As 5G and O-RAN become more widely used, the number of user equipment requesting access to the network will increase. This will require operators to expand their 5G solutions by purchasing more hardware to handle the increase in demand. The acquisition of new hardware will have both an economic and an environmental impact. Hardware is costly for operators, both in initial cost and when operating it. There is also a significant energy cost associated, which has a negative environmental impact.     This thesis explores the benefits of more advanced control over the path taken within the Radio Access Network, with the goal of increasing the number of user equipment able to connect to a static set of hardware. The control comes from new algorithms designed with the intuition that providing connections with only the bare essentials and nothing more would, in theory, increase the capacity of the whole network. Three algorithms were tested, with one representing a basic control method of selecting the first valid connection, and the other two were built on the intuition of the worst acceptable connection.     The three algorithms were tested on four different shapes of network configuration at four different sizes. The tests were run on a graph data structure implemented in C++ that represents the logical paths a connection could take. This resulted in a noticeable improvement in networks that exhibited a triangular structure, with more units as one moved toward the edge of the network. The largest improvement observed managed to fit 18.9% more units into the network.

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This thesis comprehensively examines the rApp lifecycle within the O-RAN Alliance (O- RAN) Non-Real Time RIC (Non-RT RIC) framework, serving as a practical guide for exper- imental research and development. The focus is on the entire lifecycle of rApp development, from designing and onboarding to deployment and execution, using a spectral efficiency op- timization use case to illustrate the process. The study develops and integrates a Spectrum Optimization (SO)rApp employing Reinforcement Learning (RL) techniques, specifically a Deep Q-Network (DQN) model, within the O-RAN architecture. The research highlights how the SOrApp dynamically allocates spectrum resources to enhance network performance under varying demand conditions. Utilizing the Network Simulator (NS)-3 5G-LENA simulator, the thesis replicates diverse service demand scenarios to evaluate the rApp's effectiveness in optimizing spectral efficiency. The findings demonstrate that integrating Artificial Intelligence (AI)-driven rApps within the O-RAN framework significantly improves spectral efficiency and overall network performance, providing valuable insights and methodologies for future research and practical implementations in 5G networking. / Master of Science / As 5G networks grow more advanced, managing them effectively becomes increasingly chal- lenging. This thesis explores a method to improve network performance using specialized software applications, known as rApp, within the O-RAN Non-RT RIC framework. By focusing on the lifecycle of these rApps—how they are created, onboarded, deployed, and executed. To illustrate this process, used a real-world example of optimizing the efficiency of spectrum use, which is crucial for maintaining high-speed data and reliable communication in 5G networks. Our findings show that integrating intelligent rApps driven by Machine Learning (ML) can significantly enhance the performance and efficiency of 5G networks, offering valuable insights for future innovations in this rapidly evolving field.

Thesis (D.M.A.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 124-128). Available also in a digital version from Dissertation Abstracts.

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There is a lack of understanding of the threat vectors and attacks in Radio Access Network (RAN) systems. In addition, there is a lack of knowledge in adversary behaviour and tactics in RAN. To gain an increased understanding of the threat landscape in RANs and potentially increase the overall security for RANs, this thesis project designed, implemented, and evaluated a honeypot for Ericsson’s RAN. Developing a suitable honeypot required an initial literature study of honeypots, RANs, and Long-Term Evolution (LTE) networks. In addition, previous research and work related to this topic were included in the literature study. The open-source Secure Shell Protocol (SSH) honeypot project, Cowrie, was used as a fundamental building block for the honeypot. Moreover, a high-level architecture of the honeypot system (HoneyRAN) was designed and used as a basis for the implementation process. For evaluating the honeypot, a penetration test was conducted in which an internal Ericsson penetration tester evaluated the honeypot. The Elasticsearch, Logstash, and Kibana (ELK) stack was utilised to facilitate log analysis. The results from the penetration test were better than expected and are promising as HoneyRAN achieved the three claimed goals/objectives: understanding adversarial behaviour and tactics, stalling the adversaries, and early detection of attacks. The outcome of the evaluation suggests that HoneyRAN is a good initial approach for increasing the overall security of RANs and that honeypots are an effective deception technique for stalling attackers. The conclusions from the evaluation of HoneyRAN are that HoneyRAN’s implementation using Cowrie achieved an essential desired outcome, namely realism, deception strategies are essential to implement deception techniques (such as honeypots) effectively, and the design and implementation choices of HoneyRAN provides a foundation for other solutions. / Det finns begränsad förståelse för hotvektorer och attacker i RAN system. Dessutom finns det även begränsad kunskap om fientlig beteende och taktiker som används i RAN. För att få en ökad förståelse för de hotbilderna som finns i RAN så designade, implementerade och utvärderade detta avhandlingsprojekt en så kallad honungskruka för Ericssons RAN. Att utveckla en lämplig honungskruka krävde en inledande litteraturstudie på honungskrukor, RAN, och LTE nätverk. I litteraturstudien krävdes det även att man utförde en forskning om tidigare forskning och arbeten relaterat till detta ämne. En översikt på de komponenter som behövdes för att implementera honungskrukan (HoneyRAN) skapades och användes som grund för implementeringsprocessen. För att utvärdera systemet genomfördes ett penetrationstest som utfördes av en intern penetrationstestare på Ericsson. ELK stack användes för att underlätta logganalys. Resultaten från penetrationstestet var bättre än förväntat och är lovande eftersom honungskrukan uppnådde de tre påstådda målen: att få en förståelse av fientlig beteende och taktik, att uppehålla motståndarna, och att upptäcka tidiga faser av attacker. Dessutom tyder resultatet på att HoneyRAN är ett bra första steg till att öka den övergripande säkerheten i RAN och att honungskrukor är en effektiv vilseledningsteknik för att uppehålla attackerare. Slutsatserna från utvärderingen av HoneyRAN är att användingen av Cowrie uppnådde en väsentlig faktor, nämligen att HoneyRAN ser realistisk ut, vilseledningsstrategier är viktiga för att kunna effektivt implementera en honungskruka, och designvalen som togs för implementeringen av Honey- RAN kan utgöra en grund för framtida lösningar att bygga vidare på.

