Location-Aware Wireless Resource Allocation in Industrial-Like Environment

Abstract

The advent of the fourth Industrial Revolution (Industry 4.0) requires wireless networked solutions to connect machines. However, the industrial environment is notorious for being averse to wireless communication, with traditional wireless resource mechanisms prone to errors because of metallic objects. In this work, we propose to exploit the knowledge of location to derive context information and dynamically allocate wireless resources in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">time and space</i> to target devices. We exploit the spatial geometry of the Access Points (APs) and we introduce a statistical model that maps the user position’s spatial distribution to an angle error distribution and derive a hypothesis test to declare if the link is under metallic blockage or not. In order to avoid changes to the client side and operate with a single interface radio, we use <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">the same</i> wireless network both for positioning and scheduling. We experimentally show that our system can localize four mobile robots deployed in a very harsh environment with metal obstacles and reflections. Context information applied to wireless resources protocol help increasing up to 40 percent of the network throughput in the above industrial-like scenario.