Cloud-radio access network (CRAN) is expected to be the core network architecture for next generation mobile radio system. In CRANs, joint signal processing is performed at multiple cloud computing centers (clouds) that are connected to several base stations (BSs) via high capacity backhaul links. As a result, large-scale interference management and network power consumption reduction can be effectively achieved. Unlike recent works on CRANs which consider a single cloud processing and treat inter-cloud interference as background noise, the first part of this thesis focuses on the more practical scenario of the downlink of a multi-cloud radio access network where BSs are connected to each cloud through wireline backhaul links. Assume that each cloud serves a set of pre-known single-antenna mobile users (MUs). This part focuses on minimizing the network total power consumption subject to practical constraints. The problems are solved using sophisticated techniques from optimization theory (e.g. Dual Decomposition-based algorithm and the alternating direction method of multipliers (ADMM)-based algorithm). One highlight of this part is that the proposed solutions can be implemented in a distributed fashion by allowing a reasonable information exchange between the coupled clouds. Additionally, feasible solutions of the considered optimization problems can be estimated locally at each iteration. Simulation results show that the proposed distributed algorithms converge to the centralized algorithms in a reasonable number of iterations. To further account of the backhaul congestion due to densification in CRANs, the second part of this thesis considers the downlink of a cache-enabled CRAN where each BS is equipped with a local-cache with limited size used to store the popular files without the need for backhauling. Further, each cache-enabled BS is connected to the cloud via limited capacity backhaul link and can serve a set of pre-known single antenna MUs. This part assumes that only imperfect channel state information (CSI) is available at the cloud. This part focuses on jointly minimizing the network total power consumption as well as backhaul cost. It then suggests solving this optimization problem using the majorization-minimization (MM) approach. Simulation results show that the proposed algorithm converges in a reasonable number of iterations.

Optical fibre has become the dominant theme of transmission in long haul, high data rate communication systems due to its tremendous bandwidth and low loss. Radio over Fibre (RoF) technology facilitates the seamless integration between wireless and optical communication systems and found to be the most promising solution to meet the exponential bandwidth demands expected for the upcoming years. However, the main bit-rate/distance limitation in RoF systems is the chromatic dispersion. In this thesis, the two generations of RoF technologies, namely Analogue RoF (ARoF) and Digital RoF (DRoF) are investigated. The overall aim of this research is to optimise the optical bandwidth utilisation of these two approaches for a typical transmission of the fronthaul link proposed in the next generation Centralised Radio Access Network (C-RAN). Consequently, a number of physical layer design scenarios for the optimised transmission of the Radio Frequency (RF) signals over a Standards Single Mode Fibre (SSMF) are demonstrated. Firstly, for an ARoF transmission, where the analogue RF signals are transported over SSMF using an optical carrier, a bidirectional link transmitting four Downlink/Uplink channels in a chromatic dispersion limited scenario is designed. Simulation results have shown a clear constellation diagram of a 2.5 Gb/s RF signal transmission over 120 km fibre length. Secondly, a DRoF system with reduced optical bandwidth occupancy is proposed. This system employs an optical Duobinary transmission to the digitised RF signal at the transmitter side to reduce its spectrum and to address the chromatic dispersion effect, simultaneously. Simulation results demonstrate the capability of the proposed system to maintain high-quality transmission of the digitised signals over 70 km of fibre distance without dispersion compensation requirements. Finally, an advanced DRoF transmission link based on integrating digital Optical Single Sideband (OSSB) transmission with Duobinary encoding scheme is designed. Simulation results have clearly verified system's robustness against transmission impairments and have better performances in terms of the obtained BER and EVM with respect to the 3GPP standardised values. Moreover, the results show that both transmission distance and power budget are furtherly improved in comparison with two other digital transmission scenarios.

