Yi Shi (with Canming Jiang, Thomas Hou , Wenjing Lou, Sastry Kompella , and Scott Midkiff )

1. Squeezing the Most Out of Interference: An Optimization Framework for Joint Interference Exploitation and Avoidance Yi Shi (with Canming Jiang, Thomas Hou, WenjingLou, SastryKompella, and Scott Midkiff) IEEE INFOCOM 2012 – Orlando, Florida

2. Synopsis Interference avoidance & interference exploitation Previous work Successive interference cancellation An optimization framework Numerical results IEEE INFOCOM 2012 2

3. Traditional Interference Management interference signal time slot 1 sub-channel 1 time slot 2 sub-channel 2 Blue link interferes withred link! Interference avoidance schemes • Can we do better? • YES! We can! • Random • CSMA • CSMA/CA Interference exploitation • Deterministic • TDMA • FDMA • CDMA IEEE INFOCOM 2012 3

4. Interference Exploitation time slot 1 time slot 1 Potential throughput improvement! • Allows simultaneous transmissions • Relies on some advanced decoding schemes • Separating overlapping signals and interferences IEEE INFOCOM 2012 4

5. Previous Work • [S. Verdu ’98] • Successive interference cancellation (SIC); • Parallel interference cancellation • Iterative interference cancellation • SIC as one of the most promising techniques due to its simplicity and effectiveness • Analog network coding [S. Kattiet al., ’07] and ZigZag decoding [S. Gollakotaet al., ’08] • Require knowledge of some bits in one of the collision packets • Smart antenna-based interference cancellation • MIMO, directional antenna • Scope of this paper: How to apply SIC in a multi-hopnetwork? IEEE INFOCOM 2012 5

6. Synopsis Interference avoidance & interference exploitation Previous work Successive interference cancellation An optimization framework Numerical results IEEE INFOCOM 2012 6

7. SIC: An Overview 2 With SIC Without SIC OK 1 3 • Receiver decodes the strongest signal • If successful, subtracts it from the composite signal and decodes the next strongest signal IEEE INFOCOM 2012 7

8. Benefits of SIC • Enable interference rejection 2 3 1 4 interference • General case Allows concurrent receptions from multiple transmitters IEEE INFOCOM 2012 8

9. Limitations of SIC ? 2 1 3 • Sequential decoding limit • We proved: # of successfully decoded signals at receiver is no more than Sequential SINR constraint IEEE INFOCOM 2012 9

10. Pros & Cons • Interference exploitation • Pros: throughput improvement; approaching to theoretical limits • Cons: more complex; limited to decode and cancel all interference How to take the best of both worlds while avoid each other’s pitfalls? • Interference avoidance (IA) • Pros: easy to implement • Cons: far from information theoretical limits IEEE INFOCOM 2012 10

11. Our Approach and Challenges Tighten couplings across three layers! • Our approach: Use IA to alleviate limitations of SIC • Developing a tractable cross-layer model suitable for formal optimization • Physical layer: Sequential decoding constraints brings significant difficulty • Link layer: Scheduling (i.e., IA) needed to address the limitations of SIC • Network layer: More links enabled by SIC; more routing options IEEE INFOCOM 2012 11

12. Synopsis Interference avoidance & interference exploitation Previous work Successive interference cancellation An optimization framework Numerical results IEEE INFOCOM 2012 12

13. Network Settings s s d d d s • Ad hoc wirelessnetwork • Multiple sessions and multi-hop routing • Interference exploitation • SIC • Interference avoidance • Scheduling IEEE INFOCOM 2012 13

14. Scheduling Constraints Scheduling variable One transmitter can transmit to at most one receiver Half-duplex constraints IEEE INFOCOM 2012 14

15. Joint PHY-Link Constraints All stronger signals must be decodable! Desired signal must be decodable! Residual SINR The following constraints need to be satisfied IEEE INFOCOM 2012 15

16. Flow Routing Constraints • Flow balance • Source node: • Relay node: • Destination node: • Flow rate constraint IEEE INFOCOM 2012 16

17. An Optimization Framework IEEE INFOCOM 2012 17

18. Synopsis Interference avoidance & interference exploitation Previous work Successive interference cancellation An optimization framework Numerical results IEEE INFOCOM 2012 18

19. A Throughput Maximization Problem Max s.t. All constraints in the optimization framework IEEE INFOCOM 2012 19

20. Routing Results IEEE INFOCOM 2012 20

21. Scheduling Results Interference rejection & concurrent reception! IEEE INFOCOM 2012 21

22. Comparison to Pure Interference Avoidance • Pure interference avoidance • Throughput is 4.5 • Interference exploitation and avoidance • Throughput is 6.6 • Our joint interference exploitation-avoidance scheme can increase throughput by (6.6-4.5)/4.5 = 47% IEEE INFOCOM 2012 22

23. Summary • Advocated joint interference exploitation and avoidance • Combines the best of both worlds while avoids each’spitfalls • First work combining SIC and interference avoidance in a multi-hop wireless network • Proposed a formal optimization framework with cross-layerformulation of PHY, link, and network layers • A rather complete design space for SIC with the goal to squeeze the most out of interference • Can be used to address a broad class of research problems IEEE INFOCOM 2012 23