13 research outputs found

    Enhanced Nonlinear System Identification by Interpolating Low-Rank Tensors

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    Function approximation from input and output data is one of the most investigated problems in signal processing. This problem has been tackled with various signal processing and machine learning methods. Although tensors have a rich history upon numerous disciplines, tensor-based estimation has recently become of particular interest in system identification. In this paper we focus on the problem of adaptive nonlinear system identification solved with interpolated tensor methods. We introduce three novel approaches where we combine the existing tensor-based estimation techniques with multidimensional linear interpolation. To keep the reduced complexity, we stick to the concept where the algorithms employ a Wiener or Hammerstein structure and the tensors are combined with the well-known LMS algorithm. The update of the tensor is based on a stochastic gradient decent concept. Moreover, an appropriate step size normalization for the update of the tensors and the LMS supports the convergence. Finally, in several experiments we show that the proposed algorithms almost always clearly outperform the state-of-the-art methods with lower or comparable complexity.Comment: 12 pages, 4 figures, 3 table

    Cooperative Beamforming Design for Multiple RIS-Assisted Communication Systems

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    Reconfigurable intelligent surface (RIS) provides a promising way to build programmable wireless transmission environments. Owing to the massive number of controllable reflecting elements on the surface, RIS is capable of providing considerable passive beamforming gains. At present, most related works mainly consider the modeling, design, performance analysis and optimization of single-RIS-assisted systems. Although there are a few of works that investigate multiple RISs individually serving their associated users, the cooperation among multiple RISs is not well considered as yet. To fill the gap, this paper studies a cooperative beamforming design for multi-RIS-assisted communication systems, where multiple RISs are deployed to assist the downlink communications from a base station to its users. To do so, we first model the general channel from the base station to the users for arbitrary number of reflection links. Then, we formulate an optimization problem to maximize the sum rate of all users. Analysis shows that the formulated problem is difficult to solve due to its non-convexity and the interactions among the decision variables. To solve it effectively, we first decouple the problem into three disjoint subproblems. Then, by introducing appropriate auxiliary variables, we derive the closed-form expressions for the decision variables and propose a low-complexity cooperative beamforming algorithm. Simulation results have verified the effectiveness of the proposed algorithm through comparison with various baseline methods. Furthermore, these results also unveil that, for the sum rate maximization, distributing the reflecting elements among multiple RISs is superior to deploying them at one single RIS

    Towards a Recommender System for In-Vehicle Antenna Placement in Harsh Propagation Environments

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    This paper presents a novel approach to improving wireless communications in harsh propagation environments to achieve higher overall reliability and durability of wireless battery powered sensor systems in the context of in-vehicle communication. The goal is to investigate the physical layer and establish an antenna recommendation system for a specific harsh environment, i.e., an engine compartment of a vehicle. We propose the usage of electromagnetic (EM) and ray tracing simulations as a computationally cost-effective method to establish such a recommendation system, which we test by means of an experimental testbed—or test environment—that consists of both a physical, as well as its identical simulation, model. A pool of antennas is evaluated to identify and verify antenna behavior and properties at specified positions in the harsh environment. We use a vector network analyzer (VNA) for accurate measurements and a received signal strength indicator (RSSI) for a first estimation of system performance. Our analysis of the experimental measurements and its EM simulation counterparts shows that both types of data lead to equivalent antenna recommendations at each of the defined positions and experimental conditions. This evaluation and verification process by measurements on an experimental testbed is important to validate the antenna recommendation process. Our results indicate that—with properly characterized antennas—such measurements can be substituted with EM simulations on an accurate EM model, which can contribute to dramatically speeding up the antenna positioning and selection process

    Antennas and Propagation for UAV-Assisted Wireless Networks Towards Next Generation Mobile Systems

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    Unmanned Aerial Vehicles (UAV), also known as "drones", are attracting increasing attention as enablers for many technical applications and services, and this trend is likely to continue in the near future. UAVs are expected to be used extensively in civil and military applications where aerial surveillance and assistance in emergency situations are key factors. UAVs can be more useful and flexible in reaction to specific events, like natural disasters and terrorist attacks since they are faster to deploy, easier to reconfigure and assumed to have better communication means due to their improved position in the sky, improved visibility over ground, and reduced hindrance for propagation. In this regard, UAV enabled communications emerge as one of the most promising solutions for setting-up the next-generation mobile networks, with a special focus on the extension of coverage and capacity of mobile radio networks for 5G applications and beyond. However, air-to-ground (A2G) propagation conditions are likely to be different and more challenging than those experienced by traditional piloted aircraft. For this reason, knowledge of this specific propagation channel – together with the UAV antenna design and placement - is paramount for defining an efficient communication system and for evaluating its performance. This PhD thesis tackles this challenge, and it aims at further investigating the narrowband properties of the air-to-ground propagation channel by means of GPU accelerated ray launching simulations for 5G communications and beyond. As a conclusion, this PhD thesis might bring deep insights into the air-to-ground channel characteristics and UAV antenna design, which can be helpful for designing UAV communication networks and evaluating or optimising their performances in a fast and reliable manner, with no need for exhausting – multiple - in-field measurement campaigns

    Design of terahertz transceiver schemes for ultrahigh-speed wireless communications