Yes / Tumour suppressor proteins, such as p53, BRCA1, and ABC, play key roles in preventing the development of a malignant phenotype, but those that function as transcriptional regulators need to enter the nucleus in order to function. The export of proteins between the nucleus and cytoplasm is complex. It occurs through nuclear pores and exported proteins need a nuclear export signal (NES) to bind to nuclear exportin proteins, including CRM1 (Chromosomal Region Maintenance protein 1), and the energy for this process is provided by the RanGTP/RanGDP gradient. Due to the loss of DNA repair and cell cycle checkpoints, drug resistance is a major problem in cancer treatment, and often an initially successful treatment will fail due to the development of resistance. An important mechanism underlying resistance is nuclear export, and a number of strategies that can prevent nuclear export may reverse resistance. Examples include inhibitors of CRM1, antibodies to the nuclear export signal, and alteration of nuclear pore structure. Each of these are considered in this review.

The thesis speculates upon the three movements of Concerto da Camera II (1987), scored for Bb clarinet, string quartet and piano) in these four aspects: 1) the formal structure, 2) the manipulation of the notes of whole-tone, octatonic, and chromatic scales in octave displacement, 3) the potential combination of subsets that present different levels of pitch transformation in melodic and harmonic structure, and 4) the usage of intervals of minor seconds, tritones, and perfect fourths or fifths which dominates the linear writing. All of these features demonstrate that the music has strong structural elements in form, motives, and sonorities, which unify the piece in an aurally coherent style as an organic whole. This study should provide more insight into the understanding of Ran's unique compositional technique and style.

De nos jours, la montée en débit observée dans les réseaux mobiles est une problématique. A long terme, la densification des réseaux radios mobiles s'avérera inefficace. En plus de cela cette densification entraînera une baisse de rentabilité des réseaux d'accès mobiles et augmentera la complexité au niveau de la gestion des fréquences mobile qui accroîtra inéluctablement le risque de la présence des interférences. Pour pallier ce manque de rentabilité et pour faciliter le déploiement de certaines techniques d'optimisation et d'amélioration de l'interface air comme le « Coordinated MultiPoint » (CoMP), les acteurs des télécommunications proposent une nouvelle architecture innovante désignée par les termes Mobile Cloud ou « Centralized or Cloud Radio Access Network » (C-RAN). Le C-RAN consiste à déporter l'entité de traitement des données numérisées appelée « Base Band Unit » (BBU) du site d'antenne vers un local plus sécurisé nommé « Central Oce (CO) ». L'entité de traitement radio dénommée « Remote Radio Head (RRH) »est toujours localisée sur le site d'antenne. Cette délocalisation crée un nouveau segment réseau appelé « fronthaul ». Le fronthaul est un segment réseau très gourmand en bande passante par conséquent la fibre est désignée comme le support idéal pour assurer la communication bidirectionnelle entre la RRH et la BBU. Dans notre thèse, nous avons étudié les solutions de déploiement du fronthaul. Etant donné que l'interface fronthaul utilise de grands débits pour la transmission de données numérisées, elle est soumise à un phénomène physique nommé gigue qui a tendance à dégrader les performances de transmission. Les effets et l'impact de la gigue sur l'interface fronthaul et sur l'interface air ont été aussi étudiés. / In Europe, the competition between the mobile operators is so strong that the profitability of the mobile network has decreased. The cost to implement, to operate and to upgrade the mobile network is increasing while the revenues generated by the latter are not sufficient. Therefore, the operators should find the way to reduce the CAPEX and the OPEX. To keep competitive, the operators have begun to think about a novel RAN architecture. This new architecture is called Centralized or Cloud Radio Access Network. The traditional antenna site consists of the Radio Remote Head (RRH) which performs the radio processing, and the Base Band Unit (BBU) which carries out the digital processing. The principle of C-RAN consists to move the BBU from antenna site towards the local secured belonging to an operator called Central Office (CO). The move of BBU from antenna site to CO leads to the appearance of a new network segment called fronthaul. During this thesis, the different solutions to the deployment of fronthaul are studied and also the effects and the impacts of jitter on the fronthaul interface.

