232 research outputs found
Handling Spontaneous Traffic Variations in 5G+ via Offloading onto mmWave-Capable UAV `Bridges'
Unmanned aerial vehicles (UAVs) are increasingly employed for numerous public
and civil applications, such as goods delivery, medicine, surveillance, and
telecommunications. For the latter, UAVs with onboard communication equipment
may help temporarily offload traffic onto the neighboring cells in
fifth-generation networks and beyond (5G+). In this paper, we propose and
evaluate the use of UAVs traveling over the area of interest to relieve
congestion in 5G+ systems under spontaneous traffic fluctuations. To this end,
we assess two inherently different offloading schemes, named routed and
controlled UAV `bridging'. Using the tools of renewal theory and stochastic
geometry, we analytically characterize these schemes in terms of the fraction
of traffic demand that can be offloaded onto the UAV `bridge' as our parameter
of interest. This framework accounts for the unique features of millimeter-wave
(mmWave) radio propagation and city deployment types with potential
line-of-sight (LoS) link blockage by buildings. We also introduce enhancements
to the proposed schemes that significantly improve the offloading gains. Our
findings offer evidence that the UAV `bridges' may be used for efficient
traffic offloading in various urban scenarios.Comment: This work has been accepted for publication in the IEEE Transactions
on Vehicular Technolog
An Accurate Approximation of Resource Request Distributions in Millimeter Wave 3GPP New Radio Systems
The recently standardized millimeter wave-based 3GPP New Radio technology is
expected to become an enabler for both enhanced Mobile Broadband (eMBB) and
ultra-reliable low latency communication (URLLC) services specified to future
5G systems. One of the first steps in mathematical modeling of such systems is
the characterization of the session resource request probability mass function
(pmf) as a function of the channel conditions, cell size, application demands,
user location and system parameters including modulation and coding schemes
employed at the air interface. Unfortunately, this pmf cannot be expressed via
elementary functions. In this paper, we develop an accurate approximation of
the sought pmf. First, we show that Normal distribution provides a fairly
accurate approximation to the cumulative distribution function (CDF) of the
signal-to-noise ratio for communication systems operating in the millimeter
frequency band, further allowing evaluating the resource request pmf via error
function. We also investigate the impact of shadow fading on the resource
request pmf.Comment: The 19th International Conference on Next Generation Wired/Wireless
Networks and Systems (New2An 2019
Ondas milimétricas e MIMO massivo para otimização da capacidade e cobertura de redes heterogeneas de 5G
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
Identification of misbehavior detection solutions and risk scenarios in advanced connected and automated driving scenarios
The inclusion of 5G cellular communication system into vehicles, combined with other connected-vehicle technology, such as sensors and cameras, makes connected and advanced vehicles a promising application in the Cooperative Intelligent Transport Systems. One of the most challenging task is to provide resilience against misbehavior i.e., against vehicles that intentionally disseminate false information to deceive receivers and induce them to manoeuvre incorrectly or even dangerously. This calls for misbehaviour detection mechanisms, whose purpose is to analyze information semantics to detect and filter attacks. As a result, data correctness and integrity are ensured. Misbehaviour and its detection are rather new concepts in the literature; there is a lack of methods that leverage the available information to prove its trustworthiness. This is mainly because misbehaviour techniques come with several flavours and have different unpredictable purposes, therefore providing precise guidelines is rather ambitious. Moreover, dataset to test detection schemes are rare to find and inconvenient to customize and adapt according to needs. This work presents a misbehaviour detection scheme that exploits information shared between vehicles and received signal properties to investigate the behaviour of transmitters. Differently from most available solutions, this is based on the data of the on-board own resources of the vehicle. Computational effort and resources required are minor concerns, and concurrently time efficiency is gained. Also, the project addresses three different types of attack to show that detecting misbehaviour methods are more vulnerable to some profile of attacker than others. Moreover, a rich dataset was set up to test the scheme. The dataset was created according to the latest standardised evaluation methodologies and provides a valuable starting point for any further development and research
Socially Aware V2X Localized QoS
Vehicle-to-everything (V2X) is a core 5G technology. V2X and its enabler,
Device-to-Device (D2D), are essential for the Internet of Things (IoT) and the
Internet of Vehicles (IoV). V2X enables vehicles to communicate with other
vehicles (V2V), networks (V2N), and infrastructure (V2I). While V2X enables
ubiquitous vehicular connectivity, the impact of bursty data on the network's
overall Quality of Service (QoS), such as when a vehicle accident occurs, is
often ignored. In this work, we study both 4G and 5G V2X utilizing Evolved
Universal Terrestrial Radio Access New Radio (E-UTRA-NR) and propose the use of
socially aware 5G NR Dual Connectivity (en-DC) for traffic differentiation. We
also propose localized QoS, wherein high-priority QoS flows traverse 5G road
side units (RSUs) and normal-priority QoS flows traverse 4G Base Station (BS).
