Fog-Based Detection for Random-Access IoT Networks with Per-Measurement Preambles
2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)(2020)
摘要
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 intercell interference power and the fronthaul capacity are sufficiently large.
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关键词
Random Access,IoT,Fog-RAN,Hypothesis Testing
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