论文标题
关于增强现实的信息时代，无线Terahertz（THZ）网络
On the Ruin of Age of Information in Augmented Reality over Wireless Terahertz (THz) Networks
论文作者
论文摘要
确保新的可靠信息用于增强现实（AR）服务是为用户提供实时体验并维持高质量的物理体验（QOPE）的关键挑战。在本文中，Terahertz（THZ）细胞网络用于交换渴望速率的AR含量。对于此网络，必须保证瞬时低峰值信息（PAOI）以克服THZ通道的不确定性。特别是，提出了一种新颖的经济概念，即，提出了毁灭的风险，以研究罕见但极高的PAOI发生的可能性，这可能会危害AR服务的运作。为了评估这些危害的严重程度，PAOI的累积分布函数（CDF）是针对两种不同的调度策略得出的。然后，该CDF用于找到废墟PAOI最大严重程度的概率。此外，为了提供有关AR含量年龄的长期见解，还得出了整个系统的平均PAOI。仿真结果表明，在预期和最坏情况下，用户数量的增加将对PAOI产生积极影响。同时，带宽的增加减少了平均PAOI，但导致破坏性能的严重程度下降。结果还表明，具有有限尺寸缓冲液的首次先发制人的系统是有限的废墟性能（LCFS）的表现更好（保证不那么严重的PAOI而同时增加了用户数量的可能性增加了12％），而首次首次服用（FCFS）的（fcfs）的排队有限的缓冲液会导致平均paoi较低的PAOI（45％PAOI）（45％PAOI）提高了paoi（45％的PAOI）。
Guaranteeing fresh and reliable information for augmented reality (AR) services is a key challenge to enable a real-time experience and sustain a high quality of physical experience (QoPE) for the users. In this paper, a terahertz (THz) cellular network is used to exchange rate-hungry AR content. For this network, guaranteeing an instantaneous low peak age of information (PAoI) is necessary to overcome the uncertainty stemming from the THz channel. In particular, a novel economic concept, namely, the risk of ruin is proposed to examine the probability of occurrence of rare, but extremely high PAoI that can jeopardize the operation of the AR service. To assess the severity of these hazards, the cumulative distribution function (CDF) of the PAoI is derived for two different scheduling policies. This CDF is then used to find the probability of maximum severity of ruin PAoI. Furthermore, to provide long term insights about the AR content's age, the average PAoI of the overall system is also derived. Simulation results show that an increase in the number of users will positively impact the PAoI in both the expected and worst-case scenarios. Meanwhile, an increase in the bandwidth reduces the average PAoI but leads to a decline in the severity of ruin performance. The results also show that a system with preemptive last come first served (LCFS) queues of limited size buffers have a better ruin performance (12% increase in the probability of guaranteeing a less severe PAoI while increasing the number of users), whereas first come first served (FCFS) queues of limited buffers lead to a better average PAoI performance (45% lower PAoI as we increase the bandwidth).
