Information-Centric Grant-Free Access for IoT Fog Networks: Edge vs. Cloud Detection and Learning

Rahif Kassab, Osvaldo Simeone, Petar Popovski

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

A multi-cell Fog-Radio Access Network (F-RAN) architecture is considered in which Internet of Things (IoT) devices periodically make noisy observations of a Quantity of Interest (QoI) and transmit using grant-free access in the uplink. The devices in each cell are connected to an Edge Node (EN), which may also have a finite-capacity fronthaul link to a central processor. In contrast to conventional information-Agnostic protocols, the devices transmit using a Type-Based Multiple Access (TBMA) protocol that is tailored to enable the estimate of the field of correlated QoIs in each cell based on the measurements received from IoT devices. In this paper, this form of information-centric radio access is studied for the first time in a multi-cell F-RAN model with edge or cloud detection. Edge and cloud detection are designed and compared for a multi-cell system. Optimal model-based detectors are introduced and the resulting asymptotic behavior of the probability of error at cloud and edge is derived. Then, for the scenario in which a statistical model is not available, data-driven edge and cloud detectors are discussed and evaluated in numerical results.

Original languageEnglish (US)
Article number9123545
Pages (from-to)6347-6361
Number of pages15
JournalIEEE Transactions on Wireless Communications
Volume19
Issue number10
DOIs
StatePublished - Oct 2020
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

Keywords

  • 5G
  • IoT
  • fog-ran
  • grant-free access
  • information-centric access
  • machine-Type communications
  • type-based multiple access

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