Letteratura scientifica selezionata sul tema "5G (téléphonie mobile) – Cartes"
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Articoli di riviste sul tema "5G (téléphonie mobile) – Cartes":
Roche, Edward M., Benjamin H. Dickens-Jr. e Walker Townes. "La prochaine génération de téléphonie mobile (5G) et ses implications (Infrastructure, Réglementation)". Netcom, n. 32-1/2 (16 dicembre 2018): 139–62. http://dx.doi.org/10.4000/netcom.2869.
Achilleas, Philippe. "La bataille de la 5G et le droit international". Annuaire français de droit international 66, n. 1 (2020): 709–31. http://dx.doi.org/10.3406/afdi.2020.5489.
Tesi sul tema "5G (téléphonie mobile) – Cartes":
Mallik, Mohammed Tariqul Hassan. "Electromagnetic Field Exposure Reconstruction by Artificial Intelligence". Electronic Thesis or Diss., Université de Lille (2022-....), 2023. https://pepite-depot.univ-lille.fr/ToutIDP/EDENGSYS/2023/2023ULILN052.pdf.
The topic of exposure to electromagnetic fields has received muchattention in light of the current deployment of the fifth generation(5G) cellular network. Despite this, accurately reconstructing theelectromagnetic field across a region remains difficult due to a lack ofsufficient data. In situ measurements are of great interest, but theirviability is limited, making it difficult to fully understand the fielddynamics. Despite the great interest in localized measurements, thereare still untested regions that prevent them from providing a completeexposure map. The research explored reconstruction strategies fromobservations from certain localized sites or sensors distributed inspace, using techniques based on geostatistics and Gaussian processes.In particular, recent initiatives have focused on the use of machinelearning and artificial intelligence for this purpose. To overcome theseproblems, this work proposes new methodologies to reconstruct EMFexposure maps in a specific urban area in France. The main objective isto reconstruct exposure maps to electromagnetic waves from some datafrom sensors distributed in space. We proposed two methodologies basedon machine learning to estimate exposure to electromagnetic waves. Forthe first method, the exposure reconstruction problem is defined as animage-to-image translation task. First, the sensor data is convertedinto an image and the corresponding reference image is generated using aray tracing-based simulator. We proposed an adversarial network cGANconditioned by the environment topology to estimate exposure maps usingthese images. The model is trained on sensor map images while anenvironment is given as conditional input to the cGAN model.Furthermore, electromagnetic field mapping based on the GenerativeAdversarial Network is compared to simple Kriging. The results show thatthe proposed method produces accurate estimates and is a promisingsolution for exposure map reconstruction. However, producing referencedata is a complex task as it involves taking into account the number ofactive base stations of different technologies and operators, whosenetwork configuration is unknown, e.g. powers and beams used by basestations. Additionally, evaluating these maps requires time andexpertise. To answer these questions, we defined the problem as amissing data imputation task. The method we propose takes into accountthe training of an infinite neural network to estimate exposure toelectromagnetic fields. This is a promising solution for exposure mapreconstruction, which does not require large training sets. The proposedmethod is compared with other machine learning approaches based on UNetnetworks and conditional generative adversarial networks withcompetitive results
Zhang, Chao. "Caractérisation des performances limites des jeux non-coopératifs avec observation imparfaite : application à la téléphonie mobile 5G". Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS570/document.
A large part of the results reported in this thesis is based on an observation which has never been made for wireless communications and power control in particular: transmit power levels and more generally transmit covariance matrices can be exploited to embed information such as coordination information and available interference-dependent feedback samples can be exploited as a communication channel. First, we show that the famous iterative water-filling algorithm does not exploit the available information sufficiently well in terms of sum-utility. Indeed, we show that global channel state information can be acquired from the sole knowledge of an SINR-type feedback. A natural question then arises. Is it possible to design a distributed power control algorithm which exploits as well as possible the available information? To answer this question, we derive the characterization of the utility region for the considered problem and show how to exploit this characterization not only to measure globally efficiency but also to obtain globally efficient one-shot power control functions. Motivated by the success of our approach for single-band and multi-band interference networks, we asked ourselves whether it could be exploited for MIMO networks. We have identified at least one very relevant scenario. Indeed, we show that opportunistic interference alignment can be implemented by only assuming interference-plus-noise covariance feedback at the secondary transmitter. Then, in the last chapter, we generalize the problem of quantization, the motivation for this being given by some observations made in the previous chapters. First, we assume that the quantizer and de-quantizer are designed to maximize a general utility function instead of the conventional distortion function. Second, we assume that the quantizer and de-quantizer may have different utility functions. This raises non-trivial technical problems, our claim is to make a very first step into solving them
Mohammadi, Alireza. "Cloud Native MANO for Next Generation Mobile Networks". Electronic Thesis or Diss., Sorbonne université, 2023. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2023SORUS633.pdf.
