Mathematical Modelling and Analysis of Spatially Correlated Heterogeneous and Vehicular Networks - A Stochastic Geometry Approach

Heterogeneous Cellular Networks (HCNs) and vehicular communications are two key ingredients of future 5G communication networks, which aim at providing high data rates on the one former case and high reliability on the latter one. Nevertheless, in these two scenarios, interference is the main limiting factor, which makes achieving the required performance, i.e., data rate or reliability, a challenging task. Hence, in order to cope with such issue, concepts like uplink/downlink (UL/DL) decoupling, Interference-Aware (IA) strategies or cooperative communications with Cloud Radio Access Networks (CRANs) has been introduced for new releases of 4G and future 5G networks. Additionally, for the sake of increasing the data rates, new multiple access schemes like Non-Orthogonal Multiple Access (NOMA) has been proposed for 5G networks. All these techniques and concepts require accurate and tractable mathematical modelling for performance analysis. This analysis allows us to obtain theoretical insights about key performance indicators leading to a deep understanding about the considered techniques. Due to the random and irregular nature that exhibits HCNs, as well as vehicular networks, stochastic geometry has appeared recently as a promising tool for system-level modelling and analysis. Nevertheless, some features of HCNs and vehicular networks, like power control, scheduling or frequency planning, impose spatial correlations over the underlying point process that complicates significantly the mathematical analysis. In this thesis, it has been used stochastic geometry and point process theories to investigate the performance of these aforementioned techniques. Firstly, it is derived a mathematical framework for the analysis of an Interference-Aware Fractional Power Control (IAFPC) for interference mitigation in the UL of HCNs. The analysis reveals that IAFPC outperforms the classical FPC in terms of Spectral Efficiency (SE), average transmitted power, and mean and variance of the interference. Then, it is investigated the performance of a scheduling algorithm where the Mobile Terminals (MTs) may be turned off if they cause a level of interference greater than a given threshold. Secondly, a multi-user UL model to assess the coverage probability of different MTs in each cell is proposed. Then, the coverage probability of cellular systems under Hoyt fading (Nakagami-q) is studied. This fading model, allows us to consider more severe fading conditions than Rayleigh, which is normally the considered fading model for the sake of tractability. Thirdly, a novel NOMA-based scheme for CRANs is proposed, modelled and analyzed. In this scheme, two users are scheduled in the same resources according to NOMA; however the performance of cell-edge users is enhanced by means of coordinated beamforming. Finally, the performance of a decentralized Medium Access Control (MAC) algorithm for vehicular communications is investigated. With this strategy, the cellular network provides frequency and time synchronization for direct Vehicle to Vehicle (V2V) communication, which is based on its geographical information. The analysis demonstrates that there exists an operation regime where the performance is noise-limited. Then, the optimal transmit power that maximizes the Energy Efficiency (EE) of the system subject to a minimum capture probability constraint is derived

