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

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.

References in corpus (6)

• On the Performance of Non-Orthogonal Multiple Access in 5G Systems with Randomly Deployed Users
• Fog Computing based Radio Access Networks: Issues and Challenges
• Coded Slotted ALOHA: A Graph-Based Method for Uncoordinated Multiple Access
• Rician MIMO Channel- and Jamming-Aware Decision Fusion
• Optimality of Received Energy in Decision Fusion over Rayleigh Fading Diversity MAC with Non-Identical Sensors
• Start Making Sense: Semantic Plane Filtering and Control for Post-5G Connectivity

Cited by in corpus (4)

• Learning to Demodulate from Few Pilots via Offline and Online Meta-Learning
• Dynamic Resource Configuration for Low-Power IoT Networks: A Multi-Objective Reinforcement Learning Method
• Joint Source-Channel Coding for Semantics-Aware Grant-Free Radio Access in IoT Fog Networks
• Information Bottleneck-Inspired Type Based Multiple Access for Remote Estimation in IoT Systems