This thesis crystallizes significant contributions pivoted around integral concepts such as Consistent DevOps and Declarative Automation to realize the envisioned cloud-native MANO. These principles are applied in the context of multi-x systems, where ‘x’ represents various dimensions such as RAN vendor, OS, and cloud, addressing the level of heterogeneity and diversity in the modern networks. Interpreting multi-x as a cloud-native extension to the Open RAN ecosystem, the thesis is conceived and validated through a concrete proof-of-concept prototype for multi-vendor 5G networks. This addresses the complexities of next generation private and public cloud-native MANO systems by incorporating advanced technologies such as eBPF and recent developments in the cloud-native domain, including Kubernetes
Oussakel, Imane. "4G/5G cellular networks metrology and management". Thesis, Toulouse 3, 2020. http://www.theses.fr/2020TOU30261.
The proliferation of sophisticated applications and services comes with diverse performance requirements as well as an exponential traffic growth for both upload and download. The cellular networks such as 4G and 5G are advocated to support this diverse and huge amount of data. This thesis work targets the enforcement of advanced cellular network supervision and management techniques taking the traffic explosion and diversity as two main challenges in these networks. The first contribution tackles the intelligence integration in cellular networks through the estimation of users uplink instantaneous throughput at small time granularities. A real time 4G testbed is deployed for such aim with an exhaustive metrics benchmark. Accurate estimations are achieved.The second contribution enforces the real time 5G slicing from radio resources perspective in a multi-cell system. For that, two exact optimization models are proposed. Due to their high convergence time, heuristics are developed and evaluated with the optimal models. Results are promising, as two heuristics are highly enforcing the real time RAN slicing
Nguyen, Thanh-Son-Lam. "Wireless Resource Allocation in 5G-NR V2V Communications". Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG052.
This doctoral dissertation explores the enhancement of wireless resource allocation in Vehicle-to-Everything (V2X) communications, as specified by the 3GPP Release 16 standard. The specific area of our research is the NR-V2X Sidelink communication, also known as the New Radio-Vehicles to Vehicles (NR-V2V) communication. Our goal is to formulate a novel optimization protocol that not only guarantees high-quality services (QoS) but also outperforms existing methodologies in NR-V2V communication.Initially, we introduce Adaptive Physical Configuration (APC), a search-based algorithm designed to identify the optimal physical layer configuration within a set of environmental factors, specifically tailored for a broadcast communication scheme. Following this, we evolve APC into a Radio Aware variant (RA-APC), broadening its scope by incorporating unicast communication and establishing a more flexible structure for PHY resources. In the final phase, we further refine RA-APC by integrating a machine learning algorithm, specifically a decision tree. This integration uncovers patterns within the input factors, thereby augmenting both the accuracy and efficiency of the allocation optimization process
Arrano, Scharager Hernan. "Full-duplex for cellular networks : a stochastic geometry approach". Electronic Thesis or Diss., Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAT001.
