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The paper describes the methodology and experimental results for revealing similarities in thermal dependencies of biases of accelerometers and gyroscopes from 250 inertial MEMS chips (MPU-9250). Temperature profiles were measured on an experimental setup with a Peltier element for temperature control. Classification of temperature curves was carried out with machine learning approach.
A perfect sensor should not have thermal dependency at all. Thus, only sensors inside the clusters with smaller dependency (smaller total temperature slopes) might be pre-selected for production of high accuracy inertial navigation modules. It was found that no unified thermal profile (“family” curve) exists for all sensors in a production batch. However, obviously, sensors might be grouped according to their parameters. Therefore, the temperature compensation profiles might be regressed for each group. 12 slope coefficients on 5 degrees temperature intervals from 0°C to +60°C were used as the features for the k-means++ clustering algorithm.
The minimum number of clusters for all sensors to be well separated from each other by bias thermal profiles in our case is 6. It was found by applying the elbow method. For each cluster a regression curve can be obtained.
The next generation cellular networks are expected to improve reliability, energy efficiency, data rate, capacity and latency. Originally, Machine Type Communication (MTC) was designed for low-bandwidth high-latency applications such as, environmental sensing, smart dustbin, etc., but there is additional demand around applications with low latency requirements, like industrial automation, driver-less cars, and so on. Improvements are required in 4G Long Term Evolution (LTE) networks towards the development of next generation cellular networks for providing very low latency and high reliability. To this end, we present an in-depth analysis of parameters that contribute to the latency in 4G networks along with a description of latency reduction techniques. We implement and validate these latency reduction techniques in the open-source network simulator (NS3) for narrowband user equipment category Cat-Ml (LTE-M) to analyze the improvements. The results presented are a step towards enabling narrowband Ultra Reliable Low Latency Communication (URLLC) networks.
Vehicle-to-Everything (V2X) communication promises improvements in road safety and efficiency by enabling low-latency and reliable communication services for vehicles. Besides using Mobile Broadband (MBB), there is a need to develop Ultra Reliable Low Latency Communications (URLLC) applications with cellular networks especially when safety-related driving applications are concerned. Future cellular networks are expected to support novel latencysensitive use cases. Many applications of V2X communication, like collaborative autonomous driving requires very low latency and high reliability in order to support real-time communication between vehicles and other network elements. In this paper, we classify V2X use-cases and their requirements in order to identify cellular network technologies able to support them. The bottleneck problem of the medium access in 4G Long Term Evolution(LTE) networks is random access procedure. It is evaluated through simulations to further detail the future limitations and requirements. Limitations and improvement possibilities for next generation of cellular networks are finally detailed. Moreover, the results presented in this paper provide the limits of different parameter sets with regard to the requirements of V2X-based applications. In doing this, a starting point to migrate to Narrowband IoT (NB-IoT) or 5G - solutions is given.
Uncontrollable manufacturing variations in electrical hardware circuits can be exploited as Physical Unclonable Functions (PUFs). Herein, we present a Printed Electronics (PE)-based PUF system architecture. Our proposed Differential Circuit PUF (DiffC-PUF) is a hybrid system, combining silicon-based and PE-based electronic circuits. The novel approach of the DiffC-PUF architecture is to provide a specially designed real hardware system architecture, that enables the automatic readout of interchangeable printed DiffC-PUF core circuits. The silicon-based addressing and evaluation circuit supplies and controls the printed PUF core and ensures seamless integration into silicon-based smart systems. Major objectives of our work are interconnected applications for the Internet of Things (IoT).