Cooperation strategies for inter-cell interference mitigation in OFDMA systems

Recently the use of modern cellular networks has drastically changed with the emerging Long Term Evolution Advanced (LTE-A) technology. Homogeneous networks which were initially designed for voice-centric and low data rates face unprecedented challenges for meeting the increasing traffic demands of high data-driven applications and their important quality of service requirements. Therefore, these networks are moving towards the so called Heterogeneous Networks (HetNets). HetNets represent a new paradigm for cellular networks as their nodes have different characteristics such as transmission power and radio frequency coverage area. Consequently, a HetNet shows completely different interference characteristics compared to homogeneous deployment and attention must be paid to these disparities when different tiers are collocated together. This is mostly due to the potential spectrum frequency reuse by the involved tiers in the HetNets. Hence, efficient inter-cell interference mitigation solutions in co-channel deployments of HetNets remain a challenge for both industry and academic researchers. This thesis focuses on LTE-A HetNet systems which are based on Orthogonal Frequency Division Multiplexing Access (OFDMA) modulation. Our aim is to investigate the aggressive interference issue that appears when different types of base stations are jointly deployed together and especially in two cases, namely Macro-Femtocells and Macro-Picocells co-existence. We propose new practical power adjustment solutions for managing inter-cell interference dynamically for both cases. In the first part dedicated to Femtocells and Macrocell coexistence, we design a MBS-assisted femtocell power adjustment strategy which takes into account femtocells users performance while mitigating the inter-cell interference on victim macrocell users. Further, we propose a new cooperative and context-aware interference mitigation method which is derived for realistic scenarios involving mobility of users and their varying locations. We proved numerically that the Femtocells are able to maintain their interference under a desirable threshold by adjusting their transmission power. Our strategies provide an efficient means for achieving the desired level of macrocell/femtocell throughput trade-off. In the second part of the studies where Picocells are deployed under the umbrella of the Macrocell, we paid a special attention and efforts to the interference management in the situation where Picocells are configured to set up a cell range expansion. We suggest a MBS-assisted collaborative scheme powered by an analytical model to predict the mobility of Macrocell users passing through the cell range expansion area of the picocell. Our goal is to adapt the muting ratio ruling the frequency resource partitioning between both tiers according to the mobility behavior of the range-expanded users, thereby providing an efficient trade-off between Macrocell and Picocell achievable throughputs.Récemment, l'utilisation des réseaux cellulaires a radicalement changé avec l’émergence de la quatrième génération (4G) de systèmes de télécommunications mobiles LTE/LTE-A (Long Term Evolution-Advanced). Les réseaux de générations précédentes (3G), initialement conçus pour le transport de la voix et les données à faible et moyen débits, ont du mal à faire face à l’augmentation accrue du trafic de données multimédia tout en répondant à leurs fortes exigences et contraintes en termes de qualité de service (QdS). Pour mieux répondre à ces besoins, les réseaux 4G ont introduit le paradigme des Réseaux Hétérogènes (HetNet).Les réseaux HetNet introduisent une nouvelle notion d’hétérogénéité pour les réseaux cellulaires en introduisant le concept des smalls cells (petites cellules) qui met en place des antennes à faible puissance d’émission. Ainsi, le réseau est composé de plusieurs couches (tiers) qui se chevauchent incluant la couverture traditionnelle macro-cellulaire, les pico-cellules, les femto-cellules, et les relais. Outre les améliorations des couvertures radio en environnements intérieurs, les smalls cells permettent d’augmenter la capacité du système par une meilleure utilisation du spectre et en rapprochant l’utilisateur de son point d’accès au réseau. Une des conséquences directes de cette densification cellulaire est l’interférence générée entre les différentes cellules des diverses couches quand ces dernières réutilisent les mêmes fréquences. Aussi, la définition de solutions efficaces de gestion des interférences dans ce type de systèmes constitue un de leurs défis majeurs. Cette thèse s’intéresse au problème de gestion des interférences dans les systèmes hétérogènes LTE-A. Notre objectif est d’apporter des solutions efficaces et originales au problème d’interférence dans ce contexte via des mécanismes d’ajustement de puissance des petites cellules. Nous avons pour cela distingués deux cas d’étude à savoir un déploiement à deux couches macro-femtocellules et macro-picocellules. Dans la première partie dédiée à un déploiement femtocellule et macrocellule, nous concevons une stratégie d'ajustement de puissance des femtocellules assisté par la macrocellule et qui prend en compte les performances des utilisateurs des femtocells tout en atténuant l'interférence causée aux utilisateurs des macrocellules sur leurs liens montants. Cette solution offre l’avantage de la prise en compte de paramètres contextuels locaux aux femtocellules (tels que le nombre d’utilisateurs en situation de outage) tout en considérant des scénarios de mobilité réalistes. Nous avons montré par simulation que les interférences sur les utilisateurs des macrocellules sont sensiblement réduites et que les femtocellules sont en mesure de dynamiquement ajuster leur puissance d'émission pour atteindre les objectifs fixés en termes d’équilibre entre performance des utilisateurs des macrocellules et celle de leurs propres utilisateurs. Dans la seconde partie de la thèse, nous considérons le déploiement de picocellules sous l'égide de la macrocellule. Nous nous sommes intéressés ici aux solutions d’extension de l’aire picocellulaire qui permettent une meilleure association utilisateur/cellule permettant de réduire l’interférence mais aussi offrir une meilleure efficacité spectrale. Nous proposons donc une approche basée sur un modèle de prédiction de la mobilité des utilisateurs qui permet de mieux ajuster la proportion de bande passante à partager entre la macrocellule et la picocellule en fonction de la durée de séjour estimée de ces utilisateurs ainsi que de leur demandes en bande passante. Notre solution a permis d’offrir un bon compromis entre les débits réalisables de la Macro et des picocellules

