17 research outputs found

    Design of static intercell interference coordination schemes for realistic lte-based cellular networks

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    Today, 3.5 and 4G systems including Long Term Evolution (LTE) and LTE-Advanced (LTE-A) support packet-based services and provide mobile broadband access for bandwidth-hungry applications. In this context of fast evolution, new and challenging technical issues must be e ectively addressed. The nal target is to achieve a signi cant step forward toward the improvement of the Quality of Experience (QoE). To that end, interference management has been recognized by the industry as a key enabler for cellular technologies based on OFDMA. Indeed, with a low frequency reuse factor, intercell interference (ICI) becomes a major concern since the Quality of Service (QoS) is not uniformly delivered across the network, it remarkably depends on user position. Hence, cell edge performance is an important issue in LTE and LTE-A. Intercell Interference Coordination (ICIC) encompasses strategies whose goal is to keep ICI at cell edges as low as possible. This alleviates the aforementioned situation. For this reason, the novelties presented in this Ph.D. thesis include not only developments of static ICIC mechanisms for data and control channels, but also e orts towards further improvements of the energy e ciency perspective. Based on a comprehensive review of the state of the art, a set of research opportunities were identi ed. To be precise, the need for exible performance evaluation methods and optimization frameworks for static ICIC strategies. These mechanisms are grouped in two families: the schemes that de ne constraints on the frequency domain and the ones that propose adjustments on the power levels. Thus, Soft- and Fractional Frequency Reuse (SFR and FFR, respectively) are identi ed as the base of the vast majority of static ICIC proposals. Consequently, during the rst part of this Ph.D. thesis, interesting insights into the operation of SFR and FFR were identi ed beyond well-known facts. These studies allow for the development of a novel statistical framework to evaluate the performance of these schemes in realistic deployments. As a result of the analysis, the poor performance of classic con gurations of SFR and FFR in real-world contexts is shown, and hence, the need for optimization is established. In addition, the importance of the interworking between static ICIC schemes and other network functionalities such as CSI feedback has also been identi ed. Therefore, novel CSI feedback schemes, suitable to operate in conjunction with SFR and FFR, have been developed. These mechanisms exploit the resource allocation pattern of these static ICIC techniques in order to improve the accuracy of the CSI feedback process. The second part is focused on the optimization of SFR and FFR. The use of multiobjective techniques is investigated as a tool to achieve e ective network-speci c optimization. The approach o ers interesting advantages. On the one hand, it allows for simultaneous optimization of several con icting criteria. On the other hand, the multiobjective nature results in outputs composed of several high quality (Pareto e cient) network con gurations, all of them featuring a near-optimal tradeo between the performance criteria. Multiobjective evolutionary algorithms allow employing complex mathematical structures without the need for relaxation, thus capturing accurately the system behavior in terms of ICI. The multiobjective optimization formulation of the problem aims at achieving e ective adjustment of the operational parameters of SFR and FFR both at cell level and network-wide. Moreover, the research was successfully extended to the control channels, both the PDCCH and ePDCCH. Finally, in an e ort to further improve the network energy e ciency (an aspect always considered throughout the thesis), the framework of Cell Switch O (CSO), having close connections with ICIC, is also introduced. By means of the proposed method, signi cant improvements with respect to traditional approaches, baseline con gurations, and previous proposals can be achieved. The gains are obtained in terms of energy consumption, network capacity, and cell edge performance.Actualmente los sistemas 3.5 y 4G tales como Long Term Evolution (LTE) y LTE-Advanced (LTE-A) soportan servicios basados en paquetes y proporcionan acceso de banda ancha m ovil para aplicaciones que requieren elevadas tasas de transmisi on. En este contexto de r apida