Fairness-aware Age-of-Information Minimization in WPT-Assisted Short-Packet THz Communications for mURLLC
<|reference_start|>Fairness-aware Age-of-Information Minimization in WPT-Assisted Short-Packet THz Communications for mURLLC: The technological landscape is swiftly advancing towards large-scale systems, creating significant opportunities, particularly in the domain of Terahertz (THz) communications. Networks designed for massive connectivity, comprising numerous Internet of Things (IoT) devices, are at the forefront of this advancement. In this paper, we consider Wireless Power Transfer (WPT)-enabled networks that support these IoT devices with massive Ultra-Reliable and Low-Latency Communication (mURLLC) services.The focus of such networks is information freshness, with the Age-of-Information (AoI) serving as the pivotal performance metric. In particular, we aim to minimize the maximum AoI among IoT devices by optimizing the scheduling policy. Our analytical findings establish the convexity property of the problem, which can be solved efficiently. Furthermore, we introduce the concept of AoI-oriented cluster capacity, examining the relationship between the number of supported devices and the AoI performance in the network. Numerical simulations validate the advantage of our proposed approach in enhancing AoI performance, indicating its potential to guide the design of future THz communication systems for IoT applications requiring mURLLC services.<|reference_end|>
@article{zhu2024fairness-aware,
    title={Fairness-aware Age-of-Information Minimization in WPT-Assisted
  Short-Packet THz Communications 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},
    archivePrefix={arXiv},
    eprint={2404.02159},
    primaryClass={cs.IT eess.SP math.IT}
}