Control Over Gaussian Channels With and Without Source–Channel Separation

Khina, Anatoly; Garding, Elias Riedel; Pettersson, Gustav M.; Kostina, Victoria; Hassibi, Babak

doi:10.1109/tac.2019.2912255

Cited by 24 publications

(14 citation statements)

References 52 publications

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“…Proposition 2: Under the assumptions of Lemma 2, using the estimation (17) and the quantization policy described in Fig. 2, if the sensor has causal knowledge of delays (i.e., the controller acknowledges the packet reception times), then it can calculate {x(t k+ c )} k∈N .…”

Section: Sufficient and Necessary Conditions On The Information Tmentioning

confidence: 99%

“…Assume |z(0)| = |x(0) −x(0)| < J. Using the estimation (17) and the quantization policy described in Fig. 2…”

Section: Sufficient and Necessary Conditions On The Information Tmentioning

confidence: 99%

“…, then (14) holds for all reception times {t k c } k∈N if J > M Aρ0 (e Aγ − 1). Proof: Using 11, (17), and the triangular inequality, we deduce |z(t c ) −z(t c )| ≤ Je A(tc−ts) |(1 − e A(ts−q(ts)) )| + | tc ts e A(tc−τ ) w(τ )dτ |. By applying the bounds (3), (2), and (12) on first and second addend respectively it follows…”

Section: Sufficient and Necessary Conditions On The Information Tmentioning

confidence: 99%

“…Extensions to noisy communication channels are considered in [7]- [10]. Additional formulations include stabilization of switched linear systems [11], uncertain systems [12], nonlinear systems [13], [14], multiplicative noise [15], and optimal control [16], [17].…”

Section: Introductionmentioning

confidence: 99%

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Exploiting Timing Information in Event-Triggered Stabilization of Linear Systems With Disturbances

Khojasteh

Hedayatpour

Cortés

et al. 2021

IEEE Trans. Control Netw. Syst.

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Similar to the way pauses are used in spoken language to convey information, it is also possible to transmit information in communication networks not only by message content, but also with its timing. This paper presents an eventtriggering strategy that utilizes timing information by transmitting in a state-dependent fashion. We consider the stabilization of a continuous-time, time-invariant, linear plant over a digital communication channel with bounded delay and subject to bounded plant disturbances and establish two main results. On the one hand, we design an encoding-decoding scheme that guarantees a sufficient information transmission rate for stabilization. On the other hand, we determine a lower bound on the information transmission rate necessary for stabilization by any control policy.

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Section: Sufficient and Necessary Conditions On The Information Tmentioning

confidence: 99%

“…Assume |z(0)| = |x(0) −x(0)| < J. Using the estimation (17) and the quantization policy described in Fig. 2…”

Section: Sufficient and Necessary Conditions On The Information Tmentioning

confidence: 99%

Section: Sufficient and Necessary Conditions On The Information Tmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Exploiting Timing Information in Event-Triggered Stabilization of Linear Systems With Disturbances

Khojasteh

Hedayatpour

Cortés

et al. 2021

IEEE Trans. Control Netw. Syst.

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show abstract

“…A crucial aspect of this scenario is the fact that the messages

to be encoded are contained in the sequence w, a signal internal to the loop; they can be regarded as a corrupted version of the decoded messages, which comprise the sequence v. This is a key difference with respect to the available literature on feedback capacity, where, to the best of the authors’ knowledge, the messages are exogenous and the feedback signal only helps in the encoding task (exceptions can be found in some papers on networked control which consider in-the-loop channel coding, such as, e.g., [ 41 , 42 ]). In Figure 7 , the latter standard scenario corresponds to encoding the sequence r.…”

Section: Giving Operational Meaning To the Directed Information: In-the-loop Channel Codingmentioning

confidence: 99%

Directed Data-Processing Inequalities for Systems with Feedback

Derpich

Østergaard

2021

Entropy

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We present novel data-processing inequalities relating the mutual information and the directed information in systems with feedback. The internal deterministic blocks within such systems are restricted only to be causal mappings, but are allowed to be non-linear and time varying, and randomized by their own external random input, can yield any stochastic mapping. These randomized blocks can for example represent source encoders, decoders, or even communication channels. Moreover, the involved signals can be arbitrarily distributed. Our first main result relates mutual and directed information and can be interpreted as a law of conservation of information flow. Our second main result is a pair of data-processing inequalities (one the conditional version of the other) between nested pairs of random sequences entirely within the closed loop. Our third main result introduces and characterizes the notion of in-the-loop (ITL) transmission rate for channel coding scenarios in which the messages are internal to the loop. Interestingly, in this case the conventional notions of transmission rate associated with the entropy of the messages and of channel capacity based on maximizing the mutual information between the messages and the output turn out to be inadequate. Instead, as we show, the ITL transmission rate is the unique notion of rate for which a channel code attains zero error probability if and only if such an ITL rate does not exceed the corresponding directed information rate from messages to decoded messages. We apply our data-processing inequalities to show that the supremum of achievable (in the usual channel coding sense) ITL transmission rates is upper bounded by the supremum of the directed information rate across the communication channel. Moreover, we present an example in which this upper bound is attained. Finally, we further illustrate the applicability of our results by discussing how they make possible the generalization of two fundamental inequalities known in networked control literature.

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LQG control and linear policies for noisy communication links with synchronized side information at the decoder

Stavrou

Skoglund

2021

Automatica

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Control Over Gaussian Channels With and Without Source–Channel Separation

Cited by 24 publications

References 52 publications

Exploiting Timing Information in Event-Triggered Stabilization of Linear Systems With Disturbances

Exploiting Timing Information in Event-Triggered Stabilization of Linear Systems With Disturbances

Directed Data-Processing Inequalities for Systems with Feedback

LQG control and linear policies for noisy communication links with synchronized side information at the decoder

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