evoluci on, aparecen nuevos retos t ecnicos que deben ser resueltos e cientemente. El objetivo ultimo es conseguir un salto cualitativo importante en la experiencia de usuario (QoE). Con tal n, un factor clave que ha sido reconocido en las redes celulares basadas en Orthogonal Frequency- Division Multiple Access (OFDMA) es la gesti on de interferencias. De hecho, la utilizaci on de un factor de reuso bajo permite una elevada e ciencia espectral pero a costa de una distribuci on de la calidad de servicio (QoS) que no es uniforme en la red, depende de la posici on del usuario. Por lo tanto, el rendimiento en los l mites de la celda se ve muy penalizado y es un problema importante a resolver en LTE y LTE-A. La coordinaci on de interferencias entre celdas (ICIC, del ingl es Intercell Interfe- rence Coordination) engloba las estrategias cuyo objetivo es mantener la interferencia intercelular (ICI) lo m as baja posible en los bordes de celda. Esto permite aliviar la situaci on antes mencionada. La contribuci on presentada en esta tesis doctoral incluye el dise~no de nuevos mecanismos de ICIC est atica para los canales de datos y control, as como tambi en mejoras desde el punto de vista de e ciencia energ etica. A partir de una revisi on completa del estado del arte, se identi caron una serie de retos abiertos que requer an esfuerzos de investigaci on. En concreto, la necesidad de m etodos de evaluaci on exibles y marcos de optimizaci on de las estrategias de ICIC est aticas. Estos mecanismos se agrupan en dos familias: los esquemas que de nen restricciones sobre el dominio de la frecuencia y los que proponen ajustes en los niveles de potencia. Es decir, la base de la gran mayor a de propuestas ICIC est aticas son la reutilizaci on de frecuencias de tipo soft y fraccional (SFR y FFR, respectivamente). De este modo, durante la primera parte de esta tesis doctoral, se han estudiado los aspectos m as importantes del funcionamiento de SFR y FFR, haciendo especial enfasis en las conclusiones que van m as all a de las bien conocidas. Ello ha permitido introducir un nuevo marco estad stico para evaluar el funcionamiento de estos sistemas en condiciones de despliegue reales. Como resultado de estos an alisis, se muestra el pobre desempe~no de SFR y FFR en despliegues reales cuando funcionan con sus con guraciones cl asicas y se establece la necesidad de optimizaci on. Tambi en se pone de mani esto la importancia del funcionamiento conjunto entre esquemas ICIC est aticos y otras funcionalidades de la red radio, tales como la informaci on que env an los usuarios sobre el estado de su canal downlink (feedback del CSI, del ingl es Channel State Information). De este modo, se han propuesto diferentes esquemas de feedback apropiados para trabajar conjuntamente con SFR y FFR. Estos mecanismos explotan el patr on de asignaci on de recursos que se utiliza en ICIC est atico para mejorar la precisi on del proceso. La segunda parte se centra en la optimizaci on de SFR y FFR. Se ha investigado el uso de t ecnicas multiobjetivo como herramienta para lograr una optimizaci on e caz, que es espec ca para cada red. El enfoque ofrece ventajas interesantes, por un lado, se permite la optimizaci on simult anea de varios criterios contradictorios. Por otro lado, la naturaleza multiobjetivo implica obtener como resultado con guraciones de red de elevada calidad (Pareto e cientes), todas ellas con un equilibrio casi- optimo entre las diferentes m etricas de rendimiento. Los algoritmos evolucionarios multiobjetivo permiten la utilizaci on de estructuras matem aticas complejas sin necesidad de relajar el problema, de este modo capturan adecuadamente su comportamiento en t erminos de ICI. La formulaci on multiobjetivo consigue un ajuste efectivo de los par ametros operacionales de SFR y FFR, tanto a nivel de celda como a nivel de red. Adem as, la investigaci on se extiende con resultados satisfactorios a los canales de control, PDCCH y ePDCCH. Finalmente, en un esfuerzo por mejorar la e ciencia energ etica de la red (un aspecto siempre considerado a lo largo de la tesis), se introduce en el an alisis global el apagado inteligente de celdas, estrategia con estrechos v nculos con ICIC. A trav es del m etodo propuesto, se obtienen mejoras signi cativas con respecto a los enfoques tradicionales y propuestas previas. Las ganancias se obtienen en t erminos de consumo energ etico, capacidad de la red, y rendimiento en el l mite de las celdas.Actualment els sistemes 3.5 i 4G tals com Long Term Evolution (LTE) i LTE- Advanced (LTE-A) suporten