10 research outputs found

    Multiuser Optimal Transmit Beamforming: Performance Studies, Antennas Selection, A Genetic Algorithm Approach

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    RÉSUMÉ La formation de faisceaux est une technique très prometteuse utilisant un grand nombre d'antennes pour transmettre un signal vers un ou plusieurs utilisateurs. L'objectif est d'augmenter la puissance du signal chez l'utilisateur souhaité et de réduire la puissance d'interférence chez les utilisateurs non visés. Étant donné que la transmission de la formation de faisceaux augmente la puissance dans une direction spécifique, cela permet à un accès multiple par division spatiale de servir plusieurs utilisateurs simultanément. Cependant, le problème est de garder un équilibre entre maximiser la puissance du signal et minimiser la puissance d'interférence dans les systèmes multi-utilisateurs. Cette thèse décrit une structure simple qui fournit une base théorique pour un système de formation de faisceau optimal. Dans cette thèse, nous étudions les propriétés des systèmes linéaires et optimaux dans différents scénarios, tels que les rapports des signaux faibles et élevés au bruit, des nombres multiple d'antennes, le canal à évanouissement de Rayleigh et les retards multiples. Nous analysons les scénarios lorsque la formation de faisceaux linéaires fonctionnent comme une formation de faisceau optimale. Ensuite, nous proposons une méthode simple pour sélectionner le nombre minimum d'antennes suffisantes pour satisfaire aux exigences de qualité de service des utilisateurs. Lorsque le nombre d’antennes à la station de base est très grand, il ne sera peut-être pas nécessaire d’utiliser toutes les antennes pour desservir seulement quelques utilisateurs. Cette situation incite à choisir un nombre d’antennes limité. Cependant, le nombre choisi peut ne pas suffire à satisfaire les exigences de qualité de service des utilisateurs en raison de fortes interférences, de conditions de canal et du nombre d'utilisateurs. Pour résoudre ce problème NP-difficile, il faut faire une recherche exhaustive ou une recherche heuristique des méthodes itératives avec un coût de complexité informatique acceptable. Ainsi, nous proposons un cadre simple pour sélectionner un ensemble d'antennes suffisantes pour satisfaire les besoins de l'utilisateur. Enfin, nous proposons un algorithme génétique pour une formation de faisceaux optimale avec une complexité d'implémentation faible. Considérant l'algorithme de réduction de branche comme une référence, nous comparons la performance de l'algorithme proposé dans différents scénarios.---------- ABSTRACT Transmit beamforming is a very promising technique to transmit the signal from a large array of antennas to one or multiple users. The goal is to increase the signal power at the desired user and reduce the interference power at the non-intended users. Since transmit beamforming increases the power to a specific direction, it allows for space division multiple access to serve multiple users simultaneously. However, the problem is to keep the balance between maximizing the signal power and minimizing the interference power in multi-user systems. This thesis describes a simple structure that provides a theoretical foundation for optimal beamforming scheme. In this thesis, we study the properties of linear and optimal beamforming schemes in different scenarios such as low to high signal to noise ratio ranges, multiple number of antennas, simple Rayleigh fading channel, Rayleigh fading channel with Doppler effects. We analyze the scenarios when linear beamforming performs as an optimal beamforming. Next, we propose a simple method to select the minimum number of antennas that is enough to satisfy the quality of service requirements of the users. In case of massive number of antennas at base station, it may not be necessary to use all antennas to serve only few users. That situation motivates the selection of a set of limited number of antennas. However, the number of chosen antennas may not be enough to satisfy the quality of service requirements of the users due to strong interference, channel conditions and number of users. To solve this NP-hard problem, it requires an exhaustive search or heuristic search, iterative methods with a cost of computational complexity. Thus, we propose a simple framework to select a set of antennas that is enough to satisfy the user’s requirements. Finally, we propose a genetic algorithm for optimal beamforming with low implementation complexity. Considering the branch reduce and bound algorithm as a benchmark, we compare the performance of the proposed algorithm in different scenarios

