activity
20142023
most citedStochastic Event-triggered Sensor Schedule for Remote State Estimation

398 citations · 620 across the 43 of their papers we have counts for

collaborators

43 papers

eess.SP2023

Consistent and Asymptotically Efficient Localization from Range-Difference Measurements

Guangyang Zeng, Biqiang Mu, Ling Shi +2

We consider signal source localization from range-difference measurements. First, we give some readily-checked conditions on measurement noises and sensor deployment to guarantee t…

eess.SY2022★ 2 cited

Towards Efficient Dynamic Uplink Scheduling over Multiple Unknown Channels

Shuang Wu, Xiaoqiang Ren, Qing-Shan Jia +2

Age-of-Information (AoI) is a critical metric for network applications. Existing works mostly address optimization with homogeneous AoI requirements, which is different from practi…

eess.SP2022

Stochastic Event-triggered Variational Bayesian Filtering

Xiaoxu Lv, Peihu Duan, Zhisheng Duan +2

This paper proposes an event-triggered variational Bayesian filter for remote state estimation with unknown and time-varying noise covariances. After presetting multiple nominal pr…

eess.SY2022

Sensor Scheduling Design for Complex Networks under a Distributed State Estimation Framework

Peihu Duan, Lidong He, Lingying Huang +2

This paper investigates sensor scheduling for state estimation of complex networks over shared transmission channels. For a complex network of dynamical systems, referred to as nod…

eess.SY2021

Consensus-Based Distributed Filtering with Fusion Step Analysis

Jiachen Qian, Peihu Duan, Zhisheng Duan +2

For consensus on measurement-based distributed filtering (CMDF), through infinite consensus fusion operations during each sampling interval, each node in the sensor network can ach…

cs.MA2021

Linear Quadratic Regulator Design for Multi-input Systems with A Distributed Cooperative Strategy

Peihu Duan, Lidong He, Zhisheng Duan +1

In this paper, a cooperative Linear Quadratic Regulator (LQR) problem is investigated for multi-input systems, where each input is generated by an agent in a network. The input mat…

eess.SY2021★ 3 cited

A Differential Private Method for Distributed Optimization in Directed Networks via State Decomposition

Xiaomeng Chen, Lingying Huang, Lidong He +2

In this paper, we study the problem of consensus-based distributed optimization where a network of agents, abstracted as a directed graph, aims to minimize the sum of all agents' c…

eess.SY2021★ 1 cited

Multi-Party Dynamic State Estimation that Preserves Data and Model Privacy

Yuqing Ni, Junfeng Wu, Li Li +1

In this paper we focus on the dynamic state estimation which harnesses a vast amount of sensing data harvested by multiple parties and recognize that in many applications, to impro…

eess.SY2020★ 1 cited

Optimal Unbiased Linear Sensor Fusion over Multiple Lossy Channels with Collective Observability

Yuchi Wu, Kemi Ding, Yuzhe Li +1

In this paper, we consider optimal linear sensor fusion for obtaining a remote state estimate of a linear process based on the sensor data transmitted over lossy channels. There is…

eess.SY2020★ 4 cited

Privacy-Preserving Push-sum Average Consensus via State Decomposition

Xiaomeng Chen, Lingying Huang, Kemi Ding +2

Average consensus is extensively used in distributed networks for computation and control, where all the agents constantly communicate with each other and update their states in or…

eess.SY2020

Learning Hidden Markov Models for Linear Gaussian Systems with Applications to Event-based State Estimation

Kaikai Zheng, Dawei Shi, Ling Shi

This work attempts to approximate a linear Gaussian system with a finite-state hidden Markov model (HMM), which is found useful in solving sophisticated event-based state estimatio…

eess.SY2020★ 25 cited

Stochastic Event-based Sensor Schedules for Remote State Estimation in Cognitive Radio Sensor Networks

