next generation 802.11n
DESCRIPTION
Next Generation 802.11n. Dina Katabi Jointly with Kate Lin and Shyamnath Gollakota. 1-antenna devices. 2-antenna devices. 3-antenna devices. Wireless nodes increasingly have heterogeneous numbers of antennas. 802.11 Was Designed for 1-Antenna Nodes. Alice. Bob. Chris. - PowerPoint PPT PresentationTRANSCRIPT
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Next Generation 802.11n
Dina Katabi
Jointly with Kate Lin and Shyamnath Gollakota
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Wireless nodes increasingly haveheterogeneous numbers of antennas
1-antenna devices 2-antenna devices3-antenna devices
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802.11 Was Designed for 1-Antenna Nodes
When a single-antenna node transmits,multi-antenna nodes refrain from transmitting
Alice
Bob
Chris
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But, MIMO Nodes Can Receive Multiple Concurrent Streams
Alice
Bob
Chris
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Alice
It’s Not That Simple
But, how do we transmit without interfering at receivers with fewer antennas?
Interference!!
Interference!!Bob
Chris
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802.11n+
• Enables 802.11 nodes to contend for both time and concurrent transmissions
• Maintains random access
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1. How to transmit without interfering with receivers with fewer antennas? Interference nulling Interference alignment
2. How do we achieve it in a random access manner? Multi-dimensional carrier sense
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1. How to transmit without interfering with receivers with fewer antennas? Interference nulling Interference alignment
2. How do we achieve it in a random access manner? Multi-dimensional carrier sense
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Interference Nulling
Alice
Bob nullin
g
• Signals cancel each other at Alice’s receiver• Signals don’t cancel each other at Bob’s receiver
Because channels are different
y
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h1y h2y 0
Interference Nulling
• Signals cancel each other at Alice’s receiver• Signals don’t cancel each other at Bob’s receiver
Because channels are different• Bob’s sender learns channels either by feedback
from Alice’s receiver or via reciprocity
Alice
y
y
h1
h2
0Bob
Nulling : h1 h2
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Interference Nulling
Interference Nulling
Q: How to transmit without interfering with receivers with fewer
antennas?A: Nulling
h1y h2y 0Alice
y
y
h1
h2
0Bob
Nulling : h1 h2
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Alice
Bob
Chris
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Is Nulling Alone Enough? NO!!
Alice
Bob
Chris
NO!
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Is Nulling Alone Enough? NO!!
Alice
Bob
Chris
NO!
Chris needs to null at three antennas
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(h11h21h31)z 0
Is Nulling Alone Enough? NO!!
Alice
Bob
z
z
zChris
(h12h22h32)z 0
(h13h23h33)z 0
Only solution 0
Transmit Nothing!!!
NO!null
z
Are we doomed?No, we can use interference alignment
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MIMO Basics1. N-antenna node receives in N-dimensional
space
antenna 1
antenna 2
antenna 1
antenna 1
antenna 2
antenna 3
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MIMO Basics1. N-antenna node receives in N-dimensional
space2. N-antenna receiver can decode N signals
2-antenna receivery1 y2
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MIMO Basics1. N-antenna node receives in N-dimensional
space2. N-antenna receiver can decode N signals3. Transmitter can rotate the received signal
y’y2-antenna receiver = Ry
Rotate by multiplying transmitted signal by a rotation matrix R
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Interference Alignment
wanted signalI1I2
If I1 and I2 are aligned, appear as one interferer 2-antenna receiver can decode the wanted signal
2-antenna receiver
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Interference Alignment
If I1 and I2 are aligned, appear as one interferer 2-antenna receiver can decode the wanted signal
2-antenna receiver I1 + I2wanted signal
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align
ing
Use Nulling and Alignment
nullin
g Alice(unwanted)Bob
Chris
Alice
Bob
Chris
Null as before
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align
ing
Use Nulling and Alignment
Alice
Bob
Chris
nullin
g
Alice + Chris
(unwanted)Bob
2-signals in 2D-spaceCan decode Bob’s signal
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Alice
Bob
Chris
Use Nulling and Alignment
3 packets through receivers have fewer than 3
antennas
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MAC Protocol• Each sender computes in a distributed
way where and how to null where and how to align
• Analytically proved: # concurrent streams = # max antenna per
sender
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1. How to transmit without interfering with ongoing transmissions? Interference nulling Interference alignment
2. How do we achieve it in a random access manner? Multi-dimensional carrier sense
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1. How to transmit without interfering with receivers with fewer antennas? Interference nulling Interference alignment
2. How do we achieve it in a random access manner? Multi-dimensional carrier sense
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In 802.11, contend using carrier sense
Multi-Dimensional Carrier Sense
But, how to contend despite ongoing transmissions?
