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

2. Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project FLoWS Overview and Progress Andrea Goldsmith

3. DARPA’s ITMANET Challenge Hypothesis: A better understanding of MANET capacity limits will lead to better network design and deployment. Develop and exploit a more powerful information theory for mobile wireless networks. Anticipated byproducts include new separation theorems to inform wireless network "layering" as well as new protocol ideas.

4. MANET Capacity: What we don’t know • Capacity of time-varying links (with/without feedback) Yi-1 Xi Yi Tx Rx p(yi,si|xi,si-1) Si-1 Si D • Capacity of basic network building blocks • Capacity of large dynamic networks

5. Shannon and Wireless Networks • Shannon’s capacity definition based on infinite delay and asymptotically small error was brilliant • Much progress in finding the Shannon capacity limits of wireless single and multiuser channels • Little known about these limits for mobile wireless networks, even for simple (canonical) models • Few fundamental design insights have emerged. • Queuing and capacity theory incompatible if capacity implies infinite delay and no error. • How should capacity be defined for wireless networks?

6. Limitations in theory of MANETs today Wireless Information Theory • Shannon capacity pessimistic for wireless channels and intractable for large networks Wireless Network Theory B. Hajek and A. Ephremides, “Information theory and communications networks: An unconsummated union,” IEEE Trans. Inf. Theory, Oct. 1998. Optimization Theory • Large body of wireless (and wired) network theory that is ad-hoc, lacks a basis in fundamentals, and lacks an objective success criteria. • Little cross-disciplinary work spanning these fields • Optimization techniques applied to given network models, which rarely take into account fundamental network capacity or dynamics

7. Our Approach: Consummating Unions • When capacity is not the only metric, a new theory is needed to deal with nonasymptopia (i.e. delay, random traffic) and application requirements • Shannon theory generally breaks down when delay, error, or user/traffic dynamics must be considered • Fundamental limits are needed outside asymptotic regimes • Optimization provides the missing link to address these issues Wireless Information Theory Wireless Network Theory Menage a Trois Optimization Theory

8. FLoWSProgram Objectives • Develop tractable and insightful metrics and models for MANET information theory. • Define fundamental performance limits for MANETs in terms of desired objective metrics. • Obtain upper and lower performance bounds for these metrics for a given set of MANET models. • Define the negotiation between the application and network for resource allocation and performance optimization of our given metrics • Bound the cost of using our set of metrics as the interface between the network and applications.

9. MANET Metrics Constraints Capacity and Fundamental Limits Capacity Layerless Dynamic Networks Delay Models and Dynamics Upper Bound New Paradigms for Upper Bounds 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 Application Metrics and Network Performance

10. Thrust Objectives and Rationale • Models and Metrics (Leads: Effros,Goldsmith,Medard): • Objective:Develop a set of metrics for dynamic networks that capture requirements of current and future applications • Rationale: Models for MANETs are needed that are tractable yet lead to general design and performance insights • New Paradigms for Upper Bounds (Leads: Effros,Koetter,Medard) • Objective:Obtain bounds on a diversity of objectively-defined metrics for complex interconnected systems. • Rationale:A comprehensive theory for upper bounding the performance limits of MANETs will help guide design • Layerless Dynamic Networks (Lead: Zheng) • Objective:Design of networking strategies as a single dynamic probabilistic mapping, without pre-assigned layered structure • RationaleRemove layering and statics from MANET theory. • End-to-End Metrics and Performance(Leads: Ozdaglar,Shah) • Objective: Provide an interface between application metrics and network performance • Rationale:A theory of generalized rate distortion, separation, and network optimization will improve application performance

11. Thrust Synergies and New Intellectual Tools Thrust 1 New Bounding Techniques Code Construction Combinatorial Tools Thrust 2 Dynamic Network IT Optimization Structured Coding Thrust 3 CSI, Feedback, and Robustness Stochastic Network Analysis Optimization Game Theory

