论文标题
基于雾气的随机访问IoT网络的检测，具有每测序列
Fog-Based Detection for Random-Access IoT Networks with Per-Measurement Preambles
论文作者
论文摘要
可以部署物联网（IoT）系统以监视空间分布的兴趣量（QOIS），例如噪声或污染水平。本文考虑了一个基于雾的物联网网络，在该网络中，主动物联网设备将受监视的QOI的测量值传输到局部边缘节点（EN），而ENS则通过有限容量的Fronthaul链接连接到云处理器。尽管常规方法将前序用作元数据来保留通信资源，但在这里，我们考虑将前序直接分配给所有设备的测量水平。最终的基于类型的多重访问（TBMA）协议可以有效地远程检测QOI，而不是单个有效载荷的远程检测。根据误差指数评估了基于边缘和基于云的检测或假设测试的性能。当基于云的假设检验在理论上和通过数值结果表明是有利的。
Internet of Things (IoT) systems may be deployed to monitor spatially distributed quantities of interests (QoIs), such as noise or pollution levels. This paper considers a fog-based IoT network, in which active IoT devices transmit measurements of the monitored QoIs to the local edge node (EN), while the ENs are connected to a cloud processor via limited-capacity fronthaul links. While the conventional approach uses preambles as metadata for reserving communication resources, here we consider assigning preambles directly to measurement levels across all devices. The resulting Type-Based Multiple Access (TBMA) protocol enables the efficient remote detection of the QoIs, rather than of the individual payloads. The performance of both edge and cloud-based detection or hypothesis testing is evaluated in terms of error exponents. Cloud-based hypothesis testing is shown theoretically and via numerical results to be advantageous when the inter-cell interference power and the fronthaul capacity are sufficiently large.
