Optimization of Spectrum Management in Massive Array Antenna Systems with MIMO

Fifth generation (5G), is being considered as a revolutionary technology in the telecommunication domain whose the challenges are mainly to achieve signal quality and great ability to work with free spectrum in the millimetre waves. Besides, other important innovations are the introduction of a more current architecture and the use of multiple antennas in transmission and reception. Digital communication using multiple input and multiple output (MIMO) wireless links has recently emerged as one of the most significant technical advances in modern communications. MIMO technology is able to offer a large increase in the capacity of these systems, without requiring a considerable increase in bandwidth or power required for transmission. This dissertation presents an overview of theoretical concepts of MIMO systems. With such a system a spatial diversity gain can be obtained by using space-time codes, which simultaneously exploit the spatial domain and the time domain. SISO, SIMO and MISO systems are differentiated by their channel capacity and their configuration in relation to the number of antennas in the transmitter/receiver. To verify the effectiveness of the MIMO systems a comparison between the capacity of SISO and MIMO systems has been performed using the Shannon’s principles. In the MIMO system some variations in the number of antennas arrays have been considered, and the superiority of transmission gains of the MIMO systems have been demonstrated. Combined with millimetre waves (mmWaves) technology, massive MIMO systems, where the number of antennas in the base station and the number of users are large, is a promising solution. SDR implementations have been performed considering a platform with Matlab code applied to MIMO 2x2 Radio and Universal Software Peripheral Radio (USRP). A detailed study was initially conducted to analyze the architecture of the USRP. Complex structures of MIMO systems can be simplified by using mathematical methods implemented in Matlab for the synchronization of the USRP in the receiver side. SISO transmission and reception techniques have been considered to refine the synchronization (with 16-QAM), thus facilitating the future implementation of the MIMO system. OpenAirInterface has been considered for 4G and 5G implementations of actual mobile radio communication systems. Together with the practical MIMO, this type of solution is the starting point for future hardware building blocks involving massive MIMO systems.A quinta geração (5G) está sendo considerada uma tecnologia revolucionária no setor de telecomunicações, cujos desafios são principalmente a obtenção de qualidade de sinal e grande capacidade de trabalhar com espectro livre nas ondas milimétricas. Além disso, outras inovações importantes são a introdução de uma arquitetura mais atual e o uso de múltiplas antenas em transmissão e recepção. A comunicação digital usando ligaçõe sem fio de múltiplas entradas e múltiplas saídas (MIMO) emergiu recentemente como um dos avanços técnicos mais significativos nas comunicações modernas. A tecnologia MIMO é capaz de oferecer um elevado aumento na capacidade, sem exigir um aumento considerável na largura de banda ou potência transmitida. Esta dissertação apresenta uma visão geral dos conceitos teóricos dos sistemas MIMO. Com esses sistemas, um ganho de diversidade espacial pode ser obtido utilizando códigos espaço-tempo reais. Os sistemas SISO, SIMO e MISO são diferenciados pela capacidade de seus canais e a sua configuração em relação ao número de antenas no emissor/receptor. Para verificar a eficiência dos sistemas MIMO, realizou-se uma comparação entre a capacidade dos sistemas SISO e MIMO utilizado os princípios de Shannon. Nos sistemas MIMO condecideraram-se algumas variações no número de agregados de antenas, e a superioridade dos ganhos de transmissão dos sistemas MIMO foi demonstrada. Combinado com a tecnologia de ondas milimétricas (mmWaves), os sistemas massivos MIMO, onde o número de antenas na estação base e o número de usuários são grandes, são uma solução promissora. As implementações do SDR foram realizadas considerando uma plataforma com código Matlab aplicado aos rádios MIMO 2x2 e Universal Software Peripheral Radio (USRP). Um estudo detalhado foi inicialmente conduzido para analisar a arquitetura da USRP. Estruturas complexas de sistemas MIMO podem ser simplificadas usando métodos matemáticos implementados no Matlab para a sincronização do USRP no lado do receptor. Consideraram-se técnicas de transmissão e recepção SISO para refinar a sincronização (com 16-QAM), facilitando assim a implementação futura do sistema MIMO . Considerou-se o OpenAirInterface para implementações 4G e 5G de sistemas reais de comunicações móveis. Juntamente com o MIMO na pratica, este tipo de solução é o ponto de partida para futuros blocos de construção de hardware envolvendo sistemas MIMO massivos