12. Thrust 0 Recent Achievements Models Coleman, Effros, Goldsmith, Medard, Zheng: Channels and Networks with Feedback Effros: networks with side information Goldsmith: Cognitive Nodes Moulin: Mobility Medard, Zheng: Diversity-distortion tradeoff Effros, Goldsmith: Expectation and Outage in Capacity and Distortion Zheng: UEP Goldsmith: Diversity/multiplexing/delay tradeoffs Medard: delay/energy minimization Shah: multicast capacity Metrics

13. Thrust 1 Recent Achievements New bounding techniques Moulin: converse for Gelfand-Pinsker MAC Code construction Network information theory Effros: effect of feedback in networks Goldsmith: multiple sender interference channel Zheng: unequal error protection converse Effros: networks with side information Effros: game-theoretic approaches to network coding Koetter, Medard: joint coding and scheduling in wireless networks Medard: coded time-division duplex for delay or energy minimization Koetter, Medard: Distributed scheduling for network coded multicast Moulin: mobility for interference mitigation Shah: multicast capacity of large wireless networks Networking and Optimization Combinatorial Tools

14. Thrust 2 Recent Achievements Dynamic Network Information Theory Goldsmith: cognitive interference/Z channel Goldsmith: Interference Forwarding Goldsmith: MIMO cognitive network Moulin: Mobility to mitigate interference Medard Koetter: Hypergraph scheduling Shah: Scaling of heterogeneous networks Goldsmith: Finite State (BC) channels with Feedback Coleman: Control Principle for feedback designs Effros: Network coding and distributed Source coding Goldsmith: MIMO-ARQ Diversity/Multiplexing/Delay Medard: Network coding with FB in TDD Medard, Zheng: Diversity-distortion tradeoff Effros: Contents Feedback for Network Coding Zheng: UEP and applications Zheng: Message-wise UEP and Feedback CSI, feedback, and robustness Structured coding

15. Thrust 3 Recent Achievements Optimization Boyd, Goldsmith: Wireless network utility maximization as stochastic optimal control Ozdaglar: Distributed second order methods for network optimization Shah, Medard: Queueing analysis for coded networks with feedback Goldsmith, Johari: Oblivious equilibrium for stochastic games with concave utility Moulin: Interference mitigating mobility Ozdaglar: Noncooperative scheduling with correlated channel states Johari: Fluid limits for gossip Meyn: Relaxation techniques for network optimization Effros: Noncooperative network coding Stochastic Network Analysis Game Theory

16. Progress on what we don’t know • Capacity of time-varying links (with/without feedback) • Capacity of finite-state Markov channels with feedback • Converses under unequal error protection • Multiplexing-diversity-delay-distortion tradeoffs in MIMO • Generalized capacity and separation Yi-1 Xi Yi Tx Rx p(yi,zi,si|xi,si-1) Si-1 Si D • Capacity of basic network building blocks • Capacity region/bounds for Z channel and interference channels • Capacity bounds for cognitive interference/MIMO channels • Upper bounds and converses for interference channels with a relay (via interference and message forwarding)

17. Capacity of dynamic networks • Network equivalence • Scaling laws for arbitrary node placement and demand • Multicast capacity • Effect of feedback and side information • Dynamic/multiperiod network utility maximization • Generalized Max-Weight policies • Game-theoretic approaches • Mobility for interference mitigation • Delay or energy minimization • Distributed optimization

18. FLoWS progress since last September • New breakthroughs in upper bounds, feedback and CSI, cognitive techniques, interference forwarding, multicast traffic, and dynamic/distributed network optimization, • New synergies within and between our thrust areas • New and ongoing collaborations among PIs • Overview paper for Scientific American • Co-authors: Effros, Goldsmith, Medard • Paper accepted for publication • Magazine paper with overview of FLoWS • Paper near completion – will be submitted within 3 weeks • All Phase 2 progress criteria have been met • Website updated with Sept. PI meeting slides, recent publications, and recent results.