A Study about Heterogeneous Network Issues Management based on Enhanced Inter-cell Interference Coordination and Machine Learning Algorithms

Under the circumstance of fast growing demands for mobile data, Heterogeneous Networks (HetNets) has been considered as one of the key technologies to solve 1000 times mobile data challenge in the coming decade. Although the unique multi-tier topology of HetNets has achieved high spectrum efficiency and enhanced Quality of Service (QoS), it also brings a series of critical issues. In this thesis, we present an investigation on understanding the cause of HetNets challenges and provide a research on state of arts techniques to solve three major issues: interference, offloading and handover. The first issue addressed in the thesis is the cross-tier interference of HetNets. We introduce Almost Blank Subframes (ABS) to free small cell UEs from cross-tier interference, which is the key technique of enhanced Inter-Cell Interference Coordination (eICIC). Nash Bargain Solution (NBS) is applied to optimize ABS ratio and UE partition. Furthermore, we propose a power based multi-layer NBS Algorithm to obtain optimal parameters of Further enhanced Inter-cell Interference Coordination (FeICIC), which significantly improve macrocell efficiency compared to eICIC. This algorithm not only introduces dynamic power ratio but also defined opportunity cost for each layer instead of conventional zero-cost partial fairness. Simulation results show the performance of proposed algorithm may achieve up to 31.4% user throughput gain compared to eICIC and fixed power ratio FeICIC. This thesis’ second focusing issue is offloading problem of HetNets. This includes (1) UE offloading from macro cell and (2) small cell backhaul offloading. For first aspect, we have discussed the capability of machine learning algorithms tackling this challenge and propose the User-Based K-means Algorithm (UBKCA). The proposed algorithm establishes a closed loop Self-Organization system on our HetNets scenario to maintain desired offloading factor of 50%, with cell edge user factor 17.5% and CRE bias of 8dB. For second part, we further apply machine learning clustering method to establish cache system, which may achieve up to 70.27% hit-ratio and reduce request latency by 60.21% for Youtube scenario. K-Nearest Neighbouring (KNN) is then applied to predict new users’ content preference and prove our cache system’s suitability. Besides that, we have also proposed a system to predict users’ content preference even if the collected data is not complete. The third part focuses on offloading phase within HetNets. This part detailed discusses CRE’s positive effect on mitigating ping-pong handover during UE offloading, and CRE’s negative effect on increasing cross-tier interference. And then a modified Markov Chain Process is established to map the handover phases for UE to offload from macro cell to small cell and vice versa. The transition probability of MCP has considered both effects of CRE so that the optimal CRE value for HetNets can be achieved, and result for our scenario is 7dB. The combination of CRE and Handover Margin is also discussed