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Multi-Dimensional Carrier SenseAlice
BobContend
BenAlice
Contend
Alice
Bob and Ben contend for a second concurrent transmission
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Multi-Dimensional Carrier SenseAlice
Bob
BenAlice
Project orthogonal to Alice’s signal
AliceContend
Contend
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Multi-Dimensional Carrier SenseAlice
BobContend
orthogonal to Aliceno signal from Alice!!
Alice
orthogonal to Aliceno signal from Alice!!
BenAlice
Contend
Project orthogonal to Alice’s signal
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Multi-Dimensional Carrier SenseAlice
BobAlice
Apply carrier sense in the orthogonal space
BenAlice
orthogonal to Aliceno signal from Alice!!
orthogonal to Aliceno signal from Alice!!
Contend
Contend
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Alice
Alice
Bob
Bob
Detect energy after projection
Multi-Dimensional Carrier Sense
Win
LoseBen
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To contend for the next concurrent transmission
• Project orthogonal to ongoing signals
• Apply standard carrier sense
Multi-Dimensional Carrier Sense
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1. How to transmit without interfering with receivers with fewer antennas? Interference nulling Interference alignment
2. How do we achieve it in a random access manner? Multi-dimensional carrier sense
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Performance
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Implementation
• Implemented in USRP2
• OFDM with 802.11-style modulations and convolutional codes
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Experiment
Alice
Bob
Chris
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Throughput Results
0 10 20 30 40 50 60 70 800
0.2
0.4
0.6
0.8
1
Total throughput [Mb/s]
CDFs
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0 10 20 30 40 50 60 70 800
0.2
0.4
0.6
0.8
1
802.11n+ 802.11n
Total throughput [Mb/s]
CDFs
Throughput Results
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0 10 20 30 40 50 60 70 800
0.2
0.4
0.6
0.8
1
802.11n+ 802.11n
Total throughput [Mb/s]
CDFs
Throughput Results
~2x
n+ doubles the median throughput
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MegaMIMO: Scaling Wireless Throughput with
the Number of Users
Hariharan Rahul, Swarun Kumar and Dina Katabi
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MegaMIMO
MegaMIMO alleviates the capacity crunch by transmitting more bits per unit of spectrum using a distributed
MIMO transmitter
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Access
Point 1
Access
Point 2
Today’s Wireless NetworksEthernet Acces
s Point
3
User 2User 3User
1
Interference!
Access Points Can’t Transmit Together in the Same Channel
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Interference from x2+x3≈0
Data: x1 survives
MegaMIMO
All Access Points Can Transmit Simultaneously in the Same Channel
Interference from x1+x3≈0
Data: x2 survives
Interference from x1+x2≈0
Data: x3 survives
User 2User 3User
1
Access
Point 1
Access
Point 2
Ethernet Acces
s Point
3
Enables senders to transmit together without interference
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User 1
Ethernet
AP1
User 2
AP2
User 3
AP3
User 10
AP10…
…
Distributed protocol for APs to act as a huge MIMO transmitter with sum of antennas
10 APs 10x higher throughput
MegaMIMO = Distributed MIMO
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Diving Into The Details
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AP 2
AP 1
Cli 1
Cli 2
Wants x1Receives y1
y1 = d1 x1 + 0 . x2
Wants x2Receives y2
y2 = 0 . x1 + d2 x2
y1
y2=
x1
x2
d1
00d2
Transmitting Without Interference
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AP 2
AP 1
Cli 1
Cli 2
Wants x1
y1 = d1 x1 + 0 . x2
Wants x2
y2 = 0 . x1 + d2 x2
y1
y2=
x1
x2D Diagonal
Transmitting Without Interference
Receives y1 Receives y2
Goal: Make the effective channel matrix diagonal
Diagonal Matrix Non-Interference
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On-Chip MIMO• All antennas on the MIMO sender are
synchronized in time to within nanoseconds of each other.
