Combating Cross-Technology Interference
Shyamnath Gollakota
Fadel AdibDina Katabi
Srinivasan Seshan
ISM Band Is Increasingly Crowded
• Most problems are from cross-technology high-power interferers
• Responsible for more than 50% of the customer complaints
• Lead to complete loss of connectivity
Microwave Ovens Cordless PhonesBaby Monitors
Multiple independent studies [Cisco, Ofcom, Jupiter, Farpoint]
Experimental Setup
• Two Netgear 802.11n devices
• Baby monitors, cordless phones and microwave ovens
• WiFi devices about 20 feet away from each other
• Move interferer 1-90 feet away from WiFi receiver
WiFi tx
WiFi rx
20 feet
Effect of High-Power Interferers on WiFiW
iFi T
hrou
ghpu
t (i
n M
bps)
0 1 2 3 4 5 6 7 8 9 100
20
40
60
80
1 foot 90 feet
Line of sight Non- Line of sight
Interferer Location #
0 1 2 3 4 5 6 7 8 9 100
20
40
60
80Without Interferers
With Microwave
With baby MonitorWith Cordless Phone
Effect of High-Power Interferers on WiFi
Interferer Location #
Line of sight Non- Line of sight
WiF
i Thr
ough
put
(in
Mbp
s)
1 foot 90 feet
Traditional Solutions to Cross Technology Interference Don’t Work
• Avoid interferer frequencies Much wider bandwidth than WiFi Interferer can occupy multiple WiFi channels
Traditional Solutions to Cross Technology Interference Don’t Work
• Avoid interferer frequencies Much wider bandwidth than WiFi Interferer can occupy multiple WiFi channels
• Treat interferer as noise and use lower rate High power interferers (e.g., 8-100X WiFi power) Can’t get even lowest WiFi rate
How can we deal with such high-power interference?How can we deal with such high-power interference?
Technology Independent Multiple Output (TIMO)
• First WiFi receiver that decodes in presence of high-power
cross-technology interferers
• Is agnostic to the interferer’s technology
• Implemented and evaluated with baby monitors, microwave
ovens and cordless phones Convert no-connectivity scenarios to operational networks
Idea: Try to leverage MIMO
APClient
Today, streams are of the same technology
Idea: Try to leverage MIMO
APClient
If MIMO can work across diverse technologies
Idea: Try to leverage MIMO
APClient
Challenge: Current MIMO doesn’t work with diverse technologies
If MIMO can work across diverse technologies
MIMO Primer
APClient1h
2h
4h
3h
111Shy
If channels are known, AP can solve equations to decode the two streams, S1 and S2
23Sh
122Shy
24Sh
1S
2S
1y
2y
How do current APs estimate the channels?• Client sends a known preamble on the two antennas• AP correlates with known preamble to estimate channels• Doesn’t work across technologies
How do current APs estimate the channels?• Client sends a known preamble on the two antennas• AP correlates with known preamble to estimate channels• Doesn’t work across technologies
Ih4
Shy22
Say, Interferer is One of the Streams
APClient1h
2h
But, AP doesn’t know interferer technology / preamble Can’t compute interferer channels, h3 and h4
Shy11
Ih3
I
S
3h
4h
Scenario 2
c
IchShy
311
c
IchShy
422
InterferenceChannel
Scenario 1
InterferenceChannel
IhShy311
IhShy422
Fundamental Limitation of Channel Estimation
Can’t distinguish between the two scenario Impossible to exactly estimate interferer channels
How Does TIMO Work?
AP is not interested in decoding baby monitor
I APClient
IhShy311
I
S 1h
2h
3h
4h
IhShy422
• Reduce the number of unknowns to three
How Does TIMO Work?
I APClient
IhShy311
I
S 1h
2h
3h
4h
IhShy422
Ih
h
3
4
AP is not interested in decoding baby monitor
• Reduce the number of unknowns to three
How Does TIMO Work?
APClient
IShy 11
I
S 1h
2h
3h
4h I
h
hShy
3
4
223
4
h
h
AP is not interested in decoding baby monitor
• Reduce the number of unknowns to three• β is the interferer channel ratio
How Does TIMO Work?
APClient
IShy 11
I
S 1h
2h
3h
4h
IShy 22
3
4
h
h
AP is not interested in decoding baby monitor
• Reduce the number of unknowns to three• β is the interferer channel ratio • Focus on channel ratio instead of channels
Getting Around the Fundamental Limitation
Unlike channels, the channel ratio is not ambiguous
Scenario 2
c
IchShy
311
c
IchShy
422
InterferenceChannel
Scenario 1
InterferenceChannel
IhShy311
IhShy422
3
4
h
h
ch
ch
3
4The scaling factor, c, introduces ambiguity into channels
If β Can be Computed, AP Can Decode WiFi Client
APClient
IShy 11
I
S 1h
2h
3h
4h
IShy 22
3
4
h
h
AP can solve the two equations to decode the WiFi client
Question: How do we compute β?
