A fog-radio access network (F-RAN) architecture is studied for an Internet-of-Things (IoT) system in which wireless sensors monitor a number of multi-valued events and transmit in the uplink using grant-free random access to multiple edge nodes (ENs). Each EN is connected to a central processor (CP) via a finite-capacity fronthaul link. In contrast to conventional information-agnostic protocols based on separate source-channel (SSC) coding, where each device uses a separate codebook, this paper considers an information-centric approach based on joint source-channel (JSC) coding via a non-orthogonal generalization of type-based multiple access (TBMA). By leveraging the semantics of the observed signals, all sensors measuring the same event share the same codebook (with non-orthogonal codewords), and all such sensors making the same local estimate of the event transmit the same codeword. The F-RAN architecture directly detects the events values without first performing individual decoding for each device. Cloud and edge detection schemes based on Bayesian message passing are designed and trade-offs between cloud and edge processing are assessed.
翻译:用于互联网连接系统的雾- 无线电网络( F-RAN) 结构, 其中无线传感器监测多种有价事件, 并使用无赠与随机访问多边缘节点( ENs) 进行上行传输。 每个EN都通过一个有限容量前厅链接连接到中央处理器( CP) 。 与基于不同源- 通道编码的常规信息- 机密协议( SSC) 相比, 每个设备都使用单独的代码簿, 本文认为一种基于联合源- 通道( JSC) 的以信息为中心的方法, 即通过非垂直的基于类型多重访问( TBMA) 编码, 并在上链接中进行传输。 通过利用所观测到的信号的语义, 所有测量同一事件的传感器都使用相同的代码簿( 带有非垂直代码词), 所有对事件进行同一本地估计的传感器都传输同一代码词。 F- RAN 结构直接检测事件的价值, 而不首先对每个设备进行单个解码。 基于 Bayes 边缘处理的云端探测计划是设计, 和传输的云端偏偏偏。