Lingying Huang, Jiazheng Wang, Enoch Kung +3

We consider the problem of communication allocation for remote state estimation in a cognitive radio sensor network~(CRSN). A sensor collects measurements of a physical plant, and…

eess.SY2019★ 14 cited

Mean-Field Transmission Power Control in Dense Networks

Yuchi Wu, Junfeng Wu, Minyi Huang +1

We consider uplink power control in wireless communication when a large number of users compete over the channel resources. The CDMA protocol, as a supporting technology of 3G netw…

cs.IT2019

On the Performance Analysis of Binary Hypothesis Testing with Byzantine Sensors

Yuqing Ni, Kemi Ding, Yong Yang +1

We investigate the impact of Byzantine attacks in distributed detection under binary hypothesis testing. It is assumed that a fraction of the transmitted sensor measurements are co…

eess.SY2019

Finite Time Encryption Schedule in the Presence of an Eavesdropper with Operation Cost

Lingying Huang, Alex S. Leong, Daniel E. Quevedo +1

In this paper, we consider a remote state estimation problem in the presence of an eavesdropper. A smart sensor takes measurement of a discrete linear time-invariant (LTI) process…

eess.SY2019

Time Synchronization Attack and Countermeasure for Multi-System Scheduling in Remote Estimation

Ziyang Guo, Yuqing Ni, Wing Shing Wong +1

We consider time synchronization attack against multi-system scheduling in a remote state estimation scenario where a number of sensors monitor different linear dynamical processes…

eess.SY2019★ 8 cited

Max-Min Fair Sensor Scheduling: Game-theoretic Perspective and Algorithmic Solution

Shuang Wu, Xiaoqiang Ren, Yiguang Hong +1

We consider the design of a fair sensor schedule for a number of sensors monitoring different linear time-invariant processes. The largest average remote estimation error among all…

eess.SY2018★ 3 cited

Optimal Denial-of-Service Attack Energy Management over an SINR-Based Network

Jiahu Qin, Menglin Li, Ling Shi +1

We consider a scenario in which a DoS attacker with the limited power resource jams a wireless network through which the packet from a sensor is sent to a remote estimator to estim…

eess.SY2018★ 4 cited

Randomized Consensus based Distributed Kalman Filtering over Wireless Sensor Networks

Jiahu Qin, Jie Wang, Ling Shi +1

This paper is concerned with developing a novel distributed Kalman filtering algorithm over wireless sensor networks based on randomized consensus strategy. Compared with the centr…

eess.SY2018★ 54 cited

Learning Optimal Scheduling Policy for Remote State Estimation under Uncertain Channel Condition

Shuang Wu, Xiaoqiang Ren, Qing-Shan Jia +2

We consider optimal sensor scheduling with unknown communication channel statistics. We formulate two types of scheduling problems with the communication rate being a soft or hard…

cs.MA2018★ 1 cited

A Novel Warehouse Multi-Robot Automation System with Semi-Complete and Computationally Efficient Path Planning and Adaptive Genetic Task Allocation Algorithms

Kam Fai Elvis Tsang, Yuqing Ni, Cheuk Fung Raphael Wong +1

We consider the problem of warehouse multi-robot automation system in discrete-time and discrete-space configuration with focus on the task allocation and conflict-free path planni…

eess.SY2018★ 9 cited

Deep Reinforcement Learning for Wireless Sensor Scheduling in Cyber-Physical Systems

Alex S. Leong, Arunselvan Ramaswamy, Daniel E. Quevedo +2

In many Cyber-Physical Systems, we encounter the problem of remote state estimation of geographically distributed and remote physical processes. This paper studies the scheduling o…

eess.SY2018★ 50 cited

Optimal Scheduling of Multiple Sensors over Lossy and Bandwidth Limited Channels

Shuang Wu, Kemi Ding, Peng Cheng +1

This work considers the sensor scheduling for multiple dynamic processes. We consider linear dynamic processes, the state of each process is measured by a sensor, which transmi…

eess.SY2017★ 5 cited

Distributed Kalman Filters with State Equality Constraints: Time-based and Event-triggered Communications

Xingkang He, Chen Hu, Yiguang Hong +2

In this paper, we investigate a distributed estimation problem for multi-agent systems with state equality constraints (SEC). First, under a time-based consensus communication prot…