Adaptive Admission Control in Interference-Coupled Wireless Data Networks: A Planning and Optimization Tool Set

Abstract-Typically, wireless network performance decreases in high traf c regimes, e. g., at traf c hot spots and peak hours, since a large number of active users have to share limited radio resources. From a network perspective, even congestion may occur in some cells, which may lead to drastic deterioration of user throughputs. As a consequence, network operators employ admission control in their base stations in order to prevent congestion and enhance quality of experience. In this paper, we develop an effective network planning and optimization tool set, which considers the dynamic behavior of mobile traf c. The tool set allows for a more accurate prediction of data request blocking probabilities and data throughputs under admission control, since it explicitly considers the inter-cell interference coupled nature of frequency reuse one networks. This enables more reliable planning and (self-) optimization of wireless networks. We prove utility by applying the tool set to a traf c-adaptive admission control scheme and compare the resulting network performance with that of static admission control schemes under demands of high mobile data traf c. We nd that the adaptive algorithm is able to exploit the trade-offs between blocking of requests, reduced interference, and guaranteed resources for individual data transmissions in each of the cells. Under high traf c conditions, it yields better performance compared to any other static scheme investigated

Reference Network and Localization Architecture for Smart Manufacturing based on 5G

5G promises to shift Industry 4.0 to the next level by allowing flexible production. However, many communication standards are used throughout a production site, which will stay so in the foreseeable future. Furthermore, localization of assets will be equally valuable in order to get to a higher level of automation. This paper proposes a reference architecture for a convergent localization and communication network for smart manufacturing that combines 5G with other existing technologies and focuses on high-mix low-volume application, in particular at small and medium-sized enterprises. The architecture is derived from a set of functional requirements, and we describe different views on this architecture to show how the requirements can be fulfilled. It connects private and public mobile networks with local networking technologies to achieve a flexible setup addressing many industrial use cases.Comment: 10 pages; submitted to 6th International Conference on System-Integrated Intelligence. Intelligent, flexible and connected systems in products and production, 7-9 September Genova, Ital

Optimal UAV Base Station Trajectories Using Flow-Level Models for Reinforcement Learning

Cellular base stations (BS) and remote radio heads can be mounted on unmanned aerial vehicles (UAV) for flexible, traffic-aware deployment. These UAV base station networks (UAVBSN) promise an unprecendented degree of freedom that can be exploited for spectral efficiency gains as well as optimal network utilization. However, the current literature lacks realistic radio and traffic models for UAVBSN deployment planning and for performance evaluation. In this paper, we propose flow-level models (FLM) for realistically characterizing the UAVBSN performance in terms of a broad range of flow- and system-level metrics. Further, we propose a deep reinforcement learning (DRL) approach that relies on the UAVBSN FLM for learning the optimal traffic-aware UAV trajectories. For a given user traffic density and starting UAV locations, our RL approach learns the optimal UAV trajectories offline that maximizes a cumulative performance metric. We then execute the learned UAV trajectories in a discrete event simulator to evaluate online UAVBSN performance. For M = 9 UAVs deployed in a simulated Downtown San Francisco model, where the UAV trajectories are defined by N = 20 discrete actions, our approach achieves approximately a three-fold increase in the average user throughput compared to the initial UAV placement, while simultaneously balancing traffic loads across the BSs.QC 20200122</p

Joint Bandwidth Allocation and Small Cell Switching in Heterogeneous Networks

Abstract-One major topic of research into self-organizing network technology is the coordination of SON use cases. Network operators expect a coordinated handling of the parameter and configuration changes submitted to the operating network by closed-loop SON use case implementations. There are currently two basic approaches for SON use case coordination discussed in the literature: A so-called heading or tailing use case external coordination and the combination of separate use cases into one joint algorithm. In this paper, we extend a verified framework to combine mobility load balancing and inter-cell interference coordination use cases, especially for a heterogeneous network environment. Our approach results in a coordinated set of cell range expansion offsets, an efficient bandwidth allocation to support the (enhanced) inter-cell interference coordination use case, and an energy-efficient smart cell switching of the small capacity cells in a heterogeneous networks environment for a varying traffic demand during the course of a day, resulting in significant capacity enhancements while saving energy at the same time

Requirements and current solutions of wireless communication in industrial automation

The industrial wireless automation sector exhibitsa huge market growth in the last years. Today, many applicationsalready use wireless technologies. However, the existingwireless solutions do not yet offer sufficient performance withrespect to real-time and reliability requirements, particularlyfor closed-loop control applications. As a result, low latencywireless communication technologies will bridge the gap andcan become a key factor for the wide-spread penetration ofwireless in industrial communication systems. It is therefore themain goal of this paper to provide a comprehensive overviewon requirements, current solutions, and challenges as well asopportunities for future wireless industrial systems. Thereby,presented requirement figures, analysis results, and performanceevaluations are based on numerous practical examples fromindustry

Arabidopsis MAP kinase 4 negatively regulates systemic acquired resistance

Transposon inactivation of Arabidopsis MAP kinase 4 produced the mpk4 mutant exhibiting constitutive systemic acquired resistance (SAR) including elevated salicylic acid (SA) revels, increased resistance to virulent pathogens, and constitutive pathogenesis-related gene expression shown by Northern and microarray hybridizations. MPK4 kinase activity is required to repress SAR, as an inactive MPK4 form failed to complement mpk4. Analysis of mpk4 expressing the SA hydroxylase NahG and of mpk4/npr1 double mutants indicated that SAR expression in mpk4 is dependent upon elevated SA levels but is independent of NPR1. PDF1.2 and THI2.1 gene induction by jasmonate was blocked in mpk4 expressing NahG, suggesting that MPK4 is required for jasmonic acid-responsive gene expression