8,481 research outputs found
Empirical Coordination with Two-Sided State Information and Correlated Source and State
The coordination of autonomous agents is a critical issue for decentralized
communication networks. Instead of transmitting information, the agents
interact in a coordinated manner in order to optimize a general objective
function. A target joint probability distribution is achievable if there exists
a code such that the sequences of symbols are jointly typical. The empirical
coordination is strongly related to the joint source-channel coding with
two-sided state information and correlated source and state. This problem is
also connected to state communication and is open for non-causal encoder and
decoder. We characterize the optimal solutions for perfect channel, for
lossless decoding, for independent source and channel, for causal encoding and
for causal decoding.Comment: 5 figures, 5 pages, presented at IEEE International Symposium on
Information Theory (ISIT) 201
Empirical Coordination with Channel Feedback and Strictly Causal or Causal Encoding
In multi-terminal networks, feedback increases the capacity region and helps
communication devices to coordinate. In this article, we deepen the
relationship between coordination and feedback by considering a point-to-point
scenario with an information source and a noisy channel. Empirical coordination
is achievable if the encoder and the decoder can implement sequences of symbols
that are jointly typical for a target probability distribution. We investigate
the impact of feedback when the encoder has strictly causal or causal
observation of the source symbols. For both cases, we characterize the optimal
information constraints and we show that feedback improves coordination
possibilities. Surprisingly, feedback also reduces the number of auxiliary
random variables and simplifies the information constraints. For empirical
coordination with strictly causal encoding and feedback, the information
constraint does not involve auxiliary random variable anymore.Comment: 5 pages, 6 figures, presented at IEEE International Symposium on
Information Theory (ISIT) 201
Successive Refinement with Decoder Cooperation and its Channel Coding Duals
We study cooperation in multi terminal source coding models involving
successive refinement. Specifically, we study the case of a single encoder and
two decoders, where the encoder provides a common description to both the
decoders and a private description to only one of the decoders. The decoders
cooperate via cribbing, i.e., the decoder with access only to the common
description is allowed to observe, in addition, a deterministic function of the
reconstruction symbols produced by the other. We characterize the fundamental
performance limits in the respective settings of non-causal, strictly-causal
and causal cribbing. We use a new coding scheme, referred to as Forward
Encoding and Block Markov Decoding, which is a variant of one recently used by
Cuff and Zhao for coordination via implicit communication. Finally, we use the
insight gained to introduce and solve some dual channel coding scenarios
involving Multiple Access Channels with cribbing.Comment: 55 pages, 15 figures, 8 tables, submitted to IEEE Transactions on
Information Theory. A shorter version submitted to ISIT 201
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