Estimating Age of Information in Wireless Systems With Unknown Distributions of Inter-Arrival/Service Time

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2024-09-03 DOI:10.1109/TNSE.2024.3453959

Licheng Chen;Yunquan Dong

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引用次数: 0

Abstract

In this paper, we estimate the average age of information (AoI) of the status updating over a wireless channel with an unknown fading model. Different from most related works which take the distributions of the inter-arrival time and transmission time of updates as known information, we approximate the average AoI of the system by using their first and second-order moments. Note that these distributions are often not accessible or known with inevitable errors while their moments are much easier to obtain, e.g., by using counting and statistics. We model the communications over the fading channel with a continuous transmission model and a discrete transmission model, which use the variable-rate scheme and the fixed-rate scheme, respectively. We assume that the arrival of the continuous transmission model is a Bernoulli process and make no assumptions about the arrival process of the discrete transmission model. Based on these information, we present two pairs of tight lower and upper bounds for the AoI of the two models. We show that obtained bounds are the tightest when the inter-arrival time (or transmission time) follows the degenerate distribution and are the loosest when it follows the two-point distribution, which randomly takes value from two possible outcomes. We also show that tighter bounds can be obtained by using higher order moments.

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在到达/服务时间分布未知的情况下估算无线系统中的信息年龄

本文估算了在未知衰减模型的无线信道上进行状态更新的平均信息年龄（AoI）。与将更新到达时间和传输时间的分布作为已知信息的大多数相关工作不同，我们通过使用它们的一阶和二阶矩来近似计算系统的平均 AoI。需要注意的是，这些分布通常无法获得或已知时难免会有误差，而它们的矩则更容易获得，例如通过计数和统计。我们用连续传输模型和离散传输模型来模拟衰减信道上的通信，这两种模型分别使用可变速率方案和固定速率方案。我们假设连续传输模型的到达是一个伯努利过程，而对离散传输模型的到达过程不做任何假设。基于这些信息，我们提出了两种模型的 AoI 的两对严格下限和上限。我们表明，当到达间隔时间（或传输时间）遵循退化分布时，所获得的界限是最严格的；而当它遵循两点分布（随机从两种可能结果中取值）时，所获得的界限是最宽松的。我们还证明，利用高阶矩可以获得更严格的边界。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.