Successive Interference Cancellation: Successive Interference Cancellation: A Back of the Envelope PerspectiveA 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

Simple Case of Wireless Transmission

Decoding successful if:

AP

Signal = Noise

SNR =

T1Bigger fontsWrite “Threshold”Do so for next 2 slides

Bigger fontsWrite “Threshold”Do so for next 2 slides

3

Interferer

What if parallel transmissions?

Decoding successful only if:

Signal = Interference + Noise

SINR =

T1AP

T2

4

Collision

Collision

Decoding fails because:

Signal = Interference + Noise

SINR =

Interferer

T1AP

T2

5

Successive Interference Cancellation

Interferer

T1AP

T2

- =

3. Decode as ifsimple transmission

1. Decode strongest signal first

1. Decode strongest signal first

2. Model and subtract2. 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.

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

SIC Capacity

SNR =

Rblue = Sblue

noiselog 1 +

SINR =

R*green = Sgreen

Sblue + noiselog 1+

T1T2

Interferer

AP

RSIC = Sblue + Sgreen

noiselog 1+

Rate of green signal far lessRate of green signal far lessRate of blue signal remains sameRate of blue signal remains same

Strong signal penalized, weak signal gets all the benefits

7

Channel Capacity w/o SIC

SNR =

Rblue = Sblue

noiselog 1 +

T1T2

Interferer

AP

SNR =

SgreenRgreen = noise

log 1 +

RSIC = Sblue + Sgreen

noiselog 1+

RwoSIC = max( Rblue, Rgreen )

Gainsic =

8

SIC PHY Capacity Gain

9

SIC PHY Capacity Gain

Max SIC gain when equal signal strengths

We were tempted to schedule packet transmissions of similar signal strengths ...

As protocol designers ...

Our interpretation was that ...

maximizing SIC capacity will maximize throughput

This paper studies the SIC implications on throughputon two types of scenarios

1. Two transmitters transmitting to a common receiver

2. Two transmitters transmitting to distinct receivers

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 sufferMAC Layer throughput can actually suffer

T1T2

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

Mathematically ...

T1T2

Interferer

AP

HOLE

Packet Transmission Time

Timesic =

TimewoSIC =

Packet Transmission Time

L

Rblue

L

R*green

max ,=

L

Rblue

L

Rgreen

+=

GainSIC =

The “=” sign is also animated. Remove

The “=” sign is also animated. Remove

14

SIC Throughput Gain

15

SIC Throughput Gain

Max throughput gain when signal strengths are 2:1

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.Draw a single double-sided arrow to depict capacity ... then explain throughput.

by reducing size of the hole ...

Can’t we improve MAC layer throughput with SIC

18

(1) Power Control

Reduce power of blue Tx such that

SINR*green = Rgreen

Rblue

= 2 *

Reduce

19

(2) Client Pairing

T1 T2 T3

Rgreen

Rblue

Make 2 pairsMake 2 pairs

20

(2) Client Pairing

T1 T2 T3

Rgreen

Rblue

Rgreen

Rred

21

(3) MultiRate Packetization

Multirate Packetization Send the strong packet at high rate after weak packet has finished

R*green

Rblue RgreenRblue

22

(4) Packet Packing

Packet Packing Send multiple packets to fill up the hole Hard because stronger signal modeling becomes difficult

R*green

Rblue

- Perform Monte Carlo Simulations

How Does Adaptation Help?

24

Considerable Improvement with AdaptationConsiderable Improvement with Adaptation

Performance with MAC Modifications

25

SIC Capacity: Two Tx same Rx

T1T2

Interferer

AP

How does SIC perform for different receivers?

26

SIC MAC: Two Transmitter Different Receiver

Various Topologies

No SIC SIC at R2

SIC at R1 SIC at R1 and R2

- Perform Monte Carlo Simulations

How often such topologies occur and what is the relative gain?

28

Gain with SIC in less than 10% of the casesGain with SIC in less than 10% of the cases

Two Tx Different Rx: Monte Carlo Simulation

29

Not many topologies offer gain even with MAC modifications

Not many topologies offer gain even with MAC modifications

Does MAC Adaptation Help?

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

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

Questions, comments?

Thank you

Duke SyNRG Research Grouphttp://synrg.ee.duke.edu

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

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

Can we “Uncollide” Packets?

But >

Signal = Interference + Noise

SINR =

The interfering transmission can be decodedThe interfering transmission can be decoded

Interferer

T1AP

T2

Note to Protocol Designers: To maximize throughput with SIC schedule transmissions of equal strength

- Lets verify that!

37

Why is This Happening?

T1T2

Interferer

AP

=

HOLE

Rgreen

Rblue

38

Why is This Happening?

Maximizing capacity does not maximize throughputMaximizing capacity does not maximize throughput

HOLE

Capacity

Throughput =

+

++

39

SIC Throughput Gain

Rgreen

Rblue

This happens because

Max throughput gain when signal strengths are 2:1

40

Improving MAC Throughput: Power Control

Rate of strong Tx depends on signal strength of weak Tx

Reduce power of blue Tx such that

SINRgreen = HOLE

Rgreen

Rblue

SINR*green = Rgreen

Rblue

= 2 *