193 research outputs found
Smart Pattern V2I Handover Based on Machine Learning Vehicle Classification
The mmwave frequencies will be widely used in future vehicular communications. At these frequencies, the radio channel becomes much more vulnerable to slight changes in the environment like motions of the device, reflections or blockage. In high mobility vehicular communications the rapidly changing vehicle environments and the large overheads due to frequent beam training are the critical disadvantages in developing these systems at mmwave frequencies. Hence, smart beam management procedures are desired to establish and maintain the radio channels. In this thesis, we propose that using the positions and respective velocities of the vehicles in the dynamic selection of the beam pair, and then adapting to the changing environments using machine learning algorithms, can improve both network performance and communication stability in high mobility vehicular communications
An Efficient Uplink Multi-Connectivity Scheme for 5G mmWave Control Plane Applications
The millimeter wave (mmWave) frequencies offer the potential of orders of
magnitude increases in capacity for next-generation cellular systems. However,
links in mmWave networks are susceptible to blockage and may suffer from rapid
variations in quality. Connectivity to multiple cells - at mmWave and/or
traditional frequencies - is considered essential for robust communication. One
of the challenges in supporting multi-connectivity in mmWaves is the
requirement for the network to track the direction of each link in addition to
its power and timing. To address this challenge, we implement a novel uplink
measurement system that, with the joint help of a local coordinator operating
in the legacy band, guarantees continuous monitoring of the channel propagation
conditions and allows for the design of efficient control plane applications,
including handover, beam tracking and initial access. We show that an
uplink-based multi-connectivity approach enables less consuming, better
performing, faster and more stable cell selection and scheduling decisions with
respect to a traditional downlink-based standalone scheme. Moreover, we argue
that the presented framework guarantees (i) efficient tracking of the user in
the presence of the channel dynamics expected at mmWaves, and (ii) fast
reaction to situations in which the primary propagation path is blocked or not
available.Comment: Submitted for publication in IEEE Transactions on Wireless
Communications (TWC
Interface Selection in 5G vehicular networks
ITA
Negli ultimi anni, la quantità di dati condivisa nel mondo è aumentata esponenzialmente grazie alle applicazioni innovative che riguardano la sicurezza (e.g. domotica, smart cities, controllo del traffico stradale, veicoli autonomi) e i servizi di intrattenimento (e.g. audio e video streaming, ricerche web, videogiochi online di massa). Per supportare questo trend, le principali compagnie nell’industria delle telecomunicazioni stanno sviluppando nuovi standard che saranno disponibili agli utenti finali nei prossimi anni e che saranno presentati come la Quinta Generazione di Reti Cellulari (5G). Questi standard prevedono miglioramenti ai precedenti standard 4G (e.g. LTE, WiMax, DSRC) e tecnologie completamente nuove (e.g. onde millimetriche, comunicazione con luce visibile) per permettere la diffusione di nuovi servizi che richiedono un throughput estremamente alto e una latency bassa. Nella maggior parte dei casi, queste tecnologie dovranno cooperare per assicurare una rete affidabile e accessibile in ogni situazione.
Una delle applicazioni più promettenti di questa nuova generazione di tecnologie sono le reti veicolari, un insieme di servizi che includono la comunicazione con le infrastrutture, come il download di un film da Internet o la ricezione di informazioni riguardanti l’ambiente circostante (e.g. un semaforo manda un messaggio a un veicolo in avvicinamento per farlo fermare), o la comunicazione direttamente tra veicoli, in questo caso il datarate è tipicamente più basso dato che l’uso più tipico sarà, per esempio, mandare informazioni riguardanti le macchine più vicine per fare in modo di diminuore il numero di incidenti stradali o gestire il traffico.
Questa tesi è focalizzata sulle applicazioni per reti veicolari, l’obiettivo è di analizzare le prestazioni del protocollo IEEE 802.11p a diversi datarate in un tipico
scenario V2V, e di confrontare LTE e mmWaves usando una comunicazione V2I in diverse circostanze, per mostrare come ogni tecnologia offra vantaggi per determinate applicazioni mentre non è adatta per altre.
ENG
In the last years, the amount of data shared among the world is increased exponentially thanks to the novel applications for security (e.g. home automation,
smart cities, traffic control, autonomous vehicles) and infotainment (e.g. audio and video streaming, web browsing, massive online videogames). To support this
trend, the major companies in the telecommunication industry are developing new standards that will be available to the final users in the next years and that will
be presented as the Fifth Generation of Cellular Networks (5G). These standards provide improvements to the 4G standards (e.g. LTE, WiMax, DSRC) and brand
new technologies (e.g. mmWaves, Visible Light Communication) to enable new services that demand extremely high throughput and low latency. In most cases
these technologies will cooperate to ensure a reliable and accessible network in every situation.
One of the most promising applications of these new generation technologies is vehicular networks, a set of services that includes the communication with infrastructures, such as the download of a film from the Internet or the reception of information about the surrounding environment (e.g. a traffic light sends a
message to an incoming vehicle to make it stop), or the communication between vehicles, in this case the datarate is tipically lower since the typical use will be, for example, to send information about the closest cars in order to decrease the number of accidents or to manage the traffic.
