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Mobile Networks

Project Overview

Here you will find a number of projects we have realized in the fields of Mobile Networks. Use the ‘+’-sign to see additional information.

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Start date: 01.01.2019

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Funded by: Research contract

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Local head of project:? Tobias Foth

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Local scientists:

Prof. Dr. Bernhard Bauer

Andrea Fendt

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External scientists / cooperations:

Dr.-Ing. Henning Sanneck (Nokia Bell Labs)

Dr. Jürgen Goerge (Nokia Bell Labs)

Dr. Christian Mannweiler (Nokia Bell Labs)

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Abstract

Mobile networks are exposed to numerous uninfluenceable external factors particularly in the domain of radio access networks.
Flexible and extensive configuration options are therefore necessary.
Oftentimes, abstraction layers are used in order to master the resulting complexity and e.g. to abstract business goals in a logical way from technical configurations.

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Model-based techniques will be used as part of this project to define and evaluate transformations between multiple abstraction layers.
Furthermore, these techniques are to be used to automate network management tasks and consequently reduce the expenses caused by adjustments between technical configurations and abstract goals.

Start date: 01.04.2017

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Funded by: Research contract

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Local head of project: Andrea Fendt

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Local scientists: Prof. Dr. Bernhard Bauer

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External scientists / cooperations:

Dr.-Ing. Henning Sanneck (Nokia Bell Labs)

Dipl.-Ing. Lars Christoph Schmelz (Nokia Bell Labs)

Dr. Christian Mannweiler (Nokia Bell Labs)

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Abstract

Modern mobile networks are evolving towards constantly connected devices. Not only the number of connected devices and their mobile data traffic are expected to grow by 10 times between 2016 and 2022, but also new use cases will arise such as industrial and sensor networks introducing massive Machine Type Communication (mMTC). In addition to the conventional enhanced Mobile Broadband (eMBB) use cases, Ultra-Reliable and Low Latency Communication (URLLC), e.g. for car-to-x communication, as well as large sensor and Internet of Things (IoT) networks will introduce very diverse requirements on the mobile networks of the fifth generation.

Network slicing is seen as one of the key enablers to cope with those divergent requirements in existing physical networks. Network slices are virtual networks providing isolated end-to-end connections, as specified in associated Service Level Agreements (SLAs), on a shared physical network infrastructure.

In this project, an end-to-end network slice resource allocation process will be developed. The process shall allow to give fast feedback on the feasibility of embedding new network slices. A mixed wired and wireless end-to-end network slice embedding algorithm will be developed. This algorithm will also account for fluctuations and uncertainties in the availability of mobile and core network resources.

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Start date: 01.01.2007

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Funded by: Research contract

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Local head of project: Simon Lohmüller

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Local scientists:

Prof. Dr. Bernhard Bauer

Christoph Frenzel

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External scientists / cooperations:

Dr.-Ing. Henning Sanneck (Nokia)

Dipl.-Ing. Lars Christoph Schmelz (Nokia)

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Abstract

Mobile communication is based on highly complex network architectures requiring frequent (re)configurations of network elements. In this project a concept is developed for reducing management complexity and raising the degree of automation in mobile networks. For this purpose, policy-based techniques are applied, which enable the management system to take decisions autonomically by correlating events, conditions, and actions. Thus, human knowledge is encapsulated in a machine-executable way, thereby reducing the amount of work and time to be spent by human operators for operation, administration and maintenance of the network.

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Donwload Projektposter

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Nokia Website

Start date: 01.01.2014

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Funded by: Universit?t Augsburg

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Local head of project: Christoph Frenzel

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Abstract

Mobile communications are an integral part of modern society. People want to talk to their friends, play on-line games, or watch YouTube videos while they are on the go. This forces Mobile Network Operators (MNOs) to continuously upgrade and extend their mobile networks in order to keep up with the ever growing data rate requirements and provide the users with satisfactory Quality of Service (QoS). However, user are not willing to pay more for mobile communications leading to a decrease in the price per data unit. Due to this development, MNOs are faced with a serious pressure to reduce their Operational Expenditure (OPEX). The focus, thereby, lies on the reduction of manual efforts in network operations, i.e., the configuration and control of the Base Stations (BSs) such that the operational objectives by the MNO, defined as target values for network Key Performance Indicators (KPIs), are satisfied.

Self-Organizing Network (SON) is a concept for automating the operation of mobile networks by relieving human operators from repetitive, low-level network operations tasks. In principle, a SON consists of a set of close-loop control functions, referred to as SON functions, which perform specific operations tasks. For instance, Coverage and Capacity Optimization (CCO) improves the network capacity and Mobility Robustness Optimization (MRO) optimizes the handover performance. The introduction of SON lifts the work of human operators from network operations to SON operations: instead of analyzing and configuring all the BSs in the network, the operational personnel has to configure and control the SON functions in order to adapt them to the network environment and specific operational objectives. This is due to the gap between the objectives and the low-level, technical configuration interface of the SON functions. As a result, MNOs ask for a further increase in the level of automation.

