1. Interference in MANETs: Friend or Foe? Andrea Goldsmith
ITMANET FLoWS Focus Talk
Interference in MANETs: Friend or Foe?
Andrea Goldsmith
Joint work with Dabora, Gunduz, Kramer, Liu, Maric, Poor, Shamai

2. 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

3. 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 Channel
Interference Channel
Relay Channel
General MANETs

4. Interference: Friend or Foe?
If treated as noise: Foe
If decodable or precodable: Neutral
Neither friend nor foe
Increases BER,
Reduces capacity
Multiuser detecion (MUD) and precoding
can completely remove interference
Common coding strategy to approach capacity

5. If exploited via coding, cooperation, and cognition
Interference: Friend or Foe?
If exploited via coding, cooperation, and cognition
Friend
Especially in a network setting

6. Exploiting Interference through Coding
The Z Channel
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

7. Exploiting Interference through Cognition
Cognitive user has knowledge of other user’s message and/or encoding strategy
Used to help noncognitive transmission
Used to presubtract noncognitive interference
RX1 CR
RX2
NCR
Joint with Maric, Kramer, Shamai

8. Proposed Transmission Strategy
To allow each receiver to decode part of the other node’s message  reduces interference
Cooperation at CR TX
Cooperation atCR TX
Removes the NCR
interference at the CR RX
Cooperation at CR TX
Precoding against interference at CR TX
To help in sending NCR’s message to its RX
It is CLEAR that it needs
Precoding against interference at CR TX
Rate splitting
We optimally combine
these approaches into
one strategy

9. More Precisely: Transmission for Achievable Rates
The NCR uses single-user encoder
RX1
RX2
NCR CR
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
Rate
split CR
NCR

10. Upper Bounds 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
How far are the achievable rates from the outer bound?

11. Performance Gains from Cognitive Encoding
outer bound
our scheme
prior schemes CR
broadcast bound

12. Exploiting Interference through Relaying
TX1
TX2
relay
RX2
RX1 X1 X2
Y3=X1+X2+Z3
Y4=X1+X2+X3+Z4
Y5=X1+X2+X3+Z5
X3= f(Y3)
Relaying strategies:
Relay can forward all or part of the messages
Much room for innovation
Relay can forward interference
To help subtract it out
Joint with Maric, Dabora, Medard

13. Achievable Rates with Interference Forwarding
dest1
dest2
encoder 1
encoder 2
relay
for any distribution p(p(x1)p(x2,x3)p(y1,y2|x1,x2,x3)
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

14. Capacity Gains from Interference Forwarding

15. Diversity-Multiplexing Tradeoffs in Multi-Antenna MANETs
Focus on (M1, M2, M3)
Quasi-static Rayleigh fading channel
Channel state known only at the receivers
Joint with Gunduz, Poor

16. Diversity-Multiplexing Tradeoff in Point-to-Point MIMO Channels
- Multiplexing gain r: - Diversity gain d

17. 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

18. Half-duplex Relay Static Protocols:
The source transmits during the first aT channel uses, 0<a<1
The 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)‏

19. 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

22. Multiple Relay Networks
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

23. End to End Distortion Use antennas for multiplexing:
Use antennas for diversity
High-Rate
Quantizer
ST Code
High Rate
Decoder
We optimize the point on the DMT tradeoff curve to minimize distortion
ST Code
High
Diversity
Low-Rate
Quantizer
Decoder

24. 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 channels
Separate source and channel coding optimal
We found the operating point on the DMT multihop region for minimal distortion
Under delay constraints, optimization needed

25. Summary
Fundamental performance limits of MANETS requires understanding and exploiting interference
Interference can be exploited via coding/relaying, cooperation, or cognition
The 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 node
Use antennas for multiplexing, diversity, or IC?

26. 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