Work or Sleep: Freshness-Aware Energy Scheduling for Wireless Powered Communication Networks with Interference Consideration

This paper explores how to schedule energy to optimize the information freshness in wireless powered communication networks (WPCNs) when considering channel interference among adjacent sensor nodes. We introduce Age of Information (AoI) to quantitatively evaluate the information freshness and formul...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:2023 60th ACM/IEEE Design Automation Conference (DAC) S. 1 - 6
Hauptverfasser: Lin, Ling, Ju, Lei, Xue, Chun Jason, Zhou, Mingliang, Zhang, Wei, Zhou, Zimeng
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 09.07.2023
Schlagworte:
channel interference
energy scheduling
Focusing
Information age
information freshness
Interference
Schedules
Throughput
Wireless communication
Wireless powered communication network
Wireless sensor networks
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This paper explores how to schedule energy to optimize the information freshness in wireless powered communication networks (WPCNs) when considering channel interference among adjacent sensor nodes. We introduce Age of Information (AoI) to quantitatively evaluate the information freshness and formulate the AoI optimization problem. Unlike prior works focusing on system optimization for WPCNs while ignoring channel interference in energy transfer, this work reveals situations where channel interference among adjacent sensor nodes cannot be neglected and explores optimizing information freshness with interference consideration. To take the phenomena into account, we propose an energy scheduling solution to detect the channel interference and then judiciously determine the energy and time allocation for individual sensor nodes to improve the AoI performance as well as the system throughput. We implement a multi-node WPCN testbed to validate the functional correctness of the proposed solution, and extensive experiments have demonstrated the effectiveness of the proposed solution. The experimental results show that the proposed solution can reduce the average AoI by 54.7% and the average throughput by 49.8% on average compared to the state-of-the-art solutions.
DOI:10.1109/DAC56929.2023.10247675