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    Future ultra-high-speed wireless communication systems face difficult challenges due to the fundamental limitations of current technologies operating at microwave frequencies. Supporting high transmission rates will require the use of more spectral resources that are only available at higher frequencies. Within this context, terahertz (THz) communications have been attracting more and more attention, being considered by the research community as one of the most promising research fields on the topic due to the availability of extensive unused bandwidth segments. However, its widespread use is not yet possible due to some obstacles, such as the high propagation losses that occur in this band and the difficulty in designing devices that can effectively perform both transmission and detection tasks. The purpose of this dissertation is to contribute for the solution of both of the aforementioned problems and to propose novel THz transceiver schemes for ultra-high-speed wireless communications. Three main research areas were addressed: device modelling for the THz; index modulation (IM) based schemes for Beyond 5G (B5G) networks and hybrid precoding designs for THz ultra massive (UM) – multiple input multiple output (MIMO) systems. The main contributions of this work include the creation of a new design for a reconfigurable THz filter; the proposal of a precoded generalized spatial modulation scheme for downlink MIMO transmissions in B5G networks; the creation of a low-complexity hybrid design algorithm with a near fully-digital performance for multiuser (MU) mmWave/THz ultra massive MIMO systems that can incorporate different analog architectures; and the system-level assessment of cloud radio access network (C-RAN) deployments based on low-complexity hybrid precoding designs for massive MIMO downlink transmissions in B5G networks. The first contribution is especially suited for the implementation of reconfigurable THz filters and optical modulators, since it is based on a simple design, which transits from situations in which it presents a full transparency to situations where it achieves full opacity. Moreover, this approach can also be used for the implementation of simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surfaces (RIS) which are important for enabling flexible system designs in RIS-assisted networks. The second contribution showed that the implementation of precoding schemes based on generalised spatial modulations is a solution with a considerable potential for future B5G systems, since it can provide larger throughputs when compared to conventional MU-MIMO schemes with identical spectral efficiencies.The last two contributions showed that through the proposed hybrid design algorithm it becomes possible to replace a fully digital precoder/combiner by a fully-connected or even by a partially-connected architecture (array of subarrays and dynamic array of subarrays), while achieving good tradeoffs between spectral efficiency, power consumption and implementation complexity. These proposals are particularly relevant for the support of UM-MIMO in severely hardware constrained THz systems. Moreover, the capability of achieving significant improvements in terms of throughput performance and coverage over typical cellular networks, when considering hybrid precoding‐based C-RAN deployments in two indoor office scenarios at the THz band, was demonstrated.Os futuros sistemas de comunicação sem fios de velocidade ultra-elevada enfrentam desafios difíceis devido às limitações fundamentais das tecnologias atuais que funcionam a frequências de microondas. O suporte de taxas de transmissão altas exigirá a utilização de mais recursos espectrais que só estão disponíveis em frequências mais elevadas. A banda Terahertz (THz) é uma das soluções mais promissoras devido às suas enormes larguras de banda disponíveis no espectro eletromagnético. No entanto, a sua utilização generalizada ainda não é possível devido a alguns obstáculos, tais como as elevadas perdas de propagação que se verificam nesta banda e a dificuldade em conceber dispositivos que possam desempenhar eficazmente as tarefas de transmissão e deteção. O objetivo desta tese de doutoramento, é contribuir para ambos os problemas mencionados anteriormente e propor novos esquemas de transcetores THz para comunicações sem fios de velocidade ultra-elevada. Três grandes áreas de investigação foram endereçadas, contribuindo individualmente para um todo: a modelação do dispositivo para o THz; esquemas baseados em modulações de índice (IM) para redes pós-5G (B5G) e desenhos de pré-codificadores híbridos para sistemas THz MIMO ultra-massivos. As principais contribuições deste trabalho incluem a criação de um novo design para um filtro THz reconfigurável; a proposta de uma nova tipologia de modulação espacial generalizada pré-codificada para transmissões MIMO de ligação descendente para redes B5G; a criação de um algoritmo de design híbrido de baixa complexidade com desempenho quase totalmente digital para sistemas MIMO multi-utilizador (MU) mmWave/THz ultra massivos que podem incorporar diferentes arquiteturas analógicas e a avaliação das implementações da rede de acesso de rádio na nuvem (C-RAN) com base em designs de pré-codificação híbridos de baixa complexidade para transmissões MIMO de ligação descendente massivas em redes B5G. A primeira contribuição é especialmente adequada para a implementação de filtros THz reconfiguráveis e moduladores óticos, uma vez que se baseia numa concepção mais simples, que transita de situações em que apresenta uma transparência total para situações em que atinge uma opacidade total. Para além disso, esta abordagem também pode ser utilizada para a implementação de superfícies inteligentes reconfiguráveis (RIS) de transmissão e reflexão simultânea (STAR). A segunda contribuição mostrou que a implementação de esquemas de pré-codificação baseados em modulações espaciais generalizadas é uma solução com um potencial considerável para futuros sistemas B5G, uma vez que permite alcançar maiores ganhos em termos de débito binário quando comparado com esquemas convencionais MU-MIMO com eficiências espectrais idênticas. As duas últimas contribuições mostraram que através do algoritmo proposto torna-se possível substituir a utilização de uma arquitectura totalmente digital por uma arquitetura totalmente conectada ou mesmo por uma arquitetura parcialmente conectada (arrays de subarrays e arrays dinâmicos de subarrays), conseguindo-se bons tradeoffs entre eficiência espectral, consumo de energia e complexidade de implementação. Estas propostas são particularmente relevantes para dar suporte a sistemas THz UM-MIMO com restrições severas ao nível de hardware. Demonstrou-se também a capacidade de se alcançar melhorias significativas em termos de débito binário e cobertura em relação a redes celulares típicas, considerando dois cenários na banda THz
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