Shy11
I
Shy22
I
Answer: Send known symbol
• WiFi client sends known symbol at beginning of its packet
Question: How do we compute β?
Answer: Send known symbol
Known
Known
• WiFi client sends known symbol at beginning of its packet
• Solve equations to get β
• Once β is known, it can be used to decode subsequent
symbols
I Shy11
Shy22
I
Use β to decode subsequent symbols
But, what if interferer is concentrated in time
Time
Known symbol
Question: How do we compute β?
Answer: Send known symbol
Known symbol
Time
Known symbol
Question: How do we compute β?
Answer: Send known symbol
But, what if interferer is concentrated in timeWe have a solution to compute β without known symbolsWe have a solution to compute β without known symbols
Intuition: Exploit the WiFi Symbol Structure
Real
Imaginary
• BPSK – ‘1’ bit sent as +1 and ‘0’ bit sent as -1
+1-1
Intuition: Exploit the WiFi Symbol Structure
Real
Imaginary
• BPSK – ‘1’ bit sent as +1 and ‘0’ bit sent as -1• If no interference, received symbols are close to expected symbols
+1-1
Intuition: Exploit the WiFi Symbol Structure
Real
Imaginary
+1-1
• BPSK – ‘1’ bit sent as +1 and ‘0’ bit sent as -1• If no interference, received symbols are close to expected symbols• If interference, received symbols are far from expected symbols
Correct estimate Average error is small
Error
correct
Intuition: Exploit the WiFi Symbol Structure
Real
Imaginary
+1-1
• BPSK – ‘1’ bit sent as +1 and ‘0’ bit sent as -1• If no interference, received symbols are close to expected symbols• If interference, received symbols are far from expected symbols
Bad estimate Average error is big
Error
correct
guess1
Intuition: Exploit the WiFi Symbol Structure
Real
Imaginary
+1-1
• BPSK – ‘1’ bit sent as +1 and ‘0’ bit sent as -1• If no interference, received symbols are close to expected symbols• If interference, received symbols are far from expected symbols
Better Estimate Average error reduce
Error
• Design gradient descent style algorithm to iteratively converge to actual channel ratio
• Paper described algorithm that works across modulations
• Design gradient descent style algorithm to iteratively converge to actual channel ratio
• Paper described algorithm that works across modulations
correct
guess1guess2
Performance
• Implement using USRP2s
• WiFi modulations and coding rates
• OFDM over 10 MHz
• Bits rates between 3-27 Mbps
• No carrier sense
Implementation
Testbed
• Place USRP prototype for 802.11 at blue locations
• Change the location of interferer over red locations
RxTx
Throughput Performance with Baby Monitor
Interferer Location #
802.
11 T
hrou
ghpu
t (i
n M
bps)
1 2 3 4 5 6 7 8 9 100
5
10
15
20
25
Line of sight Non- Line of sight
WiFi
1 foot 90 feet
1 2 3 4 5 6 7 8 9 100
5
10
15
20
25
Interferer Location #
Line of sight Non- Line of sight
60 feet away
802.
11 T
hrou
ghpu
t (i
n M
bps)
Throughput Performance with Baby Monitor
USRP WiFi
WiFi
1 foot 90 feetDespite disabling carrier sense, complete loss of connectivity in more than half the location
Despite disabling carrier sense, complete loss of connectivity in more than half the location
USRP WiFi with TIMO
Interferer Location #1 foot 90 feet
Line of sight Non- Line of sight
802.
11 T
hrou
ghpu
t (i
n M
bps)
Throughput Performance with Baby Monitor
Without interference
WiFi
USRP WiFi
1 2 3 4 5 6 7 8 9 1005
10152025
Throughput Performance
1 2 3 4 5 6 7 8 9 100
5
10
15
20
25
802.
11 T
hrou
ghpu
t (in
Mbp
s)
Interferer Location #
Cordless Phones
w/o TIMO
with TIMO
802.
11 T
hrou
ghpu
t (in
Mbp
s)
1 2 3 4 5 6 7 8 9 100
5
10
15
20
25
Interferer Location #
w/o TIMO
with TIMO
Microwave Ovens
TIMO transforms scenarios with a complete loss of connectivity to operational networks
TIMO transforms scenarios with a complete loss of connectivity to operational networks
• Decoding Interference [IC, SAM, Beamforming, …]
• Cognitive Communication [Samplewidth, Jello, Swift, …]
Related Work
- Don’t work with cross-technology interference
- Don’t operate on the same frequency
First system to decode in the presence of cross-technology interference on same band
Conclusions
• First WiFi receiver that decodes in presence of high-power
cross-technology interferers
• Enable MIMO to work across technologies
• Implemented and evaluated with baby monitors, microwave
ovens and cordless phones Convert no-connectivity scenarios to operational networks