ITMANET FLoWS Focus Talk Interference in MANETs: Friend or Foe? Andrea Goldsmith Joint work with...
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Transcript of ITMANET FLoWS Focus Talk Interference in MANETs: Friend or Foe? Andrea Goldsmith Joint work with...
ITMANET FLoWS Focus Talk
Interference in MANETs: Friend or Foe?
Andrea Goldsmith
Joint work with Dabora, Gunduz, Kramer, Liu, Maric, Poor, Shamai
MANET Characteristics
Peer-to-peer communications All transmissions interfere due to broadcast
nature of radio Highly dynamic Nodes can cooperate to forward data Can introduce feedback to improve
performance
Interference in MANETs Radio is a broadcast medium
Radios in the same spectrum interfere
MANET capacity in unknown for all canonical networks with interference (even when exploited)Z ChannelInterference ChannelRelay ChannelGeneral MANETs
Interference: Friend or Foe?
If treated as noise: Foe
If decodable or precodable: Neutral Neither friend nor foe
IN
PSNR
Increases BER,
Reduces capacity
Multiuser detecion (MUD) and precoding
can completely remove interferenceCommon coding strategy to
approach capacity
If exploited via coding, cooperation, and
cognition
Friend
Interference: Friend or Foe?
Especially in a network setting
Exploiting Interference through
Coding
Capacity of Z channel unknown in general
We obtain capacity for a class of Z channels• Korner/Marton technique applicable• Enough to consider superposition
encoding• Han/Kobayashi achievable region is
capacity region
Yields capacity for large class of Gaussian interference channels
The Z Channel
Exploiting Interference through
Cognition
Cognitive user has knowledge of other user’s message and/or encoding strategyUsed to help noncognitive
transmissionUsed to presubtract noncognitive
interferenceRX1
RX2NCR
CR
Joint with Maric, Kramer, Shamai
8
Proposed Transmission Strategy
Rate splitting
Precoding againstinterference
at CR TX
Cooperationat CR TXCooperation
atCR TX
Coop
era
tion
at
CR
TX P
reco
din
g a
gain
stin
terfe
ren
ceat C
R T
X
To allow each receiver to decode part of the other node’s message
reduces interference
Removes the NCR interference at the CR RX
To help in sending NCR’s
message to its RX
We optimally combine these approaches into
one strategy
More Precisely: Transmission for Achievable Rates
Rate split
(.)1cUP
NCR
)|(. 1| 11 cUU uPca
2W(.)
2XPNX2
1W cW
aW1
N
cU
1
NX2
NX2
NN
acUU
11,
NX2
NX1
2W
CR
The NCR uses single-user encoder
The CR uses - Rate-splitting to allow receiver 2 to decode part of cognitive user’s message and thus reduce interference at that receiver - Precoding while treating the codebook for user 2 as interference to improve rate to its own receiver - Cooperation to increase rate to receiver 2
RX1
RX2NCR
CR
10
Upper Bounds
How far are the achievable rates from the outer bound?
• Follows from standard approach: • Invoke Fano’s inequality
• Reduces to outer bound for full cooperation for R2=0
• Has to be evaluated for specific channels
Performance Gains from Cognitive
Encoding
CRbroadcast
bound
outer bound
our schemeprior schemes
Exploiting Interference through Relaying
Relaying strategies: Relay can forward all or part of the
messages Much room for innovation
Relay can forward interference To help subtract it out
TX1
TX2
relay
RX2
RX1X1
X2
Y3=X1+X2+Z3
Y4=X1+X2+X3+Z4
Y5=X1+X2+X3+Z5
X3= f(Y3)
Joint with Maric, Dabora, Medard
Achievable Rates withInterference Forwarding
)|;(
);,,(
);,,(
)|;,(
),|;(
3322
232121
132121
12322
32111
XYXIR
YXXXIRR
YXXXIRR
XYXXIR
XXYXIR
• The strategy to achieve these rates is:
- Single-user encoding at the encoder 1 to send W1
- Decode/forward at encoder 2 and the relay to send message W2
• This region equals the capacity region when the interference is strong and the channel is degraded
for any distribution p(p(x1)p(x2,x3)p(y1,y2|x1,x2,x3)
dest1
dest2
encoder 1
encoder 2
relay
Capacity Gains fromInterference Forwarding
Diversity-Multiplexing Tradeoffs in