serveis basats en paquets i proporcionen acc es de banda ampla m obil per a aplicacions que requereixen elevades taxes de transmissi o. En aquest context de r apida evoluci o, apareixen nous reptes t ecnics que han de ser resolts e cientment. L'objectiu ultim es aconseguir un salt qualitatiu important en l'experi encia d'usuari (QoE). Amb tal , un factor clau que ha estat reconegut a les xarxes cel lulars basades en Orthogonal Frequency-Division Multiple Access (OFDMA) es la gesti o d'interfer encies. De fet, la utilizaci o d'un factor de re us baix permet una elevada e ci encia espectral per o a costa d'una distribuci o de la qualitat de servei (QoS) que no es uniforme a la xarxa, dep en de la posici o de l'usuari. Per tant, el rendiment en els l mits de la cel la es veu molt penalitzat i es un problema important a resoldre en LTE i LTE-A. La coordinaci o d'interfer encies entre cel les (ICIC, de l'angl es Intercell Interfe- rence Coordination) engloba les estrat egies que tenen com a objectiu mantenir la interfer encia intercel lular (ICI) el m es baixa possible en les vores de la cel la. Aix o permet alleujar la situaci o abans esmentada. La contribuci o presentada en aquesta tesi doctoral inclou el disseny de nous mecanismes de ICIC est atica per als canals de dades i control, aix com tamb e millores des del punt de vista d'e ci encia energ etica. A partir d'una revisi o completa de l'estat de l'art, es van identi car una s erie de reptes oberts que requerien esfor cos de recerca. En concret, la necessitat de m etodes d'avaluaci o exibles i marcs d'optimitzaci o de les estrat egies de ICIC est atiques. Aquests mecanismes s'agrupen en dues fam lies: els esquemes que de neixen restriccions sobre el domini de la freq u encia i els que proposen ajustos en els nivells de pot encia. Es a dir, la base de la gran majoria de propostes ICIC est atiques s on la reutilitzaci o de freq u encies de tipus soft i fraccional (SFR i FFR, respectivament). D'aquesta manera, durant la primera part d'aquesta tesi doctoral, s'han estudiat els aspectes m es importants del funcionament de SFR i FFR, fent especial emfasi en les conclusions que van m es enll a de les ben conegudes. Aix o ha perm es introduir un nou marc estad stic per avaluar el funcionament d'aquests sistemes en condicions de desplegament reals. Com a resultat d'aquestes an alisis, es mostra el pobre acompliment de SFR i FFR en desplegaments reals quan funcionen amb les seves con guracions cl assiques i s'estableix la necessitat d'optimitzaci o. Tamb e es posa de manifest la import ancia del funcionament conjunt entre esquemes ICIC est atics i altres funcionalitats de la xarxa radio, tals com la informaci o que envien els usuaris sobre l'estat del seu canal downlink (feedback del CSI, de l'angl es Channel State Information). D'aquesta manera, s'han proposat diferents esquemes de feedback apropiats per treballar conjuntament amb SFR i FFR. Aquests mecanismes exploten el patr o d'assignaci o de recursos que s'utilitza en ICIC est atic per millorar la precisi o del proc es. La segona part se centra en l'optimitzaci o de SFR i FFR. S'ha investigat l' us de t ecniques multiobjectiu com a eina per aconseguir una optimitzaci o e ca c, que es espec ca per a cada xarxa. L'enfocament ofereix avantatges interessants, d'una banda, es permet l'optimitzaci o simult ania de diversos criteris contradictoris. D'altra banda, la naturalesa multiobjectiu implica obtenir com resultat con guracions de xarxa d'elevada qualitat (Pareto e cients), totes elles amb un equilibri gaireb e optim entre les diferents m etriques de rendiment. Els algorismes evolucionaris multiobjectiu permeten la utilitzaci o d'estructures matem atiques complexes sense necessitat de relaxar el problema, d'aquesta manera capturen adequadament el seu comportament en termes de ICI. La formulaci o multiobjectiu aconsegueix un ajust efectiu dels par ametres operacionals de SFR i FFR, tant a nivell de cel la com a nivell de xarxa. A m es, la recerca s'est en amb resultats satisfactoris als canals de control, PDCCH i ePDCCH. Finalment, en un esfor c per millorar l'e ci encia energ etica de la xarxa (un aspecte sempre considerat al llarg de la tesi), s'introdueix en l'an alisi global l'apagat intel ligent de cel les, estrat egia amb estrets vincles amb ICIC. Mitjan cant el m etode proposat, s'obtenen millores signi catives pel que fa als enfocaments tradicionals i propostes pr evies. Els guanys s'obtenen en termes de consum energ etic, capacitat de la xarxa, i rendiment en el l mit de les cel les

