Precise position information is considered as the main enabler for the implementation of smart manufacturing systems in Industry 4.0. In this article, a time-of-flight based indoor positioning system for LiFi is presented based on the ITU -T recommendation G.9991. Our objective is to realize positioning by reusing already existing functions of the LiFi communication protocol which has been adopted by several vendors. Our positioning algorithm is based on a coarse timing measurement using the frame synchronization preamble, similar to the ranging, and a fine timing measurement using the channel estimation preamble. This approach works in various environments and it requires neither knowledge about the beam characteristics of transmitters and receivers nor the use of fingerprinting. The new algorithm is validated through both, simulations and experiments. Results in an 1m × 1m × 2m area indicate that G.9991-based positioning can reach an average distance error of a few centimeters in three dimension. Considering the common use of lighting in indoor environments and the availability of a mature optical wireless communication system using G.9991, the proposed LiFi positioning is a promising new feature that can be added to the existing protocols and enhance the capabilities of smart lighting systems further for the benefit of Industry 4.0.

Efficient routing is one of the key challenges of wireless networking for unmanned aerial vehicles (UAVs) due to dynamically changing channel and network topology characteristics. Various well known mobile-ad-hoc routing protocols, such as AODV, OLSR and B.A.T.M.A.N. have been proposed to allow for proactive and reactive routing decisions. In this paper, we present a novel approach which leverages application layer knowledge derived from mobility control algorithms guiding the behavior of UAVs to fulfill a dedicated task. Thereby a prediction of future trajectories of the UAVs can be integrated with the routing protocol to avoid unexpected route breaks and packet loss. The proposed extension of the B.A.T.M.A.N. routing protocol by a mobility prediction component -called B.A.T.Mobile -has shown to be very effective to realize this concept. The results of in-depth simulation studies show that the proposed protocol reaches a distinct higher availability compared to the established approaches and shows robust behavior even in challenging channel conditions.

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In recent years, the interest in interconnecting production machines has grown and new technologies such as augmented reality enter the shop floor. This evolution is driven by hyped topics such as Industry 4.0 and Internet of Things. These topics promise benefits through increasing transparency in factories, such as improvement in efficiency and reduced costs, e.g., due to data analysis. As a result, the demand on new concepts and technologies for factory networks is rising to fulfill the upcoming new requirements. Therefore, the development of 5G comes just in time. This paper is focused on one of the 5G core technologies network function virtualization (NFV). We propose two use cases that demonstrate how NFV enables flexible smart manufacturing. In NFV technology, virtual network functions (VNF) are composed to network services. We introduce the application of our vertical-specific network services that enable augmented reality on-demand and the flexible interconnection of production machines with services in company's cloud backend.

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