Communication scheduling and remote estimation with additive noise channels
type: CreativeWork
description: Communication scheduling and remote estimation scenarios arise in the context of wireless sensor networks, which involve monitoring and controlling the state of a dynamical system from remote locations. This entails joint design of transmission and estimation policies, where a sensor (or a group of sensors) observes the state of the system over a given horizon, but has to be selective in what (and when) it transmits due to energy constraints. The estimator, on the other hand, needs to generate real-time estimates of the state regardless of whether there is a transmission from the sensor or not. Hence, a communication scheduling strategy for the sensor and an estimation strategy for the estimator should be jointly designed to minimize the estimation error subject to the energy constraints. Prior works on this topic assumed that the communication channel between the sensor and the estimator is noiseless, which may not be that realistic even though it was an important first step. In this thesis, we study communication scheduling and remote estimation problems with additive noise channels. In particular, we consider a series of four problems as follows. In the first problem, the sensor has two options, namely, not transmitting its observation, or transmitting its observation over an additive noise channel subject to some communication cost. Because of the presence of channel noise, if the sensor decides to transmit its observation over the noisy channel, it needs to encode the message. Furthermore, the estimator needs to decode the noise-corrupted message. Hence, a pair of encoding and decoding strategies should also be jointly designed along with the communication scheduling strategy. In the second problem, the sensor has three options, where two of the options are the same as those in the first problem, and the third one is that the sensor can transmit its observation via a noiseless but more costly channel. The third problem is a variant of the first one, where the e…
abstract: Communication scheduling and remote estimation scenarios arise in the context of wireless sensor networks, which involve monitoring and controlling the state of a dynamical system from remote locations. This entails joint design of transmission and estimation policies, where a sensor (or a group of sensors) observes the state of the system over a given horizon, but has to be selective in what (and when) it transmits due to energy constraints. The estimator, on the other hand, needs to generate real-time estimates of the state regardless of whether there is a transmission from the sensor or not. Hence, a communication scheduling strategy for the sensor and an estimation strategy for the estimator should be jointly designed to minimize the estimation error subject to the energy constraints. Prior works on this topic assumed that the communication channel between the sensor and the estimator is noiseless, which may not be that realistic even though it was an important first step. In this thesis, we study communication scheduling and remote estimation problems with additive noise channels. In particular, we consider a series of four problems as follows. In the first problem, the sensor has two options, namely, not transmitting its observation, or transmitting its observation over an additive noise channel subject to some communication cost. Because of the presence of channel noise, if the sensor decides to transmit its observation over the noisy channel, it needs to encode the message. Furthermore, the estimator needs to decode the noise-corrupted message. Hence, a pair of encoding and decoding strategies should also be jointly designed along with the communication scheduling strategy. In the second problem, the sensor has three options, where two of the options are the same as those in the first problem, and the third one is that the sensor can transmit its observation via a noiseless but more costly channel. The third problem is a variant of the first one, where the e…
author: Gao, Xiaobin
language: en
keywords: Sensor networks, Estimation, Cyber physical security, Game theory
date published: 2019-02-06T19:32:38Z
date modified: 2026-07-22T22:24:40Z
provider: University of Illinois - Urbana-Champaign
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Illinois at Urbana-Champaign

PropertyValue
property ID: Handle
value: http://hdl.handle.net/2142/102389