Multi-Antenna MANETs
iiii
i WXHM
SNRY
• Focus on (M1, M2, M3)
• Quasi-static Rayleigh fading channel
• Channel state known only at the receivers
Joint with Gunduz, Poor
- Multiplexing gain r: - Diversity gain d
Diversity-Multiplexing Tradeoff in
Point-to-Point MIMO Channels
))(()( 2121kMkMkd MM
DMT for Full-duplex Relays
The relay can receive and transmit simultaneously
The DMT for (M1,M2,M3) full-duplex system is
The hop with the minimum diversity gain is the bottleneck
Achieved by decode-and-forward relaying with block Markov structure
Follows easily since DF achieves capacity
)}(),(min{)(3221321
rdrdrd MMMMMMM
Half-duplex Relay
Static Protocols: The source transmits during the first aT channel
uses, 0<a<1The relay tries to decode the message and forwards over the remaining (1-a)T channel uses:
decode-and-forward with fixed allocation (fDF)
The DMT for half-duplex (M1,M2,M3) system with fixed time allocation a
Optimize a for each multiplexing gain: decode-and-forward with variable
allocation (vDF)
a
rd
a
rdrd MMMM
fDF
MMM 1,min)(
3221321
Dynamic Decode-and-Forward (DDF) for Half-duplex Relay
Introduced by Azarian et al. (IT’05): Relay listens until decoding Transmits only after decoding
Achieves the best known DMT for half-duplex relay channels, yet short of the upper bound
We show: Achieves optimal DMT in multi-hop relay channels
Not piece-wise linear, no general closed form expression
Can be cast into a convex optimization problem
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10
0.5
1
1.5
2
2.5
3
3.5
4
Multiplexing gain, (r)
Div
ers
ity g
ain
, d(r
)
DMT of (4,1,3) half-duplex relay channel
d4,1
(r)
d1,3
(r)
dDDF
(r)
dvDF
(r)
dfDF
(r), a=0.5
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20
0.5
1
1.5
2
2.5
3
3.5
4
Multiplexing gain, (r)
Div
ers
ity g
ain
, d(r
)DMT of (2,2,2) half-duplex relay channel
d2,2
(r)
dDDF
(r)
dvDF
(r)
• Multiple full-duplex relays: • DMT dominated by hop with minimum diversity gain.
• Multiple half-duplex relays: • Odd and even numbered relays transmit in turn. • DDF (with time limitation for successive hops) is DMT optimal.• DMT dominated by 2 consecutive hops with min. diversity gain
Multiple Relay Networks
End to End DistortionUse antennas for multiplexing:
Use antennas for diversity
High-RateQuantizer
ST CodeHigh Rate Decoder
Low-RateQuantizer
ST CodeHigh
DiversityDecoder
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20
0.5
1
1.5
2
2.5
3
3.5
4
Multiplexing gain, (r)
Div
ers
ity g
ain
, d(r
)
DMT of (2,2,2) half-duplex relay channel
d2,2
(r)
dDDF
(r)
dvDF
(r)
We optimize the point on the DMT tradeoff curve to minimize distortion
Exploiting Interference reduces
End-to-End Distortion
Interference exploitation at the physical layer improves end-to-end distortion
We have proved a separation theorem for a class of interference channelsSeparate source and channel
coding optimal
We found the operating point on the DMT multihop region for minimal distortionUnder delay constraints,
optimization needed
Summary Fundamental performance limits of
MANETS requires understanding and exploiting interference
Interference can be exploited via coding/relaying, cooperation, or cognitionThe right strategy depends on CSI,
dynamics, network topology, and node capabilities.
Exploiting interference leads to higher capacity, more robustness, and better end-to-end performance
MIMO adds a new degree of freedom at each nodeUse antennas for multiplexing, diversity, or
IC?
Final Comments: Startup Lessons
Learned People in industry read our papers and
implement our ideas• Communication and network theory can be
implemented in a real system in 3-9 months
• Information Theory heavily influences current and next-gen. wireless systems (mainly at the PHY & MAC layers)• Idealized assumptions have been
liberating• Wireless network design above PHY/MAC layer is ad-hoc
• The most effective way to do tech transfer is to start a company