Industrial Internet of Things (IIoT) is an emerging area that fifth-generation (5G) mobile communication system penetrates industrial manufacturing applications. The indoor factory has larger space and there are a lot of metal machine tools distributed in it, which makes its radio propagation characteristics and corresponding channel models significantly different from those of the indoor office and indoor hotspot. To support the design and the evaluation of the IIoT techniques, the 3rd Generation Partnership Project (3GPP) released the first 5G IIoT standard model in October 2019. In this article, we give a detailed explanation of this IIoT model and compare it with other indoor models. First, we introduce the standardization of 3GPP IIoT channel model and its motivation. Second, four IIoT subscenarios, which are classified according to the clutter density and antenna height, are described. Third, the potential frequency bands of 5G IIoT are summarized. Fourth, the models of channel parameters, including the path loss and the line-of-sight (LOS) probability, the root mean-square (RMS) delay spread, and the angular spread, are given. Among them, the models of path loss and LOS probability take the antenna height and clutter density into consideration. The model of RMS delay spread changes from frequency-dependent to volume-dependent in order to catch the size variation of factories. Finally, two newly added key channel characteristics, dual mobility and absolute time of arrival, which help to describe the robot movement and positioning, are also presented.

The bands 3.5 and 28 GHz are both very important for the fifth-generation (5G) wireless communication system. To model their propagation characteristics and study their channel properties, we conduct measurements at these two frequencies in indoor and outdoor scenarios. The measured bandwidths at 3.5 and 28 GHz are 100 and 400 MHz, respectively. To make a fair comparison, the measurement results at 28 GHz are divided into four groups with bandwidths from 100 to 400 MHz. This is also helpful to study the effect of bandwidth on the channel properties, especially numbers of clusters and their growth rate. We choose the Saleh-Valenzuela (S-V) model to analyze the wireless channel. Its cluster-based property is very suitable to describe the power delay profiles (PDPs) in our measurement. To maintain the time continuity of multipath components (MPCs) during the clustering, we propose a new heuristic cluster algorithm. Based on the clustering results, we obtain the channel parameters, i.e., the number of clusters, inter-cluster interval, intra-cluster root mean square (RMS) delay spread, cluster decay factor, and ray decay factor. From the comparative study, we can find that the rays suffer a larger attenuation at 28 GHz than at 3.5 GHz. Increasing bandwidth can further strengthen this phenomenon. But the effects of frequency on the cluster decay rate are different in indoor and outdoor scenarios. The cluster decay rate is smaller at 28 GHz in the indoor scenario.

Visible light communication (VLC) is considered a promising technology for enabling Internet of Everything (IoE) applications in the sixth generation (6G), owing to its specific advantages over radio frequency (RF) communications. A comprehensive understanding of VLC channel characteristics and models is imperative for optimizing VLC technology, designing systems, and evaluating performance. This article presents an overview of ongoing research in channel characterization and modeling for VLC-IoE applications in the context of 6G. Recent advancements are systematically summarized, encompassing channel modeling methods, application scenarios, emerging combining technologies, such as reconfigurable intelligent surfaces (RISs) and integrated sensing and communication (ISAC), and distinctive channel characteristics. Additionally, future research directions in these domains are outlined to provide insights into forthcoming investigations for VLC-IoE applications in 6G.

Integrated Sensing and Communication (ISAC) is a promising technology in 6G systems. The existing 3D Geometry-Based Stochastic Model (GBSM), standardized for 5G systems, addresses solely communication channel and lacks consideration of the integration with sensing channel. Therefore, this letter extends 3D GBSM to support ISAC research, with a particular focus on capturing the sharing feature of both channels, including shared scatterers, clusters, paths, and similar propagation parameters, which have been experimentally verified in our previous work. The proposed approach can be summarized as follows: Firstly, we propose an ISAC channel model that combines shared and non-shared clusters, where the former co-exist or disappear for communication and sensing. Secondly, to characterize the target, the sensing channel is modeled as a cascade of Tx-target link, target-Rx link, and target scattering response. A novel parameter S is introduced for the extraction of shared targets/scatterers and clusters. Finally, an ISAC channel implementation framework is proposed, allowing flexible configuration of the sharing feature and the joint generation of communication and sensing channels. The proposed ISAC channel model can be well-compatible with the 3GPP standards and offers promising support for ISAC technology evaluation.

Accurate radar cross section (RCS) modeling is crucial for characterizing target scattering and improving the precision of Integrated Sensing and Communication (ISAC) channel modeling. Existing RCS models are typically designed for specific target types, leading to increased complexity and lack of generalization. This makes it difficult to standardize RCS models for 3GPP ISAC channels, which need to account for multiple typical target types simultaneously. Furthermore, 3GPP models must support both system-level and link-level simulations, requiring the integration of large-scale and small-scale scattering characteristics. To address these challenges, this paper proposes a unified RCS modeling framework that consolidates these two aspects. The model decomposes RCS into three components: (1) a large-scale power factor representing overall scattering strength, (2) a small-scale angular-dependent component describing directional scattering, and (3) a random component accounting for variations across target instances. We validate the model through mono-static RCS measurements for UAV, human, and vehicle targets across five frequency bands. The results demonstrate that the proposed model can effectively capture RCS variations for different target types. Finally, the model is incorporated into an ISAC channel simulation platform to assess the impact of target RCS characteristics on path loss, delay spread, and angular spread, providing valuable insights for future ISAC system design.