Zodiac Aerospace (Germany)

The problem of wireless M2M communication is twofold: the reliability aspect and the scalability aspect. The solution to this problem demands a delay constrained random access protocol. To this end, we propose admission control based traffic-agnostic delay-constrained random access (AC/DC-RA) protocol. Our main contribution is enabling the stochastic delay constraints agnostic to the traffic, such that the stochastic delay constraint is valid with respect to a varying number of arrivals. We achieve this with an admission control decision that uses a novel collision estimation algorithm for an active number of arrivals per contention resource. We use an adaptive contention resolution algorithm to react to the varying number of arrivals. Using these tools, the admission control solves the stability problem. We show with simulations that the AC/DC-RA provide stochastic delay constrained random access in a traffic agnostic way to sustain a stable performance against Poisson and Beta arrivals without any modification to the protocol.

Fifth-generation (5G) systems are being designed not only to face the unprecedented growth of mobile data traffic forecasted for the coming years but also to support other multiple and diverse use cases associated with new market segments and vertical industries (e.g., connected cars, smart cities, e-health, and smart factories). Hence, 5G systems are envisioned to become flexible and versatile network infrastructures that can be leveraged through a wide range of service-delivery models (e.g., neutral network hosting, network as a service, and private networks) and operators can customize for different applications and customer needs using network slicing.

ABSTRACTKnow‐how reuse is an approach that has been always used by engineers to take advantage of their accumulated knowledge and practices. But, the difficulty to formalize and reuse expert know‐how is increasing alongside the complexity of systems. To deal with this challenge, this paper aims to open the way to new approaches of know‐how reuse, in order to improve engineering activities. For that purpose, it explores the capabilities of three reuse approaches (commercial off‐the‐shelf (COTS), set‐based design, and patterns), and their ability to be linked with a model‐based systems engineering (MBSE) framework.

Abstract There is certainly room for economy‐class travelers to make their trips more pleasant. A travel pillow might improve comfort. In this study, the comfort expectations and experience of travel pillows were examined. Comparing these 2 aspects indicated that it is not always possible to predict the comfort experience associated with a product based on a picture, and that there is a discrepancy between expected and experienced comfort. Experienced comfort is highest for travel pillows that restrict head movements in all directions in order to maintain a neutral posture. The results of this study also support earlier studies that suggested that discomfort experience can be predicted by observing the number of participants’ in‐seat movements; more movements result in higher experienced discomfort.

This paper presents a generic study of battery's modeling in aeronautic field. A model identification protocol is discussed at first, the validity of the model is then evaluated, using a LiFePO 4 /graphite cell, for a presumed aeronautic load profile in order to test its capability in ensuring the required specifications.

In this article, the authors study the convergence of an iterative algorithm for the joint estimation of the signal-to-noise ratio (SNR) and the transmission channel in orthogonal frequency division multiplexing context. At each step of the algorithm, the authors use the minimum-mean-square error (MMSE)-based SNR estimation, which feeds the linear MMSE channel estimation. Reciprocally, this efficient channel estimation is used to perform the SNR estimation. The authors provide a proof of convergence of the algorithm to a single value. Furthermore, we derive an accurate approximation of the bias of the estimation. Simulations show that the algorithm converges quickly and verifies the theoretical results. They also show the efficiency of both SNR and channel estimation. By comparing with the existing methods, the authors show that the tradeoff between the number of required pilots in the preamble and the performance of the SNR estimation were improved. Furthermore, for a fixed bit error rate, the SNR gap between the proposed channel estimation and the perfect one is <0.5 dB.