arXiv subjects

Hans D. Schotten

Publications and source records attributed to Hans D. Schotten.

At least 199 records · Page 11Linked to original sources

arXiv2019

Design of a 5G Ready and Reliable Architecture for the Smart Factory of the Future

The increasing demands for highly individual products as well as for flexible production lines represent new challenges. To address these demands, future plants must be highly flexible and dynamically reconfigurable. Current systems are usually based on wired technologies for the connection of sensors, actuators, and controlling or monitoring devices that allow only very limited dynamics. New applications, such as the use of robots, drones, or reconfigurable production lines, require the exploitation of wireless communication technologies. However, current technologies are not able to meet the high requirements in terms of latency, robustness, resilience and data rate. The introduction of the 5th generation (5G) cellular communication system will meet these requirements for the first time. Besides the use of radio-based solutions in new plants - so-called greenfield scenarios - deploying 5G also represents an efficient migration of existing plants - so-called brownfield scenarios - to Industry 4.0. In order to ensure that the challenging requirements are indeed meet in practical deployments of the new 5G technology, a tailor-made architecture is being developed within the Tactile Internet 4.0 (TACNET 4.0) project. As a basis for the design of the architecture, representative Industry 4.0 application scenarios, which are also be considered by the 3rd Generation Partnership Project (3GPP), were analyzed and compliance with the latest developments in the relevant standardization is also our target. The paper gives an overview of the considered use cases as well as the relevant reference architectures and the design process of the TACNET 4.0 architecture.

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arXiv2019

Cloud Control AGV over Rayleigh Fading Channel -- The Faster The Better

This paper analyzes the stability of the control system of an Autonomous Guided Vehicle (AGV) using a central controller. The control commands are transmitted to an AGV over a Rayleigh fading channel causing potential packet drops. This paper analyzes the mutual dependencies of control system and mobile communication system. Among the important parameters considered are the sampling time of the discrete control system, the maximum tolerable outages for the control system, the AGV velocity, the number of users, as well as mobile communication channel conditions. It is shown that increasing the velocity of an AGV leads to a lower risk of instability due to the higher time-variance of the mobile channel. While this still is a 'sandbox' example, it shows the potential for a manifold co-optimization of control systems operated over imperfect mobile communication channels.

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arXiv2019

A Controller for Network-Assisted CACC based Platooning

Platooning involves a set of vehicles moving in a cooperative fashion at equal inter-vehicular distances. Taking advantage of wireless communication technology, this paper aims to show the impact of network protocols on a platoon using a controller, based on the Cooperative Adaptive Cruise Control (CACC) principles. The network protocols used in this work are DSRC (Dedicated Short Range Communication) and LTE-V2V sidelink (Mode 4). The main focus of this work is to showcase the ability of the controller to maintain platoon stability despite having uncertainties in both, the platoon and the message delivery rates over the network protocols. The controller interacts with all vehicles using messages transmitted over the network protocols. The controller is designed to be responsible for micro-managing every vehicle in the platoon and to ensure that the platoon does not break under any circumstances. SUMO (Simulation of Urban MObility) is used as the simulation platform. Results indicate, that the controller manages to achieve platoon stability in all scenarios, unless a set number of consecutive messages are not transmitted, in which case it leads to collisions. This work also presents certain bottlenecks pertaining to wireless communication with vehicles.

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arXiv2019

A Utility-Driven Multi-Queue Admission Control Solution for Network Slicing

The combination of recent emerging technologies such as network function virtualization (NFV) and network programmability (SDN) gave birth to the Network Slicing revolution. 5G networks consist of multi-tenant infrastructures capable of offering leased network "slices" to new customers (e.g., vertical industries) enabling a new telecom business model: Slice-as-aService (SlaaS). In this paper, we aim i ) to study the slicing admission control problem by means of a multi-queuing system for heterogeneous tenant requests, ii ) to derive its statistical behavior model, and iii ) to provide a utility-based admission control optimization. Our results analyze the capability of the proposed SlaaS system to be approximately Markovian and evaluate its performance as compared to legacy solutions.

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arXiv2019

System-Level Simulator of LTE Sidelink C-V2X Communication for 5G

In recent years, Cellular-Vehicle-to-Everything (CV2X) has been an emerging area of interest attracting both the industry and academy societies to develop, which is also a prominent emerging service for the next generation of the cellular network (5G). In the time of the development, standardization, and further improvement of 5G, so simulations are essential to test and optimize algorithms and procedures prior to their implementation process of the equipment manufactures. And CV2X communication is used for information exchange among the traffic participants with network-assisted which can reduce traffic accidents and improve traffic efficiency. Moreover, it is also the primary enabler for cooperative driving. But CV2X communication has to meet different Quality of Service (QoS) requirements (e.g., ultra-high reliability (99.999%) and ultra-low latency). Guaranteeing high-level reliability is a big challenge. In order to assess system performance, accurate simulations of simple setups, as well as simulations of more complex systems via abstracted models are necessary for the CV2X communication. For checking the performance of the C-V2X communication on a highway scenario, a system-level simulator has been implemented. And, this simulation has been carried out on the network (system-level) context. Finally, the analysis and the simulation results for the C-V2X communication are presented, which shows that different objectives can be met via system-level simulation.