This thesis focuses on proposing a Software Defined Network (SDN) based programmable and capacity optimized backhaul and core network which is critical for 5G network design. Cloud Radio Access networks (CRAN) which is key enabler of 5G networks can address a number of challenges that mobile operators face while trying to support ever-growing end-users' needs towards 5th generation of mobile networks (5G). A novel layered and modular programmable CRAN architecture called Software Defined Virtualised Cloud Radio Access Network (SD-vCRAN) is introduced with Network Function Virtualization (NFV) and Software Defined Network (SDN) capabilities. The SDN-Base Band Unit (BBU) pool is shifted to the programmable core network site, where a centralised SDN controller manages the network servers and virtualised network function entities - Mobile Management Entity (MME), Serving/Packet Data Network Data plane (S/PGW-D), Serving/Packet Data Network Control plane (S/PGW-C), Software Network Defined Baseband Unit (SDN-BBU) and Local controllers (LC) via OpenFlow (OF) protocol. This approach simplifies network operations, improve traffic management, enable system-wide optimisation of Quality of Service (QoS) and network-aware application development. The control plane (excluding the preserved 3GPP standard interfaces: S1-MME, S6a, Gx) managed by the network servers provides load balancing, traffic management and optimisation tools for the data plane. The proposed work starts by reviewing the requirements of 5G networks, followed by discussion on 5G backhaul and core challenge. Then, an overview of CRAN, Evolved Programmable Core (EPC), SDN, NFV and related works. The simulation details of the proposed architecture are discussed along with the challenges faced by adopting SDN and NFV in mobile core. A thorough assessment of the interfaces and protocols that should be conserved or enhanced on both data and control plane is conducted. The result enables an architecture where the SDN-BBU pool shares a single cloud with the programmable EPC and the control plane is migrated from the network elements to a centralized controller, running on a virtual machine in the mobile core. The data and control plane separation removes overlaps and provides better signalling, as well as efficient network functioning to comply with latency demands. The proposed system performance is validated in terms of throughput, datagram loss, and packet delay variation under three scenarios: 1. single policy installation, 2. multiple policy installation and 3. load balancing. The load balancing performance of proposed system is validated comparing the performance of two different SDN controllers: Floodlight and OpenDaylight, where the later performs better in terms of throughput (no bandwidth restriction), packet loss (below 0.3%) and jitter (below 0.2ms). Furthermore, a detailed comparison of two SDN controller's - Floodlight and OpenDaylight performances is presented, which shows that OpenDaylight performs better only for less dense networks which needs less processing of messages without being blocked, and the Floodlight performs better in ultra-dense network. Some directions and preliminary thoughts for future work and necessary information to operators for building their roadmap to the upcoming technologies is presented.

In this thesis, components and parameters based power models (PMs) are produced to measure the power consumption (PC) of cloud radio access network (CRAN) architecture. In components PM, the power figure of each component within C-RAN is evaluated. After, this model is parametrised such that the computation complexity of each component is converted to a straightforward, but accurate method, called parameterised PM. This model compares cooling and total PC of traditional LTE architecture with C-RAN. This comparison considered different parameters such as, utilised bandwidth, number of antenna, base band units (BBUs) and remote radio heads (RRHs). This model draws about 33% reduction in power. Next, this PC model is updated to serve and exhibit the cost of integrating software defined networks (SDNs) with C-RAN. Alongside, modelling the power cost of the control plane units in the core network (CN), such as serving gateway (SGW), packet gateway (PGW) and mobility management entity (MME). Although there is power cost, the proposed model shows the directions to mitigate it. Consequently, a simplified PM is proposed for virtualisation based C-RAN. In this model, the power cost of server virtualisation by hosting several virtual machines (VMs) is shown, in a time and cost effective way. The total reduction in the PC was about 75%, due to short-cutting the number of active servers in the network. Alongside, the latency cost due to such technique is modelled. Finally, to enable efficient virtualisation technology, live migrating the VMs amongst the servers is vital. However, this advantageous situation is concurrent with VM's migration time and power cost. Therefore, a model is proposed to calculate the power cost of VM's live migration, and shows the effect of such decision upon the total PC of the network/C-RAN. The proposed work converts the complexity of other proposed PMs, to a simplified and costless method. Concurrently, the time cost is added to the imposed virtualisation's time cost to formulate the total delay expected prior to these techniques' execution.

