submission
Explanation of Channel Statistics
• Channels characterized in terms of the following statistical parameters– RMS delay as a function of distance.
– Mean excess delay as a function of distance.
– Number of multipath components per channel.
– Occupancy probabilities as a function of excess delay.
– Mean log relative magnitudes as a function of excess delay.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 46
doc.: IEEE 802.15-02/240SG3a
Submission
delays
amplitudes
LOS delay
kth excess delay: k – 0
0 1k
a0a1 ak
amax
Channel Statistics
• Mean excess delay is a weighted average of the excess delays in the CIR.
• CIR amplitudes are the weights
• RMS delay is the standard deviation of the excess delays.• again using the CIR amplitudes as the weights.
kth relative magnitude:maxa
ak
time
multipath component
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 47
doc.: IEEE 802.15-02/240SG3a
Submission
excess delay
rela
tive
mag
nit
ud
e
Mean relative magnitude over a collection of CIRs
Channel Statistics
excess delay
pro
ba
bil
ity
of
occ
up
anc
y
Probability that there is a multipath component at a given excess delay offset
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 48
doc.: IEEE 802.15-02/240SG3a
Submission
Dependence of Channel Statistics on CLEAN Algorithm
Stopping Condition
• Channel statistics computed from channel impulse response as calculated by CLEAN algorithm.
• Dependence of channel statistics on stopping criteria assessed.
• The following energy capture stopping criteria were evaluated: 80%, 85%, 90%, 95%
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 49
doc.: IEEE 802.15-02/240SG3a
Submission
80% Energy Capture(notional)
amplitudes
time
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 50
doc.: IEEE 802.15-02/240SG3a
Submission
amplitudes
time
85% Energy Capture(notional)
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 51
doc.: IEEE 802.15-02/240SG3a
Submission
90% Energy Capture(notional)
amplitudes
time
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 52
doc.: IEEE 802.15-02/240SG3a
Submission
95% Energy Capture(notional)
amplitudes
time
What is the effect on channel statistics?
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 53
doc.: IEEE 802.15-02/240SG3a
Submission
Comparison of Statistics Across Energy Capture Ratios
85% energy capture 95% energy capture
Avg. RMS Delay
Mean Number of Components per Channel
Avg. Mean Excess Delay
11.57 ns8.78 ns
12.41 ns10.04 ns
36.1 86.0
I. NLOS, 0 to 4 meters, metal stud
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 54
doc.: IEEE 802.15-02/240SG3a
Submission
Comparison of Statistics Across Energy Capture Ratios
II. LOS, 0 to 4 meters, metal stud
85% energy capture 95% energy capture
Avg. RMS Delay
Mean Number of Components per Channel
Avg. Mean Excess Delay
6.36 ns5.27 ns
5.17 ns4.95 ns
24.0 42.3
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 55
doc.: IEEE 802.15-02/240SG3a
Submission
Comparison of Statistics Across Energy Capture Ratios
III. NLOS, 4 to 10 meters, metal stud
85% energy capture 95% energy capture
Avg. RMS Delay
Mean Number of Components per Channel
Avg. Mean Excess Delay
14.59 ns 16.80 ns
15.95 ns14.24 ns
61.6 117.7
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 56
doc.: IEEE 802.15-02/240SG3a
Submission
85% Energy Capture Ratio Used for Statistical Analysis
• Number of multipath components per channel is the statistic that is most sensitive to changes in the stopping criteria.
• Large change in number of multipath components causes only small changes in other statistics in going from 85% to 95% energy capture ratio.
• 85% stopping criteria also good from a least squares point of view.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 57
doc.: IEEE 802.15-02/240SG3a
Submission
Statistical Environmental Models
• Each environment characterized by statistical profile of channels collected from that environment.
• Statistical analysis and model fitting done only for metal stud measurements.– 369 metal stud measurements.– 60 wood stud measurements not enough for statistical
breakdown.– Three scenarios considered:
• I. NLOS, 0 to 4 meters, metal stud (120 channels).• II. LOS, 0 to 4 meters, metal stud (xxx channels).• III. NLOS, 4 to 10 meters, metal stud (xxx channels).