• All antennas on a MIMO sender have exactly the same oscillator, i.e., no frequency offset.
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y1 = h11 x1 + h12 x2 y2 = h21 x1 + h22 x2
y1
y2=
x1
x2
h11
h22
h12
h21
On-Chip MIMO
Non-diagonal Matrix Interference
AP
Cli 1
Cli 2
Sends x1 Sends x2
h11 h12 h21h22
y1 y2
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y1 = h11 x1 + h12 x2 y2 = h21 x1 + h22 x2
y1
y2=
x1
x2
h11
h22
h12
h21
On-Chip MIMO
AP
Cli 1
Cli 2
Sends x1 Sends x2
h11 h12 h21h22
y1 y2
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y1 = h11 s1 + h12 s2 y2 = h21 s1 + h22 s2
y1
y2=
s1
s2
h11
h22
h12
h21
On-Chip MIMO
AP
Cli 1
Cli 2
Sends s1 Sends s2
h11 h12 h21h22
y1 y2
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y1 = h11 s1 + h12 s2 y2 = h21 s1 + h22 s2
y1
y2=
s1
s2H
On-Chip MIMO
AP
Cli 1
Cli 2
Sends s1 Sends s2
h11 h12 h21h22
y1 y2
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y1 = h11 s1 + h12 s2 y2 = h21 s1 + h22 s2
y1
y2=
s1
s2H
Making Effective Channel Matrix Diagonal
AP
Cli 1
Cli 2
Sends s1 Sends s2
h11 h12 h21h22
y1 y2
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y1 = h11 s1 + h12 s2 y2 = h21 s1 + h22 s2
y1
y2=
s1
s2H
Making Effective Channel Matrix Diagonal
AP
Cli 1
Cli 2
Sends s1 Sends s2
h11 h12 h21h22
y1 y2
x1
x2H-1
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y1 = h11 s1 + h12 s2 y2 = h21 s1 + h22 s2
y1
y2=
x1
x2HH-1
Effective channel is diagonal
Making Effective Channel Matrix Diagonal
AP
Cli 1
Cli 2
Sends s1 Sends s2
h11 h12 h21h22
y1 y2
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• MIMO sender computes its beamformed signal si using the equation
• Clients 1 and 2 decode x1 and x2 independently
• Measure channels from sending antennas to clients
• Clients report measured channels back to APs
Beamforming System DescriptionChannel Measurement:
Data Transmission:
s = H-1 x
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Distributed Transmitters Are Different
• Nodes are not synchronized in time.–We use SourceSync to synchronize
senders within 10s of ns –Works for OFDM based systems like Wi-
Fi, LTE etc.• Oscillators are not synchronized and
have frequency offsets relative to each other.
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• Nodes are not synchronized in time.–We use SourceSync to synchronize
senders within 10s of ns –Works for OFDM based systems like Wi-
Fi, LTE etc.• Oscillators are not synchronized and
have frequency offsets relative to each other.
Distributed Transmitters Are Different
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AP 2
AP 1
Cli 1
Cli 2
h11 h12 h21h22
h22h21
h11 h12
What Happens with Independent Oscillators?
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AP 2
AP 1
Cli 1
Cli 2
h11 h12 h21h22
h22h21
h11 h12ej(ω - ω )tT1 R1
ω T1
ω R1
What Happens with Independent Oscillators?
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AP 2
AP 1
Cli 1
Cli 2
h11 h12 h21h22
h22h21
h11 h12ej(ω - ω )tT1 R1
ω T1
ω R1
What Happens with Independent Oscillators?
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AP 2
AP 1
Cli 1
Cli 2
h11 h12 h21h22
h22h21
h11 h12ej(ω - ω )tT1 R1 ej(ω - ω )tT2 R1
ω T1
ω R1
ω T2
What Happens with Independent Oscillators?
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AP 2
AP 1
Cli 1
Cli 2
h11 h12 h21h22
h22h21
h11 h12ej(ω - ω )tT1 R1 ej(ω - ω )tT2 R1
ω T1
ω R1
ω T2
What Happens with Independent Oscillators?