This thesis explores a novel technique for transceiver design in future wireless systems, which is cloud radio access networks (CRANs) with single radio frequency (RF) chain antennas at each remote radio head (RRH). This thesis seeks to make three contributions. Firstly, it proposes a novel algorithm to solve the oscillatory/unstable behaviour of electronically steerable parasitic array radiators (ESPAR) when it provides multi-antenna functionality with a single RF chain. This thesis formulates an optimization problem and derives closed-form expressions when calculating the configuration of an ESPAR antenna (EA) for arbitrary signals transmission. This results in simplified processing at the transmitter. The results illustrate that the EA transmitter, when utilizing novel closed-form expressions, shows significant improvement over the performance of the EA transmitter without any pre-processing. It performs at nearly the same symbol error rate (SER) as standard multiple antenna systems. Secondly, this thesis illustrates how a practical peak power constraint can be put into an EA transceiver design. In an EA, all the antenna elements are fed centrally by a single power amplifier. This makes it more probable that during use, the power amplifier reaches maximum power during transmission. Considering limited power availability, this thesis proposes a new algorithm to achieve stable signal transmission. Thirdly, this thesis shows that an energy efficiency (EE) optimization problem can be formulated and solved in CRANs that deploy single RF chain antennas at RRHs. The closed-form expressions of the precoder and power allocation schemes to transmit desired signals are obtained to maximise EE for both single-user and multi-user systems. The results show that the CRANs with single RF chain antennas provide superior EE performance compared to the standard multiple antenna based systems.

Yes / Fifth generation (5G) cellular networks will be comprised of millions of connected devices like wearable devices, Androids, iPhones, tablets and the Internet of Things (IoT) with a plethora of applications generating requests to the network. The 5G cellular networks need to cope with such sky-rocketing tra c requests from these devices to avoid network congestion. As such, cloud radio access networks (C-RAN) has been considered as a paradigm shift for 5G in which requests from mobile devices are processed in the cloud with shared baseband processing. Despite call admission control (CAC) being one of radio resource management techniques to avoid the network congestion, it has recently been overlooked by the community. The CAC technique in 5G C-RAN has a direct impact on the quality of service (QoS) for individual connections and overall system e ciency. In this paper, a novel Fuzzy-Logic based CAC scheme with pre-emption in C-RAN is proposed. In this scheme, cloud bursting technique is proposed to be used during congestion, where some delay tolerant low-priority connections are pre-empted and outsourced to a public cloud with a penalty charge. Simulation results show that the proposed scheme has low blocking probability below 5%, high throughput, low energy consumption and up to 95% of return on revenue.

