Advancing Wireless Link Signatures
for Location Distinction
Junxing Zhang
M h
Mohammad
d H.
H Firooz
Fi
Neal Patwari
Sneha K. Kasera
Location Distinction
z
z
¾
¾
¾
monitoring
trigger for
localization
location based
authentication
wireless link
Mo
ove
z
ability to know when
a device has changed
position
unlike localization, no
location estimation
applications
wireless link
2
O G
Our
Goall
location distinction based on unique
measurable wireless link
characteristics, or link signatures
3
Temporal Link Signature
[Patwari, Kasera 07]
z
magnitude of channel
impulse response
essentially
essent
ally superposition
superpos t on of
multipath
signature:
z
keep history of signatures
z
z
wall
4
Temporal Link Signature
(contd.)
z
z
distance between signatures
compare new signature with history, detect location change
if distance greater than threshold
5
Multiple Tone Signature
[Li et al 06]
z
multiple carrier waves or
tones simultaneously
transmitted to receiver
measure complex frequency
response of each tone
s gnature
signature:
z
keep history of signatures
z
z
wall
6
Multiple Tone Signature
(contd.)
z
z
correlation between signatures
¾
original
¾
our refinement
compare new signature
i
with
i h hi
history, detect
d
location change if correlation less than
threshold
7
O
Overview
i
z
z
z
z
z
qualitative comparison of two
signatures
g
develop new signature
performance comparison
temporal behavior study
summary
8
Qualitative Comparison
z
both measure multipath to identify links
z
temporal CIR signature
¾
¾
¾
z
multipath
p
orthogonal
g
in time domain
phase change of one path affects only small
portion of signature
robust against small changes in multipath
multiple tone signature
¾
¾
p
phase
preserved
p
in complex-valued
p
response
p
phase change of one path affects every
frequency response
9
Advancement: Complex
p
Temporal Signature
z
complex channel impulse response
signature:
z
combines
bi
b
bestt f
features
t
z
¾
¾
z
robust to small changes in multipath
preserves phase information
however, …
10
U d i bl Phase
Undesirable
Ph
Changes
Ch
z
z
z
received signal
phase: ϕ+2πft
imperfect clock
synchronization,
2 fΔt
2πfΔt
differences in
carrier
i f
frequency,
2πΔft
same link,
link different signatures
11
Change
h
in Distance
D
Metric
M
z
z
z
to cope with undesired phase changes
intuition: rotate one signature to align
with other
new ϕ2 metric:
12
M
Measurement
B
Based
d Evaluation
E l
z
z
z
data from [Patwari, Kasera 07]
9000 measurements in office
environment, after hours
DSSS signal with 40 MHz chip rate,
rate
1024 code-length, central frequency
2443 MHz
13
Multiple Tone Correlation
Refinement
z
Original correlation
z
Our refinement
f m
Significant
g
increase in p
probability
y of detection
14
Comparison of Three Signatures
complex temporal signature
z
outperforms existing ones
z
performs especially well at low false alarm rates
15
Temporal Behavior of Signatures
z
external factors affect signatures of a
link over time
¾
z
z
can cause high false alarms
previous measurement done in static
environment (after hours)
new measurement campaign
¾
¾
measurements taken during work hours
four Tx/Rx location pairs to obtain data
under temporally
p
y varying
y g conditions
16
Modeling Temporal Behavior
z
z
use non-linear
dimensionality
reduction
reduced 100D
signatures
i
t
tto jjustt
1D or 2D
z
z
2D embedding example
signatures fall into different groups
17
M k Model
Markov
M d l of
f Signatures
z
z
model each group of
link signatures as a
state in Markov
chain
how to find
probabilities
b bl
of
f
state transition?
z
z
1D embedding example
state transitions from amplitude changes
18
E
Extract
Transition Probabilities
P b bl
z
z
z
treat 1D
embedding as AM
signall
pass squared signal
th
through
h low-pass
l
filter to track
envelope
set threshold to
detect transitions
19
Incorporating Temporall Model
M d l
z
z
Goal: reducing false alarms due to
temporal
p
variation in link signatures
g
a new buffer replacement policy
¾
¾
before: single FIFO for signature
history, length B
advancement: one FIFO each for K
states of Markov chain, length B/K
20
Original Buffer Replacement Policy
1
2
Enqueue
A single FIFO buffer of size B, B=4
1
2
2
1
1
2
Different State
False Alarm
( S )
(DSFA)
21
New Buffer Replacement Policy
1
Enqueue
2
K separate FIFO buffers,
buffers each with size
B/K. B=4, K=2 in this example.
1
1
1
2
2
2
22
O i i l B
Original
Buffer
ff P[DSFA]
z
z
decreases
exponentially with
length of history
new buffer policy
removes these
th
false alarms
23
C
Conclusions
l i
z
z
z
z
compared existing multipath-based
link signatures
developed a new link signature that
outperforms existing ones
modeled the temporal behavior of link
signatures
reduced false alarms in location
distinction
24
Thank You
?? && //
Visit http://www.cs.utah.edu/~junxing for more information
BACKUP SLIDES
M l i
Multipath
h Ch
Channell Response
R
z
z
z
z
Wireless channel consists of multiple paths
caused by reflections, diffractions, and
scattering
g of radio waves
When sending s(t) through channel, receiver
receives:
Channel Impulse Response: channel response in
the time domain – h(t)
Channel Frequency Response: channel response
in the frequency domain – H(f)
27
Evaluation: Multiple Receiver
Refined Metric
28
Evaluation: Multiple Receiver
Complex Temporal Signature
29
K 2 State
K>2
S
Markov
M k Chains
Ch i
z
z
z
z
Hitting time:
When hitting time is longer than N, we will
have DSFA error
A
Assuming
i tail
t il of
f th
the probability
b bilit mass
function T is geometric, for large N:
Probability of DSFA is:
30
F
Future
Work
W k
z
z
z
Apply our methodology to more data
Build system on software defined
radio platform
Continue advancing link signatures
31