Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project

1. Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project Thrust 2 Layerless Dynamic Networks Lizhong Zheng, Todd Coleman

2. MANET Metrics Constraints Capacity and Fundamental Limits Capacity Layerless Dynamic Networks Delay Models and Dynamics Upper Bound Lower Bound Degrees of Freedom Power Application and Network Optimization Capacity Delay (C*,D*,E*) Utility=U(C,D,E) FLoWS Power Fundamental Limits of Wireless Systems Models New MANET Theory Application Metrics Metrics 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/reliability; • Broadcasting and interference, beyond point-to-point communications; • Layerless: New signaling schemes, new metrics • Network information theory: cooperative/cognitive transmissions, relay and soft information processing; • Dynamic information exchange, feedbacks and multi-way communication; • 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.

4. Thrust Areas • Network information theory • Multi-terminal communication schemes with cooperative and cognitive signaling, interference mitigation, broadcast/relay; • Generalizing network coding • Structured code designs • Efficient transmission of heterogeneous data and applications; • Universal and robust algorithms • Feedback and dynamic communication problems

5. Recent Thrust Achievements:Relaying, forwarding, and combining soft information • Likelihood forwarding – Koetter • General relaying for multicast – Goldsmith • Interference forwarding -- Goldsmith • Broadcasting Channel with Cognitive Relay – Goldsmith • Multicasting with relay – Goldsmith • Structured codes based on the structure of the network; • Finite field channel / linear codes vs. Gaussian channel / nested lattice codes • Sum capacity for deterministic interference channels -- El Gamal • Broadcasting Channel with 3+ receivers – El Gamal (focus talk) • Analytical study for zig-zag decoding -- Medard

6. Recent Thrust Achievements:Structured codes and Applications Broadcasting with layered source codes –Goldsmith Generalized capacity/distortion for joint source channel codes –Effros & Goldsmith UEP: performance limits and applications – Zheng Joint source channel coding with limited feedback -- Goldsmith Successive refinement with progressive transmissions Dynamic of channel blocks between layers Distortion-outage tradeoff -- Medard & Zheng Comparison between multiple description and multi-resolution codes New interface to the physical layer Low complexity channel coding with Polar codes – Effros

7. Recent Thrust Achievements: Generalized Network Coding • Contents feedback with Network Coding – Effros • Linear representation in Network Coding – Effos • When linear coding suffices for all interior nodes? • Low SNR Relay Networks – Medard • Peaky signaling with network coding • Distributed network coding with coded side information – Effros • Multiple uni-cast with Network Coding -- Medard

8. Recent Thrust Achievements: Feedback, channel memory, and dynamics • Generalization to finite state broadcast channels (FSBC) • - Goldsmith • Control principles for feedback channels – Coleman • Dynamic coding problem interpreted with stochastic control • Reverse iterated function system (RIFS) decoding algorithms (w/ linear complexity) achieve capacity • Lyapunov exponents of dynamical systems provide clean way to demonstrate how posterior matching achieves capacity • Tilted posterior matching for feedback channels • -- Zheng (focus talk) • Joint source channel code with outage, with limited feedback -- Goldsmith • Exploiting mobility in relay networks -- Moulin

9. 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 Posterior matching for feedback channels – Coleman, Zheng General Relaying, interference forwarding -- Goldsmith 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 Joint source channel coding with outage – Goldsmith Thrust 3 Application Metrics and Network Performance

10. Thrust 2 Achievements Overview Dynamic Network Information Theory Goldsmith: general relaying, soft combining Goldsmith: Interference forwarding Goldsmith: Multicast with relay; BC with cognitive relay El Gamal: BC with 3+ receivers Moulin: exploiting mobility of relay networks Effros: distributed network coding with coded side information Cover: coordination capacity Effros: linear representation of network coding Coleman: Control principle for feedback channels Medard, Zheng: Diversity-distortion tradeoff Goldsmith: Feedback and Directed Information Goldsmith: Joint source channel coding / outage Moulin: Universal Decoding in MANETs Effros: two stage polar codes Zheng: tilted matching for feedback channels Goldsmith: Broadcasting with layered code Zheng: Mismatched receivers CSI, feedback, and robustness Structured coding

11. Thrust Achievement Summary • Revolutionize upper bounding techniques (thrust 1) • Determine the optimal channel/network “coding” that achieves these capacity upper bounds when possible, and characterize for which classes of networks gaps still exist between achievability and upper bounds, and why. • Coordination capacity – Cover (focus talk); • Develop new achievability results for key performance metrics based on networks designed as a single probabilistic mapping with dynamics over multiple timescales • General framework for systematic development and comparison of signaling schemes • New metrics and new interfaces • Error-erasure, distortion-outage, joint source channel codes; • New signaling techniques • Generalized network coding, soft information combining, interference management; • Message embedding, layered codes; • Robust and universal algorithms; • Dynamic communication problems, feedback, mobility; • Develop a generalized theory of rate distortion and network utilization (thrust 3) • Demonstrate the consummated union between information theory, networks, and control; and why all three are necessary ingredients in this union. • Large network results; • Control view of dynamic information exchange

12. Thrust Challenges • Formulations beyond capacity • Philosophical alignment of achievability and converse methodologies • Bounds vs. approximations • New metrics focusing on delays and robustness • Hidden dimensions of limits • Coordination and Networks • Not all communication has to be reliable: how to measure/utilize soft information for end-to-end reliability? • Robustness and imperfect side information • Coordination overhead • Coded side info. / unintended helper / confidential messages • Feedback and dynamic communication problems: are rate and error exponent the right metrics? • Impacts and insights to practical problems