The increasing demand on user rates in the fifth generation (5G) requires network architectures that can support high data rates with acceptable reliability. In order to increase the data rates in the presence of the current spectrum crisis, shrinking cells and reusing the spectrum is a proposed solution. Conventional implementation of dense cells requires a large number of expensive BSs to locally process and decode users’ signals. Another limiting factor that degrades the performance in a dense network is the inter-cell interference. A cloud radio access network (CRAN) is a promising solution to those cost, complexity, and interference challenges. A typical CRAN architecture consists of simplified low-cost base stations (BSs), termed radio units (RUs), that collect the radio frequency (RF) user equipments’ (UEs) signals and forward them over the fronthaul links to the central office (CO) where signal processing is done over shared resources. Besides the reduced cost and complexity of a CRAN, the joint processing at the CO enables joint interference mitigation techniques. However, the performance of CRANs depends critically on the availability of reliable fronthaul links with large bandwidth that may be expensive. Analog optical fronthaul links provide high data rates at lower cost and complexity since UEs’ signals are optically analog-modulated without digitalization, however, they suffer from other channel impairments and nonlinearities. In this thesis, analog optical fronthaul topologies are considered in which radio signals are forwarded over free-space optical (FSO) links, termed radio-over-free-space optical (RoFSO) links, and optical fiber (OF) links, termed radio-over-fiber (RoF) links. Firstly, a CRAN with mixed RF/RoFSO fronthaul is considered to investigate the performance improvement when RF fronthaul links are replaced one-by-one by RoFSO links. A novel joint optimization problem is introduced for the given architecture in which the weighted sum of UEs’ rates is maximized by jointly designing RF and RoFSO links. The optimization problem is solved over different numbers of RF and RoFSO links and under various weather conditions. Under favorable weather conditions, the replacement of 1 RF link by a RoFSO link is shown to increase the 50th percentile of UEs’ rates by 7 times. Secondly, the reliability of a CRAN with two-hop RoFSO/RoF fronthaul links is derived along with other performance metrics such as the average bit-error rate and the cumulative distribution function of UEs’ rates. For the given architecture, the Gaussian noise model of fiber nonlinearity is applied and an optimal OF average optical power is derived to minimize the outage probability. Using the optimal power, and under favorable weather conditions, the 50th percentile of user rate exceeds 1:5 Gbps. Finally, a CRAN with passive all-optical two-hop fronthaul links is considered where optical signals from the first RoFSO fronthaul hop are passively coupled into the RoF fronthaul link. The fronthaul outage probability is derived in the context of network planning to provide guidance on designing a set of system parameters. Those parameters include coverage area radius, density of RUs, RoFSO gain, RoFSO optical power and RoF length. / Thesis / Doctor of Philosophy (PhD) / The upcoming generation of wireless communications, termed fifth generation (5G), promises faster data rates and lower latency. In order to achieve this, more base stations (BSs) have to be deployed which increases the cost and complexity of the network. A solution to this challenge is to install simple BSs, i.e. radio units (RUs), that collect signals from users and forward them to a central office (CO) for joint processing which is referred to as a cloud radio access network (CRAN). The fronthaul network in a CRAN connects the RUs to the CO and it can be implemented using different kinds of links. While there are several fronthaul media (e.g., radio frequency (RF), free-space optical (FSO) links, copper lines, satellite communications, and optical fiber (OF)), optical links provide high data rates that are promising to achieve the 5G requirements. In this thesis, a novel architecture of a CRAN is considered in which analog optical links, namely FSO links and OF links, are used for fronthauling. Performance improvement in terms of rate and reliability is investigated and optimized through different design tools. In response to the challenges introduced by the proposed architecture, such as the nonlinearities of analog FSO and OF links, various design parameters are proposed in the optimization problems to tackle those challenges. Furthermore, a network planning framework is introduced to provide guidance and insights on designing the network.

