In this letter, we propose a distributed Q-learning (DQL) based joint relay selection and access control (JRSAC) scheme for Internet of Things (IoT)-oriented satellite terrestrial relay networks (STRNs) with massive IoT devices and multiple relays. Firstly, a semi-random access (SRA) architecture is proposed to improve the learning efficiency of the DQL algorithm. Subsequently, a JRSAC optimization problem is formulated and solved by the proposed DQL algorithm. Simulation results show that the proposed DQL based JRSAC scheme significantly outperforms conventional schemes in terms of the medium access control (MAC) throughput, total access delay, and sum rate.

中文翻译：

---

基于分布式Q-Learning的面向物联网卫星地面中继网络的联合中继选择和访问控制方案

在这封信中，我们提出了一种基于分布式 Q 学习 (DQL) 的联合中继选择和访问控制 (JRSAC) 方案，用于面向物联网 (IoT) 的卫星地面中继网络 (STRN)，具有大量物联网设备和多个中继。首先，提出了一种半随机访问（SRA）架构来提高DQL算法的学习效率。随后，通过提出的 DQL 算法制定并解决了 JRSAC 优化问题。仿真结果表明，所提出的基于 DQL 的 JRSAC 方案在媒体访问控制 (MAC) 吞吐量、总访问延迟和总速率方面明显优于传统方案。