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AP 2
AP 1
Cli 1
Cli 2
h11 h12 h21h22
h22h21
h11 h12ej(ω - ω )tT1 R1 ej(ω - ω )tT2 R1
ω T1
ω R1
ω T2
ω R2
ej(ω - ω )tT1 R2 ej(ω - ω )tT2 R2
What Happens with Independent Oscillators?
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AP 2
AP 1
Cli 1
Cli 2
h11 h12 h21h22
h22h21
h11 h12ej(ω - ω )tT1 R1 ej(ω - ω )tT2 R1
ω T1
ω R1
ω T2
ω R2
ej(ω - ω )tT1 R2 ej(ω - ω )tT2 R2
What Happens with Independent Oscillators?
Time Varying
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AP 2
AP 1
Cli 1
Cli 2
h11 h12 h21h22
ω T1
ω R1
ω T2
ω R2
H(t)
Channel is Time Varying
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s1(t)
AP 2
AP 1
Cli 1
Cli 2
h11 h12 h21h22
ω T1
ω R1
ω T2
ω R2
H(t)y1(t)y2(t)
= s2(t)
Does Traditional Beamforming Still Work?
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AP 2
AP 1
Cli 1
Cli 2
h11 h12 h21h22
ω T1
ω R1
ω T2
ω R2
H(t)y1(t)y2(t)
=x1(t)x2(t)H-1 Not
Diagonal
Does Traditional Beamforming Still Work?
Beamforming does not work
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ChallengeChannel is Rapidly Time Varying
Relative Channel Phases of Transmitted Signals Changes Rapidly With Time
Prevents Beamforming
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Distributed Phase Synchronization
• Pick one AP as the lead• All other APs are slaves– Imitate the behavior of the lead AP
by fixing the rotation of their oscillator relative to the lead.
High Level Intuition:
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h22h21
h11 h12ej(ω - ω )tT1 R1 ej(ω - ω )tT2 R1
ej(ω - ω )tT1 R2 ej(ω - ω )tT2 R2
Decomposing H(t)
h22h21
h11 h12ej(ω )tT1 ej(ω )tT2
ej(ω )tT1 ej(ω )tT2
e-jω tR1
e-jω tR2
0
0
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h22h21
h11 h12ej(ω )tT1 ej(ω )tT2
ej(ω )tT1 ej(ω )tT2
e-jω tR1
e-jω tR2
0
0
Decomposing H(t)
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h22h21
h11 h12e-jω tR1
e-jω tR2
0
0
Decomposing H(t)
ejω tT1
ejω tT2
0
0
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h22h21
h11 h12e-jω tR1
e-jω tR2
0
0
Decomposing H(t)
ejω tT1
ejω tT2
0
0
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e-jω tR1
e-jω tR2
0
0
ejω tT1
ejω tT2
0
0
H
Decomposing H(t)
DiagonalDevices cannot track their own oscillator
phases…
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e-jω tR1
e-jω tR2
0
0
ejω tT1
ejω tT2
0
0
H
Decomposing H(t)
ejω tT1 e-jω tT1
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ej(ω - ω )t T1 0
0
H
Decomposing H(t)
R1
ej(ω - ω )t T1 R2
0
0 ej(ω - ω )t T2 T1
1
R(t) T(t)Depends only on
transmitters
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ej(ω - ω )t T1 0
0
H
Decomposing H(t)
R1
ej(ω - ω )t T1 R2
0
0 ej(ω - ω )t T2 T1
1
R(t) T(t)H(t) = R(t).H.T(t)
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Beamforming with Different Oscillators
s1(t)H(t)y1(t)y2(t)
= s2(t)R(t).H.T(t)
s1(t)s2(t)
=x1(t)x2(t)H-1T(t)-1
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Beamforming with Different Oscillators
H(t)y1(t)y2(t)
=R(t).H.T(t)
s1(t)s2(t)
=x1(t)x2(t)H-1T(t)-1
x1(t)x2(t)H-1T(t)-1
Diagonal
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Transmitter Compensation
T(t) =0
0 ej(ω - ω )t T2 T1
1
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Transmitter Compensation
T(t)-1 =0
0 e-j(ω - ω )t T2 T1
1
Slave AP imitates lead by multiplying each sample by oscillator rotation relative to
leadRequires only local information Fully
distributed
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Measuring Phase Offset• Multiply frequency offset by elapsed
time• Requires very accurate estimation of
frequency offset– Error of 25 Hz (10 parts per BILLION)
changes complete alignment to complete misalignment in 20 ms.