De nos jours, la demande en trafic mobile a considérablement augmenté. Face à cette croissance, plusieurs propositions font l'objet d'étude pour remédier à un tel défi. L’architecture des réseaux d’accès de type Cloud (C-RAN) est l’une des propositions pour faire face à cette demande croissante, et constitue une solution candidate potentielle pour les réseaux futurs 5G. L'architecture C-RAN dissocie deux éléments principaux de la station de base: La BBU ou ``Baseband Unit", qui constitue une unité intelligente pour le traitement des données en bande de base, et le RRH ou ``Remote Radio Head", constituant en une antenne passive pour fournir l'accès aux utilisateurs (UEs). Grâce à l’architecture C-RAN, les BBUs sont centralement regroupées, alors que les RRHs sont distribués sur plusieurs sites. Plusieurs avantages sont ainsi dérivés, tels que le gain en multiplexage statistique, l’efficacité d’utilisation des ressources, et l’économie de puissance. Contrairement à l’architecture conventionnelle où chaque RRH est exclusivement associé à une BBU, dans l’architecture C-RAN, plusieurs RRHs sont regroupés en une seule BBU lorsque les conditions de charge sont faibles. Ceci présente plusieurs avantages, tel que l’amélioration en efficacité énergétique et la minimisation en consommation de puissance. Dans cette thèse, nous adressons le problème d’optimisation des associations BBU-RRH. Nous nous intéressons à l’optimisation des regroupements des RRHs aux BBUs en tenant compte de critères multiples. Plusieurs contraintes sont ainsi envisagées, tel que la réduction de la consommation d'énergie sous garantie de Qualité de Service (QoS) minimale. En outre, la prise en compte du changement du niveau d’interférence en activant/désactivant les BBUs est primordiale pour l’amélioration de l’efficacité spectrale. En plus, décider dynamiquement de la réassociation des RRHs aux BBUs sous des conditions de charges variables représente un défi, vu que les UEs connectés aux RRHs changeant leurs associations font face à des ``handovers" (HOs). / The demand on mobile traffic has been largely increasing nowadays. Facing such growth, several propositions are being studied to cope with this challenge. Cloud-Radio Access Networks Architecture (C-RAN) is one of the proposed solutions to address the increased demand, and is a potential candidate for future 5G networks. The C-RAN architecture dissociates two main elements composing the base station: The Baseband Unit (BBU), consisting in an intelligent element to perform baseband tasks functionalities, and the Remote Radio Head (RRH), that consists in a passive antenna element to provide access for serviced User Equipments (UEs). In C-RAN architecture, the BBUs migrate to a Cloud data center, while RRHs remain distributed across multiple sites. Several advantages are derived, such as statistical multiplexing gain, efficiency in resource utilization and power saving. Contrarily to conventional architecture, where each RRH is associated to one BBU, in C-RAN architecture, multiple RRHs can be embraced by one single BBU when network load conditions are low, bringing along several benefits, such as enhanced energy efficiency, and power consumption minimization. In this thesis, the BBU-RRH association optimization problem is addressed. Our aim is to optimize the BBU-RRH association schemes, taking into consideration several criteria. The problem presents many constraints: For example, achieving minimized power consumption while guaranteeing a minimum level of Quality of Service (QoS) is a challenging task. Further, taking into account the interference level variation while turning ON/OFF BBUs is paramount to achieve enhanced spectral efficiency. Moreover, deciding how to re-associate RRHs to BBUs under dynamic load conditions is also a challenge, since connected UEs face handovers (HOs) when RRHs change their associations.

