Der Ansatz des Konnektivismus und die rasante Verbreitung von Massive Open Online Courses (MOOCs) haben eine anhaltende Debatte um die Chancen, Schwierigkeiten und Perspektiven offener Lernnetzwerke in der Hochschulbildung ausgelöst. Die Diskussion reicht dabei vom befürchteten Verlust des Einflusses der Dozierenden als Gewährleister einer kritischen und vielseitigen Auseinandersetzung mit Themen und Lerninhalten, über die lernerseitigen Voraussetzungen für eine erfolgreiche und gewinnbringende Beteiligung an konnektivistischen Kursangeboten, bis hin zur Frage, inwiefern offenes, vernetztes Lernen im institutionell verfestigten Rahmen der Hochschule überhaupt realisiert werden kann. Verlässliche Daten über konnektivistisch ausgerichtete MOOC-Angebote (sogenannte cMOOCs) mit vorrangig studentischer Beteiligung gibt es kaum, da diese im deutschsprachigen Raum bisher vor allem in non-formalen Settings bzw. im Weiterbildungsbereich angeboten und genutzt wurden. Dieser Beitrag stellt zentrale Ergebnisse der Durchführung und Evaluation eines cMOOC mit hauptsächlich studentischen Teilnehmenden vor, der im Sommersemester 2013 und Wintersemester 2013/14 in Kooperation zwischen drei deutschen Universitäten (Dresden, Chemnitz, Siegen) durchgeführt wurde. Der Fokus liegt auf der Frage, in welchem Ausmaß offenes, vernetztes Lernen im Rahmen eines Hochschulkurses ermöglicht werden kann und Lernergebnisse sich identifizieren lassen. Hierzu erfolgt eine Kombination quantitativer und qualitativer Evaluationsdaten.

abstract: The recent increase in users of cellular networks necessitates the use of new technologies to meet this demand. Massive multiple input multiple output (MIMO) communication systems have great potential for increasing the network capacity of the emerging 5G+ cellular networks. However, leveraging the multiplexing and beamforming gains from these large-scale MIMO systems requires the channel knowlege between each antenna and each user. Obtaining channel information on such a massive scale is not feasible with the current technology available due to the complexity of such large systems. Recent research shows that deep learning methods can lead to interesting gains for massive MIMO systems by mapping the channel information from the uplink frequency band to the channel information for the downlink frequency band as well as between antennas at nearby locations. This thesis presents the research to develop a deep learning based channel mapping proof-of-concept prototype. Due to deep neural networks' need of large training sets for accurate performance, this thesis outlines the design and implementation of an autonomous channel measurement system to analyze the performance of the proposed deep learning based channel mapping concept. This system obtains channel magnitude measurements from eight antennas autonomously using a mobile robot carrying a transmitter which receives wireless commands from the central computer connected to the static receiver system. The developed autonomous channel measurement system is capable of obtaining accurate and repeatable channel magnitude measurements. It is shown that the proposed deep learning based channel mapping system accurately predicts channel information containing few multi-path effects. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2020

Multiple-input-multiple-output (MIMO) systems of current LTE releases are capable of adaptation in the azimuth only. More recently, the trend is to enhance the system performance by exploiting the channel's degrees of freedom in the elevation through the dynamic adaptation of the vertical antenna beam pattern. This necessitates the derivation and characterization of three-dimensional (3D) channels. Over the years, channel models have evolved to address the challenges of wireless communication technologies. In parallel to theoretical studies on channel modeling, many standardized channel models like COST-based models, 3GPP SCM, WINNER, ITU have emerged that act as references for industries and telecommunication companies to assess system-level and link-level performances of advanced signal processing techniques over real-like channels. Given the existing channels are only two dimensional (2D) in nature; a large effort in channel modeling is needed to study the impact of the channel component in the elevation direction. The first part of this work sheds light on the current 3GPP activity around 3D channel modeling and beamforming, an aspect that to our knowledge has not been extensively covered by a research publication. The standardized MIMO channel model is presented, that incorporates both the propagation effects of the environment and the radio effects of the antennas. In order to facilitate future studies on the use of 3D beamforming, the main features of the proposed 3D channel model are discussed. A brief overview of the future 3GPP 3D channel model being outlined for the next generation of wireless networks is also provided. In the subsequent part of this work, we present an information-theoretic channel model for MIMO systems that supports the elevation dimension. The model is based on the principle of maximum entropy, which enables us to determine the distribution of the channel matrix consistent with the prior information on the angles of departure and angles of arrival of the propagation paths. Based on this model, an analytical expression for the cumulative density function (CDF) of the mutual information (MI) for systems with a single receive and finite number of transmit antennas in the general signal-to-interference-plus-noise-ratio (SINR) regime is provided. The result is extended to systems with multiple receive antennas in the low SINR regime. A Gaussian approximation to the asymptotic behavior of the MI distribution is derived for the large number of transmit antennas and paths regime. Simulation results study the performance gains realizable through meticulous selection of the transmit antenna down tilt angles, confirming the potential of elevation beamforming to enhance system performance. The results validate the proposed analytical expressions and elucidate the dependence of system performance on azimuth and elevation angular spreads and antenna patterns. We believe that the derived expressions will help evaluate the performance of 3D 5G massive MIMO systems in the future.

