238 research outputs found

    Machine Learning-Based 3D Channel Modeling for U2V mmWave Communications

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    Ondas milimétricas e MIMO massivo para otimização da capacidade e cobertura de redes heterogeneas de 5G

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    Today's Long Term Evolution Advanced (LTE-A) networks cannot support the exponential growth in mobile traffic forecast for the next decade. By 2020, according to Ericsson, 6 billion mobile subscribers worldwide are projected to generate 46 exabytes of mobile data traffic monthly from 24 billion connected devices, smartphones and short-range Internet of Things (IoT) devices being the key prosumers. In response, 5G networks are foreseen to markedly outperform legacy 4G systems. Triggered by the International Telecommunication Union (ITU) under the IMT-2020 network initiative, 5G will support three broad categories of use cases: enhanced mobile broadband (eMBB) for multi-Gbps data rate applications; ultra-reliable and low latency communications (URLLC) for critical scenarios; and massive machine type communications (mMTC) for massive connectivity. Among the several technology enablers being explored for 5G, millimeter-wave (mmWave) communication, massive MIMO antenna arrays and ultra-dense small cell networks (UDNs) feature as the dominant technologies. These technologies in synergy are anticipated to provide the 1000_ capacity increase for 5G networks (relative to 4G) through the combined impact of large additional bandwidth, spectral efficiency (SE) enhancement and high frequency reuse, respectively. However, although these technologies can pave the way towards gigabit wireless, there are still several challenges to solve in terms of how we can fully harness the available bandwidth efficiently through appropriate beamforming and channel modeling approaches. In this thesis, we investigate the system performance enhancements realizable with mmWave massive MIMO in 5G UDN and cellular infrastructure-to-everything (C-I2X) application scenarios involving pedestrian and vehicular users. As a critical component of the system-level simulation approach adopted in this thesis, we implemented 3D channel models for the accurate characterization of the wireless channels in these scenarios and for realistic performance evaluation. To address the hardware cost, complexity and power consumption of the massive MIMO architectures, we propose a novel generalized framework for hybrid beamforming (HBF) array structures. The generalized model reveals the opportunities that can be harnessed with the overlapped subarray structures for a balanced trade-o_ between SE and energy efficiently (EE) of 5G networks. The key results in this investigation show that mmWave massive MIMO can deliver multi-Gbps rates for 5G whilst maintaining energy-efficient operation of the network.As redes LTE-A atuais não são capazes de suportar o crescimento exponencial de tráfego que está previsto para a próxima década. De acordo com a previsão da Ericsson, espera-se que em 2020, a nível global, 6 mil milhões de subscritores venham a gerar mensalmente 46 exa bytes de tráfego de dados a partir de 24 mil milhões de dispositivos ligados à rede móvel, sendo os telefones inteligentes e dispositivos IoT de curto alcance os principais responsáveis por tal nível de tráfego. Em resposta a esta exigência, espera-se que as redes de 5a geração (5G) tenham um desempenho substancialmente superior às redes de 4a geração (4G) atuais. Desencadeado pelo UIT (União Internacional das Telecomunicações) no âmbito da iniciativa IMT-2020, o 5G irá suportar três grandes tipos de utilizações: banda larga móvel capaz de suportar aplicações com débitos na ordem de vários Gbps; comunicações de baixa latência e alta fiabilidade indispensáveis em cenários de emergência; comunicações massivas máquina-a-máquina para conectividade generalizada. Entre as várias tecnologias capacitadoras que estão a ser exploradas pelo 5G, as comunicações através de ondas milimétricas, os agregados MIMO massivo e as redes celulares ultradensas (RUD) apresentam-se como sendo as tecnologias fundamentais. Antecipa-se que o conjunto destas tecnologias venha a fornecer às redes 5G um aumento de capacidade de 1000x através da utilização de maiores larguras de banda, melhoria da eficiência espectral, e elevada reutilização de frequências respetivamente. Embora estas tecnologias possam abrir caminho para as redes sem fios com débitos na ordem dos gigabits, existem ainda vários desafios que têm que ser resolvidos para que seja possível aproveitar totalmente a largura de banda disponível de maneira eficiente utilizando abordagens de formatação de feixe e de modelação de canal adequadas. Nesta tese investigamos a melhoria de desempenho do sistema conseguida através da utilização de ondas milimétricas e agregados MIMO massivo em cenários de redes celulares ultradensas de 5a geração e em cenários 'infraestrutura celular-para-qualquer coisa' (do inglês: cellular infrastructure-to-everything) envolvendo utilizadores pedestres e veiculares. Como um componente fundamental das simulações de sistema utilizadas nesta tese é o canal de propagação, implementamos modelos de canal tridimensional (3D) para caracterizar de forma precisa o canal de propagação nestes cenários e assim conseguir uma avaliação de desempenho mais condizente com a realidade. Para resolver os problemas associados ao custo do equipamento, complexidade e consumo de energia das arquiteturas MIMO massivo, propomos um modelo inovador de agregados com formatação de feixe híbrida. Este modelo genérico revela as oportunidades que podem ser aproveitadas através da sobreposição de sub-agregados no sentido de obter um compromisso equilibrado entre eficiência espectral (ES) e eficiência energética (EE) nas redes 5G. Os principais resultados desta investigação mostram que a utilização conjunta de ondas milimétricas e de agregados MIMO massivo possibilita a obtenção, em simultâneo, de taxas de transmissão na ordem de vários Gbps e a operação de rede de forma energeticamente eficiente.Programa Doutoral em Telecomunicaçõe

    Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

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    With the rapid development of marine activities, there has been an increasing number of maritime mobile terminals, as well as a growing demand for high-speed and ultra-reliable maritime communications to keep them connected. Traditionally, the maritime Internet of Things (IoT) is enabled by maritime satellites. However, satellites are seriously restricted by their high latency and relatively low data rate. As an alternative, shore & island-based base stations (BSs) can be built to extend the coverage of terrestrial networks using fourth-generation (4G), fifth-generation (5G), and beyond 5G services. Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs. Despite of all these approaches, there are still open issues for an efficient maritime communication network (MCN). For example, due to the complicated electromagnetic propagation environment, the limited geometrically available BS sites, and rigorous service demands from mission-critical applications, conventional communication and networking theories and methods should be tailored for maritime scenarios. Towards this end, we provide a survey on the demand for maritime communications, the state-of-the-art MCNs, and key technologies for enhancing transmission efficiency, extending network coverage, and provisioning maritime-specific services. Future challenges in developing an environment-aware, service-driven, and integrated satellite-air-ground MCN to be smart enough to utilize external auxiliary information, e.g., sea state and atmosphere conditions, are also discussed

    A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles

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    In recent years, there has been a dramatic increase in the use of unmanned aerial vehicles (UAVs), particularly for small UAVs, due to their affordable prices, ease of availability, and ease of operability. Existing and future applications of UAVs include remote surveillance and monitoring, relief operations, package delivery, and communication backhaul infrastructure. Additionally, UAVs are envisioned as an important component of 5G wireless technology and beyond. The unique application scenarios for UAVs necessitate accurate air-to-ground (AG) propagation channel models for designing and evaluating UAV communication links for control/non-payload as well as payload data transmissions. These AG propagation models have not been investigated in detail when compared to terrestrial propagation models. In this paper, a comprehensive survey is provided on available AG channel measurement campaigns, large and small scale fading channel models, their limitations, and future research directions for UAV communication scenarios

    MM-Wave HetNet in 5G and beyond Cellular Networks Reinforcement Learning Method to improve QoS and Exploiting Path Loss Model

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    This paper presents High density heterogeneous networks (HetNet) which are the most promising technology for the fifth generation (5G) cellular network. Since 5G will be available for a long time, previous generation networking systems will need customization and updates. We examine the merits and drawbacks of legacy and Q-Learning (QL)-based adaptive resource allocation systems. Furthermore, various comparisons between methods and schemes are made for the purpose of evaluating the solutions for future generation. Microwave macro cells are used to enable extra high capacity such as Long-Term Evolution (LTE), eNodeB (eNB), and Multimedia Communications Wireless technology (MC), in which they are most likely to be deployed. This paper also presents four scenarios for 5G mm-Wave implementation, including proposed system architectures. The WL algorithm allocates optimal power to the small cell base station (SBS) to satisfy the minimum necessary capacity of macro cell user equipment (MUEs) and small cell user equipment (SCUEs) in order to provide quality of service (QoS) (SUEs). The challenges with dense HetNet and the massive backhaul traffic they generate are discussed in this study. Finally, a core HetNet design based on clusters is aimed at reducing backhaul traffic. According to our findings, MM-wave HetNet and MEC can be useful in a wide range of applications, including ultra-high data rate and low latency communications in 5G and beyond. We also used the channel model simulator to examine the directional power delay profile with received signal power, path loss, and path loss exponent (PLE) for both LOS and NLOS using uniform linear array (ULA) 2X2 and 64x16 antenna configurations at 38 GHz and 73 GHz mmWave bands for both LOS and NLOS (NYUSIM). The simulation results show the performance of several path loss models in the mmWave and sub-6 GHz bands. The path loss in the close-in (CI) model at mmWave bands is higher than that of open space and two ray path loss models because it considers all shadowing and reflection effects between transmitter and receiver. We also compared the suggested method to existing models like Amiri, Su, Alsobhi, Iqbal, and greedy (non adaptive), and found that it not only enhanced MUE and SUE minimum capacities and reduced BT complexity, but it also established a new minimum QoS threshold. We also talked about 6G researches in the future. When compared to utilizing the dual slope route loss model alone in a hybrid heterogeneous network, our simulation findings show that decoupling is more visible when employing the dual slope path loss model, which enhances system performance in terms of coverage and data rate
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