Cloud radio access network (C-RAN) is a promising architecture for the next-generation RAN to meet the diverse and stringent requirements envisioned by fifth generation mobile communication systems (5G) and future generation mobile networks. C-RAN offers several advantages, such as reduced capital expenditure (CAPEX) and operational expenditure (OPEX), increased spectral efficiency (SE), higher capacity and improved cell-edge performance, and efficient hardware utilization through resource sharing and network function virtualization (NFV). However, these centralization gains come with the need for a fronthaul, which is the transport link connecting remote radio units (RRUs) to the base band unit (BBU) pool. In conventional C-RAN, legacy common public radio interface (CPRI) protocol is used on the fronthaul network to transport the raw, unprocessed baseband in-phase/quadrature-phase (I/Q) samples between the BBU and the RRUs, and it demands a huge fronthaul bandwidth, a strict low-latency, in the order of a few hundred microseconds, and a very high reliability. Hence, in order to relax the excessive fronthaul bandwidth and stringent low-latency requirements, as well as to enhance the flexibility of the fronthaul, it is utmost important to redesign the fronthaul, while still profiting from the acclaimed centralization benefits. Therefore, a flexibly centralized C-RAN with different functional splits has been introduced. In addition, 5G mobile fronthaul (often also termed as an evolved fronthaul ) is envisioned to be packet-based, utilizing the Ethernet as a transport technology. In this thesis, to circumvent the fronthaul bandwidth constraint, a packetized fronthaul considering an appropriate functional split such that the fronthaul data rate is coupled with actual user data rate, unlike the classical C-RAN where fronthaul data rate is always static and independent of the traffic load, is justifiably chosen. We adapt queuing and spatial traffic models to derive the mathematical expressions for statistical multiplexing gains that can be obtained from the randomness in the user traffic. Through this, we show that the required fronthaul bandwidth can be reduced significantly, depending on the overall traffic demand, correlation distance and outage probability. Furthermore, an iterative optimization algorithm is developed, showing the impacts of number of pilots on a bandwidth-constrained fronthaul. This algorithm achieves additional reduction in the required fronthaul bandwidth. Next, knowing the multiplexing gains and possible fronthaul bandwidth reduction, it is beneficial for the mobile network operators (MNOs) to deploy the optical transceiver (TRX) modules in C-RAN cost efficiently. For this, using the same framework, a cost model for fronthaul TRX cost optimization is presented. This is essential in C-RAN, because in a wavelength division multiplexing-passive optical network (WDM-PON) system, TRXs are generally deployed to serve at a peak load. But, because of variations in the traffic demands, owing to tidal effect, the fronthaul can be dimensioned requiring a lower capacity allowing a reasonable outage, thus giving rise to cost saving by deploying fewer TRXs, and energy saving by putting the unused TRXs in sleep mode. The second focus of the thesis is the fronthaul latency analysis, which is a critical performance metric, especially for ultra-reliable and low latency communication (URLLC). An analytical framework to calculate the latency in the uplink (UL) of C-RAN massive multiple-input multiple-output (MIMO) system is presented. For this, a continuous-time queuing model for the Ethernet switch in the fronthaul network, which aggregates the UL traffic from several massive MIMO-aided RRUs, is considered. The closed-form solutions for the moment generating function (MGF) of sojourn time, waiting time and queue length distributions are derived using Pollaczek–Khinchine formula for our M/HE/1 queuing model, and evaluated via numerical solutions. In addition, the packet loss rate – due to the inability of the packets to reach the destination in a certain time – is derived. Due to the slotted nature of the UL transmissions, the model is extended to a discrete-time queuing model. The impact of the packet arrival rate, average packet size, SE of users, and fronthaul capacity on the sojourn time, waiting time and queue length distributions are analyzed. While offloading more signal processing functionalities to the RRU reduces the required fronthaul bandwidth considerably, this increases the complexity at the RRU. Hence, considering the 5G New Radio (NR) flexible numerology and XRAN functional split