1. Successive Interference Cancellation: A Back of the Envelope Perspective Souvik Sen, Naveen Santhapuri, Romit Roy Choudhury, Srihari Nelakuditi I have inserted some text in the text box below for the first few slides. This should help in getting started with the flow of the talk. Also, some suggestions for modifications are inserted in these yellow post-it notes. Make those changes. I have also reduced the mentioning of “holes”... we were bringing it up too much. I have inserted some text in the text box below for the first few slides. This should help in getting started with the flow of the talk. Also, some suggestions for modifications are inserted in these yellow post-it notes. Make those changes. I have also reduced the mentioning of “holes”... we were bringing it up too much.

2. 2 Simple Case of Wireless Transmission Decoding successful if: AP Signal = Noise SNR = T1 Bigger fonts Write “Threshold” Do so for next 2 slides Bigger fonts Write “Threshold” Do so for next 2 slides

3. 3 Interferer What if parallel transmissions? Decoding successful only if: Signal = Interference + Noise SINR = T1 AP T2

4. 4 Collision Decoding fails because: Signal = Interference + Noise SINR = Interferer T1 AP T2

5. 5 Successive Interference Cancellation Interferer T1 AP T2 - = 3. Decode as if simple transmission 1. Decode strongest signal first 1. Decode strongest signal first 2. Model and subtract 2. Model and subtract Thus, it is as if SIC can “uncollide” signals, resulting in two successful transmissions Correct the animation. Make the 3 boxes come with the corresponding picture. See the text in the lower panel so you know how to explain it.

6. 6 SIC Capacity SNR = R blue = S blue noise log 1 + SINR = R* green = S green S blue + noise log 1+ T1 T2 Interferer AP R SIC = S blue + S green noise log 1+ Rate of green signal far less Rate of blue signal remains same Strong signal penalized, weak signal gets all the benefits

7. 7 Channel Capacity w/o SIC SNR = R blue = S blue noise log 1 + T1 T2 Interferer AP SNR = S green R green = noise log 1 + R SIC = S blue + S green noise log 1+ R woSIC = max( R blue, R green ) Gain sic =

8. 8 SIC PHY Capacity Gain

9. 9 Max SIC gain when equal signal strengths

10. We were tempted to schedule packet transmissions of similar signal strengths... As protocol designers... Our interpretation was that... maximizing SIC capacity will maximize throughput

11. This paper studies the SIC implications on throughput on two types of scenarios 1. Two transmitters transmitting to a common receiver 2. Two transmitters transmitting to distinct receivers

12. 12 SIC: MAC Layer Packet Perspective Weaker blue packet can be at a high rate Stronger green packet has to be at low rate MAC Layer throughput can actually suffer T1 T2 Interferer AP HOLE Packet Transmission Time Rate Make first bullet come with green box, then second bullet with blue box. Correct hole animation Make first bullet come with green box, then second bullet with blue box. Correct hole animation

13. 13 Mathematically... T1 T2 Interferer AP HOLE Packet Transmission Time Time sic = Time woSIC = Packet Transmission Time L R blue L R* green max, = L R blue L R green + = Gain SIC = The “=” sign is also animated. Remove

14. 14 SIC Throughput Gain

15. 15 SIC Throughput Gain Max throughput gain when signal strengths are 2:1

16. 16 Capacity Vs. Throughput We expected:  Maximizing SIC capacity will maximize throughput Reality:  Equal signal strengths maximize capacity  Disparate signal strengths (2:1) maximize throughput Capacity Draw a single double-sided arrow to depict capacity... then explain throughput.

17. by reducing size of the hole... Can’t we improve MAC layer throughput with SIC

18. 18 (1) Power Control Reduce power of blue Tx such that SINR* green = R green R blue = 2 * Reduce

19. 19 (2) Client Pairing T1T2T3 R green R blue Make 2 pairs

20. 20 (2) Client Pairing T1T2T3 R green R blue R green R red

21. 21 (3) MultiRate Packetization Multirate Packetization  Send the strong packet at high rate after weak packet has finished R* green R blue R green R blue

22. 22 (4) Packet Packing Packet Packing  Send multiple packets to fill up the hole  Hard because stronger signal modeling becomes difficult R* green R blue

23. - Perform Monte Carlo Simulations How Does Adaptation Help?

24. 24 Considerable Improvement with Adaptation Performance with MAC Modifications

25. 25 SIC Capacity: Two Tx same Rx T1 T2 Interferer AP How does SIC perform for different receivers?

26. 26 SIC MAC: Two Transmitter Different Receiver Various Topologies No SICSIC at R 2 SIC at R 1 SIC at R 1 and R 2

27. - Perform Monte Carlo Simulations How often such topologies occur and what is the relative gain?

28. 28 Gain with SIC in less than 10% of the cases Two Tx Different Rx: Monte Carlo Simulation

29. 29 Not many topologies offer gain even with MAC modifications Not many topologies offer gain even with MAC modifications Does MAC Adaptation Help?

30. 30 SIC Benefit in Different Wireless Architectures Enterprise Wireless LAN  Upload Traffic: Considerable SIC gain with 2 clients to 1 AP  Download Traffic: Two AP to one client, not beneficial  Download Traffic: Two AP to diff. clients, same as 2 tx diff. rx Residential Wireless LAN  Upload same as EWLAN  Download topologies provide a bit more opportunity than EWLAN

31. 31 Conclusion SIC may not be promising to improve wireless throughput  Bitrate selection is reaching optimality  SIC constraint: Stronger Tx needs to be decoded under interference SIC has promising gain in upload scenarios Interference cancellation useful when interfering tx known  No bitrate constraint like SIC: ANC, ZigZag, CSMA/CN

32. Questions, comments? Thank you Duke SyNRG Research Group http://synrg.ee.duke.edu

33. 33 Successive Interference Cancellation Received signal is the sum of interfering and own signal Decode strong interfering signal Subtract it from total signal Decode own (weaker) signal  Its implementation is in time domain Cancellation: - = Next Decode: SIC can decode both packets even though they are received simultaneously

34. 34 Successive Interference Cancellation Received signal is the sum of interfering and own signal Decode strong interfering signal Subtract it from total signal Decode own (weaker) signal  Its implementation is in time domain Cancellation: - = Next Decode: SIC can decode both packets even though they are received simultaneously

35. 35 Can we “Uncollide” Packets? But> Signal = Interference + Noise SINR = The interfering transmission can be decoded Interferer T1 AP T2

36. Note to Protocol Designers: To maximize throughput with SIC schedule transmissions of equal strength - Lets verify that!

37. 37 Why is This Happening? T1 T2 Interferer AP = HOLE R green R blue

38. 38 Why is This Happening? Maximizing capacity does not maximize throughput HOLE Capacity Throughput = + + +

39. 39 SIC Throughput Gain R green R blue This happens because Max throughput gain when signal strengths are 2:1

40. 40 Improving MAC Throughput: Power Control Rate of strong Tx depends on signal strength of weak Tx Reduce power of blue Tx such that SINR green = HOLE R green R blue SINR* green = R green R blue = 2 *