– Not enough LOS, 4 to 10 meter channels for analysis.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 58
doc.: IEEE 802.15-02/240SG3a
Submission
20
33
45
22
0
5
10
15
20
25
30
35
40
45
50
0 to 1 m 1 to 2 m 2 to 3 m 3 to 4 m
distance
nu
mb
er o
f ch
ann
els
I. NLOS, 0 to 4 meters, metal stud
Histogram of Number of Measurements per Meter
Total Number of Measured Channels: 120
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 59
doc.: IEEE 802.15-02/240SG3a
Submission
27
41
36
14
6
0
5
10
15
20
25
30
35
40
45
1 to 20 21 to 40 41 to 60 61 to 80 81 to 83
number of components per channel
nu
mb
er o
f ch
ann
els
I. NLOS, 0 to 4 meters, metal stud
Histogram of Number of Multipath Components Per Channel
Mean Number of Components Per Channel: 36.1
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 60
doc.: IEEE 802.15-02/240SG3a
Submission
Probability of Occupancy
0
0.2
0.4
0.6
0.8
1
0 5 10 15 20 25 30 35 40 45
excess delay (ns)
pro
bab
ilit
y
I. NLOS, 0 to 4 meters, metal stud
Multipath Arrival Time Distribution
Graph of the probability that an excess delay bin contains a reflection.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 61
doc.: IEEE 802.15-02/240SG3a
Submission
-2.5
-2
-1.5
-1
-0.5
0
0 10 20 30 40 50 60
excess delay (ns)
log
rel
ativ
e m
agn
itu
de
I. NLOS, 0 to 4 meters, metal stud
Mean of Log Relative Magnitude vs. Excess Delay
Mean Log Relative MagnitudeMean Log Relative Magnitude
Mean + stdv.Mean + stdv.
Mean - stdv.Mean - stdv.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 62
doc.: IEEE 802.15-02/240SG3a
Submission
0
5
10
15
20
25
0 0.5 1 1.5 2 2.5 3 3.5 4
distance (m)
me
an
RM
S d
ela
y (
ns
)
I. NLOS, 0 to 4 meters, metal stud
Mean RMS Delay vs. Distance
Mean RMS DelayMean RMS Delay
Mean + stdv.Mean + stdv.
Mean - stdv.Mean - stdv.
Mean RMS Delay: 8.78 ns
Standard Deviation of RMS Delay: 4.34 ns
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 63
doc.: IEEE 802.15-02/240SG3a
Submission
0
5
10
15
20
25
0 0.5 1 1.5 2 2.5 3 3.5 4
distance (m)
me
an
RM
S d
ela
y (
ns
)
I. NLOS, 0 to 4 meters, metal stud
Average Mean Excess Delay vs. Distance
Average Mean Excess Delay: 10.04 ns
Standard Deviation of Mean Excess Delay : 6.26 ns
Avg. Mean Excess Delay
Avg. Mean Excess Delay
Mean + stdv.Mean + stdv.
Mean - stdv.Mean - stdv.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 64
doc.: IEEE 802.15-02/240SG3a
Submission
6
27
32
14
0
10
20
30
40
0 to 1 meters 1 to 2 meters 2 to 3 meters 3 to 4 meters
distance
nu
mb
er o
f ch
ann
els
II. LOS, 0 to 4 meters, metal stud
Histogram of Number of Measurements per Meter
Total Number of Measured Channels: 79
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 65
doc.: IEEE 802.15-02/240SG3a
Submission
43
20
10
41 1
0
10
20
30
40
50
1 to 20 21 to 40 41 to 60 61 to 80 81 to 100 101 to 109
number of components
nu
mb
er o
f ch
ann
els
II. LOS, 0 to 4 meters, metal stud
Histogram of Number of Multipath Components Per Channel
Mean Number of Components Per Channel: 24.0
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 66
doc.: IEEE 802.15-02/240SG3a
Submission
Probability of Occupancy
0
0.2
0.4
0.6
0.8
1
-10 0 10 20 30 40 50 60
excess delay (ns)
pro
bab
ilit
y
II. LOS, 0 to 4 meters, metal stud
Multipath Arrival Time Distribution
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 67
doc.: IEEE 802.15-02/240SG3a
Submission
-2.5
-2
-1.5
-1
-0.5
0
-10 0 10 20 30 40 50
excess delay
log
rel
ativ
e m
agn
itu
de
II. LOS, 0 to 4 meters, metal stud
Mean of Log Relative Magnitude vs. Excess Delay
Mean Log Relative MagnitudeMean Log Relative Magnitude
Mean + stdv.Mean + stdv.
