Supporting the ultra-reliable and low-latency communications (URLLCs) has become one of the major goals for future wireless networks. In this paper, we present an analytical reliability model for user equipment (UE) connecting multiple base stations (BSs) with multi-stream carrier aggregation (MSCA) technology. We first derive a closed-form expression for reliability characterization using signal-to-interference-plus-noise (SINR) model over Nakagami-$m$ fading. We then formulate a joint resource allocation problem to maximize reliability, considering UE association, sub-carrier assignment and discrete power allocation. With distributed decision making (DDM) theory, we decouple it into two sub-problems, and each sub-problem is formulated as a separate Markov Decision Problem (MDP). We further propose the Monte Carlo Tree Search (MCTS) method to find the optimal solution for each sub-problem. The iterative joint optimization method based on DDM is also proposed. Our simulation results show that the reliability with MSCA increases with increasing the number of sub-carriers, as well as increasing the power allocation. We also show that our algorithm is an effective way in finding the optimal resource allocation for reliability improvement.

支持超可靠和低延迟通信（URLLC）已成为未来无线网络的主要目标之一。在本文中，我们提出了使用多流载波聚合（MSCA）技术连接多个基站（BS）的用户设备（UE）的分析可靠性模型。我们首先在Nakagami-S上使用信号干扰加噪声（SINR）模型导出用于可靠性表征的闭式表达式。$米$衰退。然后，我们考虑UE关联，子载波分配和离散功率分配，制定了一个联合资源分配问题以使可靠性最大化。利用分布式决策（DDM）理论，我们将其分解为两个子问题，并将每个子问题表述为单独的马尔可夫决策问题（MDP）。我们进一步提出了蒙特卡罗树搜索（MCTS）方法，以找到每个子问题的最佳解决方案。提出了一种基于DDM的迭代联合优化方法。我们的仿真结果表明，使用MSCA的可靠性随着子载波数量的增加以及功率分配的增加而增加。我们还表明，我们的算法是找到最佳资源分配以提高可靠性的有效方法。