Staffer Day Template

1
Information Theory for Mobile Ad-Hoc Networks
(ITMANET) The FLoWS Project
Thrust 2 Layerless Dynamic Networks Lizhong
Zheng
2
New Paradigms for Upper Bounds
Application Metrics and Network Performance
3
Layerless Dynamic Networks

• Dynamic Separation of functionalities by
  different time scales no longer optimal.
• Time varying channel/network environments, lack
  of information, high overhead costs
• Data/side information available in a variety of
  forms, with a wide range of quality/precision/reli
  ability
• Broadcasting and interference, beyond
  point-to-point communications
• Layerless Our solution to the dynamic problems
• Network information theory cooperative/cognitive
  transmissions, relay and soft information
  processing, feedbacks
• Heterogeneous data processing, prioritizing data
  by different levels of reliability networking
  based on new interface to the physical layer
• The principle of network coding,
  transmit-collect-combine pieces of information,
  generalized form and coordination in dynamic
  networks
• Operating with imperfect side information,
  robustness and universal designs.

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Thrust Areas

• Network information theory
• Multi-terminal communication schemes with
  cooperative and cognitive signaling, interference
  mitigation, broadcast/relay
• Generalizing network coding
• Dynamic environment and feedbacks
• Structured code designs
• Efficient transmission of heterogeneous data
• Universal and robust algorithms
• Reducing the requirement of coordination
  overhead
• Feedback
• Moving towards larger networks

5
Recent Thrust AchievementsRelaying, forwarding,
and combining soft information

• Likelihood forwarding Koetter
• General relaying for multicast Goldsmith
• DMT for multi-hop networks -- Goldsmith
• Cognitive interference / Z channels -- Goldsmith
• Based on generalized Gelfand-Pinsker channel
• Optimal structure for interference.
• Interference forwarding -- Goldsmith
• Taking advantage of the structure of codebooks
• Forwarding interference so it can be decoded and
  cancelled.
• MIMO cognitive networks -- Goldsmith
• Spatial degrees of freedom for cognition and
  cooperation
• Cooperation in broadcasting, multiple prime
  users.

6
Recent Thrust AchievementsStructured code
designs

• Broadcasting with layered source codes
  Goldsmith
• Generalized capacity/distortion for joint source
  channel codes Effros Goldsmith
• UEP performance limits and applications -- Zheng
• Theoretical limits for heterogeneous data
  transmissions
• Unifying resource allocation between control and
  data messages, a new interface to the physical
  layer.
• Layered joint source channel codes -- Medard
  Zheng
• Distortion-diversity tradeoff a performance
  metric for dynamic source-channel problems
• Multiple descriptions carried by layered channel
  codes

7
Recent Thrust Achievements Generalized Network
Coding

• Using feedbacks with linear network coding
  Medard
• ACK used to estimate transmission time and
  channel condition
• Improve delay/energy efficiency for TDD systems
• Contents feedback with Network Coding Effros
• Avoid unnecessary retransmissions
• Strictly increase capacity region for the
  butterfly network and multi-terminal source
  coding.
• Distributed source coding with network coding
  Effros
• Classical example of source networks
• extended with network coding

8
Recent Thrust Achievements Feedback, channel
memory, and dynamics

• Network coding with feedback
• Indecomposable finite state channel with Feedback
  -- Goldsmith
• Appropriate model of dynamics
• Tx-Rx synchronization to achieve the maximum over
  all channel states
• Generalization to finite state broadcast channels
  (FSBC) - Goldsmith
• Superposition codetree at the encoder
• User cooperation included
• DMDT for multi-hop MIMO Relay Network
• - Goldsmith
• Diversity-Multiplexing-Delay tradeoff
• Optimal ARQ protocol fractional variable ARQ
• Control principles for feedback channels --
  Coleman
• Feedback channel as a control problem
• Low complexity iterative encoder to achieve
  capacity

9
Recent Thrust AchievementsTowards Larger
Networks

• Interference Mitigating Mobility Strategies
  Moulin
• Using mobility to actively avoid interference to
  others
• Optimal mobility strategy to dynamically enlarge
  capacity region.
• Scaling law for heterogeneous large networks
  Shah
• Tree networks for hierarchical cooperative relay
• Arbitrary traffic/ node placement.
• Networks with Side Information Effros
• Distributed source coding joint with network
  coding
• Successive refinement for source / side
  information for multiple sinks.
• Graphical scheduling -- Medard Koetter
• Hyper graph to describe conflicts
• Distributed algorithms for hyperarc scheduling.

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Thrust Synergies
Thrust 1 New Paradigm of outer bounds
Provide building blocks for large networks,
translate design constraints into network
modeling assumptions
Performance benchmark and design justification
UEP bit-wise. vs message-wise -- Zheng
Network equivalence Effros, Medard Koetter
Thrust 2 Dynamic Network Information theory
improving performance in presence of
interference, cooperation, and dynamic environment
Provide achievable performance region, based on
which distributed algorithms and resource
allocation over large networks are designed
Guide problem formulation by identifying
application constraints and relevant performance
metrics
Network scalability, robust and distributed
algorithms
Cooperative models for wireless NUM Boyd
Goldsmith
Thrust 3 Application Metrics and Network
Performance
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Thrust 2 Achievements Previous
Dynamic Network Information Theory
CSI, feedback, and robustness
Structured coding
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Thrust 2 Achievements Recent
Dynamic Network Information Theory
CSI, feedback, and robustness
Structured coding
13
Thrust Alignment with Phase 2 Goals

• Evolve results in all thrust areas to examine
  more complex models, robustness/security, more
  challenging dynamics, and larger networks.
• Network coding for classical distributed source
  coding problem
• Impact of dynamics for feedback (BC) channels
• Multiple cooperative/cognitive scenarios
• Network coding with feedback
• Demonstrate synergies between thrust areas
• Research clustering within the thrust
• Dynamic channel models with novel multi-user
  signaling
• Network coding used for distributed source
  coding
• Synergies between thrusts
• Distributed algorithms for scheduling in networks
• Models for wireless NUM with interference and
  dynamics (focus talk. Boyd Goldsmith)
• Network coding capacity with selfish users (focus
  talk, Effros)
• Demonstrate that key synergies between
  information theory, network theory, and
  optimization/control lead to at least an order of
  magnitude performance gain for key metrics.
• Gains by modeling dynamics, allowing
  cooperative/cognitive transmissions, and
  utilizing feedbacks
• Gains by novel signaling (interference forwarding
  and message embedding)