Mean - stdv.Mean - stdv.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 68
doc.: IEEE 802.15-02/240SG3a
Submission
0
5
10
15
20
25
0 0.5 1 1.5 2 2.5 3 3.5 4
distance (m)
RM
S d
elay
(n
s)
II. LOS, 0 to 4 meters, metal stud
Mean RMS Delay vs. Distance
Mean RMS DelayMean RMS DelayMean + stdv.Mean + stdv.
Mean - stdv.Mean - stdv.
Mean RMS Delay: 5.27 ns
Standard Deviation of RMS Delay: 3.37 ns
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 69
doc.: IEEE 802.15-02/240SG3a
Submission
0
5
10
15
20
25
0 0.5 1 1.5 2 2.5 3 3.5 4
distance (m)
mea
n e
xces
s d
elay
(n
s)
II. LOS, 0 to 4 meters, metal stud
Average Mean Excess Delay vs. Distance
Average Mean Excess Delay: 4.95 ns
Standard Deviation of Mean Excess Delay: 4.14 ns
Avg. Mean Excess Delay
Avg. Mean Excess Delay
Mean + stdv.Mean + stdv.
Mean - stdv.Mean - stdv.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 70
doc.: IEEE 802.15-02/240SG3a
Submission
28
22
17
22
19
11
0
5
10
15
20
25
30
4 to 5 5 to 6 6 to 7 7 to 8 8 to 9 9 to 10
distance (m)
nu
mb
er o
f ch
ann
els
III. NLOS, 4 to 10 meters, metal stud
Histogram of Number of Measurements per Meter
Total Number of Measured Channels: 119
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 71
doc.: IEEE 802.15-02/240SG3a
Submission
7
17
41
32
13
3 3 2 1
0
5
10
15
20
25
30
35
40
45
1 to 20 21 to 40 41 to 60 61 to 80 81 to100
101 to120
121 to140
141 to160
161 to180
number of components per channel
nu
mb
er o
f ch
ann
els
Histogram of Number of Multipath Components Per Channel
III. NLOS, 4 to 10 meters, metal stud
Mean Number of Components Per Channel: 61.6
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 72
doc.: IEEE 802.15-02/240SG3a
Submission
Probability of Occupancy
0
0.2
0.4
0.6
0.8
1
-20 0 20 40 60 80 100 120
excess delay (ns)
pro
bab
ilit
yMultipath Arrival Time Distribution
III. NLOS, 4 to 10 meters, metal stud
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 73
doc.: IEEE 802.15-02/240SG3a
Submission
-2.5
-2
-1.5
-1
-0.5
0
-20 0 20 40 60 80 100
Mean of Log Relative Magnitude vs. Excess Delay
III. NLOS, 4 to 10 meters, metal stud
Mean Log Relative MagnitudeMean Log Relative Magnitude
Mean + stdv.Mean + stdv.
Mean - stdv.Mean - stdv.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 74
doc.: IEEE 802.15-02/240SG3a
Submission
0
5
10
15
20
25
4 5 6 7 8 9 10
distance (m)
RM
S d
elay
(n
s)Mean RMS Delay vs. Distance
III. NLOS, 4 to 10 meters, metal stud
Mean RMS DelayMean RMS Delay
Mean + stdv.Mean + stdv.
Mean - stdv.Mean - stdv.
Mean RMS Delay: 14.59 ns
Standard Deviation of RMS Delay: 3.41 ns
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 75
doc.: IEEE 802.15-02/240SG3a
Submission
0
5
10
15
20
25
4 5 6 7 8 9 10
distance (m)
RM
S d
elay
(n
s)Average Mean Excess Delay vs. Distance
Average Mean Excess Delay: 14.24 ns
Standard Deviation of Mean Excess Delay: 5.97 ns
III. NLOS, 4 to 10 meters, metal stud
Avg. Mean Excess Delay
Avg. Mean Excess Delay
Mean + stdv.Mean + stdv.
