712 research outputs found

    Adaptive Data-driven Optimization using Transfer Learning for Resilient, Energy-efficient, Resource-aware, and Secure Network Slicing in 5G-Advanced and 6G Wireless Systems

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    Title from PDF of title page, viewed January 31, 2023Dissertation advisor: Cory BeardVitaIncludes bibliographical references (pages 134-141)Dissertation (Ph.D)--Department of Computer Science and Electrical Engineering. University of Missouri--Kansas City, 20225G–Advanced is the next step in the evolution of the fifth–generation (5G) technology. It will introduce a new level of expanded capabilities beyond connections and enables a broader range of advanced applications and use cases. 5G–Advanced will support modern applications with greater mobility and high dependability. Artificial intelligence and Machine Learning will enhance network performance with spectral efficiency and energy savings enhancements. This research established a framework to optimally control and manage an appropriate selection of network slices for incoming requests from diverse applications and services in Beyond 5G networks. The developed DeepSlice model is used to optimize the network and individual slice load efficiency across isolated slices and manage slice lifecycle in case of failure. The DeepSlice framework can predict the unknown connections by utilizing the learning from a developed deep-learning neural network model. The research also addresses threats to the performance, availability, and robustness of B5G networks by proactively preventing and resolving threats. The study proposed a Secure5G framework for authentication, authorization, trust, and control for a network slicing architecture in 5G systems. The developed model prevents the 5G infrastructure from Distributed Denial of Service by analyzing incoming connections and learning from the developed model. The research demonstrates the preventive measure against volume attacks, flooding attacks, and masking (spoofing) attacks. This research builds the framework towards the zero trust objective (never trust, always verify, and verify continuously) that improves resilience. Another fundamental difficulty for wireless network systems is providing a desirable user experience in various network conditions, such as those with varying network loads and bandwidth fluctuations. Mobile Network Operators have long battled unforeseen network traffic events. This research proposed ADAPTIVE6G to tackle the network load estimation problem using knowledge-inspired Transfer Learning by utilizing radio network Key Performance Indicators from network slices to understand and learn network load estimation problems. These algorithms enable Mobile Network Operators to optimally coordinate their computational tasks in stochastic and time-varying network states. Energy efficiency is another significant KPI in tracking the sustainability of network slicing. Increasing traffic demands in 5G dramatically increase the energy consumption of mobile networks. This increase is unsustainable in terms of dollar cost and environmental impact. This research proposed an innovative ECO6G model to attain sustainability and energy efficiency. Research findings suggested that the developed model can reduce network energy costs without negatively impacting performance or end customer experience against the classical Machine Learning and Statistical driven models. The proposed model is validated against the industry-standardized energy efficiency definition, and operational expenditure savings are derived, showing significant cost savings to MNOs.Introduction -- A deep neural network framework towards a resilient, efficient, and secure network slicing in Beyond 5G Networks -- Adaptive resource management techniques for network slicing in Beyond 5G networks using transfer learning -- Energy and cost analysis for network slicing deployment in Beyond 5G networks -- Conclusion and future scop

    Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services

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    This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book

    Design of Multi-Layer Protocol Architecture using Hybrid Optimal Link State Routing (HOLSR) Protocol for CR Networks

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    There is a lack of spectrum due to the rising demand for sensing device communication and the inefficient use of the existing available spectrum. Through opportunistic access to licenced bands, which does not obstruct the primary sensory users (PU), it is feasible to enhance the inefficient use of the current sensor device frequency spectrum. Cognitive settings are a demanding environment in which to carry out tasks like sensor network routing and spectrum access since it is difficult to access channels due to the presence of PUs. The basic goal of the routing problem in sensor networks is to establish and maintain wireless sensor multihop paths between cognitive sensor nodes. The frequency to be used as well as the number of hops at each sensor node along the path must be determined for this assignment. In order to improve performance while using less energy, scientists suggested a unique adaptive cross-layer optimisation subcarrier distribution technique with the HOLSR protocol for wireless sensor nodes. Throughput and energy consumption parameters are used to analyse the sensor network architecture protocol that has been developed. The energy usage of the sensor nodes in the network has increased by 50%. The performance of the proposed HOLSR algorithm is assessed using the simulation results, and the results are contrasted with those of a conventional multicarrier (MC) system in terms of bit error rate and throughput