This thesis is focalized on the vehicular networks applications, it aims to analyze the performance of IEEE 802.11p protocol at different datarates in a typical V2V scenario, and to compare LTE and mmWaves using a V2I communication in different circumstances to show how each technology offers advantages for some
applications while is not suitable for others
Fastening the Initial Access in 5G NR Sidelink for 6G V2X Networks
The ever-increasing demand for intelligent, automated, and connected mobility
solutions pushes for the development of an innovative sixth Generation (6G) of
cellular networks. A radical transformation on the physical layer of vehicular
communications is planned, with a paradigm shift towards beam-based millimeter
Waves or sub-Terahertz communications, which require precise beam pointing for
guaranteeing the communication link, especially in high mobility. A key design
aspect is a fast and proactive Initial Access (IA) algorithm to select the
optimal beam to be used. In this work, we investigate alternative IA techniques
to fasten the current fifth-generation (5G) standard, targeting an efficient 6G
design. First, we discuss cooperative position-based schemes that rely on the
position information. Then, motivated by the intuition of a non-uniform
distribution of the communication directions due to road topology constraints,
we design two Probabilistic Codebook (PCB) techniques of prioritized beams. In
the first one, the PCBs are built leveraging past collected traffic
information, while in the second one, we use the Hough Transform over the
digital map to extract dominant road directions. We also show that the
information coming from the angular probability distribution allows designing
non-uniform codebook quantization, reducing the degradation of the performances
compared to uniform one. Numerical simulation on realistic scenarios shows that
PCBs-based beam selection outperforms the 5G standard in terms of the number of
IA trials, with a performance comparable to position-based methods, without
requiring the signaling of sensitive information
Smart Beam Management for Vehicular Networks Using ML
[EN] The mmWave frequencies will be widely used in future
vehicular communications. At these frequencies, the radio
channel becomes much more vulnerable to slight changes in the
environment like motions of the device, reflections or blockage. In
high mobility vehicular communications the rapidly changing
vehicle environments and the large overheads due to frequent
beam training are the critical disadvantages in developing these
systems at mmWave frequencies. Hence, smart beam
management procedures are desired to establish and maintain the
radio channels. In this paper, we propose that using the positions
and respective velocities of the vehicles in the dynamic selection
of the beam pair, and then adapting to the changing environments
using ML algorithms, can improve both network performance
and communication stability in high mobility vehicular
communications.This work was supported by the Spanish Comision
Interministerial de Ciencia y Tecnologia (CICYT) under
projects TEC2016-78028-C3-1-P and MDM2016-O6OO,
Catalan Research Group 2017 SGR 21, and Industrial
Doctorate programme (2018-DI-084) of Generalitat de
Catalunya.Bharath-Reddy, G.; Montero, L.; Perez-Romero, J.; Molins-Benlliure, J.; Ferrando Bataller, M.; Molina, J.; Romeu, J.... (2021). Smart Beam Management for Vehicular Networks Using ML. Íñigo Cuiñas Gómez. 1-4. http://hdl.handle.net/10251/1910661
5G Technology in Smart Healthcare and Smart City Development Integration with Deep Learning Architectures
As more and more medical devices, including as mobile phones, sensors, and remote monitoring equipment, require Internet access, wireless networks have gained considerable traction in the healthcare sector. High-performance technologies, such as the forthcoming fifth generation/sixth generation (5G/6G), are needed for data transit to and from medical equipment in order to give patients with state-of-the-art medical treatments. Furthermore, much better optimization techniques must be used when creating its primary components. Intelligent system design affects how all medical equipment operates, which presents a challenging issue in medical applications. Using information from many sources, electronic health records are built and stored there. These data are compiled in several formats and techniques. There are various big data strategies that could be utilised to reconcile the conflicting data. Artificial intelligence, machine learning and deep learning methods can be used to forecast diseases or other problems using the knowledge gathered from big data analytics. With the advent of 5G, augmented reality, virtual reality and spatial computing are all enhanced, which has a profound effect on healthcare informatics by allowing for real-time remote monitoring. With the advent of 5G technologies, healthcare services can be provided over vast distances via a vast network of interconnected devices and high-performance computation. Disease detection and treatment using dynamic data can be accomplished with the help of deep learning techniques such as Deep Convolutional Neural Networks (DCNN). Deep convolutional neural networks that incorporate images of sick regions are frequently employed for classification tasks
Reliable Video Streaming over mmWave with Multi Connectivity and Network Coding
The next generation of multimedia applications will require the
telecommunication networks to support a higher bitrate than today, in order to
deliver virtual reality and ultra-high quality video content to the users. Most
of the video content will be accessed from mobile devices, prompting the
provision of very high data rates by next generation (5G) cellular networks. A
possible enabler in this regard is communication at mmWave frequencies, given
the vast amount of available spectrum that can be allocated to mobile users;
however, the harsh propagation environment at such high frequencies makes it
hard to provide a reliable service. This paper presents a reliable video
streaming architecture for mmWave networks, based on multi connectivity and
network coding, and evaluates its performance using a novel combination of the
ns-3 mmWave module, real video traces and the network coding library Kodo. The
results show that it is indeed possible to reliably stream video over cellular
mmWave links, while the combination of multi connectivity and network coding
can support high video quality with low latency.Comment: To be presented at the 2018 IEEE International Conference on
Computing, Networking and Communications (ICNC), March 2018, Maui, Hawaii,
USA (invited paper). 6 pages, 4 figure
Non-Terrestrial Networks in the 6G Era: Challenges and Opportunities
Many organizations recognize non-terrestrial networks (NTNs) as a key
component to provide cost-effective and high-capacity connectivity in future
6th generation (6G) wireless networks. Despite this premise, there are still
many questions to be answered for proper network design, including those
associated to latency and coverage constraints. In this paper, after reviewing
research activities on NTNs, we present the characteristics and enabling
technologies of NTNs in the 6G landscape and shed light on the challenges in
the field that are still open for future research. As a case study, we evaluate
the performance of an NTN scenario in which satellites use millimeter wave
(mmWave) frequencies to provide access connectivity to on-the-ground mobile
terminals as a function of different networking configurations.Comment: 8 pages, 4 figures, 2 tables, submitted for publication to the IEE
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