Mean - stdv.Mean - stdv.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 76
doc.: IEEE 802.15-02/240SG3a
Submission
27
41
36
14
6
0
5
10
15
20
25
30
35
40
45
1 to 20 21 to 40 41 to 60 61 to 80 81 to 83
number of components per channel
num
ber
of c
hann
els
43
20
10
41 1
0
10
20
30
40
50
1 to 20 21 to 40 41 to 60 61 to 80 81 to 100 101 to 109
number of components per channel
num
ber
of c
hann
els
7
17
41
32
13
3 3 2 1
0
5
10
15
20
25
30
35
40
45
1 to 20 21 to 40 41 to 60 61 to 80 81 to100
101 to120
121 to140
141 to160
161 to180
number of components per channel
num
ber
of c
hann
els
NLOS
LOS
4 – 10 m
0 – 4 m
Number of Components Per Channelcomparison across scenarios
NLOS
0 – 4 m
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 77
doc.: IEEE 802.15-02/240SG3a
Submission
Probability of Occupancy
0
0.2
0.4
0.6
0.8
1
0 20 40 60 80 100
excess delay (ns)
prob
abili
ty
Probability of Occupancy
0
0.2
0.4
0.6
0.8
1
0 20 40 60 80 100
excess delay (ns)
prob
abili
ty
Probability of Occupancy
0
0.2
0.4
0.6
0.8
1
0 20 40 60 80 100
excess delay (ns)
prob
abili
ty
Distribution of Multipath Arrival Timescomparison across scenarios
NLOS
LOS
4 – 10 m
0 – 4 m
NLOS
0 – 4 m
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 78
doc.: IEEE 802.15-02/240SG3a
Submission
-2.5
-2
-1.5
-1
-0.5
0
0 20 40 60 80 100
-2.5
-2
-1.5
-1
-0.5
0
0 20 40 60 80 100
excess delay
log
rela
tive
mag
nitu
de
-2.5
-2
-1.5
-1
-0.5
0
0 20 40 60 80 100
excess delay (ns)
log
rela
tive
mag
nitu
de
Mean of Log Relative Magnitudecomparison across scenarios
NLOS
LOS
4 – 10 m
0 – 4 m
NLOS
0 – 4 m
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 79
doc.: IEEE 802.15-02/240SG3a
Submission
0
5
10
15
20
25
4 5 6 7 8 9 10
distance (m)
RM
S d
elay
(ns)
0
5
10
15
20
25
0 0.5 1 1.5 2 2.5 3 3.5 4
distance (m)
mea
n R
MS
del
ay (n
s)
0
5
10
15
20
25
0 0.5 1 1.5 2 2.5 3 3.5 4
distance (m)
RM
S d
elay
(ns)
RMS Delay vs. Distancecomparison across scenarios
NLOS
LOS
4 – 10 m
0 – 4 m
NLOS
0 – 4 m
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 80
doc.: IEEE 802.15-02/240SG3a
Submission
0
5
10
15
20
25
0 0.5 1 1.5 2 2.5 3 3.5 4
distance (m)
mea
n R
MS
del
ay (n
s)
0
5
10
15
20
25
0 0.5 1 1.5 2 2.5 3 3.5 4
distance (m)
mea
n ex
cess
del
ay (n
s)
0
5
10
15
20
25
4 5 6 7 8 9 10
distance (m)
RM
S d
elay
(ns)
RMS Delay vs. Distancecomparison across scenarios
NLOS
LOS
4 – 10 m
0 – 4 m
NLOS
0 – 4 m
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 81
doc.: IEEE 802.15-02/240SG3a
Submission
• Introduction
• Measurement Campaign
• Data Analysis
• Statistical Environmental Models
• Analytical Models
• Conclusions/Recommendations
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 82
doc.: IEEE 802.15-02/240SG3a
Submission
Modeling Approach
• Attempted to fit two different models to the data– A modified IEEE 802.11 channel model– Modified -K model
• Models evaluated on how well they reproduced the statistic distributions of the data– Bhattacharyya distance calculated between
simulated and measured distributions.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 83
doc.: IEEE 802.15-02/240SG3a
Submission
Modified IEEE 802.11 model
• Regularly spaced impulses– modified for UWB to allow for random placement
of impulses in each time bin
• Raleigh-distributed magnitudes• input parameters
– TRMS : RMS delay parameter
– TS : time discretization unit
• Was not able to match both RMS delay and multipath intensity profile simultaneously.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 84