    Alocação de recursos para sistemas móveis multi-utilizador e multi-antena

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    Doutoramento em Engenharia ElectrotécnicaThe thesis addresses the sum rate or spectral e ciency maximization problem in cellular systems with two main components, multiple antennas and multiple users. In order to solve such a problem, several resource allocation techniques are studied and developed for di erent cellular scenarios. The antennas at the transmitters are arranged in several con gurations, i.e., co-located or distributed and for such arrangements di erent levels of coordination and cooperation between transmitters are investigated. Accounting for more receiver antennas than transmitter antennas implies that system optimization must select the best transmitter-receiver match (combinatorial problem) which can be solved with di erent degrees of cooperation between transmitters. The system models studied can be classi ed either as interference limited or as power limited systems. In interference limited systems the resource allocation is carried out independently by each transmitter which yield power leakage to unintended receivers. For this kind of systems, the access network using distributed antenna architectures is examined. The properties of distributed antenna in cellular systems as well as the gains they provide in terms of frequency reuse and throughput are assessed. Accounting for multiple user scenarios, several techniques and algorithms for transmitter-receiver assignment, power allocation, and rate allocation are developed in order to maximize the spectral e ciency. In power limited systems the transmitters jointly allocate resources among transmit and receive antennas. The transmitters are equipped with multiple antennas and signal processing is implemented in order to suppress inter-user interference. Single-cell and multi-cell systems are studied and the problem of sum rate maximization is tackled by decoupling the user selection and the resource allocation (power and precoding) processes. The user selection is a function of the type of precoding technique that is implemented and the level of information that can be processed at the transmitter. The developed user selection algorithms exploit information provided by novel channel metrics which establish the spatial compatibility between users. Each metric provides a di erent trade-o between the accuracy to identify compatible users, and the complexity required to compute it. Numerical simulations are used to assess the performance of the proposed user selection techniques (metrics and algorithms) whose performance are compared to state-of-the-art techniques.Esta tese descreve o problema da maximização da taxa de transmissão ou e ciência espectral em sistemas moveis tomando em atenção duas características fundamentais destes, o número de antenas e utilizadores. A fim de resolver este tipo de problema, várias técnicas de alocação de recursos foram estudadas e propostas para diferentes cenários. As antenas nos transmissores estão organizadas em diferentes configurações, podendo ser localizadas ou distribuídas e para estes esquemas, diferentes níveis de cooperação e coordenação entre transmissores foram investigados. Assumindo mais antenas receptoras do que antenas transmissoras, implica que a otimização do sistema seleccione as melhores combinações de transmissor-receptor (problema combinatório), o que pode ser concretizado usando diferentes graus de cooperação entre transmissores. Os modelos de sistemas estudados, podem ser classificados como sistemas limitados por interferência ou sistemas limitados por potência. Em sistemas limitados por interferência a alocação de recursos e feita independentemente para cada transmissor o que resulta em perda de energia para os receptores não tomados em consideração. Para este tipo de sistemas, e considerado o caso em que a rede de acesso e constituída por antenas distribuídas. Os ganhos obtidos devido ao uso de antenas distribuídas, quer em termos do planeamento de frequências quer da maximização da taxa de transmissão são considerados. Assumindo esquemas multi-utilizador, várias técnicas e algoritmos de transmissão-recepção, alocação de potência e de taxa de transmissão foram desenvolvidos para maximizar a e ciência espectral. Para sistemas limitados em potência os transmissores alocam os recursos quer de antenas de transmissão quer de recepção conjuntamente. Os transmissores estão equipados com várias antenas e o processamento de sinal e implementado de modo a eliminar a interferência entre utilizadores. Sistemas de célula única e de múltiplas células foram estudados. Para estes foi considerado o problema da maximização de taxa de transmissão o qual foi resolvido heuristicamente, através do desacoplamento do problema em duas partes, uma onde se efectua a seleção de utilizadores e outra onde se considera a alocação de recursos. A seleção de utilizadores e feita em função do tipo de técnicas de pré-codificação implementadas e do nível de informação que o transmissor possui. Os algoritmos de seleção de utilizadores desenvolvidos verificam a compatibilidade espacial entre utilizadores, usando para tal métricas propostas. Cada uma das métricas oferece um trade-off diferente entre a precisão para identificar um utilizador compatível e a complexidade necessária para a implementar. Foram usadas simulações numéricas para avaliar a performance das técnicas de seleção de utilizadores propostas (métricas e algoritmos), performance que foi comparada com as técnicas mais inovadoras

    D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies

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    This document provides the most recent updates on the technical contributions and research challenges focused in WP3. Each Technology Component (TeC) has been evaluated under possible uniform assessment framework of WP3 which is based on the simulation guidelines of WP6. The performance assessment is supported by the simulation results which are in their mature and stable state. An update on the Most Promising Technology Approaches (MPTAs) and their associated TeCs is the main focus of this document. Based on the input of all the TeCs in WP3, a consolidated view of WP3 on the role of multinode/multi-antenna transmission technologies in 5G systems has also been provided. This consolidated view is further supported in this document by the presentation of the impact of MPTAs on METIS scenarios and the addressed METIS goals.Aziz, D.; Baracca, P.; De Carvalho, E.; Fantini, R.; Rajatheva, N.; Popovski, P.; Sørensen, JH.... (2015). D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675