Mobility management in multi-RAT multiI-band heterogeneous networks

Support for user mobility is the raison d'etre of mobile cellular networks. However, mounting pressure for more capacity is leading to adaption of multi-band multi-RAT ultra-dense network design, particularly with the increased use of mmWave based small cells. While such design for emerging cellular networks is expected to offer manyfold more capacity, it gives rise to a new set of challenges in user mobility management. Among others, frequent handovers (HO) and thus higher impact of poor mobility management on quality of user experience (QoE) as well as link capacity, lack of an intelligent solution to manage dual connectivity (of user with both 4G and 5G cells) activation/deactivation, and mmWave cell discovery are the most critical challenges. In this dissertation, I propose and evaluate a set of solutions to address the aforementioned challenges. The beginning outcome of our investigations into the aforementioned problems is the first ever taxonomy of mobility related 3GPP defined network parameters and Key Performance Indicators (KPIs) followed by a tutorial on 3GPP-based 5G mobility management procedures. The first major contribution of the thesis here is a novel framework to characterize the relationship between the 28 critical mobility-related network parameters and 8 most vital KPIs. A critical hurdle in addressing all mobility related challenges in emerging networks is the complexity of modeling realistic mobility and HO process. Mathematical models are not suitable here as they cannot capture the dynamics as well as the myriad parameters and KPIs involved. Existing simulators also mostly either omit or overly abstract the HO and user mobility, chiefly because the problems caused by poor HO management had relatively less impact on overall performance in legacy networks as they were not multi-RAT multi-band and therefore incurred much smaller number of HOs compared to emerging networks. The second key contribution of this dissertation is development of a first of its kind system level simulator, called SyntheticNET that can help the research community in overcoming the hurdle of realistic mobility and HO process modeling. SyntheticNET is the very first python-based simulator that fully conforms to 3GPP Release 15 5G standard. Compared to the existing simulators, SyntheticNET includes a modular structure, flexible propagation modeling, adaptive numerology, realistic mobility patterns, and detailed HO evaluation criteria. SyntheticNET’s python-based platform allows the effective application of Artificial Intelligence (AI) to various network functionalities. Another key challenge in emerging multi-RAT technologies is the lack of an intelligent solution to manage dual connectivity with 4G as well 5G cell needed by a user to access 5G infrastructure. The 3rd contribution of this thesis is a solution to address this challenge. I present a QoE-aware E-UTRAN New Radio-Dual Connectivity (EN-DC) activation scheme where AI is leveraged to develop a model that can accurately predict radio link failure (RLF) and voice muting using the low-level measurements collected from a real network. The insights from the AI based RLF and mute prediction models are then leveraged to configure sets of 3GPP parameters to maximize EN-DC activation while keeping the QoE-affecting RLF and mute anomalies to minimum. The last contribution of this dissertation is a novel solution to address mmWave cell discovery problem. This problem stems from the highly directional nature of mmWave transmission. The proposed mmWave cell discovery scheme builds upon a joint search method where mmWave cells exploit an overlay coverage layer from macro cells sharing the UE location to the mmWave cell. The proposed scheme is made more practical by investigating and developing solutions for the data sparsity issue in model training. Ability to work with sparse data makes the proposed scheme feasible in realistic scenarios where user density is often not high enough to provide coverage reports from each bin of the coverage area. Simulation results show that the proposed scheme, efficiently activates EN-DC to a nearby mmWave 5G cell and thus substantially reduces the mmWave cell discovery failures compared to the state of the art cell discovery methods

Contributions to Analysis and Mitigation of Cochannel Interference in Cellular Wireless Networks

Cellular wireless networks have become a commodity. We use our cellular devices every day to connect to others, to conduct business, for entertainment. Strong demand for wireless access has made corresponding parts of radio spectrum very valuable. Consequently, network operators and their suppliers are constantly being pressured for its efficient use. Unlike the first and second generation cellular networks, current generations do not therefore separate geographical sites in frequency. This universal frequency reuse, combined with continuously increasing spatial density of the transmitters, leads to challenging interference levels in the network. This dissertation collects several contributions to analysis and mitigation of interference in cellular wireless networks. The contributions are categorized and set in the context of prior art based on key characteristics, then they are treated one by one. The first contribution encompasses dynamic signaling that measures instantaneous interference situations and allows only for such transmissions that do not harm each other excessively. A novel forward signaling approach is introduced as an alternative to traditional reverse signaling. Forward signaling allows the interference management decisions to be done at the receiver, where there is more relevant information available. The second contribution analyzes cross-link interference in heterogeneous networks. Cross-link interference is interference between downlink and uplink transmissions that can appear in time-division duplex (TDD) networks. It is shown that uplink reception of small cells can be disturbed considerably by macrocell downlink transmissions. We proposes an intuitive solution to the problem based on power control. Users in small cells have generally enough power headroom as the distance to the small base station is often short. The third contribution provides an extensive analysis of a specific interference managment method that the Long-Term Evolution (LTE) applies in cochannel heterogeneous deployments. We analyze this so-called time muting using a modern stochastic geometry approach and show that performance of the method strongly depends on residual interference in the muted sections of time. The fourth and last contribution analyzes the impact of interference rank, i.e., number of spatial streams at the interferer, on a beamformed or spatially block coded transmission. It is shown that when the interferer chooses to transmit multiple spatial streams, spreading the power in spatial domain has potential to decrease probability of outage at neighbor receiver, especially if the neighbor transmission uses beamforming