Full-duplex (FD) is a principle in which a transceiver can receive and transmit on the same time-frequency radio resource. The principle was long held as impractical due to the high self-interference that arises when simultaneously transmitting and receiving in the same resource block. When assuming perfect self-interference cancellation, FD can potentially double the spectral efficiency (SE) of a given point-to-point communication. In practice though, it is not possible to achieve the aforementioned characteristic. Moreover, under a cellular network context, not only the self-interference limits the performance, since additional co-channel interference is created by base stations (BSs) and users equipment (UEs). However, even with the higher interference dowlinks (DLs) still obtain higher SE performances, whereas uplinks (ULs) are generally critically degraded, when compared to half-duplex (HD). We focus our work in the study of alternatives that can help improve the impaired ULs in FD networks, while still trying to profit from the gains experienced by DLs.In this regard, we use stochastic geometry along the thesis as a means to characterize key performance indicators of cellular networks, such as: coverage probability, average SE and data rates. The thesis is divided into three major studies. Firstly, we propose a duplex-switching policy which enables BSs to operate in FD- or HD- depending on the UL and DL conditions. Secondly, we investigate the performance of hybrid HD/FD networks under a millimeter wave context. Finally, we propose a novel algorithm based on nonorthogonal multiple-access (NOMA) and successive interference cancellation (SIC), which allows BSs to coordinate on their respective transmission schemes to reduce the BS-to-BS interference. We demonstrate that the models presented in the thesis allow to balance the gains of one link over the other; reducing the UL degradation, while maintaining DL gains. In addition, we show that scenarios in which equipment is able to perform beamforming are ideal for FD deployments, since they directly reduce the cochannel interference
Khizar, Sadia. "Metrology for 5G edge networks (MEC). Leveraging mobile devices beyond the edge toward task offloading". Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS069.
The pervasiveness of mobile devices equipped with internet connectivity and positioning systems leads us to regard them as a valuable resource to leverage. In this thesis, we tackle the use of mobile devices from a new perspective. We consider the extension of the capacity of the MEC by using the available resources of mobile devices beyond the edge of the infrastructure network. The goal is to leverage their untapped resources to process computation on behalf of the MEC in a distributed way. It is fundamental for the MEC to be aware of its operating environment to rely on mobile nodes. In the first part of the thesis, we have focused on the temporal availability of beyond-the-edge resources. We chose to investigate the co-location of terminals and analyze their persistence in a cell. Then, we turn our attention to task allocation. We shift the focus on the spatio-temporal aspect by quantifying the resources that a cell can provide to perform a MEC task. We estimate the potential amount of computational tasks performed by nodes based on the cumulative presence time in a given cell and a given completion delay. Results provide insight into the possibilities of offloading computing tasks on mobile nodes. Furthermore, it allows knowing the locations where it is advisable to offload tasks and the time duration of tasks offloadable
Chagdali, Abdellatif. "Multi-connectivity and resource allocation for slices in 5G networks". Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST052.
Future mobile networks envision unprecedented innovation opportunities and disruptive use cases. As a matter of fact, the 5G and beyond networks' pledge to deliver mission-critical applications mandates a versatile, scalable, efficient, and cost-effective network capable of accommodating its resource allocation to meet the services' heterogeneous requirements. To face these challenges, network slicing has emerged as one of the fundamental concepts proposed to raise the 5G mobile networks' efficiency and provide the required plasticity. The idea is to provide resources for different vertical industries by building multiple end-to-end logical networks over a shared virtualized infrastructure. Each network slice is customized to deliver a specific service and adapts its architecture and radio access technologies.Precisely, applications such as industrial automation or vehicular communications pose stringent latency and reliability requirements on cellular networks. Given that the current mobile network cannot meet these requirements, ultra-reliable low-latency communications (URLLC) embodies a vital research topic that has gathered substantial momentum from academia and industrial alliances. To reach URLLC requirements, employing multi-connectivity (MC), i.e., exploiting multiple radio links as communication paths at once, is a promising approach.Therefore, the objective of the present manuscript is to investigate dynamic scheduling techniques, exploiting redundant coverage of users, guaranteed in numerous 5G radio access network scenarios. We first review the evolution of mobile networks and discuss various considerations for network slicing architecture and its impact on resource allocation design. Then, we use tools from queuing theory to model a system in which a set of URLLC users are connected simultaneously to two base stations having the same bandwidth; we refer to this scenario as the homogenous case. We introduce suitable scheduling policies and evaluate their respective performances by assessing their reliability. Next, we extend the homogenous case's results to a more general setting where the physical interfaces manage different bandwidths, referred to as the heterogeneous case. Finally, we merge the above elements to validate the choice of resource allocation schemes considering the deployed architecture
Bazin, Alexis. "Massive MIMO for 5G Scenarios with OFDM and FBMC/OQAM Waveforms". Thesis, Rennes, INSA, 2018. http://www.theses.fr/2018ISAR0019/document.
