Fairness-aware Age-of-Information Minimization in WPT-Assisted Short-Packet Data Collection for mURLLC

Fuente: arXiv
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Auteurs principaux: Zhu, Yao, Yuan, Xiaopeng, Hu, Yulin, Ai, Bo, Wang, Ruikang, Han, Bin, Schmeink, Anke
Format: Preprint
Publié: 2024
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author Zhu, Yao
Yuan, Xiaopeng
Hu, Yulin
Ai, Bo
Wang, Ruikang
Han, Bin
Schmeink, Anke
author_facet Zhu, Yao
Yuan, Xiaopeng
Hu, Yulin
Ai, Bo
Wang, Ruikang
Han, Bin
Schmeink, Anke
contents The technological landscape is rapidly evolving toward large-scale systems. Networks supporting massive connectivity through numerous Internet of Things (IoT) devices are at the forefront of this advancement. In this paper, we examine Wireless Power Transfer (WPT)-enabled networks, where a server requires to collect data from these IoT devices to compute a task with massive Ultra-Reliable and Low-Latency Communication (mURLLC) services.} We focus on information freshness, using Age-of-Information (AoI) as the key performance metric. Specifically, we aim to minimize the maximum AoI among IoT devices by optimizing the scheduling policy. Our analytical findings demonstrate the convexity of the problem, enabling efficient solutions. We introduce the concept of AoI-oriented cluster capacity and analyze the relationship between the number of supported devices and network AoI performance. Numerical simulations validate our proposed approach's effectiveness in enhancing AoI performance, highlighting its potential for guiding the design of future IoT systems requiring mURLLC services.
format Preprint
id arxiv_https___arxiv_org_abs_2404_02159
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Fairness-aware Age-of-Information Minimization in WPT-Assisted Short-Packet Data Collection for mURLLC
Zhu, Yao
Yuan, Xiaopeng
Hu, Yulin
Ai, Bo
Wang, Ruikang
Han, Bin
Schmeink, Anke
Information Theory
Signal Processing
The technological landscape is rapidly evolving toward large-scale systems. Networks supporting massive connectivity through numerous Internet of Things (IoT) devices are at the forefront of this advancement. In this paper, we examine Wireless Power Transfer (WPT)-enabled networks, where a server requires to collect data from these IoT devices to compute a task with massive Ultra-Reliable and Low-Latency Communication (mURLLC) services.} We focus on information freshness, using Age-of-Information (AoI) as the key performance metric. Specifically, we aim to minimize the maximum AoI among IoT devices by optimizing the scheduling policy. Our analytical findings demonstrate the convexity of the problem, enabling efficient solutions. We introduce the concept of AoI-oriented cluster capacity and analyze the relationship between the number of supported devices and network AoI performance. Numerical simulations validate our proposed approach's effectiveness in enhancing AoI performance, highlighting its potential for guiding the design of future IoT systems requiring mURLLC services.
title Fairness-aware Age-of-Information Minimization in WPT-Assisted Short-Packet Data Collection for mURLLC
topic Information Theory
Signal Processing
url https://arxiv.org/abs/2404.02159