Wireless Channel Modeling and Reconstruction in Massive MIMO Systems

The past few years have witnessed dramatic growth in the number of wirelessly connected devices, which will continue to increase in the future. Following this trend, the capacity of the wireless networks has been enhanced to provide high-quality service to tens of billions of devices. At the same time, in response to the network enhancement, each device unashamedly requests more and more throughput to support high-data-consuming applications such as video calls, high-definition video streaming, and online multiplayer video games. This undoubtedly indicates that the demand for high wireless throughput and numerous new connections will keep increasing in the near future. In addition, the development of new technologies such as virtual/augmented reality, self-driving cars, remote surgery, and other latency-critical applications has caused concern regarding the network response latency. Thus, next-generation wireless networks have to satisfy three main requirements: i) high throughput; ii) simultaneous service to many users; and iii) low latency. Massive multiple-input multiple-output (MIMO) technology, where a base station (BS) equipped with a large antenna array is capable of serving many users simultaneously in the same time-frequency domain, has been developed to mitigate these requirements except the last. However, massive MIMO technology has to overcome the challenges related to the channel estimation (CE) overhead, which inevitably increases the communication latency, to become the absolute leader in the list of promising technologies for next-generation wireless communication. This dissertation focuses on developing solutions that are aimed to mitigate massive MIMO CE challenges. The dissertation consists of three main parts: massive MIMO channel modeling, user localization in massive MIMO networks, and full downlink channel reconstruction. The first part (Chapter 3) discusses an approach for modeling spatially consistent channels in massive MIMO networks. The main focus is put on describing specular reflections of wireless signals from arbitrarily inclined surfaces by taking into account the signals' polarizations and the spatial distributions of massive MIMO antennas. The proposed approach has been validated through simulating signal transmissions in a realistic environment model based on Google Maps. Results show the importance of incorporating a spherical wave propagation model and the consideration of detailed 3D characteristics of the surroundings in the simulation of massive MIMO channels. The second part (Chapter 4) introduces a solution for localizing users in massive MIMO networks. The main focus is on designing algorithms that are capable of estimating the positions of users using only uplink signals by exploring the advantages of the spherical wave propagation model proposed in the first section. The designed localization schemes have been evaluated through both simulation and proof-of-concept experiments. Simulation results show that the schemes can achieve decimeter-level localization accuracy using 64 and more antenna elements for distances up to 300 meters. The proof-of-concept experiment justifies the feasibility of user localization based on the estimation of the spherical shape of the incoming wavefront. The third part (Chapter 5) investigates the problem of reconstructing the full downlink channel from incomplete uplink channel measurements in massive MIMO systems. This problem arises in the next-generation networks, where connected devices have multiple transmitting and non-transmitting antennas. To achieve high throughput, channels for non-transmitting antennas have to be reconstructed. This section presents ARDI, a scheme that builds a bridge between the radio channel and physical signal propagation environment to link spatial information about the non-transmitting antennas with their radio channels. By inferring locations and orientations of the non-transmitting antennas from an incomplete set of uplink channels, ARDI can reconstruct the downlink channels for non-transmitting antennas. The performance evaluation results demonstrate that ARDI is capable of accurately reconstructing full downlink channels when the signal-to-noise ratio is higher than 15dB, thereby expanding the channel capacity of massive MIMO networks

Radio Resource Management Optimization For Next Generation Wireless Networks

The prominent versatility of today’s mobile broadband services and the rapid advancements in the cellular phones industry have led to a tremendous expansion in the wireless market volume. Despite the continuous progress in the radio-access technologies to cope with that expansion, many challenges still remain that need to be addressed by both the research and industrial sectors. One of the many remaining challenges is the efficient allocation and management of wireless network resources when using the latest cellular radio technologies (e.g., 4G). The importance of the problem stems from the scarcity of the wireless spectral resources, the large number of users sharing these resources, the dynamic behavior of generated traffic, and the stochastic nature of wireless channels. These limitations are further tightened as the provider’s commitment to high quality-of-service (QoS) levels especially data rate, delay and delay jitter besides the system’s spectral and energy efficiencies. In this dissertation, we strive to solve this problem by presenting novel cross-layer resource allocation schemes to address the efficient utilization of available resources versus QoS challenges using various optimization techniques. The main objective of this dissertation is to propose a new predictive resource allocation methodology using an agile ray tracing (RT) channel prediction approach. It is divided into two parts. The first part deals with the theoretical and implementational aspects of the ray tracing prediction model, and its validation. In the second part, a novel RT-based scheduling system within the evolving cloud radio access network (C-RAN) architecture is proposed. The impact of the proposed model on addressing the long term evolution (LTE) network limitations is then rigorously investigated in the form of optimization problems. The main contributions of this dissertation encompass the design of several heuristic solutions based on our novel RT-based scheduling model, developed to meet the aforementioned objectives while considering the co-existing limitations in the context of LTE networks. Both analytical and numerical methods are used within this thesis framework. Theoretical results are validated with numerical simulations. The obtained results demonstrate the effectiveness of our proposed solutions to meet the objectives subject to limitations and constraints compared to other published works

Physical Layer Techniques for High Frequency Wireline Broadband Systems

This thesis collects contributions to wireline and wireless communication systems with an emphasis on multiuser and multicarrier physical layer technology. To deliver increased capacity, modern wireline access systems such as G.fast extend the signal bandwidth up from tens to hundreds of MHz. This ambitious development revealed a number of unforeseen hurdles such as the impact of impedance changes in various forms. Impedance changes have a strong effect on the performance of multi-user crosstalk mitigation techniques such as vectoring. The first part of the thesis presents papers covering the identification of one of these problems, a model describing why it occurs and a method to mitigate its effects, improving line stability for G.fast systems.A second part of the thesis deals with the effects of temperature changes on wireline channels. When a vectored (MIMO) wireline system is initialized, channel estimates need to be obtained. This thesis presents contributions on the feasibility of re-using channel coefficients to speed up the vectoring startup procedures, even after the correct coefficients have changed, e.g., due to temperature changes. We also present extensive measurement results showing the effects of temperature changes on copper channels using a temperature chamber and British cables. The last part of the thesis presents three papers on the convergence of physical layer technologies, more specifically the deployment of OFDM-based radio systems using twisted pairs in different ways. In one proposed scenario, the idea of using the access copper lines to deploy small cells inside users' homes is explored. The feasibility of the concept, the design of radio-heads and a practical scheme for crosstalk mitigation are presented in three contributions

Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools

This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen