A multi-traffic inter-cell interference coordination scheme in dense cellular networks

This paper proposes a novel semi-distributed and practical ICIC scheme based on the Almost Blank Sub-Frame (ABSF) approach specified by 3GPP. We define two mathematical programming problems for the cases of guaranteed and best-effort traffic, and use game theory to study the properties of the derived ICIC distributed schemes, which are compared in detail against unaffordable centralized schemes. Based on the analysis of the proposed models, we define Distributed Multi-traffic Scheduling (DMS), a unified distributed framework for adaptive interference-aware scheduling of base stations in future cellular networks, which accounts for both guaranteed and best-effort traffic. DMS follows a two-tier approach, consisting of local ABSF schedulers, which perform the resource distribution between the guaranteed and best effort traffic, and a light-weight local supervisor, which coordinates ABSF local decisions. As a result of such a two-tier design, DMS requires very light signaling to drive the local schedulers to globally efficient operating points. As shown by means of numerical results, DMS allows to: (i) maximize radio resources resue; (ii) provide requested quality for guaranteed traffic; (iii) minimize the time dedicated to guaranteed traffic to leave room for best-effort traffic; and (iv) maximize resource utilization efficiency for the best-effort traffic.The work of A. Banchs was supported by the H2020 5GMoNArch project (Grant Agreement No. 761445) and the 5GCity project of the Spanish Ministry of Economy and Competitiveness (TEC2016-76795-C6-3-R). The work of V. Mancuso has been supported by a Ramon y Cajal grant (ref: RYC-2014-16285) in part by the Spanish Ministry of Science, Innovation and Universities under grant TIN2017-88749-R and by the Madrid Regional Government through the TIGRE5-CM program (S2013/ICE-2919)

Enhanced content update dissemination through D2D in 5G cellular networks

Opportunistic traffic offloading has been proposed to tackle overload problems in cellular networks. However, existing proposals only address device-to-device-based offloading techniques with deadline-based data propagation, and neglect content injection procedures. In contrast, we tackle the offloading issue from another perspective: the base station interference coordination problem during content injection. In particular, we focus on dissemination of contents, and aim at the minimization of the total transmission time spent by base stations to inject the contents into the network. We leverage the almost blank subframe technique to keep under control the intercell interference in such a process. We formulate an optimization problem, prove that it is NP-hard and NP-complete, and propose a near-optimal heuristic to solve it. Our algorithm substantially outperforms classical intercell interference approaches, as we evaluate through the simulation of LTE-A networks.This work has been initially supported by the FP7 CROWD Project under Grant 318115 and later on followed up by the H2020 5G NORMA Project under Grant 671584. The work of V. Mancuso was supported by the Ramon y Cajal Grant from the Spanish Ministry of Economy and Competitiveness under Grant RYC-2014-01335

Analytical characterization of inband and outband D2D Communications for network access

Mención Internacional en el título de doctorCooperative short-range communication schemes provide powerful tools to solve interference and resource shortage problems in wireless access networks. With such schemes, a mobile node with excellent cellular connectivity can momentarily accept to relay traffic for its neighbors experiencing poor radio conditions and use Device-to-Device (D2D) communications to accomplish the task. This thesis provides a novel and comprehensive analytical framework that allows evaluating the effects of D2D communications in access networks in terms of spectrum and energy efficiency. The analysis covers the cases in which D2D communications use the same bandwidth of legacy cellular users (in-band D2D) or a different one (out-band D2D) and leverages on the characterization of underlying queueing systems and protocols to capture the complex intertwining of short-range and legacy WiFi and cellular communications. The analysis also unveils how D2D affects the use and scope of other optimization techniques used for, e.g., interference coordination and fairness in resource distribution. Indeed, characterizing the performance of D2D-enabled wireless access networks plays an essential role in the optimization of system operation and, as a consequence, permits to assess the general applicability of D2D solutions. With such characterization, we were able to design several mechanisms that improve system capabilities. Specifically, we propose bandwidth resource management techniques for controlling interference when cellular users and D2D pairs share the same spectrum, we design advanced and energy-aware access selection mechanisms, we show how to adopt D2D communications in conjunction with interference coordination schemes to achieve high and fair throughputs, and we discuss on end-to-end fairness—beyond the use of access network resources—when D2D communications is adopted in C-RAN. The results reported in this thesis show that identifying performance bottlenecks is key to properly control network operation, and, interestingly, bottlenecks may not be represented just by wireless resources when end-to-end fairness is of concern.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Marco Ajmone Marsan.- Secretario: Miquel Payaró Llisterri.- Vocal: Omer Gurewit

Enhancements in spectrum management techniques for heterogeneous 5G future networks

Mención Internacional en el título de doctorIn the last decade, cellular networks are undergoing with a radical change in their basic design foundations. The huge increase in traffic demand requires a novel design of future cellular networks. Driven by this increase, a network densification phenomena is occurring thereby, which in turns requires to devise efficient and reliable mechanisms to deal with the interference problems resulting from such densification. The architecture and mechanisms resulting from such drastic re-design of the network are commonly referred under the term ’5G network’. In this context, this work unveils that current networking solutions are no longer sufficient to (i) provide the required network spectral efficiency, and (ii) guarantee the desired level of quality of experience from the user side. In order to address this problem, in this thesis we propose a novel SDN-like framework that incorporates the needed mechanisms to improve spectral efficiency while delivering the desired quality of experience to users. In particular, our architecture includes the following two approaches: Our first approach addresses the intercell interference issues resulting from high network densification. To this end, we propose novel mechanisms to mitigate the inter-cell interference problem. We address the design of such schemes from two angles: (i) a controller-aided mechanism, which gathers all the information of the network at a centralized point and, based on this information, optimally schedules the transmission from different users, and (ii) a semi-distributed mechanism, which limits the signaling overhead involved in sending the information to a centralized point while providing close to optimal performance. One of the key novelties of our scheduling algorithms is that they are based on the Almost Blank SubFrame (ABSF) scheme; indeed, this scheme has been standardized only recently and very little work has addressed the design of algorithm to use it. Our second approach addresses spectral efficiency from a complementary angle: cellular traffic offloading for content update applications. This approach leverages high user mobility to offload the cellular downlink traffic through a device-to-device communication. In this context, we propose an adaptive algorithm to decide how to optimally transmit content to base stations in order to maximize traffic offload. By relying on control theory techniques, our approach delivers near optimally performance. A third key contribution of this thesis is the design of a solution that combines the above two approaches. In particular, our solution takes into account that traffic offload is taking place in the network and addresses the design of an optimal scheduling algorithm that leverages on the Almost Blank SubFrame (ABSF) scheme. Indeed, the combination of these kind of approaches has received little attention from the literature. The feasibility and performance of the approaches described above are thoroughly evaluated and compared against state-of-the-art solutions through an exhaustive simulation campaign. Our results show that the proposed approaches outperform conventional eICIC techniques as well as standard offloading mechanisms, respectively, and confirm their feasibility in terms of overhead and computational complexity. To the best of our knowledge, this thesis is the first attempt to design an unified framework which is able to optimally perform offloading for content-update distribution applications while boosting the network performance in terms of spectral efficiency.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Pablo Serrano Yáñez-Mingot.- Secretario: Juan José Alacaraz Espín.- Vocal: Matteo Cesan

Obstacle Avoidance Cell Discovery using mm-waves Directive Antennas in 5G Networks

With the advent of next-generation mobile devices, wireless networks must be upgraded to fill the gap between huge user data demands and scarce channel capacity. Mm-waves tech- nologies appear as the key-enabler for the future 5G networks design, exhibiting large bandwidth availability and high data rate. As counterpart, the small wave-length incurs in a harsh signal propagation that limits the transmission range. To overcome this limitation, array of antennas with a relatively high number of small elements are used to exploit beamforming techniques that greatly increase antenna directionality both at base station and user terminal. These very narrow beams are used during data transfer and tracking techniques dynamically adapt the direction according to terminal mobility. During cell discovery when initial synchronization must be acquired, however, directionality can delay the process since the best direction to point the beam is unknown. All space must be scanned using the tradeoff between beam width and transmission range. Some support to speed up the cell search process can come from the new architectures for 5G currently being investigated, where conventional wireless network and mm-waves technologies coexist. In these architecture a functional split between C-plane and U-plane allows to guarantee the continuous availability of a signaling channel through conventional wireless technologies with the opportunity to convey context information from users to network. In this paper, we investigate the use of position information provided by user terminals in order to improve the performance of the cell search process. We analyze mm-wave propagation environment and show how it is possible to take into account of position inaccuracy and reflected rays in presence of obstacle

Decentralized learning based indoor interference mitigation for 5G-and-beyond systems

Due to the explosive growth of data traffic and poor indoor coverage, ultra-dense network (UDN) has been introduced as a fundamental architectural technology for 5G-and-beyond systems. As the telecom operator is shifting to a plug-and-play paradigm in mobile networks, network planning and optimization become difficult and costly, especially in residential small-cell base stations (SBSs) deployment. Under this circumstance, severe inter-cell interference (ICI) becomes inevitable. Therefore, interference mitigation is of vital importance for indoor coverage in mobile communication systems. In this paper, we propose a fully distributed self-learning interference mitigation (SLIM) scheme for autonomous networks under a model-free multi-agent reinforcement learning (MARL) framework. In SLIM, individual SBSs autonomously perceive surrounding interferences and determine downlink transmit power without necessity of signaling interactions between SBSs for mitigating interferences. To tackle the dimensional disaster of joint action in the MARL model, we employ the Mean Field Theory to approximate the action value function to greatly decrease the computational complexity. Simulation results based on 3GPP dual-stripe urban model demonstrate that SLIM outperforms several existing known interference coordination schemes in mitigating interference and reducing power consumption while guaranteeing UEs' quality of service for autonomous UDNs

D4.3 Final Report on Network-Level Solutions

Research activities in METIS reported in this document focus on proposing solutions to the network-level challenges of future wireless communication networks. Thereby, a large variety of scenarios is considered and a set of technical concepts is proposed to serve the needs envisioned for the 2020 and beyond. This document provides the final findings on several network-level aspects and groups of solutions that are considered essential for designing future 5G solutions. Specifically, it elaborates on: -Interference management and resource allocation schemes -Mobility management and robustness enhancements -Context aware approaches -D2D and V2X mechanisms -Technology components focused on clustering -Dynamic reconfiguration enablers These novel network-level technology concepts are evaluated against requirements defined by METIS for future 5G systems. Moreover, functional enablers which can support the solutions mentioned aboveare proposed. We find that the network level solutions and technology components developed during the course of METIS complement the lower layer technology components and thereby effectively contribute to meeting 5G requirements and targets.Aydin, O.; Valentin, S.; Ren, Z.; Botsov, M.; Lakshmana, TR.; Sui, Y.; Sun, W.... (2015). D4.3 Final Report on Network-Level Solutions. http://hdl.handle.net/10251/7675

Optimisation de la gestion des interférences inter-cellulaires et de l'attachement des mobiles dans les réseaux cellulaires LTE

Driven by an exponential growth in mobile broadband-enabled devices and a continue dincrease in individual data consumption, mobile data traffic has grown 4000-fold over the past 10 years and almost 400-million-fold over the past 15 years. Homogeneouscellular networks have been facing limitations to handle soaring mobile data traffic and to meet the growing end-user demand for more bandwidth and betterquality of experience. These limitations are mainly related to the available spectrumand the capacity of the network. Telecommunication industry has to address these challenges and meet exploding demand. At the same time, it has to guarantee a healthy economic model to reduce the carbon footprint which is caused by mobile communications.Heterogeneous Networks (HetNets), composed of macro base stations and low powerbase stations of different types, are seen as the key solution to improve spectral efficiency per unit area and to eliminate coverage holes. In such networks, intelligent user association and interference management schemes are needed to achieve gains in performance. Due to the large imbalance in transmission power between macroand small cells, user association based on strongest signal received is not adapted inHetNets as only few users would attach to low power nodes. A technique based onCell Individual Offset (CIO) is therefore required to perform load balancing and to favor some Small Cell (SC) attraction against Macro Cell (MC). This offset is addedto users’ Reference Signal Received Power (RSRP) measurements and hence inducing handover towards different eNodeBs. As Long Term Evolution (LTE) cellular networks use the same frequency sub-bands, mobile users may experience strong inter-cellxv interference, especially at cell edge. Therefore, there is a need to coordinate resource allocation among the cells and minimize inter-cell interference. To mitigate stronginter-cell interference, the resource, in time, frequency and power domain, should be allocated efficiently. A pattern for each dimension is computed to permit especially for cell edge users to benefit of higher throughput and quality of experience. The optimization of all these parameters can also offer gain in energy use. In this thesis,we propose a concrete versatile dynamic solution performing an optimization of user association and resource allocation in LTE cellular networks maximizing a certainnet work utility function that can be adequately chosen. Our solution, based on gametheory, permits to compute Cell Individual Offset and a pattern of power transmission over frequency and time domain for each cell. We present numerical simulations toillustrate the important performance gain brought by this optimization. We obtain significant benefits in the average throughput and also cell edge user through put of40% and 55% gains respectively. Furthermore, we also obtain a meaningful improvement in energy efficiency. This work addresses industrial research challenges and assuch, a prototype acting on emulated HetNets traffic has been implemented.Conduit par une croissance exponentielle dans les appareils mobiles et une augmentation continue de la consommation individuelle des données, le trafic de données mobiles a augmenté de 4000 fois au cours des 10 dernières années et près de 400millions fois au cours des 15 dernières années. Les réseaux cellulaires homogènes rencontrent de plus en plus de difficultés à gérer l’énorme trafic de données mobiles et à assurer un débit plus élevé et une meilleure qualité d’expérience pour les utilisateurs.Ces difficultés sont essentiellement liées au spectre disponible et à la capacité du réseau.L’industrie de télécommunication doit relever ces défis et en même temps doit garantir un modèle économique pour les opérateurs qui leur permettra de continuer à investir pour répondre à la demande croissante et réduire l’empreinte carbone due aux communications mobiles. Les réseaux cellulaires hétérogènes (HetNets), composés de stations de base macro et de différentes stations de base de faible puissance,sont considérés comme la solution clé pour améliorer l’efficacité spectrale par unité de surface et pour éliminer les trous de couverture. Dans de tels réseaux, il est primordial d’attacher intelligemment les utilisateurs aux stations de base et de bien gérer les interférences afin de gagner en performance. Comme la différence de puissance d’émission est importante entre les grandes et petites cellules, l’association habituelle des mobiles aux stations de bases en se basant sur le signal le plus fort, n’est plus adaptée dans les HetNets. Une technique basée sur des offsets individuelles par cellule Offset(CIO) est donc nécessaire afin d’équilibrer la charge entre les cellules et d’augmenter l’attraction des petites cellules (SC) par rapport aux cellules macro (MC). Cette offset est ajoutée à la valeur moyenne de la puissance reçue du signal de référence(RSRP) mesurée par le mobile et peut donc induire à un changement d’attachement vers différents eNodeB. Comme les stations de bases dans les réseaux cellulaires LTE utilisent les mêmes sous-bandes de fréquences, les mobiles peuvent connaître une forte interférence intercellulaire, en particulier en bordure de cellules. Par conséquent, il est primordial de coordonner l’allocation des ressources entre les cellules et de minimiser l’interférence entre les cellules. Pour atténuer la forte interférence intercellulaire, les ressources, en termes de temps, fréquence et puissance d’émission, devraient être alloués efficacement. Un modèle pour chaque dimension est calculé pour permettre en particulier aux utilisateurs en bordure de cellule de bénéficier d’un débit plus élevé et d’une meilleure qualité de l’expérience. L’optimisation de tous ces paramètres peut également offrir un gain en consommation d’énergie. Dans cette thèse, nous proposons une solution dynamique polyvalente effectuant une optimisation de l’attachement des mobiles aux stations de base et de l’allocation des ressources dans les réseaux cellulaires LTE maximisant une fonction d’utilité du réseau qui peut être choisie de manière adéquate.Notre solution, basée sur la théorie des jeux, permet de calculer les meilleures valeurs pour l’offset individuelle par cellule (CIO) et pour les niveaux de puissance à appliquer au niveau temporel et fréquentiel pour chaque cellule. Nous présentons des résultats des simulations effectuées pour illustrer le gain de performance important apporté par cette optimisation. Nous obtenons une significative hausse dans le débit moyen et le débit des utilisateurs en bordure de cellule avec 40 % et 55 % de gains respectivement. En outre, on obtient un gain important en énergie. Ce travail aborde des défis pour l’industrie des télécoms et en tant que tel, un prototype de l’optimiseur a été implémenté en se basant sur un trafic HetNets émulé

