TSI-Aided Real-Time Monitoring of Brownian Motions: A Rate-Latency-Distortion Perspective

Siyuan Yu; Wei Chen; H. Vincent Poor

doi:10.1109/GLOBECOM48099.2022.10001271

TSI-Aided Real-Time Monitoring of Brownian Motions: A Rate-Latency-Distortion Perspective

Siyuan Yu, Wei Chen, H. Vincent Poor

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

Real-time monitoring of the Brownian motion or Wiener process has received considerable attention because of its potential in autonomous driving, smart grids, and factory automation. However, conventional periodic sampling-based monitoring may induce error accumulation, which will lead to an infinite distortion as the monitoring time increases. To overcome this, we present a threshold-based sampling policy for the remote reconstruction of Brownian motions. With the aid of timing side information (TSI), the sampling time information can be efficiently compressed. To provide greater insight, we present the real-time and non-real-time reconstruction errors as functions of data rate and transmission delay. Finally, a multi-threshold sampling method is presented to further reduce the transmission rate in remote monitoring with reservation-based multiple access.

Original language	English (US)
Pages (from-to)	5342-5347
Number of pages	6
Journal	Proceedings - IEEE Global Communications Conference, GLOBECOM
DOIs	https://doi.org/10.1109/GLOBECOM48099.2022.10001271
State	Published - 2022
Externally published	Yes
Event	2022 IEEE Global Communications Conference, GLOBECOM 2022 - Virtual, Online, Brazil Duration: Dec 4 2022 → Dec 8 2022

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Networks and Communications
Hardware and Architecture
Signal Processing

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10.1109/GLOBECOM48099.2022.10001271

Cite this

@article{481ff17b1311412d9eebc79804e5e063,

title = "TSI-Aided Real-Time Monitoring of Brownian Motions: A Rate-Latency-Distortion Perspective",

abstract = "Real-time monitoring of the Brownian motion or Wiener process has received considerable attention because of its potential in autonomous driving, smart grids, and factory automation. However, conventional periodic sampling-based monitoring may induce error accumulation, which will lead to an infinite distortion as the monitoring time increases. To overcome this, we present a threshold-based sampling policy for the remote reconstruction of Brownian motions. With the aid of timing side information (TSI), the sampling time information can be efficiently compressed. To provide greater insight, we present the real-time and non-real-time reconstruction errors as functions of data rate and transmission delay. Finally, a multi-threshold sampling method is presented to further reduce the transmission rate in remote monitoring with reservation-based multiple access.",

author = "Siyuan Yu and Wei Chen and Poor, {H. Vincent}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE Global Communications Conference, GLOBECOM 2022 ; Conference date: 04-12-2022 Through 08-12-2022",

year = "2022",

doi = "10.1109/GLOBECOM48099.2022.10001271",

language = "English (US)",

pages = "5342--5347",

journal = "Proceedings - IEEE Global Communications Conference, GLOBECOM",

issn = "2334-0983",

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TY - JOUR

T1 - TSI-Aided Real-Time Monitoring of Brownian Motions

T2 - 2022 IEEE Global Communications Conference, GLOBECOM 2022

AU - Yu, Siyuan

AU - Chen, Wei

AU - Poor, H. Vincent

PY - 2022

Y1 - 2022

N2 - Real-time monitoring of the Brownian motion or Wiener process has received considerable attention because of its potential in autonomous driving, smart grids, and factory automation. However, conventional periodic sampling-based monitoring may induce error accumulation, which will lead to an infinite distortion as the monitoring time increases. To overcome this, we present a threshold-based sampling policy for the remote reconstruction of Brownian motions. With the aid of timing side information (TSI), the sampling time information can be efficiently compressed. To provide greater insight, we present the real-time and non-real-time reconstruction errors as functions of data rate and transmission delay. Finally, a multi-threshold sampling method is presented to further reduce the transmission rate in remote monitoring with reservation-based multiple access.

AB - Real-time monitoring of the Brownian motion or Wiener process has received considerable attention because of its potential in autonomous driving, smart grids, and factory automation. However, conventional periodic sampling-based monitoring may induce error accumulation, which will lead to an infinite distortion as the monitoring time increases. To overcome this, we present a threshold-based sampling policy for the remote reconstruction of Brownian motions. With the aid of timing side information (TSI), the sampling time information can be efficiently compressed. To provide greater insight, we present the real-time and non-real-time reconstruction errors as functions of data rate and transmission delay. Finally, a multi-threshold sampling method is presented to further reduce the transmission rate in remote monitoring with reservation-based multiple access.

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U2 - 10.1109/GLOBECOM48099.2022.10001271

DO - 10.1109/GLOBECOM48099.2022.10001271

M3 - Conference article

AN - SCOPUS:85146954192

SN - 2334-0983

SP - 5342

EP - 5347

JO - Proceedings - IEEE Global Communications Conference, GLOBECOM

JF - Proceedings - IEEE Global Communications Conference, GLOBECOM

Y2 - 4 December 2022 through 8 December 2022

ER -

TSI-Aided Real-Time Monitoring of Brownian Motions: A Rate-Latency-Distortion Perspective

Abstract

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