论文标题
超级可靠的低延迟通信中链路适应的干扰分布预测
Interference Distribution Prediction for Link Adaptation in Ultra-Reliable Low-Latency Communications
论文作者
论文摘要
超级可靠的低延迟通信（URLLC）用例的严格延迟和可靠性要求是第五代（5G）网络设计的主要驱动因素之一。链接适应（LA）被认为是实现URLLC的瓶颈之一。在本文中，我们专注于预测用户的信号对干扰加上噪声比以增强LA。由于大多数极端潜伏期和可靠性要求的大多数URLLC用例都以半决性的流量为特征，因此我们建议利用干扰时间相关性，以计算预测下一次传输中干扰功率所需的有用统计数据。该预测在LA上下文中被利用，以最大程度地提高光谱效率，同时保证在任意级别的可靠性。将数值结果与LA的最先进的干扰预测技术进行了比较。我们表明，开发干扰的时间相关是URLLC的重要推动因素。
The strict latency and reliability requirements of ultra-reliable low-latency communications (URLLC) use cases are among the main drivers in fifth generation (5G) network design. Link adaptation (LA) is considered to be one of the bottlenecks to realize URLLC. In this paper, we focus on predicting the signal to interference plus noise ratio at the user to enhance the LA. Motivated by the fact that most of the URLLC use cases with most extreme latency and reliability requirements are characterized by semi-deterministic traffic, we propose to exploit the time correlation of the interference to compute useful statistics needed to predict the interference power in the next transmission. This prediction is exploited in the LA context to maximize the spectral efficiency while guaranteeing reliability at an arbitrary level. Numerical results are compared with state of the art interference prediction techniques for LA. We show that exploiting time correlation of the interference is an important enabler of URLLC.
