successive interference cancellation: a back of the envelope perspective souvik sen, naveen...
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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 *