D13.1 Fundamental issues on energy- and bandwidth-efficient communications and networking

Deliverable D13.1 del projecte europeu NEWCOM#The report presents the current status in the research area of energy- and bandwidth-efficient communications and networking and highlights the fundamental issues still open for further investigation. Furthermore, the report presents the Joint Research Activities (JRAs) which will be performed within WP1.3. For each activity there is the description, the identification of the adherence with the identified fundamental open issues, a presentation of the initial results, and a roadmap for the planned joint research work in each topic.Preprin

Resource and power management in next generation networks

The limits of today’s cellular communication systems are constantly being tested by the exponential increase in mobile data traffic, a trend which is poised to continue well into the next decade. Densification of cellular networks, by overlaying smaller cells, i.e., micro, pico and femtocells, over the traditional macrocell, is seen as an inevitable step in enabling future networks to support the expected increases in data rate demand. Next generation networks will most certainly be more heterogeneous as services will be offered via various types of points of access (PoAs). Indeed, besides the traditional macro base station, it is expected that users will also be able to access the network through a wide range of other PoAs: WiFi access points, remote radio-heads (RRHs), small cell (i.e., micro, pico and femto) base stations or even other users, when device-to-device (D2D) communications are supported, creating thus a multi-tiered network architecture. This approach is expected to enhance the capacity of current cellular networks, while patching up potential coverage gaps. However, since available radio resources will be fully shared, the inter-cell interference as well as the interference between the different tiers will pose a significant challenge. To avoid severe degradation of network performance, properly managing the interference is essential. In particular, techniques that mitigate interference such Inter Cell Interference Coordination (ICIC) and enhanced ICIC (eICIC) have been proposed in the literature to address the issue. In this thesis, we argue that interference may be also addressed during radio resource scheduling tasks, by enabling the network to make interference-aware resource allocation decisions. Carrier aggregation technology, which allows the simultaneous use of several component carriers, on the other hand, targets the lack of sufficiently large portions of frequency spectrum; a problem that severely limits the capacity of wireless networks. The aggregated carriers may, in general, belong to different frequency bands, and have different bandwidths, thus they also may have very different signal propagation characteristics. Integration of carrier aggregation in the network introduces additional tasks and further complicates interference management, but also opens up a range of possibilities for improving spectrum efficiency in addition to enhancing capacity, which we aim to exploit. In this thesis, we first look at the resource allocation in problem in dense multitiered networks with support for advanced features such as carrier aggregation and device-to-device communications. For two-tiered networks with D2D support, we propose a centralised, near optimal algorithm, based on dynamic programming principles, that allows a central scheduler to make interference and traffic-aware scheduling decisions, while taking into consideration the short-lived nature of D2D links. As the complexity of the central scheduler increases exponentially with the number of component carriers, we further propose a distributed heuristic algorithm to tackle the resource allocation problem in carrier aggregation enabled dense networks. We show that the solutions we propose perform significantly better than standard solutions adopted in cellular networks such as eICIC coupled with Proportional Fair scheduling, in several key metrics such as user throughput, timely delivery of content and spectrum and energy efficiency, while ensuring fairness for backward compatible devices. Next, we investigate the potentiality to enhance network performance by enabling the different nodes of the network to reduce and dynamically adjust the transmit power of the different carriers to mitigate interference. Considering that the different carriers may have different coverage areas, we propose to leverage this diversity, to obtain high-performing network configurations. Thus, we model the problem of carrier downlink transmit power setting, as a competitive game between teams of PoAs, which enables us to derive distributed dynamic power setting algorithms. Using these algorithms we reach stable configurations in the network, known as Nash equilibria, which we show perform significantly better than fixed power strategies coupled with eICIC