    Design, Modelling and Analysis of Satcoms for UAV operations

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    Η ανάγκη για άμεση συνεισφορά, απόκριση και ακρίβεια των αποτελεσμάτων οδήγησε στην είσοδο των drones και ιδιαίτερα των μη επανδρωμένων εναέριων οχημάτων (UAV) ως νέα τεχνολογικά οχήματα. Ωστόσο, η ενσωμάτωση ενός τόσο κολοσσιαίου τεχνολογικού αποκτήματος δεν είναι καθόλου εύκολη υπόθεση. Πολλές απαιτήσεις εμφανίζονται σε διάφορους τομείς όπως τηλεπικοινωνίες, προβλήματα ωφέλιμου φορτίου που πρέπει να φέρει το UAV και σχέδια λειτουργίας, απαιτήσεις που πρέπει να πληρούνται για την αποφυγή προβλημάτων ασφάλειας, αποφυγή σύγκρουσης, ασταθείς συνδέσεις και άλλα. Σκοπός της παρούσας διπλωματικής εργασίας είναι να μελετήσει όσο το δυνατόν καλύτερα και αποτελεσματικότερα τη συμβολή των δορυφορικών επικοινωνιών στην επίτευξη αξιόπιστων και ανθεκτικών επιχειρήσεων Μη Επανδρωμένων Αεροσκαφών (UAV). Θα παρουσιαστεί μια ανάλυση τριών επιπέδων που θα αφορά τον Σχεδιασμό, τη Μοντελοποίηση και την Ανάλυση δορυφορικών επικοινωνιών σε συνδυασμό με λειτουργίες UAV με τρόπο που η αποτελεσματικότητα της ζεύξης θα είναι μέγιστη εφικτή. Σε τελική ανάλυση, θα πραγματοποιηθεί ένα πείραμα που θα συζητηθούν τα αποτελέσματα και οι παράμετροι που χρησιμοποιούνται προκειμένου να υπολογιστεί η αποτελεσματικότητα του προϋπολογισμού των ζεύξεων. Είναι σημαντικό να γνωρίζουμε ότι οι κυψελοειδείς επικοινωνίες έχουν παίξει μέχρι στιγμής τον πιο σημαντικό και ακριβή ρόλο τόσο στις επίγειες όσο και στις αεροπορικές επικοινωνίες. Αυτό πρόκειται να αλλάξει καθώς οι δορυφόροι υπόσχονται χαρακτηριστικά που δεν μπορούν να ανταγωνιστούν τα επίγεια δίκτυα, με αποτέλεσμα την ενοποίηση των UAV με τις δορυφορικές επικοινωνίες. Ωστόσο, τα πράγματα είναι ασαφή και οι κίνδυνοι που ενέχουν είτε από την άποψη των προσωπικών δεδομένων είτε από την ασφάλεια και την υγεία μπορούν να λειτουργήσουν ως εμπόδιο στην ανάπτυξη και την αναβάθμιση των επικοινωνιών.The need for immediate contribution, response, and accuracy of results has led to the entry of drones and especially Unmanned Aerial Vehicles (UAVs) as new technological vehicles. However, the integration of such a colossal technological acquisition is by no means an easy task. Many requirements appear in various areas such as telecommunications, payload problems that the UAV must carry, and operations plans, requirements that must be met to avoid safety issues, collision avoidance, unstable connections, and so more. The purpose of this thesis is to study as best as possible and most effectively the contribution of satellite communications to achieve reliable and durable Unmanned Aerial Vehicles (UAVs) operations. A three-level analysis will be presented which will concern the Design, Modeling, and Analysis of satellite communications in combination with UAV operations in a way where efficiency of the link will be maximum. After all, an experiment will take place that results and parameters used will be discussed in order to compute the efficiency of the link budget. It is important to know that cellular communications have so far played the most important and accurate role in both terrestrial and air communications. This is about to change as satellites promise features that cannot compete with terrestrial networks, resulting in the integration of UAVs with satellite communications. However, things are unclear, and the risks posed either from the point of view of personal data or from safety and health can act as an obstacle in developing and upgrading communications

    Resource Management and Backhaul Routing in Millimeter-Wave IAB Networks Using Deep Reinforcement Learning