    Geometric frequency reuse for irregular cellular networks

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    PhD ThesisThis thesis uniquely addresses challenges of bandwidth management in cellular networks. The need for enhanced frequency assignment strategies in Long term evolution (LTE) systems arises due to the limiting e ects of intercell interference (ICI). In this study, the realistic scenario of irregular network coverage patterns is considered, and in addition, Heterogeneous cellular networks (HetNets). Firstly, extensive analysis using simulations is presented for static frequency reuse (FR) techniques in irregular Homogeneous (single-tier) cellular networks. Investigation was carried out over several network positional and deployment layouts. Second, a model is developed for irregular networks by de ning frameworks for their location parameters and relationships, FR bandwidth and power assignment, and the probability of interference in partitioned FR schemes. A novel Geometric FR (GeoFRe) algorithm is then proposed for single-tier networks with random BS placements. Third, an optimization framework based on user fairness is proposed and implemented for single-tier networks based on the concept of virtual UEs in di erent BS regions. Finally, a framework for HetNets is presented where macro and small BS deployments have imperfect coverage grid patterns. Performance analysis is then carried out for two implementations of the Soft FR (SFR) algorithm. Results from this research provide detailed analysis on impact of BS irregularity on UE performance under FR schemes, a simpli ed framework for modelling irregular macro BS, an improved FR model, accurate computations for the area of irregular network coverage patterns for intelligent bandwidth assignment, an optimization framework to improve user fairness (and edge UE performance) in single-tier networks and an FR model with performance analysis for irregular Het- Nets.National Information Technology Development Agency (NITDA) and Federal University of Technology Minna, both in Nigeria for o ering me scholarship and support

    Interference management in wireless cellular networks

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    In wireless networks, there is an ever-increasing demand for higher system throughputs, along with growing expectation for all users to be available to multimedia and Internet services. This is especially difficult to maintain at the cell-edge. Therefore, a key challenge for future orthogonal frequency division multiple access (OFDMA)-based networks is inter-cell interference coordination (ICIC). With full frequency reuse, small inter-site distances (ISDs), and heterogeneous architectures, coping with co-channel interference (CCI) in such networks has become paramount. Further, the needs for more energy efficient, or “green,” technologies is growing. In this light, Uplink Interference Protection (ULIP), a technique to combat CCI via power reduction, is investigated. By reducing the transmit power on a subset of resource blocks (RBs), the uplink interference to neighbouring cells can be controlled. Utilisation of existing reference signals limits additional signalling. Furthermore, cell-edge performance can be significantly improved through a priority class scheduler, enhancing the throughput fairness of the system. Finally, analytic derivations reveal ULIP guarantees enhanced energy efficiency for all mobile stations (MSs), with the added benefit that overall system throughput gains are also achievable. Following this, a novel scheduler that enhances both network spectral and energy efficiency is proposed. In order to facilitate the application of Pareto optimal power control (POPC) in cellular networks, a simple feasibility condition based on path gains and signal-to-noise-plus- interference ratio (SINR) targets is derived. Power Control Scheduling (PCS) maximises the number of concurrently transmitting MSs and minimises their transmit powers. In addition, cell/link removal is extended to OFDMA operation. Subsequently, an SINR variation technique, Power SINR Scheduling (PSS), is employed in femto-cell networks where full bandwidth users prohibit orthogonal resource allocation. Extensive simulation results show substantial gains in system throughput and energy efficiency over conventional power control schemes. Finally, the evolution of future systems to heterogeneous networks (HetNets), and the consequently enhanced network management difficulties necessitate the need for a distributed and autonomous ICIC approach. Using a fuzzy logic system, locally available information is utilised to allocate time-frequency resources and transmit powers such that requested rates are satisfied. An empirical investigation indicates close-to-optimal system performance at significantly reduced complexity (and signalling). Additionally, base station (BS) reference signals are appropriated to provide autonomous cell association amongst multiple co-located BSs. Detailed analytical signal modelling of the femto-cell and macro/pico-cell layouts reveal high correlation to experimentally gathered statistics. Further, superior performance to benchmarks in terms of system throughput, energy efficiency, availability and fairness indicate enormous potential for future wireless networks