with a detailed radio frequency (RF) chain at the RRU, the total RRU complexity is computed first, and later, a tradeoff between the required fronthaul bandwidth and RRU complexity is analyzed. We conclude that despite the numerous C-RAN benefits, the stringent fronthaul bandwidth and latency constraints must be carefully evaluated, and an optimal functional split is essential to meet diverse set of requirements imposed by new radio access technologies (RATs). / Ein cloud-basiertes Mobilfunkzugangsnetz (cloud radio access network, C-RAN) stellt eine vielversprechende Architektur für das RAN der nächsten Generation dar, um die vielfältigen und strengen Anforderungen der fünften (5G) und zukünftigen Generationen von Mobilfunknetzen zu erfüllen. C-RAN bietet mehrere Vorteile, wie z.B. reduzierte Investitions- (CAPEX) und Betriebskosten (OPEX), erhöhte spektrale Effizienz (SE), höhere Kapazität und verbesserte Leistung am Zellrand sowie effiziente Hardwareauslastung durch Ressourcenteilung und Virtualisierung von Netzwerkfunktionen (network function virtualization, NFV). Diese Zentralisierungsvorteile erfordern jedoch eine Transportverbindung (Fronthaul), die die Antenneneinheiten (remote radio units, RRUs) mit dem Pool an Basisbandeinheiten (basisband unit, BBU) verbindet. Im konventionellen C-RAN wird das bestehende CPRI-Protokoll (common public radio interface) für das Fronthaul-Netzwerk verwendet, um die rohen, unverarbeitet n Abtastwerte der In-Phaseund Quadraturkomponente (I/Q) des Basisbands zwischen der BBU und den RRUs zu transportieren. Dies erfordert eine enorme Fronthaul-Bandbreite, eine strenge niedrige Latenz in der Größenordnung von einigen hundert Mikrosekunden und eine sehr hohe Zuverlässigkeit. Um die extrem große Fronthaul-Bandbreite und die strengen Anforderungen an die geringe Latenz zu lockern und die Flexibilität des Fronthauls zu erhöhen, ist es daher äußerst wichtig, das Fronthaul neu zu gestalten und dabei trotzdem von den erwarteten Vorteilen der Zentralisierung zu profitieren. Daher wurde ein flexibel zentralisiertes CRAN mit unterschiedlichen Funktionsaufteilungen eingeführt. Außerdem ist das mobile 5G-Fronthaul (oft auch als evolved Fronthaul bezeichnet) als paketbasiert konzipiert und nutzt Ethernet als Transporttechnologie. Um die Bandbreitenbeschränkung zu erfüllen, wird in dieser Arbeit ein paketbasiertes Fronthaul unter Berücksichtigung einer geeigneten funktionalen Aufteilung so gewählt, dass die Fronthaul-Datenrate mit der tatsächlichen Nutzdatenrate gekoppelt wird, im Gegensatz zum klassischen C-RAN, bei dem die Fronthaul-Datenrate immer statisch und unabhängig von der Verkehrsbelastung ist. Wir passen Warteschlangen- und räumliche Verkehrsmodelle an, um mathematische Ausdrücke für statistische Multiplexing- Gewinne herzuleiten, die aus der Zufälligkeit im Benutzerverkehr gewonnen werden können. Hierdurch zeigen wir, dass die erforderliche Fronthaul-Bandbreite abhängig von der Gesamtverkehrsnachfrage, der Korrelationsdistanz und der Ausfallwahrscheinlichkeit deutlich reduziert werden kann. Darüber hinaus wird ein iterativer Optimierungsalgorithmus entwickelt, der die Auswirkungen der Anzahl der Piloten auf das bandbreitenbeschränkte Fronthaul zeigt. Dieser Algorithmus erreicht eine zusätzliche Reduktion der benötigte Fronthaul-Bandbreite. Mit dem Wissen über die Multiplexing-Gewinne und die mögliche Reduktion der Fronthaul-Bandbreite ist es für die Mobilfunkbetreiber (mobile network operators, MNOs) von Vorteil, die Module des optischen Sendeempfängers (transceiver, TRX) kostengünstig im C-RAN einzusetzen. Dazu wird unter Verwendung des gleichen Rahmenwerks ein Kostenmodell zur Fronthaul-TRX-Kostenoptimierung vorgestellt. Dies ist im C-RAN unerlässlich, da in einem WDM-PON-System (wavelength division multiplexing-passive optical network) die TRX im Allgemeinen bei Spitzenlast eingesetzt werden. Aufgrund der Schwankungen in den Verkehrsanforderungen (Gezeiteneffekt) kann das Fronthaul jedoch mit einer geringeren Kapazität dimensioniert werden, die einen vertretbaren Ausfall in Kauf nimmt, was zu Kosteneinsparungen durch den Einsatz von weniger TRXn und Energieeinsparungen durch den Einsatz der ungenutzten TRX im Schlafmodus führt. Der zweite Schwerpunkt der Arbeit ist die