We formulate a max-min fair QoS-aware Non-Orthogonal Multiple Access (NOMA)
resource allocation scheme, QoS reclassify. QoS reclassify enables localized
QoS and traffic steering to mitigate bursty network traffic's impact on the
network's overall QoS. We then solve QoS reclassify via Integer Linear
Programming (ILP) and derive its approximation. We demonstrate that both
optimal and approximation QoS reclassify resource allocation schemes in our
socially aware QoS management methodology outperform socially unaware legacy 4G
V2X algorithms (no localized QoS support, no traffic steering) and socially
aware 5G V2X (no localized QoS support, yet utilizes traffic steering). Our
proposed QoS reclassify scheme's QoS flow end-to-end latency requires only
of the time legacy 4G V2X requires.Comment: This work has been submitted to IEEE for possible publication.
Copyright may be transferred without notice, after which this version may no
longer be accessible. Under review by IEEE Internet of Things journa
System-Level Analysis of Blockage Dynamics in Millimeter-Wave Communications
The new generation of wireless technology, termed as the fifth generation (5G), introduces a large amount of novel features. An operation in the millimeter-wave (mmWave) spectrum becomes one of those features unlocking a wide bandwidth. The latter allows for a notable increase in the peak data rate by up to tens of gigabits per second and decreases latency to as low as few milliseconds. These improvements provide an opportunity to support high-rate and low-latency applications, such as augmented and virtual reality, eHealth, and many others.
Though mmWave communications have great potential, they suffer from severe attenuation caused by signal blockage. In addition to large-scale blockers (i.e., buildings), small-scale blockers such as human bodies bring new challenges to the operation over mmWave bands. Large attenuation losses, as well as the unpredictable mobility of human body blockers, can significantly decrease a service quality when communicating over a mmWave link. Thereby, there is a need to properly model the blockage process, evaluate its impact on mmWave network performance, and estimate performance gains brought by different blockage mitigation techniques.
The thesis proposes a mathematical methodology to characterize and evaluate the effect of blockage dynamics in mmWave networks. With the help of stochastic geometry and probability theory, it delivers mathematical models of static and dynamic small-scale blockage, as well as static large-scale blockage. It then introduces system-level performance evaluation frameworks accounting for the main features of mmWave communications, such as blockage and multipath propagation. The mathematical frameworks can also evaluate the impact of several blockage mitigation techniques in realistic deployment scenarios
Airborne Integrated Access and Backhaul Systems : Learning-Aided Modeling and Optimization
The deployment of millimeter-wave (mmWave) 5G New Radio (NR) networks is hampered by the properties of the mmWave band, such as severe signal attenuation and dynamic link blockage, which together limit the cell range. To provide a cost-efficient and flexible solution for network densification, 3GPP has recently proposed integrated access and backhaul (IAB) technology. As an alternative approach to terrestrial deployments, the utilization of unmanned aerial vehicles (UAVs) as IAB-nodes may provide additional flexibility for topology configuration. The aims of this study are to (i) propose efficient optimization methods for airborne and conventional IAB systems and (ii) numerically quantify and compare their optimized performance. First, by assuming fixed locations of IAB-nodes, we formulate and solve the joint path selection and resource allocation problem as a network flow problem. Then, to better benefit from the utilization of UAVs, we relax this constraint for the airborne IAB system. To efficiently optimize the performance for this case, we propose to leverage deep reinforcement learning (DRL) method for specifying airborne IAB-node locations. Our numerical results show that the capacity gains of airborne IAB systems are notable even in non-optimized conditions but can be improved by up to 30 % under joint path selection and resource allocation and, even further, when considering aerial IAB-node locations as an additional optimization criterion.acceptedVersionPeer reviewe
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