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以对抗衰落和同频干扰，在提升超可靠通信系统性能方面发挥着关键作用。为确定满足超可靠性约束的适当传输策略，需推导超可靠区域内的信道统计特性，进而将这些统计量纳入速率选择过程，同时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，提出一种同时考虑空间分集与超可靠信道统计特性的新型超可靠实时传输框架。首先，基于MEVT的泊松点过程方法对罕见极端事件间的相互关联进行建模，由此构建不同接收端联合接收功率序列的尾部分布。随后，通过依据联合尾部分布估计值确定最优传输速率，并在估计过程中融入置信区间以应对有限数据样本的可用性约束，从而制定最优传输策略。最终，采用中断概率指标评估系统可靠性。通过对菲亚特Linea发动机舱实测数据的分析，本研究展示了所提方法相较于传统外推方法的优越性。这种创新方法不仅实现了更高的传输速率，还有效满足了超可靠性严苛要求。结果表明，相较于传统速率选择方法，所提速率选择框架能够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解决方案。