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arXiv2019

Performances of C-V2X Communication on Highway under Varying Channel Propagation Models

In recent decades, both the industry and the academy society are sparing no efforts to develop and standardize the Cellular-Vehicle-to-Everything (C-V2X) communication which is one of the prominent emerging services of the next generation of wireless network (5G). C-V2X communication is used for information exchange among the traffic participants with network-assisted which can reduce traffic accidents and improve traffic efficiency. And it is also the primary enabler for cooperative driving. But C-V2X communication has to meet different Quality of Service (QoS) requirements (e.g., ultra-high reliability (99.999%) and ultra-low latency).

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arXiv2019

A Machine-Learning Phase Classification Scheme for Anomaly Detection in Signals with Periodic Characteristics

In this paper we propose a novel machine-learning method for anomaly detection applicable to data with periodic characteristics where randomly varying period lengths are explicitly allowed. A multi-dimensional time series analysis is conducted by training a data-adapted classifier consisting of deep convolutional neural networks performing phase classification. The entire algorithm including data pre-processing, period detection, segmentation, and even dynamic adjustment of the neural networks is implemented for fully automatic execution. The proposed method is evaluated on three example datasets from the areas of cardiology, intrusion detection, and signal processing, presenting reasonable performance.

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arXiv2019

Context-Awareness Enhances 5G Multi-Access Edge Computing Reliability

The fifth generation (5G) mobile telecommunication network is expected to support Multi- Access Edge Computing (MEC), which intends to distribute computation tasks and services from the central cloud to the edge clouds. Towards ultra-responsive, ultra-reliable and ultra-low-latency MEC services, the current mobile network security architecture should enable a more decentralized approach for authentication and authorization processes. This paper proposes a novel decentralized authentication architecture that supports flexible and low-cost local authentication with the awareness of context information of network elements such as user equipment and virtual network functions. Based on a Markov model for backhaul link quality, as well as a random walk mobility model with mixed mobility classes and traffic scenarios, numerical simulations have demonstrated that the proposed approach is able to achieve a flexible balance between the network operating cost and the MEC reliability.

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arXiv2019

Merging the Bernoulli-Gaussian and Symmetric Alpha-Stable Models for Impulsive Noises in Narrowband Power Line Channels

To model impulsive noise in power line channels, both the Bernoulli-Gaussian model and the symmetric alpha-stable model are usually applied. Towards a merge of existing noise measurement databases and a simplification of communication system design, the compatibility between the two models is of interest. In this paper, we show that they can be approximately converted to each other under certain constrains, although never generally unified. Based on this, we propose a fast model conversion.

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arXiv2018

Delay constrained Energy Optimization for Edge Cloud Offloading

Resource limited user-devices may offload computation to a cloud server, in order to reduce power consumption and lower the execution time. However, to communicate to the cloud server over a wireless channel, additional energy is consumed for transmitting the data. Also a delay is introduced for offloading the data and receiving the response. Therefore, an optimal decision needs to be made that would reduce the energy consumption, while simultaneously satisfying the delay constraint. In this paper, we obtain an optimal closed form solution for these decision variables in a multi-user scenario. Furthermore, we optimally allocate the cloud server resources to the user devices, and evaluate the minimum delay that the system can provide, for a given bandwidth and number of user devices.

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arXiv2018

Performance Analysis of Deep Learning based on Recurrent Neural Networks for Channel Coding

Channel Coding has been one of the central disciplines driving the success stories of current generation LTE systems and beyond. In particular, turbo codes are mostly used for cellular and other applications where a reliable data transfer is required for latency-constrained communication in the presence of data-corrupting noise. However, the decoding algorithm for turbo codes is computationally intensive and thereby limiting its applicability in hand-held devices. In this paper, we study the feasibility of using Deep Learning (DL) architectures based on Recurrent Neural Networks (RNNs) for encoding and decoding of turbo codes. In this regard, we simulate and use data from various stages of the transmission chain (turbo encoder output, Additive White Gaussian Noise (AWGN) channel output, demodulator output) to train our proposed RNN architecture and compare its performance to the conventional turbo encoder/decoder algorithms. Simulation results show, that the proposed RNN model outperforms the decoding performance of a conventional turbo decoder at low Signal to Noise Ratio (SNR) regions

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arXiv2018

Design of a Highly Reliable Wireless Module for Ultra-Low-Latency Short Range Applications

