144 research outputs found

    Outage probability in the uplink of multitier millimeter wave cellular networks

    Get PDF
    In this article, using the stochastic geometry, we develop a tractable uplink modeling framework for the outage probability of the multitier millimeter wave (mmWave) cellular networks. Each tier’s mmWave base stations (BSs) are randomly located and they have particular spatial density, antenna gain, receiver sensitivity, blockage parameter, and pathloss exponents. Our model takes account of the maximum power limitation and the per-user power control. More specifically, each user, which could be in line-of-sight (LOS) or non-LOS to its serving mmWave BS, controls its transmit power such that the received signal power at its serving BS is equal to a predefined threshold. Hence, a truncated channel inversion power control scheme is implemented for the uplink of mmWave cellular networks. We derive closed-form expressions for the signal-to-interference-plus-noise-ratio (SINR) outage probability for the uplink of the multitier mmWave cellular networks, which we later degrade to the single-tier network. Furthermore, we analyze the case with a dense network by utilizing the simplified model, where the LOS region is approximated as a fixed LOS disk. The results show that imposing a maximum power constraint on the user significantly affects the SINR outage probability in the uplink of mmWave cellular networks

    Energy Efficient Massive MIMO and Beamforming for 5G Communications

    Get PDF
    Massive multiple-input multiple-output (MIMO) has been a key technique in the next generation of wireless communications for its potential to achieve higher capacity and data rates. However, the exponential growth of data traffic has led to a significant increase in the power consumption and system complexity. Therefore, we propose and study wireless technologies to improve the trade-off between system performance and power consumption of wireless communications. This Thesis firstly proposes a strategy with partial channel state information (CSI) acquisition to reduce the power consumption and hardware complexity of massive MIMO base stations. In this context, the employment of partial CSI is proposed in correlated communication channels with user mobility. By exploiting both the spatial correlation and temporal correlation of the channel, our analytical results demonstrate significant gains in the energy efficiency of the massive MIMO base station. Moreover, relay-aided communications have experienced raising interest; especially, two-way relaying systems can improve spectral efficiency with short required operating time. Therefore, this Thesis focuses on an uncorrelated massive MIMO two-way relaying system and studies power scaling laws to investigate how the transmit powers can be scaled to improve the energy efficiency up to several times the energy efficiency without power scaling while approximately maintaining the system performance. In a similar line, large antenna arrays deployed at the space-constrained relay would give rise to the spatial correlation. For this reason, this Thesis presents an incomplete CSI scheme to evaluate the trade-off between the spatial correlation and system performance. In addition, the advantages of linear processing methods and the effects of channel aging are investigated to further improve the relay-aided system performance. Similarly, large antenna arrays are required in millimeter-wave communications to achieve narrow beams with higher power gain. This poses the problem that locating the best beam direction requires high power and complexity consumption. Therefore, this Thesis presents several low-complexity beam alignment methods with respect to the state-of-the-art to evaluate the trade-off between complexity and system performance. Overall, extensive analytical and numerical results show an improved performance and validate the effectiveness of the proposed techniques

    Graph-based Model for Beam Management in Mmwave Vehicular Networks

    Get PDF
    Mmwave bands are being widely touted as a very promising option for future 5G networks, especially in enabling such networks to meet highly demanding rate requirements. Accordingly, the usage of these bands is also receiving an increasing interest in the context of 5G vehicular networks, where it is expected that connected cars will soon need to transmit and receive large amounts of data. Mmwave communications, however, require the link to be established using narrow directed beams, to overcome harsh propagation conditions. The advanced antenna systems enabling this also allow for a complex beam design at the base station, where multiple beams of different widths can be set up. In this work, we focus on beam management in an urban vehicular network, using a graph-based approach to model the system characteristics and the existing constraints. In particular, unlike previous work, we formulate the beam design problem as a maximum-weight matching problem on a bipartite graph with conflicts, and then we solve it using an efficient heuristic algorithm. Our results show that our approach easily outperforms advanced methods based on clustering algorithms