Fronthaul-Latenzanalyse, die eine kritische Leistungskennzahl liefert, insbesondere für die hochzuverlässige und niedriglatente Kommunikation (ultra-reliable low latency communications, URLLC). Ein analytisches Modell zur Berechnung der Latenz im Uplink (UL) des C-RAN mit massivem MIMO (multiple input multiple output) wird vorgestellt. Dazu wird ein Warteschlangen-Modell mit kontinuierlicher Zeit für den Ethernet-Switch im Fronthaul-Netzwerk betrachtet, das den UL-Verkehr von mehreren RRUs mit massivem MIMO aggregiert. Die geschlossenen Lösungen für die momenterzeugende Funktion (moment generating function, MGF) von Verweildauer-, Wartezeit- und Warteschlangenlängenverteilungen werden mit Hilfe der Pollaczek-Khinchin-Formel für unser M/HE/1-Warteschlangenmodell hergeleitet und mittels numerischer Verfahren ausgewertet. Darüber hinaus wird die Paketverlustrate derjenigen Pakete, die das Ziel nicht in einer bestimmten Zeit erreichen, hergeleitet. Aufgrund der Organisation der UL-Übertragungen in Zeitschlitzen wird das Modell zu einem Warteschlangenmodell mit diskreter Zeit erweitert. Der Einfluss der Paketankunftsrate, der durchschnittlichen Paketgröße, der SE der Benutzer und der Fronthaul-Kapazität auf die Verweildauer-, dieWartezeit- und dieWarteschlangenlängenverteilung wird analysiert. Während das Verlagern weiterer Signalverarbeitungsfunktionalitäten an die RRU die erforderliche Fronthaul-Bandbreite erheblich reduziert, erhöht sich dadurch im Gegenzug die Komplexität der RRU. Daher wird unter Berücksichtigung der flexiblen Numerologie von 5G New Radio (NR) und der XRAN-Funktionenaufteilung mit einer detaillierten RF-Kette (radio frequency) am RRU zunächst die gesamte RRU-Komplexität berechnet und später ein Kompromiss zwischen der erforderlichen Fronthaul-Bandbreite und der RRU-Komplexität untersucht. Wir kommen zu dem Schluss, dass trotz der zahlreichen Vorteile von C-RAN die strengen Bandbreiten- und Latenzbedingungen an das Fronthaul sorgfältig geprüft werden müssen und eine optimale funktionale Aufteilung unerlässlich ist, um die vielfältigen Anforderungen der neuen Funkzugangstechnologien (radio access technologies, RATs) zu erfüllen.

Network densification has become a dominant theme for capacity enhancement in cellular networks. However, it increases the operational complexity and expenditure for mobile network operators. Consequently, the essential features of Self-Organising Networks (SON) are considered to ensure the economic viability of the emerging cellular networks. This thesis focuses on quantifying the benefits of self-organisation in Cloud Radio Access Network (C-RAN) by proposing a flexible, energy efficient, and capacity optimised system. The Base Band Unit (BBU) and Remote Radio Head (RRH) map is formulated as an optimisation problem. A self-optimised C-RAN (SOCRAN) is proposed which hosts Genetic Algorithm (GA) and Discrete-Particle-Swarm-Optimisation algorithm (DPSO), developed for optimisation. Computational results based on different network scenarios demonstrate that DPSO delivers excellent performances for the key performance indicators compared to GA. The percentage of blocked users is reduced from 10.523% to 0.409% in a medium sized network scenario and 5.394% to 0.56% in a vast network scenario. Furthermore, an efficient resource utilisation scheme is proposed based on the concept of Cell Differentiation and Integration (CDI). The two-stage CDI scheme semi-statically scales the number of BBUs and RRHs to serve an offered load and dynamically defines the optimum BBU-RRH mapping to avoid unbalanced network scenarios. Computational results demonstrate significant throughput improvement in a CDI-enabled C-RAN compared to a fixed C-RAN, i.e., an average throughput increase of 45.53% and an average blocked users decrease of 23.149% is experienced. A power model is proposed to estimate the overall power consumption of C-RAN. Approximately 16% power reduction is calculated in a CDI-enabled C-RAN when compared to a fixed C-RAN, both serving the same geographical area. Moreover, a Divide-and-Sort load balancing scheme is proposed and compared to the SOCRAN scheme. Results show excellent performances by the Divide-and-Sort algorithm in small networks when compared to SOCRAN and K-mean clustering algorithm.