A note on the observation of a Markov source through a noisy channel (Corresp.)

Devore, Jay L.

doi:10.1109/tit.1974.1055299

Cited by 16 publications

(19 citation statements)

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“…At the beginning of stage 2 the content of the receiver's memory is (14) Furthermore (15) (16) and (17) Lemma 1: Consider a two-stage system with a design where (18) so that (19) Then one can replace with (20) so that (21) and the resulting new design is at least as good as the old design.…”

Section: Notationmentioning

confidence: 99%

“…Our objectives, hence our results, are different from those of [31], [32], [46], [53]. We are interested in the structure of optimal real-time encoders and decoders, therefore, our approach to and results on real-time communication problems are different from the bounds derived in [22]- [29] and the properties of real-time decoders in [16], [17]. Our structural results on real-time encoding-decoding hold for any finite time horizon as opposed to [54] where the results on real-time encoding-decoding are developed for a large time horizon.…”

mentioning

confidence: 97%

“…Properties of real-time decoders for communication systems with noisy channels and Markov sources were discovered in [16], [17].…”

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confidence: 99%

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On the Structure of Optimal Real-Time Encoders and Decoders in Noisy Communication

Teneketzis

2006

IEEE Trans. Inform. Theory

104

127

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Abstract-The output of a discrete-time Markov source must be encoded into a sequence of discrete variables. The encoded sequence is transmitted through a noisy channel to a receiver that must attempt to reproduce reliably the source sequence. Encoding and decoding must be done in real-time and the distortion measure does not tolerate delays. The structure of real-time encoding and decoding strategies that jointly minimize an average distortion measure over a finite horizon is determined. The results are extended to the real-time broadcast problem and a real-time variation of the Wyner-Ziv problem.

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Section: Notationmentioning

confidence: 99%

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confidence: 97%

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On the Structure of Optimal Real-Time Encoders and Decoders in Noisy Communication

Teneketzis

2006

IEEE Trans. Inform. Theory

104

127

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“…Properties of real-time decoders for noisy observations of a Markov source were considered in [25] and [26]. Properties of real-time encoders for transmitting Markov sources through noiseless channels were investigated in [27] and [28].…”

Section: B Literature Overviewmentioning

confidence: 99%

“…Observe that the three step -stage sequential decomposition of (24) can be combined into a one-step -stage sequential decomposition (26) which is a deterministic dynamic program in function space. The decomposition of Theorem 3.1 is based on the refinement of time presented in Section II-D; consequently, it has a smaller search space than the decomposition of (26).…”

Section: The Global Optimization Algorithmmentioning

confidence: 99%

Optimal Design of Sequential Real-Time Communication Systems

Mahajan

Teneketzis

2009

IEEE Trans. Inform. Theory

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Abstract-Optimal design of sequential real-time communication of a Markov source over a noisy channel is investigated. In such a system, the delay between the source output and its reconstruction at the receiver should equal a fixed prespecified amount. An optimal communication strategy must minimize the total expected symbol-by-symbol distortion between the source output and its reconstruction. Design techniques or performance bounds for such real-time communication systems are unknown. In this paper a systematic methodology, based on the concepts of information structures and information states, to search for an optimal real-time communication strategy is presented. This methodology trades off complexity in communication length (linear in contrast to doubly exponential) with complexity in alphabet sizes (doubly exponential in contrast to exponential). As the communication length is usually order of magnitudes bigger than the alphabet sizes, the proposed methodology simplifies the search for an optimal communication strategy. In spite of this simplification, the resultant optimality equations cannot be solved efficiently using existing algorithmic techniques. The main idea is to formulate a zero-delay communication problem as a dynamic team with nonclassical information structure. Then, an appropriate choice of information states converts the dynamic team problem into a centralized stochastic control problem in function space. Thereafter, Markov decision theory is used to derive nested optimality equations for choosing an optimal design. For infinite horizon problems, these optimality equations give rise to a fixed point functional equation. Communication systems with fixed finite delay constraint, a higher-order Markov source, and channels with memory are treated in the same manner after an appropriate expansion of the state space. Thus, this paper presents a comprehensive methodology to study different variations of real-time communication.

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Causal coding and control for Markov chains

Varaiya

Walrand

1983

Systems & Control Letters

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A note on the observation of a Markov source through a noisy channel (Corresp.)

Cited by 16 publications

References 0 publications

On the Structure of Optimal Real-Time Encoders and Decoders in Noisy Communication

On the Structure of Optimal Real-Time Encoders and Decoders in Noisy Communication

Optimal Design of Sequential Real-Time Communication Systems

Causal coding and control for Markov chains

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