ESUME DE LA THESE EN ANGLAIS With the increase of the global data tmffic, the multiplication of co1mected devices and the diversification of the communication types, the fifth generation of cellular networks (5G) has to overcome a se1ies of challenges. In this context, massive MlMO systems hold a wide range of benefits by using a large number of antennas combined with appropriate signal processing techniques. Additionally, the use of the FBMC/OQAM modulation instead of the classical OFDM modulation may enhance the performance of the systems in cer1ain situations. Firstly, this thesis focuses on vehicular scenarios. In par1icular, massive MIMO systems are proposed to overcome the interference due to the Doppler effect for the uplink. We thus analytically highlight that increasing the number of receive antermas induces a drastic reduction of the impact of the Doppler effect. Moreover, the perfonnance of the OFDM and the FBMC/OQAM modulations are compared in this context for Non-Line-Of-Sight (NLOS) and Line-Of-Sight (LOS) environments. The second scenario investigated in this thesis considers communications in wide underse1ved areas. In this context, massive MIMO systems allow to create a long-range wireless back.haul link between two base stations. Thereby, the cost of deployment of the cellular networks is reduced. In this thesis r a new massive MLMO precoding technique is proposed in order to use the same fequency band for the backhaul link and the access links. Moreover, the impact of a desynchronization between the back haul link and the access links is studied and the use of the FBMC/OQAM modulation for the backhaul link is discussed
Chour, Hussein. "Full-Duplex Device-to-Device Communication for 5G Network". Thesis, CentraleSupélec, 2019. http://www.theses.fr/2019CSUP0002.
With the rapidly growing of the customers' data traffic demand, improving the system capacity and increasing the user throughput have become essential concerns for the future 5G wireless communication network. In this context, D2D communication and FD are proposed as potential solutions to increase the spatial spectrum utilization and the user rate in a cellular network. D2D allows two nearby devices to communicate without BS participation or with limited participation. On the other hand, FD communication enables simultaneous transmission and reception in the same frequency band. Due to the short distance property of D2D links, exploiting the FD technology in D2D communication is an excellent choice to further improve the cellular spectrum efficiency and the users’ throughput. However, practical FD transceivers add new challenges for D2D communication. For instance, the existing FD devices cannot perfectly eliminate the SI imposed on the receiver by the node’s own transmitter. Thus, the RSI which is tightly related to the transmitter power value highly affects the performance of FD transmission. Moreover, the FD technique creates additional interference in the network which may degrade its performance when compared with the half-duplex transmission. Thus, proper radio resource management is needed to exploit the benefits of FD and guarantee the QoS of the users. The works in this dissertation focus on the PA and CA of a FD-D2D network. In particular, this thesis first addresses the PA problem and proposes a simple yet efficient centralized optimal PA framework, and next, it derives the optimal joint PA and CA scheme for an FD-D2D network. A simple sub-optimal algorithm for resource allocation named CATPA, based on CA followed by PA, is also derived and proposed. This dissertation also develops, in the end, an efficient decentralized PA using game theory tools that will be an essential part of future works in the context of distributed radio resource management
Libri sul tema "5G (téléphonie mobile) – Cartes":
Venkataraman, Hrishikesh, e Ramona Trestian. 5G Radio Access Networks: Centralized RAN, Cloud-RAN and Virtualization of Small Cells. Taylor & Francis Group, 2017.
Arslan, Hüseyin, e Ertuğrul Başar. Flexible and Cognitive Radio Access Technologies for 5G and Beyond. Institution of Engineering & Technology, 2020.
Arslan, Hüseyin, e Ertuğrul Başar. Flexible and Cognitive Radio Access Technologies for 5G and Beyond. Institution of Engineering & Technology, 2020.
Ramzan, Naeem, e Muhammad Zeeshan Shakir. AI for Emerging Verticals: Human-Robot Computing, Sensing and Networking. Institution of Engineering & Technology, 2021.
Ramzan, Naeem, e Muhammad Zeeshan Shakir. AI for Emerging Verticals: Human-Robot Computing, Sensing and Networking. Institution of Engineering & Technology, 2020.