Age of information minimization for an energy harvesting cognitive radio

Shiyang Leng, Aylin Yener

Research output: Contribution to journalArticle

Abstract

Age of information (AoI) is a performance metric that measures the timeliness and freshness of information, and is particularly relevant in applications with time-sensitive data. This paper studies average AoI minimization in cognitive radio energy harvesting communications. More specifically, the system studied has a primary user with access rights to spectrum, and a secondary user who can utilize the spectrum only when it is left idle by the primary user. The secondary user is an energy harvesting sensor that harvests ambient energy with which it performs spectrum sensing and status updates of its sensing data to a destination. The status-updates are sent by opportunistically accessing the primary user's spectrum. The secondary user aims to minimize the average AoI by adaptively making sensing and update decisions based on its energy availability and the availability of the primary spectrum with either perfect or imperfect spectrum sensing. The sequential decision problems are formulated as partially observable Markov decision processes and solved by dynamic programming for finite and infinite horizon. The properties of the optimal sensing and updating policies are investigated and shown to have threshold structure. Numerical results are presented to confirm the analytical findings.

Original languageEnglish (US)
Article number8712546
Pages (from-to)427-439
Number of pages13
JournalIEEE Transactions on Cognitive Communications and Networking
Volume5
Issue number2
DOIs
StatePublished - Jun 1 2019

Fingerprint

Energy harvesting
Cognitive radio
Availability
Dynamic programming
Communication
Sensors

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

@article{8ea39ac44f6a44559f0f1d1141b8c600,
title = "Age of information minimization for an energy harvesting cognitive radio",
abstract = "Age of information (AoI) is a performance metric that measures the timeliness and freshness of information, and is particularly relevant in applications with time-sensitive data. This paper studies average AoI minimization in cognitive radio energy harvesting communications. More specifically, the system studied has a primary user with access rights to spectrum, and a secondary user who can utilize the spectrum only when it is left idle by the primary user. The secondary user is an energy harvesting sensor that harvests ambient energy with which it performs spectrum sensing and status updates of its sensing data to a destination. The status-updates are sent by opportunistically accessing the primary user's spectrum. The secondary user aims to minimize the average AoI by adaptively making sensing and update decisions based on its energy availability and the availability of the primary spectrum with either perfect or imperfect spectrum sensing. The sequential decision problems are formulated as partially observable Markov decision processes and solved by dynamic programming for finite and infinite horizon. The properties of the optimal sensing and updating policies are investigated and shown to have threshold structure. Numerical results are presented to confirm the analytical findings.",
author = "Shiyang Leng and Aylin Yener",
year = "2019",
month = "6",
day = "1",
doi = "10.1109/TCCN.2019.2916097",
language = "English (US)",
volume = "5",
pages = "427--439",
journal = "IEEE Transactions on Cognitive Communications and Networking",
issn = "2332-7731",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "2",

}

Age of information minimization for an energy harvesting cognitive radio. / Leng, Shiyang; Yener, Aylin.

In: IEEE Transactions on Cognitive Communications and Networking, Vol. 5, No. 2, 8712546, 01.06.2019, p. 427-439.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Age of information minimization for an energy harvesting cognitive radio

AU - Leng, Shiyang

AU - Yener, Aylin

PY - 2019/6/1

Y1 - 2019/6/1

N2 - Age of information (AoI) is a performance metric that measures the timeliness and freshness of information, and is particularly relevant in applications with time-sensitive data. This paper studies average AoI minimization in cognitive radio energy harvesting communications. More specifically, the system studied has a primary user with access rights to spectrum, and a secondary user who can utilize the spectrum only when it is left idle by the primary user. The secondary user is an energy harvesting sensor that harvests ambient energy with which it performs spectrum sensing and status updates of its sensing data to a destination. The status-updates are sent by opportunistically accessing the primary user's spectrum. The secondary user aims to minimize the average AoI by adaptively making sensing and update decisions based on its energy availability and the availability of the primary spectrum with either perfect or imperfect spectrum sensing. The sequential decision problems are formulated as partially observable Markov decision processes and solved by dynamic programming for finite and infinite horizon. The properties of the optimal sensing and updating policies are investigated and shown to have threshold structure. Numerical results are presented to confirm the analytical findings.

AB - Age of information (AoI) is a performance metric that measures the timeliness and freshness of information, and is particularly relevant in applications with time-sensitive data. This paper studies average AoI minimization in cognitive radio energy harvesting communications. More specifically, the system studied has a primary user with access rights to spectrum, and a secondary user who can utilize the spectrum only when it is left idle by the primary user. The secondary user is an energy harvesting sensor that harvests ambient energy with which it performs spectrum sensing and status updates of its sensing data to a destination. The status-updates are sent by opportunistically accessing the primary user's spectrum. The secondary user aims to minimize the average AoI by adaptively making sensing and update decisions based on its energy availability and the availability of the primary spectrum with either perfect or imperfect spectrum sensing. The sequential decision problems are formulated as partially observable Markov decision processes and solved by dynamic programming for finite and infinite horizon. The properties of the optimal sensing and updating policies are investigated and shown to have threshold structure. Numerical results are presented to confirm the analytical findings.

UR - http://www.scopus.com/inward/record.url?scp=85067022606&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85067022606&partnerID=8YFLogxK

U2 - 10.1109/TCCN.2019.2916097

DO - 10.1109/TCCN.2019.2916097

M3 - Article

AN - SCOPUS:85067022606

VL - 5

SP - 427

EP - 439

JO - IEEE Transactions on Cognitive Communications and Networking

JF - IEEE Transactions on Cognitive Communications and Networking

SN - 2332-7731

IS - 2

M1 - 8712546

ER -