Need to keep resynchronizing to avoid error accumulation
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ResynchronizationAP 2
AP 1
Cli 1
Cli 2
h2lead
h2lead(t) = h2
lead ej(ω - ω )t T2 T1
Directly compute phase at each slave by measuring channel from lead
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ResynchronizationAP 2
AP 1
Sync Data
Lead AP:– Prefixes data transmission with
synchronization header
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ResynchronizationAP 2
AP 1
Sync Data
Slave AP:– Receives Synchronization Header– Corrects for change in channel phase
from lead– Transmits data
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Receiver Compensation
H(t)y1(t)y2(t)
=R(t).H.T(t)s1(t)s2(t)
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H(t)y1(t)y2(t)
=R(t).H.T(t)x1(t)x2(t)H-1T(t)-1
y1(t)y2(t)
= R(t)x1(t)x2(t)
R(t)-1
Receiver Compensation
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Receiver Compensation
R(t)-1 =e-j(ω - ω )t T1 0
0
R1
e-j(ω - ω )t T1 R2
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R(t)-1 =
Receiver Compensation
e-j(ω - ω )t T1 0
0
R1
e-j(ω - ω )t T1 R2
Receiver does what it does today – correct for oscillator offset from lead
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Performance
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Implementation
• Implemented in USRP2• 2.4 GHz center frequency• OFDM with 10 MHz bandwidth• 10 software radios acting as APs, all
in the same frequency• 10 software radios acting as clients
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Testbed
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Does MegaMIMO Scale Throughput with the Number of Users?
• Fix a number of users, say N• Pick N AP locations• Pick N client locations• Vary N from 1 to 10
• Compared Schemes:– 802.11–MegaMIMO
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Does MegaMIMO Scale Throughput with the Number of Users?
1 2 3 4 5 6 7 8 9 100
50100150200250300
Tota
l Thr
ough
put
[Mb/
s]
Number of APs on Same Channel
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Does MegaMIMO Scale Throughput with the Number of Users?
1 2 3 4 5 6 7 8 9 100
50100150200250300
802.11
Tota
l Thr
ough
put
[Mb/
s]
Number of APs on Same Channel
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Does MegaMIMO Scale Throughput with the Number of Users?
1 2 3 4 5 6 7 8 9 100
50100150200250300
MegaMIMO
802.11
Tota
l Thr
ough
put
[Mb/
s]
Number of APs on Same Channel
10x
10x throughput gain over existing Wi-Fi
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What are MegaMIMO’s Scaling Limits?
• Theoretical
• Practical
N log SNRCan Scale Indefinitely with N
Errors in H and phase synchronization affect accuracy of
beamforming
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• N APs transmit to N users, N = 2 .. 10.
• Perform MegaMIMO as before, but with a zero signal for some client (i.e. null at that client)
What are MegaMIMO’s Scaling Limits?
Phase Alignment is Accurate Received signal at noise floor (0 dB)
Inaccuracy in Phase Alignment Received signal higher than noise floor
(>0 dB)
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2 3 4 5 6 7 8 9 100
0.20.40.60.8
11.21.41.6
What are MegaMIMO’s Scaling Limits?In
terf
eren
ce t
o N
oise
Rat
io
(dB)
Number of APs on Same Channel
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2 3 4 5 6 7 8 9 100
0.20.40.60.8
11.21.41.6
What are MegaMIMO’s Scaling Limits?In
terf
eren
ce t
o N
oise
Rat
io
(dB)
Number of APs on Same Channel
Interference to Noise Ratio ~1.5 dB at 10 users
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Conclusion• Learned about Nulling, Alignment, and
MegaMIMO• In N+, the gains are lower but – Transmitters need not be connected to the same
Ethernet and exchange the packets– No need for phase synchronization
• In MegaMIMO, the gains are linear with the total number of users– Need high speed Ethernet to connect the
transmitters – Need tight phase synchronization between
transmitters