doc.: IEEE 802.15-02/240SG3a
Submission
Bhattacharyya Distance: 0.626
0
0.1
0.2
0.3
0.4
0.5
2 4 6 8 10 12 14 16 18 20
RMS delay (ns)
pro
ba
bil
ity
simulated measured
I. NLOS, 0 to 4 meters, metal stud
Distribution of RMS Delay
measured: 8.85 (ns)
Mean RMS Delay
simulated: 8.58 (ns)
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 85
doc.: IEEE 802.15-02/240SG3a
Submission
-7
-6
-5
-4
-3
-2
-1
0
-20 0 20 40 60 80 100 120
excess delay (ns)
log
re
lati
ve m
ag
nit
ud
e
simulated measured
I. NLOS, 0 to 4 meters, metal stud
Mean of Log Relative Magnitude vs. Excess Delay
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 86
doc.: IEEE 802.15-02/240SG3a
Submission
-K Model
• Arrival time model– Model “clumping” of multipath arrival times by making
the probability of an arrival in a given excess delay bin dependent on whether there was an arrival in the previous bin.
– “K” value is the ratio of these conditional probabilities.• Modeling assumption is that K is constant.
– “” value is the time discretization unit.
1bin in arrival | bin in arrivalPr i-ipi
1bin in arrival no | bin in arrivalPr i-ipi
positive conditional
negative conditional
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 87
doc.: IEEE 802.15-02/240SG3a
Submission
-K Model
• Amplitude model
– Log-normal model for multipath amplitudes
– Mean and standard deviation as functions of excess delay given by the statistics of the data.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 88
doc.: IEEE 802.15-02/240SG3a
Submission
• Multipath arrival times governed by statistics of data– Probability of a multipath arrival in a given
time bin depends on whether previous bin was occupied.
– Positive and negative conditional probabilities derived from statistics of data.
– No assumption that ratio of conditional probabilities is constant.
Modified-K Model
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 89
doc.: IEEE 802.15-02/240SG3a
Submission
Simulation Results
• time discretization unit= = 0.1 ns for all cases.
• Empirical probabilities of occupancy and log relative magnitude data used as inputs to model.
– A -K simulation would use approximations to these quantities as its inputs, and hence could perform no better.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 90
doc.: IEEE 802.15-02/240SG3a
Submission
Occupancy Probabilities
0
0.1
0.2
0.3
0.4
0.5
-20 0 20 40 60 80 100
excess delay (ns)
pro
bab
ilit
y
simulated measured
II. LOS, 0 to 4 meters, metal stud
Multipath Arrival Time Distribution
95% Energy Capture data used.95% Energy Capture data used.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 91
doc.: IEEE 802.15-02/240SG3a
Submission
-5
-4.5
-4
-3.5
-3
-2.5
-2
-1.5
-1
-0.5
0
-20 0 20 40 60 80 100
excess delay (ns)
log
rel
ativ
e m
agn
itu
de
simulated measured
II. LOS, 0 to 4 meters, metal stud
Mean of Log Relative Magnitude vs. Excess Delay
95% Energy Capture data used.95% Energy Capture data used.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 92
doc.: IEEE 802.15-02/240SG3a
Submission
Bhattacharyya Distance: 0.427
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0 50 10 15
number of components per channel
pro
bab
ilit
y
simulated measured
II. LOS, 0 to 4 meters, metal stud
Distribution of Number of Multipath Components Per Channel
measured: 42.3
Mean Number of Components Per Channel
simulated: 43.995% Energy Capture data used.