    Radio Resource Management in Heterogeneous Cellular Networks

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    Heterogeneous cellular networks (HetNets) have been considered as one of enabling technologies not only to increase the cell coverage and capacity, but to improve the user experience. In this dissertation, we address two research challenges in HetNets: one is the cross-tier interference problem where cell range expansion (CRE) is applied for user offloading in cell association so that pico mobile stations located in expanded range (ER-PMSs), which are connected to macrocells unless CRE is enabled, are severely interfered. The other is the load-aware cell association which tries to overcome the drawback of the received signal strength-based cell association including CRE, i.e., the degradation of network performance by user load imbalance. In the first part, we present the frequency-domain transmit power reduction scheme for the cross-tier interference mitigation. Inspired by the fact that a macrocell accommodates more users than its underlaid picocells, we focus on minimizing the macrocell's performance degradation while improving the throughput of ER-PMSs by the transmit power reduction. Due to the discreteness of frequency resource block scheduling, we also propose a greedy-based heuristic algorithm to solve the binary integer programming problem. In the following part, we present a different approach for the cross-tier interference mitigation, which is the time-domain transmit power nulling scheme utilizing the almost blank subframes (ABSs) in 3GPP standards. We turn our attention to a network-wide performance enhancement through configuring a certain number of ABSs while improving the performance of ER-PMSs as in the first part. A new scheduling policy for pico mobile stations is proposed and the optimal ER-PMS scheduling onto ABSs/non-ABSs is solved by decomposing the problem into multiple independent problems for pico base stations. In the last part, we study the load-aware cell association problem. Due to the combinatorial nature of the cell association problem and the cross-tier interference between macrocells and picocells, we propose an online heuristic algorithm where the cell association and the number of ABSs for cross-tier interference mitigation are jointly optimized. Through approximation of the required condition for load balancing and ABS control from the network-wide utility point of view, the proposed online algorithm not only requires simple feedback messages, but also be applicable to any state of cell association/ABSs in HetNets

    Benefits and limits of machine learning for the implicit coordination on SON functions

