Measurement‐Based Experimental Statistical Modeling of Propagation Channel in Industrial IoT Scenario.

This paper presents 3–4 and 38–40 GHz wideband channel characteristics for industrial internet‐of‐things (IIoT) scenario based on measurements. The channel measurement equipment applied in the measurements consists of a programmable vector network analyzer and necessary auxiliaries. An extensive amount of data in line‐of‐sight (LoS) and non‐line‐of‐sight (NLoS) scenarios is collected with omnidirectional antennas in both transmitter and receiver ends. With the Space‐Alternating Generalized Expectation‐maximization (SAGE) algorithm, the multipath components (MPCs) of the received signals are extracted to calculate the channel model parameters, for example, channel gain coefficient, delay spread, and Ricean K factor. By studying the statistical characteristics of these parameters, a stochastic channel model in IIoT scenario is initially established and compared with the existing indoor channel models. Moreover, the distinctive characteristics of channel parameters in the millimeter wave band and sub‐6 GHz band in the IIoT scenario are demonstrated. Plain Language Summary: Usually, the industrial environments are complicated and variable, which makes the communications in factory more difficult than those in general indoor scenarios. Hence, more information about the characteristics of the radio propagation in industrial scenarios is needed. This work presents 3–4 and 38–40 GHz wideband channel characteristics for industrial internet‐of‐things (IIoT) scenarios based on measurements, which is helpful to the design of the communication systems and the installation of low‐latency, high‐speed, high‐stability communication facilities on automation production equipment in industrial environments. Key Points: The 3–4 and 38–40 GHz wideband channel models in an industrial internet‐of‐things (IIoT) scenario are presentedThe variance of shadow fading in the IIoT scenario is larger than that in general indoor scenariosThe values of K factors in the IIoT scenario demonstrate significant dependence on the premises of the Rx [ABSTRACT FROM AUTHOR]