Anytime Reliable Transmission of Real-Valued Information through Digital Noisy Channels

The problem of reliably transmitting a real-valued random vector through a digital noisy channel is relevant for the design of distributed estimation and control techniques over networked systems. One important example consists in the remote state estimation under communication constraints. In this...

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Vydáno v:	SIAM journal on control and optimization Ročník 48; číslo 6; s. 3903 - 3924
Hlavní autoři:	Como, Giacomo, Fagnani, Fabio, Zampieri, Sandro
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Philadelphia, PA Society for Industrial and Applied Mathematics 01.01.2010
Témata:	Algorithmics. Computability. Computer arithmetics Applied sciences Channels Coders Coding Coding theory Complex systems Computer science; control theory; systems Computer systems and distributed systems. User interface Control Engineering Control systems Convergence Data transmission Electrical Engineering, Electronic Engineering, Information Engineering Elektroteknik och elektronik Encoders Engineering and Technology Exact sciences and technology Mathematical analysis Mean square errors Reglerteknik Software Studies Teknik Theoretical computing Vector space Vectors (mathematics) Exponential convergence unequal error protection Electronic document Updating digital fountain codes Mean square error Digital information Convergence rate 94B70 94A34 State estimation Numerical convergence state estimation with communication constraints State constraint Probabilistic approach Source coding anytime transmission Transmission channel Decoding Real time real-time communication Computational complexity 93E10 Noisy channel Distributed control
ISSN:	0363-0129, 1095-7138, 1095-7138
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Popis
Shrnutí:	The problem of reliably transmitting a real-valued random vector through a digital noisy channel is relevant for the design of distributed estimation and control techniques over networked systems. One important example consists in the remote state estimation under communication constraints. In this case, an anytime transmission scheme consists of an encoder--which maps the real vector into a sequence of channel inputs--and a decoder--which sequentially updates its estimate of the vector as more and more channel outputs are observed. The encoder performs both source and channel coding of the data. Assuming that no channel feedback is available at the transmitter, this paper studies the rates of convergence to zero of the mean squared error. Two coding strategies are analyzed: the first one has exponential convergence rate but is expensive in terms of its encoder/decoder computational complexity, while the second one has a convenient computational complexity but subexponential convergence rate. General bounds are obtained describing the convergence properties of these classes of methods. [PUBLICATION ABSTRACT]
Bibliografie:	SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23
ISSN:	0363-0129 1095-7138 1095-7138
DOI:	10.1137/09074601X