This project aims to develop the Objective-Driven SON Operations (ODSO) concept that enables autonomic mobile network operations, i.e., the control of network operations through operational objectives on network KPIs. ODSO is built on top of SON and automates three manual tasks of SON operations: SON management that configures the SON functions, SON coordination that detects and resolves run-time conflicts between the concurrently running SON functions, and SON self-healing that detects and resolves failures in the network and the SON system.

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Infochemical-based Coordination / Runtime Efficiency Improvement of Self-organizing Emergent Systems

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Start date:?01.04.2008

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Funded by: Universit?t Augsburg

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Local head of project: Dipl.-Inf. Holger Kasinger

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Local scientists: Prof. Dr. Bernhard Bauer

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External scientists / cooperations:???????? Prof. Dr. J?rg Denzinger (University of Calgary)

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Abstract

CHEMICO:

Current computer systems consist of heterogeneous hard- and software elements with nebulous communication structures arranged in arcane system architectures. The administration of these complex systems by humans already today is time-consuming and error-prone, causing increasingly high operational expenditues for companies. The predicated characterisitcs of future systems, such as vast quantities of distributed system elements, context-awareness, openness, and locality, furthermore enhance the management complexity. Thus, the objectives of the CHEMICO (Infochemical-based?Coordination) project are to reduce the management complexity and costs by designing distributed systems with a high degree of autonomy, in which system elements organize their actions and interactions themselves by utilizing emergent effects. The essential key thereby is the capability of effective but efficient decentralized coordination. Therefore, in this project we investigate the general principles behind infochemical coordination, which is the most universally employed coordination model in nature with a plethora of inspiring examples, and adapt them for the design of coordination mechanisms for self-organizing emergent systems.

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REINS:

Self-organizing emergent systems are known for their scalability, robustness, flexibility, and adaptivity rather than their efficiency, optimality, and predictability. However, several (mainly industrial) settings require guarantees for a certain degree of performance respectively efficiency in varying situations. But due to the non-deterministic and open nature of these systems the efficiency can not be guaranteed without further ado, in particular not in priorly unexpected situations. Thus, the objective of the REINS (Runtime?Efficiency?Improvement of?Self-organizing Emergent Systems) project is to facilitate the improvement of the systems' efficiency at runtime by implementing a feedback control loop that takes into account the low observeability and poor controllability of the systems, preserves their basic self-organizing emergent behavior, and considers their opennes and autonomy. In this project, we therefore develop the concept of an advisor as dedicated system element performing the control loop. Instead of controlling the system rigidly, this element only provides advice to the system elements, how they can perform better in certain future situations, so that every problem solving decision is still locally made by each system element itself.

Start date: 01.01.2008

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Funded by: Universit?t Augsburg

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Local head of project: Dr. Raphael Romeikat

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Local scientists: Prof. Dr. Bernhard Bauer

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Abstract

Development of complex systems requires experts from different domains to collaborate with each other. Development processes usually start with specifying high-level system requirements which must be refined and implemented at lower levels. Coordination of business experts, domain experts, and technicians to align high-level system behavior and low-level implementation is a time-consuming task due to different background, vocabulary, and domain expertise. This project improves the collaboration of experts in the development process. For this purpose, an approach to system development is developed that is based on policy-based and model-driven techniques. System behavior is first modeled using abstract policies on the business layer, which are then refined step-by-step across various abstraction layers down to a technical layer, where they are finally represented in a machine-executable way. During the refinement process, information modeled at a certain layer is reused at lower layers using model transformations. The application of model-driven techniques brings benefits of MDSD to the policy domain. It simplifies the policy refinement process and at the same time increases the degree of automation.

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Start date: 01.01.2002

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End date: 20.05.2005

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Funded by: Universit?t Augsburg

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Local head of project: Dr. Christian Seitz

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Local scientists: Prof. Dr. Bernhard Bauer

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Abstract

Profile-based group forming in mobile ad hoc networks represents a new field of application. The profile-based group forming corresponds to a data mining on profiles in a ad hoc enviroment. In the profile-based group forming every mobile host is equipped with user profile. As the subscribers move around similar profiles within the ad hoc network are searched and pooled to groups. As a consequence the group members are enabled to solve a problem together. We use profile-based group forming as an example in a taxi-sharing scenario. At this at highly frequented locations persons with similar destinations are searched so that they can share a taxi.

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