Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201

Mission-Critical Communications from LMR to 5G: a Technology Assessment approach for Smart City scenarios

Radiocommunication networks are one of the main support tools of agencies that carry out actions in Public Protection & Disaster Relief (PPDR), and it is necessary to update these communications technologies from narrowband to broadband and integrated to information technologies to have an effective action before society. Understanding that this problem includes, besides the technical aspects, issues related to the social context to which these systems are inserted, this study aims to construct scenarios, using several sources of information, that helps the managers of the PPDR agencies in the technological decisionmaking process of the Digital Transformation of Mission-Critical Communication considering Smart City scenarios, guided by the methods and approaches of Technological Assessment (TA).As redes de radiocomunicações são uma das principais ferramentas de apoio dos órgãos que realizam ações de Proteção Pública e Socorro em desastres, sendo necessário atualizar essas tecnologias de comunicação de banda estreita para banda larga, e integra- las às tecnologias de informação, para se ter uma atuação efetiva perante a sociedade . Entendendo que esse problema inclui, além dos aspectos técnicos, questões relacionadas ao contexto social ao qual esses sistemas estão inseridos, este estudo tem por objetivo a construção de cenários, utilizando diversas fontes de informação que auxiliem os gestores destas agências na tomada de decisão tecnológica que envolve a transformação digital da Comunicação de Missão Crítica considerando cenários de Cidades Inteligentes, guiado pelos métodos e abordagens de Avaliação Tecnológica (TA)

Recent Advances in Cellular D2D Communications

Device-to-device (D2D) communications have attracted a great deal of attention from researchers in recent years. It is a promising technique for offloading local traffic from cellular base stations by allowing local devices, in physical proximity, to communicate directly with each other. Furthermore, through relaying, D2D is also a promising approach to enhancing service coverage at cell edges or in black spots. However, there are many challenges to realizing the full benefits of D2D. For one, minimizing the interference between legacy cellular and D2D users operating in underlay mode is still an active research issue. With the 5th generation (5G) communication systems expected to be the main data carrier for the Internet-of-Things (IoT) paradigm, the potential role of D2D and its scalability to support massive IoT devices and their machine-centric (as opposed to human-centric) communications need to be investigated. New challenges have also arisen from new enabling technologies for D2D communications, such as non-orthogonal multiple access (NOMA) and blockchain technologies, which call for new solutions to be proposed. This edited book presents a collection of ten chapters, including one review and nine original research works on addressing many of the aforementioned challenges and beyond

View on 5G Architecture: Version 2.0

The 5G Architecture Working Group as part of the 5GPPP Initiative is looking at capturing novel trends and key technological enablers for the realization of the 5G architecture. It also targets at presenting in a harmonized way the architectural concepts developed in various projects and initiatives (not limited to 5GPPP projects only) so as to provide a consolidated view on the technical directions for the architecture design in the 5G era. The first version of the white paper was released in July 2016, which captured novel trends and key technological enablers for the realization of the 5G architecture vision along with harmonized architectural concepts from 5GPPP Phase 1 projects and initiatives. Capitalizing on the architectural vision and framework set by the first version of the white paper, this Version 2.0 of the white paper presents the latest findings and analyses with a particular focus on the concept evaluations, and accordingly it presents the consolidated overall architecture design

Quality of experience characterization and provisioning in mobile cellular networks

