Combating Cross-Technology Interference

1. Combating Cross-Technology Interference ShyamnathGollakota FadelAdib Dina Katabi SrinivasanSeshan

2. ISM Band Is Increasingly Crowded Multiple independent studies [Cisco, Ofcom, Jupiter, Farpoint] • Most problems are from cross-technology high-power interferers • Responsible for more than 50% of the customer complaints • Lead to complete loss of connectivity Cordless Phones Microwave Ovens Baby Monitors

3. 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 20 feet WiFirx

4. Effect of High-Power Interferers on WiFi WiFi Throughput (in Mbps) Interferer Location # 1 foot 90 feet Line of sight Non- Line of sight

5. Effect of High-Power Interferers on WiFi Without Interferers WiFi Throughput (in Mbps) With Microwave With baby Monitor With Cordless Phone Interferer Location # 1 foot 90 feet Line of sight Non- Line of sight

6. Traditional Solutions to Cross Technology Interference Don’t Work • Avoid interferer frequencies • Much wider bandwidth than WiFi • Interferer can occupy multiple WiFi channels

7. 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?

8. 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

9. Idea: Try to leverage MIMO Client AP Today, streams are of the same technology

10. Idea: Try to leverage MIMO Client AP If MIMO can work across diverse technologies

11. Idea: Try to leverage MIMO Client AP If MIMO can work across diverse technologies Challenge: Current MIMO doesn’t work with diverse technologies

12. MIMO Primer AP Client • 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 If channels are known, AP can solve equations to decode the two streams, S1 and S2

13. Say, Interferer is One of the Streams AP Client But, AP doesn’t know interferer technology / preamble  Can’t compute interferer channels, h3 and h4

14. Fundamental Limitation of Channel Estimation Scenario 1 Scenario 2 Interference Channel Interference Channel Can’t distinguish between the two scenario  Impossible to exactly estimate interferer channels

15. How Does TIMO Work? AP Client AP is not interested in decoding baby monitor • Reduce the number of unknowns to three

16. How Does TIMO Work? AP Client AP is not interested in decoding baby monitor • Reduce the number of unknowns to three

17. How Does TIMO Work? AP Client AP is not interested in decoding baby monitor • Reduce the number of unknowns to three • β is the interferer channel ratio

18. How Does TIMO Work? AP Client 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

19. Getting Around the Fundamental Limitation Scenario 1 Scenario 2 Interference Channel Interference Channel The scaling factor, c, introduces ambiguity into channels Unlike channels, the channel ratio is not ambiguous

20. If β Can be Computed, AP Can Decode WiFi Client AP Client AP can solve the two equations to decode the WiFi client

21. Question: How do we compute β? Answer: Send known symbol • WiFi client sends known symbol at beginning of its packet

22. 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

23. Question: How do we compute β? Answer: Send known symbol Time Known symbol But, what if interferer is concentrated in time Use β to decode subsequent symbols

24. Question: How do we compute β? Answer: Send known symbol Time Known symbol Known symbol • We have a solution to compute β without known symbols But, what if interferer is concentrated in time

25. Intuition: Exploit the WiFi Symbol Structure • BPSK – ‘1’ bit sent as +1 and ‘0’ bit sent as -1 Imaginary +1 -1 Real

26. Intuition: Exploit the WiFi Symbol Structure • BPSK – ‘1’ bit sent as +1 and ‘0’ bit sent as -1 • If no interference, received symbols are close to expected symbols Imaginary +1 -1 Real

27. Intuition: Exploit the WiFi Symbol Structure • 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 Imaginary correct Correct estimate  Average error is small Error +1 -1 Real

28. Intuition: Exploit the WiFi Symbol Structure • 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 Imaginary guess1 correct Bad estimate  Average error is big +1 -1 Real Error

29. Intuition: Exploit the WiFi Symbol Structure • 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 Imaginary guess2 guess1 correct Better Estimate  Average error reduce Error +1 -1 Real • Design gradient descent style algorithm to iteratively converge to actual channel ratio • Paper described algorithm that works across modulations

30. Performance

31. Implementation • Implement using USRP2s • WiFi modulations and coding rates • OFDM over 10 MHz • Bits rates between 3-27 Mbps • No carrier sense

32. Testbed • Place USRP prototype for 802.11 at blue locations • Change the location of interferer over red locations Tx Rx

33. Throughput Performance with Baby Monitor 802.11 Throughput (in Mbps) WiFi Interferer Location # Line of sight Non- Line of sight 1 foot 90 feet

34. Throughput Performance with Baby Monitor 802.11 Throughput (in Mbps) USRP WiFi 60 feet away WiFi Interferer Location # Despite disabling carrier sense, complete loss of connectivity in more than half the location Line of sight Non- Line of sight 1 foot 90 feet

35. Throughput Performance with Baby Monitor Without interference USRP WiFi with TIMO 802.11 Throughput (in Mbps) USRP WiFi WiFi Interferer Location # Line of sight Non- Line of sight 1 foot 90 feet

36. Throughput Performance Cordless Phones Microwave Ovens with TIMO with TIMO 802.11 Throughput(in Mbps) 802.11 Throughput(in Mbps) w/o TIMO w/o TIMO TIMO transforms scenarios with a complete loss of connectivity to operational networks Interferer Location # Interferer Location #

37. Related Work • Decoding Interference [IC, SAM, Beamforming, …] • Cognitive Communication [Samplewidth, Jello, Swift, …] - 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

38. 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