    Cell-Free Massive MIMO and Millimeter Wave Channel Modelling for 5G and Beyond

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    Huge demand for wireless throughput and number of users which are connected to the base station (BS) has been observed in the last decades. Massive multiple-input multiple-output (MIMO) is a promising technique for 5G for the following reasons; 1) high throughput; 2) serving large numbers of users at the same time; 3) energy efficiency. However, the low throughput of cell-edge users remains a limitation in realistic multi-cell massive MIMO systems. In cell-free massive MIMO, on the other hand, distributed access points (APs) are connected to a central processing unit (CPU) and jointly serve distributed users. This thesis investigates the performance of cell-free Massive MIMO with limited-capacity fronthaul links from the APs to the CPU which will be essential in practical 5G networks. To model the limited-capacity fronthaul links, we exploit the optimal uniform quantization. Next, closed-form expressions for spectral and energy efficiencies are presented. Numerical results investigate the performance gap between limited fronthaul and perfect fronthaul cases, and demonstrate that exploiting a relatively few quantization bits, the performance of limited-fronthaul cell-free Massive MIMO closely approaches the perfect fronthaul performance. Next, the energy efficiency maximization problem and max-min fairness problems are considered with per-user power and fronthaul capacity constraints. We propose an iterative procedure which exploits a generalized eigen vector problem and geometric programming (GP) to solve the max-min optimization problem. Numerical results indicate the superiority of the proposed algorithms over the case of equal power allocation. On the other hand, the performance of communication systems depends on the propagation channel. To investigate the performance of MIMO systems, an accurate small scale fading channel model is necessary. Geometry-based stochastic channel models (GSCMs) are mathematically tractable models to investigate the performance of MIMO systems

    A vision-based optical character recognition system for real-time identification of tractors in a port container terminal

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    Automation has been seen as a promising solution to increase the productivity of modern sea port container terminals. The potential of increase in throughput, work efficiency and reduction of labor cost have lured stick holders to strive for the introduction of automation in the overall terminal operation. A specific container handling process that is readily amenable to automation is the deployment and control of gantry cranes in the container yard of a container terminal where typical operations of truck identification, loading and unloading containers, and job management are primarily performed manually in a typical terminal. To facilitate the overall automation of the gantry crane operation, we devised an approach for the real-time identification of tractors through the recognition of the corresponding number plates that are located on top of the tractor cabin. With this crucial piece of information, remote or automated yard operations can then be performed. A machine vision-based system is introduced whereby these number plates are read and identified in real-time while the tractors are operating in the terminal. In this paper, we present the design and implementation of the system and highlight the major difficulties encountered including the recognition of character information printed on the number plates due to poor image integrity. Working solutions are proposed to address these problems which are incorporated in the overall identification system.postprin

    Job shop scheduling with artificial immune systems

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    The job shop scheduling is complex due to the dynamic environment. When the information of the jobs and machines are pre-defined and no unexpected events occur, the job shop is static. However, the real scheduling environment is always dynamic due to the constantly changing information and different uncertainties. This study discusses this complex job shop scheduling environment, and applies the AIS theory and switching strategy that changes the sequencing approach to the dispatching approach by taking into account the system status to solve this problem. AIS is a biological inspired computational paradigm that simulates the mechanisms of the biological immune system. Therefore, AIS presents appealing features of immune system that make AIS unique from other evolutionary intelligent algorithm, such as self-learning, long-lasting memory, cross reactive response, discrimination of self from non-self, fault tolerance, and strong adaptability to the environment. These features of AIS are successfully used in this study to solve the job shop scheduling problem. When the job shop environment is static, sequencing approach based on the clonal selection theory and immune network theory of AIS is applied. This approach achieves great performance, especially for small size problems in terms of computation time. The feature of long-lasting memory is demonstrated to be able to accelerate the convergence rate of the algorithm and reduce the computation time. When some unexpected events occasionally arrive at the job shop and disrupt the static environment, an extended deterministic dendritic cell algorithm (DCA) based on the DCA theory of AIS is proposed to arrange the rescheduling process to balance the efficiency and stability of the system. When the disturbances continuously occur, such as the continuous jobs arrival, the sequencing approach is changed to the dispatching approach that involves the priority dispatching rules (PDRs). The immune network theory of AIS is applied to propose an idiotypic network model of PDRs to arrange the application of various dispatching rules. The experiments show that the proposed network model presents strong adaptability to the dynamic job shop scheduling environment.postprin

    User Satisfaction Based ZFBF Scheduling Algorithm in Multi-user MIMO System

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