Παραδοσιακά, οι προηγούμενες γενεές κινητών κυψελωτών δικτύων έχουν σχεδιαστεί με κριτήρια Ποιότητας Υπηρεσίας, έτσι ώστε να πληρούν συγκεκριμένες απαιτήσεις διαφόρων υπηρεσιών. Η «Ποιότητα Εμπειρίας» έχει, ωστόσο, πρόσφατα εμφανιστεί ως έννοια, επηρεάζοντας το σχεδιασμό των μελλοντικών γενεών των δικτύων, δίνοντας σαφή έμφαση στην πραγματικά επιτευχθείσα εμπειρία του τελικού χρήστη. Η εμφάνιση της έννοιας της Ποιότητας Εμπειρίας οφείλεται στην αναπόφευκτη, ισχυρή μετάβαση που βιώνει η βιομηχανία των Τηλεπικοινωνιών από συστημο-κεντρικά δίκτυα σε πιο χρηστο-κεντρικές λύσεις και στόχους. Οι πάροχοι κινητών δικτύων, οι πάροχοι υπηρεσιών, οι προγραμματιστές εφαρμογών, αλλά και άλλα ενδιαφερόμενα μέλη που εμπλέκονται στην αλυσίδα παροχής υπηρεσιών προσελκύονται από τις ευκαιρίες που μπορεί να προσφέρει η ενσωμάτωση γνώσης Ποιότητας Εμπειρίας στο επιχειρηματικό τους μοντέλο. Πράγματι, η παρεχόμενη Ποιότητα Εμπειρίας αποτελεί έναν καθοριστικό παράγοντα διαφοροποίησης μεταξύ των διαφόρων παικτών, μία τάση που αναμένεται να γίνει ακόμη πιο έντονη τα επόμενα χρόνια. Υποκινούμενη από αυτή την χρηστο-κεντρική τάση, η έρευνα που διεξάγεται σε αυτή τη διατριβή έχει ως στόχο την διερεύνηση των προκλήσεων και των ευκαιριών που προκύπτουν στα σύγχρονα κινητά κυψελωτά δίκτυα όταν λαμβάνεται υπόψιν η έννοια της Ποιότητας Εμπειρίας. Τέτοιες ευκαιρίες αφορούν, καταρχήν, τη δυνατότητα κατανόησης της Ποιότητας Εμπειρίας που επιτυγχάνει ένας πάροχος κατά την προσφορά μίας υπηρεσίας. Αυτό μπορεί να επιτευχθεί με την υλοποίηση και ενσωμάτωση μεθόδων αξιολόγησης Ποιότητας Εμπειρίας στην πραγματικού-χρόνου λειτουργία ενός δικτύου. Εν συνεχεία, ακολουθεί η εκμετάλλευση της συλλεγμένης ευφυΐας που σχετίζεται με την Ποιότητα Εμπειρίας, προκειμένου να επανεξεταστούν υφιστάμενοι μηχανισμοί επιπέδου δικτύου (π.χ., χρονο-προγραμματισμός ραδιοπόρων) ή μηχανισμοί επιπέδου εφαρμογής (π.χ., ροή βίντεο), αλλά και να προταθούν καινοτόμες διαστρωματικές προσεγγίσεις προς όφελος της Ποιότητας Εμπειρίας. Επιπλέον, υπάρχει η δυνατότητα πρότασης νέων αλγορίθμων που προκύπτουν από τα εγγενή χαρακτηριστικά της Ποιότητας Εμπειρίας, όπως η μη γραμμική επίδραση μετρικών Ποιότητας Υπηρεσίας στην Ποιότητα Εμπειρίας, με στόχο την περαιτέρω βελτίωσή της. Σε αυτή την κατεύθυνση, στην παρούσα διατριβή, διερευνώνται και αξιοποιούνται μοντέλα και μετρικές εκτίμησης Ποιότητας Εμπειρίας με στόχο την ποσοτικοποίησή της, έχοντας ως απώτερο στόχο την εισαγωγή βελτιώσεων στους υφιστάμενους μηχανισμούς κινητών κυψελωτών δικτύων. Ο πυρήνας αυτής της διατριβής είναι η πρόταση μίας κυκλικής διεργασίας παροχής Ποιότητας Εμπειρίας που επιτρέπει τον έλεγχο, την παρακολούθηση (ήτοι, τη μοντελοποίηση) και τη διαχείριση της Ποιότητας Εμπειρίας σε ένα κυψελωτό δίκτυο. Κάθε μία από αυτές τις λειτουργίες αναλύεται περαιτέρω, ενώ έμφαση δίνεται στις λειτουργίες μοντελοποίησης και διαχείρισης. Όσον αφορά τη μοντελοποίηση, γίνεται περιγραφή και ταξινόμηση των μεθόδων εκτίμησης και των δεικτών επιδόσεων Ποιότητας Εμπειρίας. Η παραμετρική εκτίμηση της ποιότητας αναδεικνύεται ως η πιο ελκυστική κατηγορία μοντελοποίησης Ποιότητας Εμπειρίας σε κινητά κυψελωτά δίκτυα, οπότε και περιγράφεται διεξοδικά για ευρέως χρησιμοποιούμενους τύπους υπηρεσιών, όπως η συνομιλία (φωνή) μέσω Internet Protocol (IP) και η μετάδοση βίντεο. Όσον αφορά τη διαχείριση Ποιότητας Εμπειρίας, προτείνονται νέοι μηχανισμοί που επιδεικνύουν βελτιώσεις στην εμπειρία των τελικών χρηστών, και συγκεκριμένα: α) ένα σχήμα ελέγχου των επικοινωνιών συσκευής-προς-συσκευή που λαμβάνει υπόψιν την εμπειρία των χρηστών, β) ένας «συνεπής» αλγόριθμος χρονο-προγραμματισμού ραδιοπόρων που βελτιώνει την Ποιότητα Εμπειρίας του χρήστη μετριάζοντας τις διακυμάνσεις της ρυθμαπόδοσης του δικτύου, και γ) ένας μηχανισμός προσαρμοστικής ροής βίντεο με γνώσεις «πλαισίου», ο οποίος επιτυγχάνει την εξάλειψη διακοπών του βίντεο σε συνθήκες χαμηλού εύρους ζώνης. Επιπλέον, προτείνεται μία εφαρμογή Ποιότητας Εμπειρίας βασισμένη στην αρχιτεκτονική Software-Defined Networking (SDN), ονόματι “QoE-SDN APP”, η οποία επιτρέπει την ανάδραση πληροφοριών δικτύου από παρόχους κινητής τηλεφωνίας σε παρόχους υπηρεσιών βίντεο, αναδεικνύοντας πλεονεκτήματα ως προς την Ποιότητα Εμπειρίας για τους πελάτες των παρόχων βίντεο αλλά και ως προς την εξοικονόμηση εύρους ζώνης για τους φορείς εκμετάλλευσης δικτύου. Εν κατακλείδι, η παρούσα διατριβή προωθεί την