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Factory automation is the next industrial revolution. 5G and IIoT are enabling smart factories to seamlessly create a network of wirelessly connected machines and people that can instantaneously collect, analyze, and distribute real-time data. A 5G-enabled communication network for IIOT will boost overall efficiency, launching a new era of market opportunities and economic growth. This article presents the 5G-enabled system architecture and ultra-reliable use cases in smart factories associated with automated warehouses. In particular, for URLLC-based cases, key techniques and their corresponding solutions, including diversity for high reliability, short packets for low latency, and on-the-fly channel estimation and decoding for fast receiver processing, are discussed. Then the channel modeling requirements concerning technologies and systems are also identified in industrial scenarios. Ray tracing channel simulation can meet such requirements well, and based on that, the channel characteristic analysis is presented at 28 and 60 GHz for licensed and unlicensed band frequencies to exploit the available degrees of freedom in the channels.

Long-term evolution for railway (LTE-R) represents a promising network for smart railway, enabling fast and reliable wireless communications on high-speed trains (HSTs) with speeds as high as 500 km/h. To the best of our knowledge, the existing channel models are insufficient to assess such performance. To fill this gap, we propose the tapped delay line model for a $2\times 2$ multiple-input multiple-output channel in typical LTE-R HST scenarios. The models are efficient, yet flexible, which can capture the essential channel characteristics in the delay domain, Doppler domain, and spatial domain. Due to the practical difficulties of HST channel measurements, the channel between the fixed transmitter and the high-mobile train cannot be recorded sufficiently for establishing these stochastic models. Therefore, we develop channel models using a ray-tracing (RT) simulator that is validated by HST channel measurements at 2.15 GHz. This paper gives a full parameterization for the proposed channel models, and presents their implementation in channel and link-level simulations. The verification is made through a comparison of the proposed models and the measurement-validated RT simulations in terms of the delay spreads, the eigenvalues, and the error vector magnitudes.

The upcoming fifth-generation (5G) mobile communication system is expected to support high mobility up to 500 km/h, which is envisioned in particular for high-speed trains. Millimeter wave (mmWave) spectrum is considered as a key enabler for offering the “best experience” to highly mobile users. Despite that channel characterization is necessary for the mmWave system design and validation, it is still not feasible to directly do extensive mmWave mobile channel measurements on moving high-speed trains (HST) at a speed up to 500 km/h in the present. Thus, rather than conducting mmWave HST channel sounding directly with high mobility, this study proposes a viable paradigm for realizing the realistic HST channels at the 5G mmWave band. We first propose the whole paradigm. Then, we define the scenario of interest and select the main objects and materials. Afterwards, the electromagnetic and scattering parameters of the materials are measured and estimated between 26.5 GHz and 40 GHz. With this information, the most influential materials are determined through significance analysis. Correspondingly, we reconstruct the three-dimensional mmWave outdoor HST and tunnel scenario models. Through extensive ray-tracing simulations, we determine the main propagation mechanisms in these two scenarios, the channel models based on that are validated by measurements. This verifies the whole paradigm proposed in this paper.

This paper presents a geometry-based stochastic channel model (GSCM) for a 3GPP millimeter-wave (mmWave) high-speed train (HST) scenario. An important demand of the mmWave HST channel model is the spatial consistency during movement. In order to meet this requirement, the environment pattern containing the most effective geometry information is proposed, which is useful for generating an integral and accurate channel geometry. Since the measurement of a mmWave channel is deficient for high mobility, the proposed channel model is developed using a ray-tracing (RT) simulator that is validated with the channel measurements performed in the HST scenario at 93.2 GHz. The paper gives a full parameterization for the proposed model and its implementation for channel simulation. The verification is made through a comparison of the proposed model and the measurement-validated RT simulations in terms of the power delay profile, the Ricean $K$ -factor, and the second-order statistics for the delay and angle domains. Finally, for the design of mmWave HST communication systems, the time-varying channel characteristics are evaluated in the delay and Doppler domains.