@inproceedings{56b95c1cead34a8792b370ad70b337a3,
title = "Fog-Based Detection for Random-Access IoT Networks with Per-Measurement Preambles",
abstract = "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.",
keywords = "Fog-RAN, Hypothesis Testing, IoT, Random Access",
author = "Rahif Kassab and Osvaldo Simeone and Petar Popovski",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 21st IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2020 ; Conference date: 26-05-2020 Through 29-05-2020",
year = "2020",
month = may,
doi = "10.1109/SPAWC48557.2020.9154262",
language = "English (US)",
series = "IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2020",
address = "United States",
}