    Mobility management in multi-RAT multiI-band heterogeneous networks

    Get PDF
    Support for user mobility is the raison d'etre of mobile cellular networks. However, mounting pressure for more capacity is leading to adaption of multi-band multi-RAT ultra-dense network design, particularly with the increased use of mmWave based small cells. While such design for emerging cellular networks is expected to offer manyfold more capacity, it gives rise to a new set of challenges in user mobility management. Among others, frequent handovers (HO) and thus higher impact of poor mobility management on quality of user experience (QoE) as well as link capacity, lack of an intelligent solution to manage dual connectivity (of user with both 4G and 5G cells) activation/deactivation, and mmWave cell discovery are the most critical challenges. In this dissertation, I propose and evaluate a set of solutions to address the aforementioned challenges. The beginning outcome of our investigations into the aforementioned problems is the first ever taxonomy of mobility related 3GPP defined network parameters and Key Performance Indicators (KPIs) followed by a tutorial on 3GPP-based 5G mobility management procedures. The first major contribution of the thesis here is a novel framework to characterize the relationship between the 28 critical mobility-related network parameters and 8 most vital KPIs. A critical hurdle in addressing all mobility related challenges in emerging networks is the complexity of modeling realistic mobility and HO process. Mathematical models are not suitable here as they cannot capture the dynamics as well as the myriad parameters and KPIs involved. Existing simulators also mostly either omit or overly abstract the HO and user mobility, chiefly because the problems caused by poor HO management had relatively less impact on overall performance in legacy networks as they were not multi-RAT multi-band and therefore incurred much smaller number of HOs compared to emerging networks. The second key contribution of this dissertation is development of a first of its kind system level simulator, called SyntheticNET that can help the research community in overcoming the hurdle of realistic mobility and HO process modeling. SyntheticNET is the very first python-based simulator that fully conforms to 3GPP Release 15 5G standard. Compared to the existing simulators, SyntheticNET includes a modular structure, flexible propagation modeling, adaptive numerology, realistic mobility patterns, and detailed HO evaluation criteria. SyntheticNET’s python-based platform allows the effective application of Artificial Intelligence (AI) to various network functionalities. Another key challenge in emerging multi-RAT technologies is the lack of an intelligent solution to manage dual connectivity with 4G as well 5G cell needed by a user to access 5G infrastructure. The 3rd contribution of this thesis is a solution to address this challenge. I present a QoE-aware E-UTRAN New Radio-Dual Connectivity (EN-DC) activation scheme where AI is leveraged to develop a model that can accurately predict radio link failure (RLF) and voice muting using the low-level measurements collected from a real network. The insights from the AI based RLF and mute prediction models are then leveraged to configure sets of 3GPP parameters to maximize EN-DC activation while keeping the QoE-affecting RLF and mute anomalies to minimum. The last contribution of this dissertation is a novel solution to address mmWave cell discovery problem. This problem stems from the highly directional nature of mmWave transmission. The proposed mmWave cell discovery scheme builds upon a joint search method where mmWave cells exploit an overlay coverage layer from macro cells sharing the UE location to the mmWave cell. The proposed scheme is made more practical by investigating and developing solutions for the data sparsity issue in model training. Ability to work with sparse data makes the proposed scheme feasible in realistic scenarios where user density is often not high enough to provide coverage reports from each bin of the coverage area. Simulation results show that the proposed scheme, efficiently activates EN-DC to a nearby mmWave 5G cell and thus substantially reduces the mmWave cell discovery failures compared to the state of the art cell discovery methods