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    Bedingt durch die EinfĂŒhrung neuer Netzfunktionen in den Mobilfunknetzen der nĂ€chsten Generation, z. B. Slicing oder Mehrantennensysteme, sowie durch die Koexistenz mehrerer Funkzugangstechnologien, werden die Optimierungsaufgaben Ă€ußerst komplex und erhöhen die OPEX (OPerational EXpenditures). Um den Nutzern Dienste mit wettbewerbsfĂ€higer DienstgĂŒte (QoS) zu bieten und gleichzeitig die Betriebskosten niedrig zu halten, wurde von den Standardisierungsgremien das Konzept des selbstorganisierenden Netzes (SON) eingefĂŒhrt, um das Netzmanagement um eine Automatisierungsebene zu erweitern. Es wurden dafĂŒr mehrere SON-Funktionen (SFs) vorgeschlagen, um einen bestimmten Netzbereich, wie Abdeckung oder KapazitĂ€t, zu optimieren. Bei dem konventionellen Entwurf der SFs wurde jede Funktion als Regler mit geschlossenem Regelkreis konzipiert, der ein lokales Ziel durch die Einstellung bestimmter Netzwerkparameter optimiert. Die Beziehung zwischen mehreren SFs wurde dabei jedoch bis zu einem gewissen Grad vernachlĂ€ssigt. Daher treten viele widersprĂŒchliche Szenarien auf, wenn mehrere SFs in einem mobilen Netzwerk instanziiert werden. Solche widersprĂŒchlichen Funktionen in den Netzen verschlechtern die QoS der Benutzer und beeintrĂ€chtigen die Signalisierungsressourcen im Netz. Es wird daher erwartet, dass eine existierende Koordinierungsschicht (die auch eine EntitĂ€t im Netz sein könnte) die Konflikte zwischen SFs lösen kann. Da diese Funktionen jedoch eng miteinander verknĂŒpft sind, ist es schwierig, ihre Interaktionen und AbhĂ€ngigkeiten in einer abgeschlossenen Form zu modellieren. Daher wird maschinelles Lernen vorgeschlagen, um eine gemeinsame Optimierung eines globalen Leistungsindikators (Key Performance Indicator, KPI) so voranzubringen, dass die komplizierten Beziehungen zwischen den Funktionen verborgen bleiben. Wir nennen diesen Ansatz: implizite Koordination. Im ersten Teil dieser Arbeit schlagen wir eine zentralisierte, implizite und auf maschinellem Lernen basierende Koordination vor und wenden sie auf die Koordination zweier etablierter SFs an: Mobility Robustness Optimization (MRO) und Mobility Load Balancing (MLB). Anschließend gestalten wir die Lösung dateneffizienter (d. h. wir erreichen die gleiche Modellleistung mit weniger Trainingsdaten), indem wir eine geschlossene Modellierung einbetten, um einen Teil des optimalen Parametersatzes zu finden. Wir nennen dies einen "hybriden Ansatz". Mit dem hybriden Ansatz untersuchen wir den Konflikt zwischen MLB und Coverage and Capacity Optimization (CCO) Funktionen. Dann wenden wir ihn auf die Koordinierung zwischen MLB, Inter-Cell Interference Coordination (ICIC) und Energy Savings (ES) Funktionen an. Schließlich stellen wir eine Möglichkeit vor, MRO formal in den hybriden Ansatz einzubeziehen, und zeigen, wie der Rahmen erweitert werden kann, um anspruchsvolle Netzwerkszenarien wie Ultra-Reliable Low Latency Communications (URLLC) abzudecken.Due to the introduction of new network functionalities in next-generation mobile networks, e.g., slicing or multi-antenna systems, as well as the coexistence of multiple radio access technologies, the optimization tasks become extremely complex, increasing the OPEX (OPerational EXpenditures). In order to provide services to the users with competitive Quality of Service (QoS) while keeping low operational costs, the Self-Organizing Network (SON) concept was introduced by the standardization bodies to add an automation layer to the network management. Thus, multiple SON functions (SFs) were proposed to optimize a specific network domain, like coverage or capacity. The conventional design of SFs conceived each function as a closed-loop controller optimizing a local objective by tuning specific network parameters. However, the relationship among multiple SFs was neglected to some extent. Therefore, many conflicting scenarios appear when multiple SFs are instantiated in a mobile network. Having conflicting functions in the networks deteriorates the users’ QoS and affects the signaling resources in the network. Thus, it is expected to have a coordination layer (which could also be an entity in the network), conciliating the conflicts between SFs. Nevertheless, due to interleaved linkage among those functions, it is complex to model their interactions and dependencies in a closed form. Thus, machine learning is proposed to drive a joint optimization of a global Key Performance Indicator (KPI), hiding the intricate relationships between functions. We call this approach: implicit coordination. In the first part of this thesis, we propose a centralized, fully-implicit coordination approach based on machine learning (ML), and apply it to the coordination of two well-established SFs: Mobility Robustness Optimization (MRO) and Mobility Load Balancing (MLB). We find that this approach can be applied as long as the coordination problem is decomposed into three functional planes: controllable, environmental, and utility planes. However, the fully-implicit coordination comes at a high cost: it requires a large amount of data to train the ML models. To improve the data efficiency of our approach (i.e., achieving good model performance with less training data), we propose a hybrid approach, which mixes ML with closed-form models. With the hybrid approach, we study the conflict between MLB and Coverage and Capacity Optimization (CCO) functions. Then, we apply it to the coordination among MLB, Inter-Cell Interference Coordination (ICIC), and Energy Savings (ES) functions. With the hybrid approach, we find in one shot, part of the parameter set in an optimal manner, which makes it suitable for dynamic scenarios in which fast response is expected from a centralized coordinator. Finally, we present a manner to formally include MRO in the hybrid approach and show how the framework can be extended to cover challenging network scenarios like Ultra-Reliable Low Latency Communications (URLLC)

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

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    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
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