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    Thesis (PhD (Electronic Engineering))--University of Pretoria, 2023..The increased densification of wireless networks has led to the development of integrated access and backhaul (IAB) networks. In this thesis, deep reinforcement learning was applied to solve resource management and backhaul routing problems in millimeter-wave IAB networks. In the research work, a resource management solution that aims to avoid congestion for access users in an IAB network was proposed and implemented. The proposed solution applies deep reinforcement learning to learn an optimized policy that aims to achieve effective resource allocation whilst minimizing congestion and satisfying the user requirements. In addition, a deep reinforcement learning-based backhaul adaptation strategy that leverages a recursive discrete choice model was implemented in simulation. Simulation results where the proposed algorithms were compared with two baseline methods showed that the proposed scheme provides better throughput and delay performance.Sentech Chair in Broadband Wireless Multimedia Communications.Electrical, Electronic and Computer EngineeringPhD (Electronic Engineering)Unrestricte

    Situation-aware Edge Computing

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    Future wireless networks must cope with an increasing amount of data that needs to be transmitted to or from mobile devices. Furthermore, novel applications, e.g., augmented reality games or autonomous driving, require low latency and high bandwidth at the same time. To address these challenges, the paradigm of edge computing has been proposed. It brings computing closer to the users and takes advantage of the capabilities of telecommunication infrastructures, e.g., cellular base stations or wireless access points, but also of end user devices such as smartphones, wearables, and embedded systems. However, edge computing introduces its own challenges, e.g., economic and business-related questions or device mobility. Being aware of the current situation, i.e., the domain-specific interpretation of environmental information, makes it possible to develop approaches targeting these challenges. In this thesis, the novel concept of situation-aware edge computing is presented. It is divided into three areas: situation-aware infrastructure edge computing, situation-aware device edge computing, and situation-aware embedded edge computing. Therefore, the concepts of situation and situation-awareness are introduced. Furthermore, challenges are identified for each area, and corresponding solutions are presented. In the area of situation-aware infrastructure edge computing, economic and business-related challenges are addressed, since companies offering services and infrastructure edge computing facilities have to find agreements regarding the prices for allowing others to use them. In the area of situation-aware device edge computing, the main challenge is to find suitable nodes that can execute a service and to predict a node’s connection in the near future. Finally, to enable situation-aware embedded edge computing, two novel programming and data analysis approaches are presented that allow programmers to develop situation-aware applications. To show the feasibility, applicability, and importance of situation-aware edge computing, two case studies are presented. The first case study shows how situation-aware edge computing can provide services for emergency response applications, while the second case study presents an approach where network transitions can be implemented in a situation-aware manner

    Programs and Courses Catalog 2023-2024

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    Contents: --- Academic Calendar--- Guide to Course Number Prefixes--- Course Number Explanation--- Common Course Numbers--- List of Programs by Department--- General Information--- Academic Regulations--- Academic Structure--- Admission Requirements--- Enrollment and Registration Procedures--- Fees and Financial Aid--- Graduate Information, Admission, Academic Regulations, and Degree Requirements--- Student Life--- The Fine and Performing Arts at UNI--- The University and Its Programs--- Undergraduate Information and Degree Requirements--- University Facilities and Educational Services--- Learning Outcomes--- Plan of Study (4-year plans)--- All Majors--- Business--- Education--- Humanities, Arts and Sciences--- Social and Behavioral Sciences--- Interdisciplinary--- College of Business--- Department of Accounting--- Department of Economics--- Department of Finance--- Department of Management--- Department of Marketing and Entrepreneurship--- College of Education--- Department of Curriculum and Instruction--- Department of Educational Psychology, Foundations, and Leadership Studies--- Department of Health, Recreation and Community Services--- Department of Kinesiology--- Special Education--- Teaching--- College of Humanities, Arts and Sciences--- Department of Applied Engineering & Technical Management--- Department of Art--- Department of Biology--- Department of Chemistry and Biochemistry--- Department of Communication and Media--- Department of Communication Sciences and Disorders--- Department of Computer Science--- Department of Earth and Environmental Sciences--- Iowa Lakeside Laboratory--- Department of Languages and Literatures--- Department of Mathematics--- School of Music--- Department of Philosophy and World Religions--- Department of Physics--- Science Education--- Department of Theatre--- College of Social and Behavioral Sciences--- School of Applied Human Sciences--- Department of Geography--- Department of History--- Department of Military Science--- Department of Political Science--- Department of Psychology--- Department of Social Work--- Department of Sociology, Anthropology, and Criminology--- Social Science--- Interdisciplinary Majors, Minors and Program Certificates--- Bachelor of Applied Science Degree Programs--- Bachelor of Arts Degree and Minor Programs--- Master of Arts Degree Programs--- Program Certificates--- Undergraduate Studies--- Regents Alternative Pathway to Iowa Licensure (RAPIL)https://scholarworks.uni.edu/uni_catalogs/1122/thumbnail.jp