ενοποίηση του ερευνητικού πεδίου της Ποιότητας Εμπειρίας με τον τομέα των κινητών επικοινωνιών, καθώς και τη συνεργασία αμοιβαίου ενδιαφέροντος μεταξύ των παρόχων δικτύου (επίπεδο δικτύου) με τους παρόχους υπηρεσιών (επίπεδο εφαρμογής), αναδεικνύοντας την δυναμική από τέτοιου είδους προσεγγίσεις για όλους τους εμπλεκόμενους φορείς.Traditionally, previous generations of mobile cellular networks have been designed with Quality of Service (QoS) criteria in mind, so that they manage to meet specific service requirements. Quality of Experience (QoE) has, however, recently emerged as a concept, disrupting the design of future network generations by giving clear emphasis on the actually achieved user experience. The emergence of the QoE concept has been a result of the inevitable strong transition that the Telecom industry is currently experiencing from system-centric networks to more user-centric solutions and objectives. Mobile network operators, service providers, application developers, as well as other stakeholders involved in the service provisioning chain have been attracted by the opportunities that the integration of the QoE concept could bring to their business; indeed, the provisioned QoE constitutes a determining factor of differentiation among different stakeholders, a tendency which is expected to become even more intense in the years to come. Motivated by this boost towards user-centricity, the objective of the research conducted in this thesis is to explore the challenges and opportunities that arise in modern mobile cellular networks when QoE is considered. Such opportunities concern, first of all, the possibility to comprehend the QoE that a provider achieves when provisioning a service. This can be enabled by the implementation and integration of QoE assessment methods into the real-time operation of a network. Then, the next step is the exploitation of collected QoE-related intelligence in order to re-examine existing network-layer mechanisms (e.g., radio scheduling), or application-layer mechanisms (e.g., video streaming), as well as propose novel cross-layer approaches towards ameliorating the achieved QoE. Moreover, the opportunity emerges to propose novel algorithms that stem from the inherent idiosyncrasies of QoE, such as the non-linear impact of QoS-related parameters on QoE, as a way to further enhance the users’ QoE. In this direction, throughout this thesis, QoE estimation models and metrics are explored and exploited in order to quantify QoE and thus, to improve existing mechanisms of mobile cellular networks. The core of this thesis is the proposal of a QoE provisioning cycle that allows the control, monitoring (i.e., modeling) and management of QoE in a cellular network. Each one of these functions is further analyzed, while emphasis is given on the modeling and management operations. In terms of modeling, QoE assessment methods and QoE-related performance indicators are described and classified. Parametric quality estimation is identified as the most appealing type of QoE estimation in mobile cellular networks, thus, it is thoroughly described for widely used types of services, such as Voice over IP (VoIP) and video streaming. In terms of QoE management, novel QoE-aware mechanisms that demonstrate QoE improvements for the users are proposed, namely: a) a QoE-driven Device-to-Device (D2D) communication management scheme that enhances end-user QoE, b) a “consistent” radio scheduling algorithm that improves the end-user QoE by mitigating throughput fluctuations, and c) a context-aware HTTP Adaptive Streaming (HAS) mechanism that successfully mitigates stallings (i.e., video freezing events) in the context of bandwidth-challenging scenarios. Moreover, a programmable QoE-SDN APP into the Software-Defined Networking (SDN) architecture is introduced, which enables network feedback exposure from mobile network operators to video service providers, revealing QoE benefits for the customers of video providers and bandwidth savings for the network operators. Overall, this thesis promotes the uniting of the domain of QoE with the domain of mobile communications, as well as the collaboration of mutual-interest between mobile network operators (network layer) and service providers (application layer), presenting the high potential from such approaches for all involved stakeholders

Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking

The emerging massive density of human-held and machine-type nodes implies larger traffic deviatiolns in the future than we are facing today. In the future, the network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly changing traffic demands both in time and space. This flexibility cannot be achieved when the network’s infrastructure remains static. To this end, the topic of UAVs (unmanned aerial vehicles) have enabled wireless communications, and networking has received increased attention. As mentioned above, the network must serve a massive density of nodes that can be either human-held (user devices) or machine-type nodes (sensors). If we wish to properly serve these nodes and optimize their data, a proper wireless connection is fundamental. This can be achieved by using UAV-enabled communication and networks. This Special Issue addresses the many existing issues that still exist to allow UAV-enabled wireless communications and networking to be properly rolled out

Prediction-based techniques for the optimization of mobile networks

Mención Internacional en el título de doctorMobile cellular networks are complex system whose behavior is characterized by the superposition of several random phenomena, most of which, related to human activities, such as mobility, communications and network usage. However, when observed in their totality, the many individual components merge into more deterministic patterns and trends start to be identifiable and predictable. In this thesis we analyze a recent branch of network optimization that is commonly referred to as anticipatory networking and that entails the combination of prediction solutions and network optimization schemes. The main intuition behind anticipatory networking is that knowing in advance what is going on in the network can help understanding potentially severe problems and mitigate their impact by applying solution when they are still in their initial states. Conversely, network forecast might also indicate a future improvement in the overall network condition (i.e. load reduction or better signal quality reported from users). In such a case, resources can be assigned more sparingly requiring users to rely on buffered information while waiting for the better condition when it will be more convenient to grant more resources. In the beginning of this thesis we will survey the current anticipatory networking panorama and the many prediction and optimization solutions proposed so far. In the main body of the work, we will propose our novel solutions to the problem, the tools and methodologies we designed to evaluate them and to perform a real world evaluation of our schemes. By the end of this work it will be clear that not only is anticipatory networking a very promising theoretical framework, but also that it is feasible and it can deliver substantial benefit to current and next generation mobile networks. In fact, with both our theoretical and practical results we show evidences that more than one third of the resources can be saved and even larger gain can be achieved for data rate enhancements.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Albert Banchs Roca.- Presidente: Pablo Serrano Yañez-Mingot.- Secretario: Jorge Ortín Gracia.- Vocal: Guevara Noubi

Addressing training data sparsity and interpretability challenges in AI based cellular networks

To meet the diverse and stringent communication requirements for emerging networks use cases, zero-touch arti cial intelligence (AI) based deep automation in cellular networks is envisioned. However, the full potential of AI in cellular networks remains hindered by two key challenges: (i) training data is not as freely available in cellular networks as in other fields where AI has made a profound impact and (ii) current AI models tend to have black box behavior making operators reluctant to entrust the operation of multibillion mission critical networks to a black box AI engine, which allow little insights and discovery of relationships between the configuration and optimization parameters and key performance indicators. This dissertation systematically addresses and proposes solutions to these two key problems faced by emerging networks. A framework towards addressing the training data sparsity challenge in cellular networks is developed, that can assist network operators and researchers in choosing the optimal data enrichment technique for different network scenarios, based on the available information. The framework encompasses classical interpolation techniques, like inverse distance weighted and kriging to more advanced ML-based methods, like transfer learning and generative adversarial networks, several new techniques, such as matrix completion theory and leveraging different types of network geometries, and simulators and testbeds, among others. The proposed framework will lead to more accurate ML models, that rely on sufficient amount of representative training data. Moreover, solutions are proposed to address the data sparsity challenge specifically in Minimization of drive test (MDT) based automation approaches. MDT allows coverage to be estimated at the base station by exploiting measurement reports gathered by the user equipment without the need for drive tests. Thus, MDT is a key enabling feature for data and artificial intelligence driven autonomous operation and optimization in current and emerging cellular networks. However, to date, the utility of MDT feature remains thwarted by issues such as sparsity of user reports and user positioning inaccuracy. For the first time, this dissertation reveals the existence of an optimal bin width for coverage estimation in the presence of inaccurate user positioning, scarcity of user reports and quantization error. The presented framework can enable network operators to configure the bin size for given positioning accuracy and user density that results in the most accurate MDT based coverage estimation. The lack of interpretability in AI-enabled networks is addressed by proposing a first of its kind novel neural network architecture leveraging analytical modeling, domain knowledge, big data and machine learning to turn black box machine learning models into more interpretable models. The proposed approach combines analytical modeling and domain knowledge to custom design machine learning models with the aim of moving towards interpretable machine learning models, that not only require a lesser training time, but can also deal with issues such as sparsity of training data and determination of model hyperparameters. The approach is tested using both simulated data and real data and results show that the proposed approach outperforms existing mathematical models, while also remaining interpretable when compared with black-box ML models. Thus, the proposed approach can be used to derive better mathematical models of complex systems. The findings from this dissertation can help solve the challenges in emerging AI-based cellular networks and thus aid in their design, operation and optimization