Cloud-Radio Access Network (C-RAN) est une architecture prometteuse pour faire face à l’augmentation exponentielle des demandes de trafic de données et surmonter les défis des réseaux de prochaine génération (5G). Le principe de base de CRAN consiste à diviser la station de base traditionnelle en deux entités : les unités de bande de base (BaseBand Unit, BBU) et les têtes radio distantes (Remote Radio Head, RRH) et à mettre en commun les BBUs de plusieurs stations dans des centres de données centralisés (pools de BBU). Ceci permet la réduction des coûts d’exploitation, l’amélioration de la capacité du réseau ainsi que des gains en termes d’utilisation des ressources. Pour atteindre ces objectifs, les opérateurs réseaux ont besoin d’investiguer de nouveaux algorithmes pour les problèmes d’allocation de ressources permettant ainsi de faciliter le déploiement de l’architecture C-RAN. La plupart de ces problèmes sont très complexes et donc très difficiles à résoudre. Par conséquent, nous utilisons l’optimisation combinatoire qui propose des outils puissants pour adresser ce type des problèmes.Un des principaux enjeux pour permettre le déploiement du C-RAN est de déterminer une affectation optimale des RRHs (antennes) aux centres de données centralisés (BBUs) en optimisant conjointement la latence sur le réseau de transmission fronthaul et la consommation des ressources. Nous modélisons ce problème à l’aide d’une formulation mathématique basée sur une approche de programmation linéaire en nombres entiers permettant de déterminer les stratégies optimales pour le problème d’affectation des ressources entre RRH-BBU et nous proposons également des heuristiques afin de pallier la difficulté au sens de la complexité algorithmique quand des instances larges du problème sont traitées, permettant ainsi le passage à l’échelle. Une affectation optimale des antennes aux BBUs réduit la latence de communication attendue et offre des gains en termes d’utilisation des ressources. Néanmoins, ces gains dépendent fortement de l’augmentation des niveaux d’interférence inter-cellulaire causés par la densité élevée des antennes déployées dans les réseaux C-RANs. Ainsi, nous proposons une formulation mathématique exacte basée sur les méthodes Branch-and-Cut qui consiste à consolider et ré-optimiser les rayons de couverture des antennes afin de minimiser les interférences inter-cellulaires et de garantir une couverture maximale du réseau conjointement. En plus de l’augmentation des niveaux d’interférence, la densité élevée des cellules dans le réseau CRAN augmente le nombre des fonctions BBUs ainsi que le trafic de données entre les antennes et les centres de données centralisés avec de fortes exigences en termes de latence sur le réseau fronthaul. Par conséquent, nous discutons dans la troisième partie de cette thèse comment placer d’une manière optimale les fonctions BBUs en considérant la solution split du 3GPP afin de trouver le meilleur compromis entre les avantages de la centralisation dans C-RAN et les forts besoins en latence et bande passante sur le réseau fronthaul. Nous proposons des algorithmes (exacts et heuristiques) issus de l’optimisation combinatoire afin de trouver rapidement des solutions optimales ou proches de l’optimum, même pour des instances larges du problèmes. / Cloud Radio Access Network (C-RAN) has been proposed as a promising architecture to meet the exponential growth in data traffic demands and to overcome the challenges of next generation mobile networks (5G). The main concept of C-RAN is to decouple the BaseBand Units (BBU) and the Remote Radio Heads (RRH), and place the BBUs in common edge data centers (BBU pools) for centralized processing. This gives a number of benefits in terms of cost savings, network capacity improvement and resource utilization gains. However, network operators need to investigate scalable and cost-efficient algorithms for resource allocation problems to enable and facilitate the deployment of C-RAN architecture. Most of these problems are very complex and thus very hard to solve. Hence, we use combinatorial optimization which provides powerful tools to efficiently address these problems.One of the key issues in the deployment of C-RAN is finding the optimal assignment of RRHs (or antennas) to edge data centers (BBUs) when jointly optimizing the fronthaul latency and resource consumption. We model this problem by a mathematical formulation based on an Integer Linear Programming (ILP) approach to provide the optimal strategies for the RRH-BBU assignment problem and we propose also low-complexity heuristic algorithms to rapidly reach good solutions for large problem instances. The optimal RRH-BBU assignment reduces the expected latency and offers resource utilization gains. Such gains can only be achieved when reducing the inter-cell interference caused by the dense deployment of cell sites. We propose an exact mathematical formulation based on Branch-and-Cut methods that enables to consolidate and re-optimize the antennas radii in order to jointly minimize inter-cell interference and guarantee a full network coverage in C-RAN. In addition to the increase of inter-cell interference, the high density of cells in C-RAN increases the amount of baseband processing as well as the amount of data traffic demands between antennas and centralized data centers when strong latency requirements on fronthaul network should be met. Therefore, we discuss in the third part of this thesis how to determine the optimal placement of BBU functions when considering 3GPP split option to find optimal tradeoffs between benefits of centralization in C-RAN and transport requirements. We propose exact and heuristic algorithms based on combinatorial optimization techniques to rapidly provide optimal or near-optimal solutions even for large network sizes.