    Seamless coverage for the next generation wireless communication networks

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    Data demand has exponentially increased due to the rapid growth of wireless and mobile devices traffic in recent years. With the advent of the fifth generation, 5G, and beyond networks, users will be able to take advantage of additional services beyond the capability of current wireless networks while maintaining a highquality experience. The exploitation of millimeter-wave (mm-wave) frequency in 5G promises to meet the demands of future networks with the motto of providing high data rate coverage with low latency to its users, which will allow future networks to function more efficiently. However, while planning a network using mm-wave frequencies, it is important to consider their small coverage footprints and weak penetration resistance. Heterogeneous network planning with the dense deployment of the small cells is one way of overcoming these issues, yet, without proper planning of the integrated network within the same or different frequencies could lead to other problems such as coverage gaps and frequent handovers; due to the natural physics of mm-wave frequencies. Therefore this thesis focuses on bringing ultra-reliable low-latency communication for mm-wave indoor users by increasing the indoor coverage and reducing the frequency of handovers. Towards achieving this thesis’s aim, a detailed literature review of mm-wave coverage is provided in Chapter 2. Moreover, a table that highlights the penetration loss of materials at various frequencies is provided as a result of thorough research in this field, which will be helpful to the researchers investigating this subject. According to our knowledge, this is the first table presenting the most studies that have been conducted in this field. Chapter 3 examines the interference effect of the outdoor base station (BS) inside the building in the context of a heterogeneous network environment. A single building model scenario is created, and the interference analysis is performed to observe the effects of different building materials used as walls. The results reveal the importance of choosing the material type when outdoor BS is close to the building. Moreover, the interference effect of outdoor BS should be minimized when the frequency re-use technique is deployed over very short distances. Chapter 4 presents two-fold contributions, in addition to providing a comprehensive handover study of mm-wave technology. The first study starts with addressing the problem of modelling users’ movement in the indoor environment. Therefore, a user-based indoor mobility prediction via Markov chain with an initial transition matrix is proposed, acquired from Q-learning algorithms. Based on the acquired knowledge of the user’s mobility in the indoor environment, the second contribution of this chapter provides a pre-emptive handover algorithm to provide seamless connection while the user moves within the heterogeneous network. The implementation and evaluation of the proposed algorithm show a reduction in the handover signalling costs by more than 50%, outperforming conventional handover algorithms. Lastly, Chapter 5 contributes to providing robust signal coverage for coverage blind areas and implementing and evaluating the proposed handover algorithm with the intelligent reflective surface. The results show a reduction in the handover signalling costs by more than 33%, outperforming conventional handover algorithms with the pre-emptive handover initiation

    Blockchain-assisted UAV communication systems: a comprehensive survey

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    Unmanned aerial vehicles (UAVs) have recently established their capacity to provide cost-effective and credible solutions for various real-world scenarios. UAVs provide an immense variety of services due to their autonomy, mobility, adaptability, and communications interoperability. Despite the expansive use of UAVs to support ground communications, data exchanges in those networks are susceptible to security threats because most communication is through radio or Wi-Fi signals, which are easy to hack. While several techniques exist to protect against cyberattacks. Recently emerging technology blockchain could be one of promising ways to enhance data security and user privacy in peer-to-peer UAV networks. Borrowing the superiorities of blockchain, multiple entities can communicate securely, decentralized, and equitably. This article comprehensively overviews privacy and security integration in blockchain-assisted UAV communication. For this goal, we present a set of fundamental analyses and critical requirements that can help build privacy and security models for blockchain and help manage and support decentralized data storage systems. The UAV communication system's security requirements and objectives, including availability, authentication, authorization, confidentiality, integrity, privacy, and non-repudiation, are thoroughly examined to provide a deeper insight. We wrap up with a discussion of open research challenges, the constraints of current UAV standards, and potential future research directions
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