Heterogeneous Cellular Networks: From Resource Allocation To User Association

Heterogeneous networking paradigm addresses the ever growing need for capacity and coverage in wireless networks by deploying numerous low power base stations overlaying the existing macro cellular coverage. Heterogeneous cellular networks encompass many deployment scenarios, with different backhauling techniques (wired versus wireless backhauling), different transmission coordination mechanisms and resource allocation schemes, different types of links operating at different bands and air-interface technologies, and different user association schemes. Studying these deployment scenarios and configurations, and understanding the interplay between different processes is challenging. In the first part of the thesis, we present a flow-based optimization framework that allows us to obtain the throughput performance of a heterogeneous network when the network processes are optimized jointly. This is done under a given system ``snapshot'', where the system parameters like the channel gains and the number of users are fixed and assumed known. Our framework allows us to configure the network parameters to allocate optimal throughputs to these flows in a fair manner. This is an offline-static model and thus is intended to be used at the engineering and planning phase to compare many potential configurations and decide which ones to study further. Using the above-mentioned formulation, we have been able to study a large set of deployment scenarios and different choices of resource allocation, transmission coordination, and user association schemes. This has allowed us to provide a number of important engineering insights on the throughput performance of different scenarios and their configurations. The second part of our thesis focuses on understanding the impact of backhaul infrastructure's capacity limitation on the radio resource management algorithms like user scheduling and user association. Most existing studies assume an ideal backhaul. This assumption, however, needs to be revisited as backhaul considerations are critical in heterogeneous networks due to the economic considerations. In this study, we formulate a global $\alpha$-fair user scheduling problem under backhaul limitations, and show how this limitation has a fundamental impact on user scheduling. Using results from convex optimization, we characterize the solution of optimal backhaul-aware user scheduling and show that simple heuristics can be used to obtain good throughput performance with relatively low complexity/overhead. We also study the related problem of user association under backhaul-limitations. This study is a departure from our ``snapshot'' approach. We discuss several important design considerations for an online user association scheme. We present a relatively simple backhaul-unaware user association scheme and show that it is very efficient as long as the network has fine-tuned the resource allocation