A

Average Age-of-Information Minimization in EH-enabled Low-Latency IoT Networks

Abstract

In this work, we study an energy harvesting (EH)-enabled low-latency communication network where a full-duplex server continuously performs wireless power transfer (WPT) to a half-duplex sensor. The sensor is designed to operate periodically in each updating round, during which the sensor firstly harvests energy via the WPT process, then collects measurement data and wirelessly transmits an update to the server based on the harvested energy. We assume that no energy can be reserved at the end of each round, due to the deployed capacitor-structured energy container. Leveraging the recent characterization on the error probability in the finite blocklength (FBL) regime, we derive the average Age-of-Information (AoI) in the considered network and construct a problem minimizing the average AoI via optimizing the duration of the updating round. The convexity of the optimization problem is shown, following which an efficient optimal solution is provided. At last, via Monte Carlo simulations, the convexity of the problem can also be visualised, and the average AoI performance of the network is evaluated.

Authors 5

  1. RWTH Aachen University · Wuhan University

    Affiliation as printed

    ISEK Research Area, RWTH Aachen, Germany

    School of Electronic Information, Wuhan University, China

  2. RWTH Aachen University · Wuhan University

    Affiliation as printed

    ISEK Research Area, RWTH Aachen, Germany

    School of Electronic Information, Wuhan University, China

  3. University of Kaiserslautern

    Affiliation as printed

    Technische Universität Kaiserslautern, Germany

  4. RWTH Aachen University · Wuhan University

    Affiliation as printed

    ISEK Research Area, RWTH Aachen, Germany

    School of Electronic Information, Wuhan University, China

  5. RWTH Aachen University

    Affiliation as printed

    ISEK Research Area, RWTH Aachen, Germany

Cited by 12 stored of 12

12 results

No patents citing this paper on Lens.org (checked 2026-10-06).

References 32