Coordination Capacity

Abstract

We develop elements of a theory of cooperation and coordination in networks. Rather than considering a communication network as a means of distributing information, or of reconstructing random processes at remote nodes, we ask what dependence can be established among the nodes given the communication constraints. Specifically, in a network with communication rates {R_{i,j}} between the nodes, we ask what is the set of all achievable joint distributions p(x1, ..., xm) of actions at the nodes of the network. Several networks are solved, including arbitrarily large cascade networks. Distributed cooperation can be the solution to many problems such as distributed games, distributed control, and establishing mutual information bounds on the influence of one part of a physical system on another.

Accepted to IEEE Trans. on Info. Theory, 25 pages, 23 eps figure, uses IEEEtran.cls

Cited by in corpus (51)

• Distributed Channel Synthesis
• Quantum Reverse Shannon Theorem
• The Likelihood Encoder for Lossy Compression
• Empirical processes, typical sequences and coordinated actions in standard Borel spaces
• On the Separation of Lossy Source-Network Coding and Channel Coding in Wireline Networks
• Wyner's Common Information: Generalizations and A New Lossy Source Coding Interpretation
• Strong coordination of signals and actions over noisy channels with two-sided state information
• Empirical Coordination with Two-Sided State Information and Correlated Source and State
• Empirical Coordination with Channel Feedback and Strictly Causal or Causal Encoding
• Correlation between Channel State and Information Source with Empirical Coordination Constraint
• Multiple Access Channel Simulation
• Strategic Communication with Side Information at the Decoder
• Quantum soft-covering lemma with applications to rate-distortion coding, resolvability and identification via quantum channels
• Duality of a Source Coding Problem and the Semi-Deterministic Broadcast Channel with Rate-Limited Cooperation
• Strong Coordination over Multi-hop Line Networks
• On Hypothesis Testing Against Independence with Multiple Decision Centers
• Polar Coding for Empirical Coordination of Signals and Actions over Noisy Channels
• Successive Refinement with Decoder Cooperation and its Channel Coding Duals
• Hybrid Codes Needed for Coordination over the Point-to-Point Channel
• Channel Simulation: Finite Blocklengths and Broadcast Channels
• The Likelihood Encoder for Source Coding
• Randomized Nested Polar Subcode Constructions for Privacy, Secrecy, and Storage
• Hypothesis Testing Over the Two-hop Relay Network
• Smoothing of binary codes, uniform distributions, and applications
• On the Generic Capacity of $K$-User Symmetric Linear Computation Broadcast
• The Capacity of 3 User Linear Computation Broadcast
• Coordination via a relay
• Strong Coordination over Noisy Channels
• Information Causality is a Special Point in the Dual of the Gray-Wyner Region
• Separation of source-network coding and channel coding in wireline networks
• Coordination Through Shared Randomness
• Joint Coordination-Channel Coding for Strong Coordination over Noisy Channels Based on Polar Codes
• On Exact and $\infty$-Rényi Common Informations
• A Connection between Good Rate-distortion Codes and Backward DMCs
• Continuity of Generalized Entropy and Statistical Learning
• Strong Coordination over Noisy Channels: Is Separation Sufficient?
• Scalable Capacity Bounding Models for Wireless Networks
• Exact Channel Synthesis
• Empirical Coordination in a Triangular Multiterminal Network
• On the Capacity of the Discrete Memoryless Broadcast Channel with Feedback
• Distributed Source Simulation With No Communication
• Wyner's Common Information under Rényi Divergence Measures
• Extended Gray-Wyner System with Complementary Causal Side Information
• Channel simulation via interactive communications
• Notes on Information-Theoretic Privacy
• Remote Empirical Coordination
• Strong Coordination over a Line Network
• One-shot Multiple Access Channel Simulation
• Polar codes for empirical coordination over noisy channels with strictly causal encoding
• Randomized Distributed Function Computation (RDFC): Ultra-Efficient Semantic Communication Applications to Privacy
• Secrecy in Cascade Networks