Wireless Channel Measurements and Characterization in Industrial IoT Scenarios

TL;DR

This paper presents detailed wireless channel measurements in an industrial IoT setting at 5.5 GHz, analyzing SISO and MIMO characteristics, and introduces an estimation algorithm for multi-path components affecting channel capacity.

Contribution

It provides new insights into industrial IoT wireless channels at 5.5 GHz and proposes an algorithm to effectively process multi-DMC processes in MIMO channel analysis.

Findings

Multiple DMC processes are present in industrial environments.

Ignoring DMCs can lead to overestimating singular values.

Channel capacities are significantly affected by DMCs.

Abstract

Wireless Fidelity (Wi-Fi) communication technologies hold significant potential for realizing the Industrial Internet of Things (IIoT). In this paper, both Single-Input Single-Output (SISO) and polarized Multiple-Input Multiple-Output (MIMO) channel measurements are conducted in an IIoT scenario at the less congested Wi-Fi band, i.e., 5.5~GHz. The purpose is to investigate wireless characteristics of communications between access points and terminals mounted on automated guided vehicles as well as those surrounding manufacturing areas. For SISO channel measurements, statistical properties including the delay Power Spectral Density (PSD), path loss, shadowing fading, delay spread, excess delay, K-factor, and amplitude distribution of small-scale fading are analyzed and compared with those observed in an office scenario. For MIMO channel measurements, results show that there are multiple Dense Multipath Component (DMC) processes in the delay PSD. An estimation algorithm based on the algorithm for a single DMC process is proposed to effectively process the multi-processes data. Moreover, delay, angular, power, and polarization properties of DMCs are investigated and compared with those of specular multipath components. Furthermore, effects of DMCs on Singular Values (SVs) and channel capacities are explored. Ignoring DMCs can overestimate SVs and underestimate channel capacities.