95% Energy Capture data used.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 93
doc.: IEEE 802.15-02/240SG3a
Submission
Bhattacharyya Distance: 0.721
0
0.1
0.2
0.3
0.4
0.5
2 4 6 8 10 12 14 16 18 20 22 24 26
RMS Delay (ns)
pro
bab
iity
simulated measured
II. LOS, 0 to 4 meters, metal stud
Distribution of RMS Delay
measured: 6.36 (ns)
Mean RMS Delay
simulated: 11.70 (ns)95% Energy Capture data used.
95% Energy Capture data used.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 94
doc.: IEEE 802.15-02/240SG3a
Submission
• Introduction
• Measurement Campaign
• Data Analysis
• Statistical Environmental Models
• Analytical Models
• Conclusions/Recommendations
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 95
doc.: IEEE 802.15-02/240SG3a
Submission
Conclusion• Modeling channel response as a sum of scaled/delayed
versions of channel input provides a good fit to data.
• Wide variety of channel characteristics, even within the same environment.
• Multipath arrival times and average power decay profiles follow linear or piece-wise linear trends.
• Exact parameter values for arrival times and decay profiles are dependent on the environment type.
• Occupancy probabilities and decay profiles do not completely characterize the channel data, since two models can have the same statistics for these quantities, and yet differ in the statistics of RMS delay.
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 96
doc.: IEEE 802.15-02/240SG3a
Submission
Recommendations
• IEEE 802.11 and -K model should not be used, because they do not provide good fits to the statistical models of the environments.
• Selected SG3A model should fit the collected data.– Number of multipath components per channel– Probability of occupancy – Average power decay profile– Distribution of RMS delay vs. distance– Distribution of mean excess delay vs. distance
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 97
doc.: IEEE 802.15-02/240SG3a
Submission
R.A. Scholtz, Notes on CLEAN and Related Algorithms, Technical Report to Time Domain Corporation, April 20, 2001
Homayoun Hashemi, “Impulse Response Modeling of Indoor Radio Propagation Channels”, IEEE Jornal on Slected Areas in Communications, VOL. 11, No. 7, September 1993
Theodore S. Rappaport, “Wireless Communications Principles and Practice”, 1996
Intelligent Automation, Inc., “Channel Impulse Response Modeling: Comparison Analysis of CLEAN algorithm and FT-based Deconvolution Techniques, Technical Report to Time Domain Corporation, November 21, 2001
Bob O’Hara and Al Petrick, “IEEE 802.11 Handbook A Designer’s Companion”, 1999
References
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 98
doc.: IEEE 802.15-02/240SG3a
Submission
Definitions/Terminology
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 99
doc.: IEEE 802.15-02/240SG3a
Submission
• LOS
– Line of Sight (transmit and receive antenna have a clear visible field of view relative to each other)
• NLOS
– Non-Line of Sight
• CIR
– Channel Impulse Response
• Waveform Template
– correlation template used in the correlation process (CLEAN Algorithm)
• LTI
– Linear Time Invariant
Terminology
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 100
doc.: IEEE 802.15-02/240SG3a
Submission
N
kkk tath
0
)()(
1
-1
a3
Example CIR
a2
a1
1
2
3
Where: ak are the impulse amplitudesk are the impulse delays
• CLEAN1 – Variant of a serial correlation algorithm
• Channel Modeled as LTI filter, with impulse response h(t) of the form:
Terminology
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 101
doc.: IEEE 802.15-02/240SG3a
Submission
• RMS Delay Spread can be expressed as:
N
kk
N
kkk
N
kkk
a
aa
0
2
0
2
0
22
Terminology
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 102
doc.: IEEE 802.15-02/240SG3a
Submission
• Mean Excess Delay can be expressed as:
N
kk
N
kkk
a
a
0
2
0
2
Terminology
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 103
doc.: IEEE 802.15-02/240SG3a
Submission
• Relative Magnitude can be expressed as:
max
)()(a
am
Where:
)(max0
max kNkaa
Terminology
July 2002
Marcus Pendergrass and William C. Beeler, Time Domain Corporation (TDC)
Slide 104
doc.: IEEE 802.15-02/240SG3a
Submission
• Average Multipath Intensity Profile (MIP) (or Average Power Decay Profile (APDP) can be expressed as:
)(ln()( 2 mEP
Terminology