Massive MIMO systems are shown to be a promising technology for next generations of wireless communication networks. The realization of the attractive merits promised by massive MIMO systems requires advanced linear precoding and receiving techniques in order to mitigate the interference in downlink and uplink transmissions. This work considers the precoder and receiver design in massive MIMO systems. We first consider the design of the linear precoder and receiver that maximize the minimum signal-to-interference-plus-noise ratio (SINR) subject to a given power constraint. The analysis is carried out under the asymptotic regime in which the number of the BS antennas and that of the users grow large with a bounded ratio. This allows us to leverage tools from random matrix theory in order to approximate the parameters of the optimal linear precoder and receiver by their deterministic approximations. Such a result is of valuable practical interest, as it provides a handier way to implement the optimal precoder and receiver. To reduce further the complexity, we propose to apply the truncated polynomial expansion (TPE) concept on a per-user basis to approximate the inverse of large matrices that appear on the expressions of 4 the optimal linear transceivers. Using tools from random matrix theory, we determine deterministic approximations of the SINR and the transmit power in the asymptotic regime. Then, the optimal per-user weight coefficients that solve the max-min SINR problem are derived. The simulation results show that the proposed precoder and receiver provide very close to optimal performance while reducing significantly the computational complexity. As a second part of this work, the TPE technique in a per-user basis is applied to the optimal linear precoding that minimizes the transmit power while satisfying a set of target SINR constraints. Due to the emerging research field of green cellular networks, such a problem is receiving increasing interest nowadays. Closed form expressions of the optimal parameters of the proposed low complexity precoding for power minimization are derived. Numerical results show that the proposed power minimization precoding approximates well the performance of the optimal linear precoding while being more practical for implementation.

Full dimension (FD) multiple-input multiple-output (MIMO) technology has recently attracted substantial research attention in the 3rd Generation Partnership Project (3GPP) as a promising technique for the next-generation of wireless communication networks. FD-MIMO scenarios utilize a planar two-dimensional (2D) active antenna system (AAS) that not only allows a large number of antenna elements to be placed within feasible base station (BS) form factors, but also provides the ability of elevation beamforming. This dissertation presents the elevation beamforming analysis for cellular networks utilizing FD massive MIMO antenna arrays. In particular, two architectures are proposed for the AAS - the uniform linear array (ULA) and the uniform circular array (UCA) of antenna ports, where each port is mapped to a group of vertically arranged antenna elements with a corresponding downtilt weight vector. To support FD-MIMO techniques, this dissertation presents two different 3D ray-tracing channel modeling approaches, the ITU based ‘antenna port approach’ and the 3GPP technical report (TR) 36.873 based ‘antenna element approach’. The spatial correlation functions (SCF)s for both FD-MIMO arrays are characterized based on the antenna port approach. The resulting expressions depend on the underlying angular distributions and antenna patterns through the Fourier series coefficients of the power spectra and are therefore valid for any 3D propagation environment. Simulation results investigate the performance patterns of the two arrays as a function of several channel and array parameters. The SCF for the ULA of antenna ports is then characterized in terms of the downtilt weight vectors, based on the more recent antenna element approach. The derived SCFs are used to form the Rayleigh correlated 3D channel model. All these aspects are put together to provide a mathematical framework for the design of elevation beamforming schemes in single-cell and multi-cell scenarios. Finally, this dissertation proposes to use the double scattering channel to model limited scattering in realistic propagation environments and derives deterministic equivalents of the signal-to-interference-plus-noise ratio (SINR) and ergodic rate with regularized zeroforcing (RZF) precoding. The performance of a massive MIMO system is shown to be limited by the number of scatterers. To this end, this dissertation points out future research directions

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第21557号 / 理博第4464号 / 新制||理||1641(附属図書館) / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)教授 柴田 大, 教授 田中 貴浩, 教授 井岡 邦仁 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第21565号 / 理博第4472号 / 新制||理||1642(附属図書館) / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)准教授 細川 隆史, 教授 田中 貴浩, 教授 井岡 邦仁 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

京都大学 / 0048 / 新制・課程博士 / 博士(教育学) / 甲第21987号 / 教博第240号 / 新制||教||186(附属図書館) / 京都大学大学院教育学研究科教育科学専攻 / (主査)教授 飯吉 透, 教授 楠見 孝, 准教授 酒井 博之 / 学位規則第4条第1項該当 / Doctor of Philosophy (Education) / Kyoto University / DGAM

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第22423号 / 工博第4684号 / 新制||工||1731(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 小池 克明, 教授 三ｹ田 均, 准教授 柏谷 公希, 教授 後藤 忠徳 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

京都大学 / 新制・課程博士 / 博士(工学) / 甲第23175号 / 工博第4819号 / 新制||工||1753(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 小池 克明, 教授 林 為人, 准教授 柏谷 公希 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM