In this paper, we propose a Slotted ALOHA (SA)-inspired solution for an indoor optical wireless communication (OWC)-based Internet of Things (IoT) system. Assuming that the OWC receiver exploits the capture effect, we are interested in the derivation of error probability of decoding a short-length data packet originating from a randomly selected OWC IoT transmitter. The presented OWC system analysis rests on the derivation of the signal-to-noise-and-interference-ratio (SINR) statistics and usage of finite block-length (FBL) information theory, from which relevant error probability and throughput is derived. Using the derived expressions, we obtain numerical results which are further utilized to characterize the trade-offs between the system performance and the OWC system setup parameters. The indoor OWC-based system geometry plays an important role in the system performance, thus the presented results can be used as a guideline for the system design to optimize the performance of the SA-based random access protocol.
翻译:在本文中,我们提出了一个基于室内光学无线通信(OWC)的无线通信(IoT)系统(OWC)激励的解决方案,假设OWC接收器利用捕获效应,我们有兴趣从随机选定的OWC IoT发报机解码一个短长度数据包的误差概率中推断出一个数据包。OWC系统分析是根据信号到噪音和干预-拉迪奥(SINR)统计数据的衍生结果,以及使用有限轮档长度信息理论(FBL)得出相关误差概率和吞吐量。我们利用衍生的表达方式获得了数字结果,进一步用于说明系统性能与OWC系统设置参数之间的权衡。基于室内OSW的系统几何测量系统在系统性能中发挥了重要作用,因此,可以将所介绍的结果用作系统设计的指导方针,优化SA随机访问协议的性能。