Diversity schemes play a vital role in improving the performance of ultra-reliable communication systems by transmitting over two or more communication channels to combat fading and co-channel interference. Determining an appropriate transmission strategy that satisfies ultra-reliability constraint necessitates derivation of statistics of channel in ultra-reliable region and, subsequently, integration of these statistics into rate selection while incorporating a confidence interval to account for potential uncertainties that may arise during estimation. In this paper, we propose a novel framework for ultra-reliable real-time transmission considering both spatial diversities and ultra-reliable channel statistics based on multivariate extreme value theory. First, tail distribution of joint received power sequences obtained from different receivers is modeled while incorporating inter-relations of extreme events occurring rarely based on Poisson point process approach in MEVT. The optimum transmission strategies are then developed by determining optimum transmission rate based on estimated joint tail distribution and incorporating confidence intervals into estimations to cope with the availability of limited data. Finally, system reliability is assessed by utilizing outage probability metric. Through analysis of data obtained from the engine compartment of Fiat Linea, our study showcases the effectiveness of proposed methodology in surpassing traditional extrapolation-based approaches. This innovative method not only achieves a higher transmission rate, but also effectively addresses stringent requirements of ultra-reliability. The findings indicate that proposed rate selection framework offers a viable solution for achieving a desired target error probability by employing a higher transmission rate and reducing the amount of training data compared to conventional rate selection methods.

翻译：分集方案通过利用两个或多个通信信道进行传输，有效对抗衰落和同频干扰，在提升超可靠通信系统性能中发挥关键作用。确定满足超可靠约束的合适传输策略，需要推导超可靠区域内的信道统计特性，进而将这些统计量整合到速率选择中，并引入置信区间以应对估计过程中可能出现的潜在不确定性。本文基于多元极值理论，提出一种兼顾空间分集与超可靠信道统计特性的超可靠实时传输新框架。首先，采用多元极值理论中的泊松点过程方法，在考虑罕见极端事件间相互关联性的基础上，对不同接收机获取的联合接收功率序列的尾部分布进行建模。继而通过基于估计的联合尾部分布确定最优传输速率，并在估计中引入置信区间以应对有限数据量问题，从而开发出最优传输策略。最后，利用中断概率指标评估系统可靠性。通过对菲亚特Linea发动机舱数据的分析，本研究证实了所提方法在超越传统外推方法方面的有效性。这种创新方法不仅能实现更高的传输速率，还有效满足了超可靠性的严苛要求。研究结果表明，与常规速率选择方法相比，本文提出的速率选择框架可通过采用更高传输速率并减少训练数据量，为实现目标错误概率提供可行的解决方案。