19. Focus Talks and Posters • Thrust 1: • Moulin: Towards strong converses for MANETs • Thrust 2: • Coleman: A dynamic approach to feedback coding strategies in MANETs • Thrusts 2 and 3: • Effros: The cost of selfishness in network coding capacity • Thrust 3: • Boyd and Goldsmith: Optimizing wireless network performance in stochastic environments • Posters on all recent results

20. Progress Criteria: Phase 2 • Evolve results in all thrust areas to examine more complex models, robustness/security, more challenging dynamics, and larger networks. • Network equivalence • Multihop networks with interference forwarding • Interference mitigation via mobility • Unequal error protection • Control principles for feedback designs • Capacity scaling laws for arbitrary node placement and arbitrary demand • Distributed second order methods for network optimization • Generalized Max-Weight policies with optimal distributed implementations • Local dynamics for topology formation • Oblivous equilibrium • Demonstrate synergies between thrust areas: compare and tighten upper bounds and achievability results for specific models and metrics; apply generalized theory of distortion and utility based on performance regions developed in Thrusts 1-2. • Capacity of finite-state broadcast channels w/wout feedback and Z channel (1-2) • Bounds on capacity of cognitive radio and interference channel w/relay (1-2) • New approach to optimize coding and scheduling (1-3 ) • New game-theoretic approach to network coding (1-3 ) • Multiperiod NUM applicable to any underlying network capacity region (1-2-3)

21. Progress Criteria: Phase 2 • 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. • Coding-based TDD has order of magnitude throughput increase versus uncoded • Unbounded gain in network capacity with feedback • Order of magnitude throughput gain in hyperarc scheduling • Orders of magnitude BER reduction in wireless NUM • Order of magnitude utility improvement for generalized Maxweight • Pose clearly defined community challenges related to evolving our theory that inspires other researchers to collectively make breakthrough progress. • Community challenges posed in plenary talks and tutorials, as well as invited papers and vision papers. Proposed book will define FLoWS ITMANET theory. • Publish 2 vision papers, one for the community (e.g. in the IEEE Wireless Communications Magazine) and one for the broader technical community (e.g. in Nature or Science) illuminating our ideas, results, and their potential impact • Scientific American paper accepted. Iteration with publisher ongoing. • Magazine paper near completion, will be submitted within 3 weeks. • Book proposal has been discussed with Cambridge University Press.

22. Project Impact To Date • Plenary Talks • Boyd: Dysco’07, S. Stevun Lecture’08, CNLS’08, ETH’08 • Effros: ISIT’07 • Goldsmith: ACC’07, Gomachtech’08, ISWPC’08, Infocom’08, RAWC’09, WCNC’09 • Koetter: ITW’07, WiOPT’08 • Medard: Gretsi’07, CISS’07, Gilbreth Lecture (NAE)’07, IT Winter School’08, UIUC Student Conference’08, Wireless Network Coding’08, • Meyn: Erlang Centennial’09 • Ozdaglar: ACC 2009, NecSys'09 , ASMD’08 • Johari: World Congress of the Game Theory Society’08 • Shah: Plenary talk at the Interperf/Valuetools 2007 • Recent Tutorials • Boyd: MOCCS’08, WOSP’08 • Ozdaglar: ISIT’08, CDC’08 • Medard/Koetter: PIMRC’08 • Meyn: Mathematics of OR’08 • Shah: ACM Sigmetrics/Performance ’08, CDC’09, • Conference Session/Program Chairs • ISIT’07, CTW’08, WiOpt’08, CTW’09, ITW’09, ITW’10, ISMP’09, INFORMS’09 • Invited journal papers • “Breaking spectrum gridlock through cognitive radios: an information-theoretic approach”, IEEE Proc’09 (w/ Jafar, Maric, and Srinivasa)

23. Publications to date • 16 accepted journal papers, 13 more submitted • 89 conference papers (published or to appear) • SciAM paper to appear • Magazine paper to be submitted shortly • Book on FLoWS vision and results under development • Publications website: • http://www.stanford.edu/~adlakha/ITMANET/flows_publications.htm

24. Summary Significant progress on all thrust areas Significant progress on synergies between thrust areas Ongoing and fruitful collaborations between PIs Phase 2 goals met Significant impact of FLoWS research on the broader research community (IT, communications, networking, and control/optimization)