Current radio systems are currently optimized for capacity and range. However, certain applications of wireless systems require fast and reliable communication over short distances. The challenge of these systems is to communicate with a minimum time delay (latency) while at the same time being very reliable and resilient to interference. This paper describes the concept and the proposed abstract architecture of a wireless technology that allows highly reliable and ultra low latency transmission of data between moving units over a few meters, the applications of which can be found in multitude of domains such as Train Communicaion Networks (TCNs), Truck/Tractor - Trailer Communication, Platooning, and in smart industry in the form of co-ordinating machines. The paper also describes the set of novelties that were planned to be realized as part of the final demo hardware

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arXiv2018

Machine Learning Based Obstacle Detection for Automatic Train Pairing

Short Range wireless devices are becoming more and more popular for ubiquitous sensor and actuator connectivity in industrial communication scenarios. Apart from communication-only scenarios, there are also mission-critical use cases where the distance between the two communicating nodes needs to be determined precisely. Applications such as Automatic Guided Vehicles (AGV's), Automatic Train Pairing additionally require the devices to scan the environment and detect any potential humans/obstacles. Ultra-Wide Band (UWB) has emerged as a promising candidate for Real-Time Ranging and Localization (RTRL) due to advantages such as large channel capacity, better co-existence with legacy systems due to low transmit power, better performance in multipath environments etc. In this paper, we evaluate the performance of a UWB COTS device - TimeDomain P440 which can operate as a ranging radio and a monostatic radar simultaneously. To this end, we evaluate the possibility of using Supervised Learning based estimators for predicting the presence of obstacles by constructing a multiclass hypothesis. Simulation results show that the Ensemble tree based methods are able to calculate the likelihood of obstacle collision with accuracies close to 95%.

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arXiv2018

Reliability Modeling, Analysis and Prediction of Wireless Mobile Communications

The future Fifth Generation (5G) mobile cellular networks that are currently in research phase today enable broad range of services/applications beyond classical mobile communications. One key enabler for Ultra-Reliable services to be integrated into mobile networks is the \textit{Reliability} of transmission success of a given data packet. This is harder mainly owing to the time-dependent effective link qualities of the communicating devices. However, successful indication of the availability of the instantaneous link quality (e.g., by the device) would allow opportunistic access of ultra reliable services/applications when the link conditions are fair enough. This paper introduces a framework for modeling, predicting and analyzing the theoretical reliability of the wireless link based on factors such as fading, mobility, interference etc. The analysis and prediction is based on the part stress method\cite{Birolini2010} by assuming time dependent factors as elements/components and their respective Transmission Times To Failure (TTTF). The proposed framework also supports other reliability analysis techniques such as Fault Tree Analysis and Accelerated testing. of wireless systems and to improve the components

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arXiv2018

Enabling Communication Technologies for Automated Unmanned Vehicles in Industry 4.0

Within the context of Industry 4.0, mobile robot systems such as automated guided vehicles (AGVs) and unmanned aerial vehicles (UAVs) are one of the major areas challenging current communication and localization technologies. Due to stringent requirements on latency and reliability, several of the existing solutions are not capable of meeting the performance required by industrial automation applications. Additionally, the disparity in types and applications of unmanned vehicle (UV) calls for more flexible communication technologies in order to address their specific requirements. In this paper, we propose several use cases for UVs within the context of Industry 4.0 and consider their respective requirements. We also identify wireless technologies that support the deployment of UVs as envisioned in Industry 4.0 scenarios.

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arXiv2018

A 5G Architecture for The Factory of the Future

Factory automation and production are currently undergoing massive changes, and 5G is considered being a key enabler. In this paper, we state uses cases for using 5G in the factory of the future, which are motivated by actual needs of the industry partners of the "5Gang" consortium. Based on these use cases and the ones by 3GPP, a 5G system architecture for the factory of the future is proposed. It is set in relation to existing architectural frameworks.

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arXiv2018

Admission and Congestion Control for 5G Network Slicing

Network Slicing has been widely accepted as essential feature of future 5th Generation (5G) mobile communication networks. Accounting the potentially dense demand of network slices as a cloud service and the limited resource of mobile network operators (MNOs), an efficient inter-slice management and orchestration plays a key role in 5G networks. This calls advanced solutions for slice admission and congestion control. This paper proposes a novel approach of inter-slice control that well copes with existing pre-standardized 5G architectures

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arXiv2018

A Markov Model of Slice Admission Control

The emerging feature of network slicing in future Fifth Generation (5G) networks calls for efficient slice management. Recent studies have been focusing on the mechanism of slice admission control, which functions in a manner of state machine. This paper proposes a general state model for synchronous slice admission control, and proves it to be Markovian under a set of weak constraints. An analytical approximation of the state transition matrix to reduce computational complexity in practical applications is also proposed and evaluated.

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