English

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

Information Theory 2024-12-06 v2 Signal Processing math.IT

Abstract

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.

Keywords

Cite

@article{arxiv.2404.02159,
  title  = {Fairness-aware Age-of-Information Minimization in WPT-Assisted Short-Packet Data Collection for mURLLC},
  author = {Yao Zhu and Xiaopeng Yuan and Yulin Hu and Bo Ai and Ruikang Wang and Bin Han and Anke Schmeink},
  journal= {arXiv preprint arXiv:2404.02159},
  year   = {2024}
}