    Técnicas de gestão de feixe de onda para sistemas Massive MIMO nas redes 5G NR

    Get PDF
    The use of Millimeter wave (mmWave) spectrum frequencies is seen as a key enabler technology for the future wireless communication systems to overcome the bandwidth shortage of the sub 6GHz microwave spectrum band, enabling high speed data transmissions in the 5G/6G systems. Nevertheless, mmWave propagation characteristics are associated to significant free-path losses and many more attenuations that become even more harsher as the frequency increases, rendering the communication challenging at this frequencies. To overcome these distinct disadvantages, multiple antenna arrays are employed to allow beamforming techniques for the transmission of narrower concentrated beams in more precise directions and less interference levels between them, consequently improving the link budget. Thus, to constantly assure that the communication with each device is done using the beam pair that allows the best possible connectivity, a set of Beam Management control procedures is necessary to assure an efficient beamformed connection establishment and its continuous maintenance between the device and the network. This dissertation will address the description of the Initial Beam Establishment (IBE) BM procedure, focusing the selection of the most suitable transmit-receive beam pair available after completed beam sweeping techniques to measure the different power levels of the received signal. The main goal is to design a new 3GPP-standard compliant beam pair selection algorithm based on SSS angle estimation (BSAE), that makes use of multiple Synchronization Signal Blocks (SSBs) to maximize the Reference Signal Received Power (RSRP) value at the receiver, through the selected beam pair. This optimization is done using the Secondary Synchronization Signals (SSSs) present in each SSB to perform channel estimation in the digital domain (comprising the effects of the analog processing). Afterwards, the combination of those estimations were used to perform the equivalent channel propagation matrix estimation without the analog processing effects. Finally, through the channel propagation matrix, the angle that maximizes the RSRP was determined to compute the most suitable beam through the aggregated response vector. The obtained results show that the proposed algorithm achieves better performance levels compared to a conventional beam pair selection algorithm. Furthermore, a comparison with an optimal case is also done, i.e., the situation where the channel is known, and the optimal beam pair angle can be determined. Therefore, the similar performance results compared to the optimal case indicates that the proposed algorithm is interesting for practical 5G mmWave mMIMO implementations, according to 3GPP-compliant standards.O uso de frequências na banda das ondas milimétricas é visto como uma tecnologia chave para os futuros sistemas de comunicação móveis, tendo em vista a ultrapassar o problema da escassez de banda a sub-6 GHz, e por permitir as elevadas taxas de dados requeridas para sistemas 5G/6G. Contudo, a propagação deste tipo de ondas está associado a perdas acentuadas em espaço livre e várias atenuações que se tornam cada vez mais significativas com o aumento do valor da frequência, impondo obstáculos à comunicação. Para ultrapassar estas adversidades, agregados constituídos por múltiplos elementos de antena são implementados por forma a permitir técnicas de formação de feixe e possibilitar a transmissão de feixes mais estreitos e altamente direcionais, diminuindo os níveis de interferência e melhorando consequentemente o link budget. Deste modo, para assegurar constantemente que a comunicação efetuada em cada dispositivo ocorre utilizando o conjunto de feixes que proporciona o melhor nível de conectividade, é então necessário um conjunto de procedimentos de controlo de gestão de feixe, assegurando um estabelecimento eficiente da comunicação e a sua contínua manutenção entre um dispositivo e a rede. Esta dissertação descreve o procedimento de gestão de feixe conhecido como estabelecimento inicial de feixe, focando o processo de seleção do melhor par de feixe de transmissão-receção disponível após o uso de técnicas de varrimento de feixe por fim a efetuar medições dos diferentes níveis de potência do sinal recebido. O principal objetivo passa pela conceção de um novo algoritmo de estabelecimento de par de feixes baseado em estimações de ângulo (BSAE), que explora o uso de múltiplos SSBs definidos pelo 3GPP, por forma a maximizar o RSRP no recetor, através do feixe selecionado. Esta otimização é feita usando os sinais de sincronização secundários (SSSs) presentes em cada SSB para efetuar uma estimação de canal no domínio digital (que contém o efeito do processamento analógico). Depois, combinando essas estimações, foi feita uma estimação da matriz do canal de propagação, sem o efeito desse processamento analógico. Finalmente, através da matriz do canal de propagação, foi determinado o ângulo que maximiza o RSRP, e calculado o feixe através do vetor de resposta do agregado. Os resultados obtidos demonstram que o algoritmo proposto atinge melhor desempenho quando comparado com o algoritmo convencional de seleção de par de feixes. Foi feita ainda uma comparação com o caso ótimo, isto é, com o caso em que se conhece completamente o canal e se obtém um ângulo ótimo. Os resultados obtidos pelo algoritmo proposto foram muito próximos do caso ótimo, pelo que é bastante interessante para sistemas práticos 5G mmWave mMIMO, que estejam de acordo com o padrão 3GPP.Mestrado em Engenharia Eletrónica e Telecomunicaçõe
    corecore