Overview of high-speed TDM-PON beyond 50 Gbps per wavelength using digital signal processing [Invited Tutorial]

The recent evolution of passive optical network standards and related research activities for physical layer solutions that achieve bit rates well above 10 Gbps per wavelength (lambda) is discussed. We show that the advancement toward 50, 100, and 200 Gbps/lambda will certainly require a strong introduction of advanced digital signal processing (DSP) technologies for linear, and maybe nonlinear, equalization and for forward error correction. We start by reviewing in detail the current standardization activities in the International Telecommunication Union and the Institute of Electrical and Electronics Engineers, and then we present a comparison of the DSP approaches for traditional direct detection solutions and for future coherent detection approaches. (c) 2022 Optica Publishing Grou

Joint access-backhaul mechanisms in 5G cell-less architectures

Older generations of wireless networks, such as 1G and 2G were deployed using leased line, copper or fibre line as backhaul. Later, in 3G and 4G, microwave wireless links have also worked as backhaul links while the backbone of the network was still wireline-based. However, due to multiple different use cases and deployment scenarios of 5G, solo wireline based backhaul network is not a cost-efficient option for the operators anymore. For cost-efficient and fast deployment, wireless backhaul options are very attractive. As drawbacks, wireless backhaul links have capacity and distance limitations. To take the advantages of both the solutions, i.e., wired and wireless, 5G transport networks are anticipated to be a heterogeneous, complex, and with stringent performance requirements. To address the aforementioned challenges, wireless backhaul options are providing more attractive solutions, and hence, technologies using the same resources (e.g., frequency channels) may be used by both access and backhaul networks. In this scenario, blurring the separation line between access and backhaul networks allows resource sharing and cooperation between both the networks and minimizes the network deployment and maintenance cost significantly. Therefore, in 5G, the access and backhaul networks cannot be seen as separate entities; rather, we seek to integrate them together to ensure the best use of resources. In this thesis, firstly, we investigate the challenges and potential technologies of 5G transport network. Later, to address these challenges, we identify and present different approaches to perform joint access-backhaul mechanism. An initial performance evaluation of access-aware backhaul optimization is presented, where backhaul network is dynamically assigned with the required resources to serve the dynamic requirements of a 5G access network. The evaluation results and discussions manifest the resource efficiency of joint access-backhaul mechanisms. Functional splits in different layers of the access network comes as an intelligent solution to reduce the enormous capacity requirements of the transport network in a centralized radio access network approach, which tends to centralize almost all the functionalities into a central unit, leaving only radio frequency functions at the access points. From the joint access-backhaul mechanism perspective, we propose a novel technique, which takes the benefit of functional splits at physical layer, to design a heterogeneous transport network in an economical budget-limited and capacity-limited scenario. Till today, the limited capacity of the wireless backhaul links remains a challenge, and hence, frequency spectrum becomes scarce, and requires efficient utilization. To address this challenge, a joint spectrum sharing technique to implement joint accessbackhaul mechanism is presented. Evaluation results show that our proposed joint spectrum sharing technique, where spectrum allocation in the backhaul network follows the access network's traffic load, is fair and efficient in terms of spectrum utilization. We also propose a machine learning technique, which analyses data from a real network and estimates access network's traffic pattern, and subsequently, assigns bandwidth in the access network according to the traffic estimations. Presented evaluation results show that a well-trained machine learning model can be very efficient to obtain an efficient utilization of frequency spectrum.Las primeras generaciones de redes móviles, se implementaron utilizando líneas de cobre o fibra para la conexión entre la red de acceso y el núcleo de la red (conexión backhaul). Más tarde, los enlaces inalámbricos también han funcionado como backhaul mientras que la columna vertebral de la red seguía basada en cable. Sin embargo, debido a los múltiples escenarios de implementación de 5G, una red de backhaul basada solamente en cable ya no es una opción rentable para los operadores. Para una implementación rentable y rápida, las opciones de backhaul inalámbrico son muy atractivas. Como inconvenientes, los enlaces backhaul inalámbricos tienen limitaciones de capacidad y distancia. Para aprovechar las ventajas de ambas soluciones, es decir, cableadas e inalámbricas, se prevé que las redes de transporte 5G sean heterogéneas, complejas y con estrictos requisitos de rendimiento. Para abordar los desafíos antes mencionados, las opciones de backhaul inalámbrico brindan soluciones más atractivas y, por lo tanto, las tecnologías que usan los mismos recursos (por ejemplo, canales de frecuencia) pueden usarse tanto en las redes de acceso como en las de backhaul. En este escenario, desdibujar la línea de separación entre las redes de acceso y backhaul permite el intercambio de recursos y la cooperación entre ambas redes, y minimiza significativamente los costes de implementación y mantenimiento de la red. Por lo tanto, en 5G las redes de acceso y backhaul no pueden verse como entidades separadas; más bien consideraremos su integración para asegurar el mejor uso de los recursos. En esta tesis, en primer lugar, investigamos los desafíos y las tecnologías potenciales para la implementación de la red de backhaul 5G. Más tarde, para abordar dichos desafíos, identificamos diferentes enfoques para un mecanismo conjunto de gestión de la red de acceso y backhaul. Se presenta una evaluación de rendimiento inicial para la optimización de backhaul que tiene en cuenta el estado de la red de acceso, donde la red de backhaul se equipa dinámicamente con los recursos necesarios para cumplir con los requisitos de la red de acceso 5G. Los resultados de la evaluación manifiestan la mayor eficiencia de los mecanismos de gestión de recursos que consideran redes de acceso y backhaul conjuntamente. Las divisiones funcionales en diferentes capas de la red de acceso (functional splits) se presentan como una solución inteligente para reducir los enormes requisitos de capacidad de la red de transporte en un enfoque de red de acceso, que tiende a centralizar casi todas las funcionalidades en una unidad central, dejando solo las funciones más relacionadas con la transmisión/recepción de señales en los puntos de acceso. Desde la perspectiva del mecanismo conjunto de red de acceso y backhaul, proponemos una técnica novedosa, que aprovecha las divisiones funcionales en la capa física para diseñar una red de transporte heterogénea con un presupuesto económico y un escenario de capacidad limitada. Hasta el día de hoy, la capacidad limitada de los enlaces inalámbricos sigue siendo un desafío, dado que el espectro de frecuencias es escaso y requiere una utilización eficiente. Para hacer frente a este desafío, se presenta una técnica de gestión de recursos espectrales compartidos entre red de acceso y backhaul. Los resultados de la evaluación muestran que nuestra propuesta, donde la asignación de espectro en la red de backhaul se hace de acuerdo a la carga de tráfico de la red de acceso, es justa y eficiente. También proponemos una técnica de aprendizaje automático, que analiza datos de una red real y estima el patrón de tráfico de la red de acceso para, posteriormente, asignar ancho de banda en la red de acceso de acuerdo con dichas estimaciones. Los resultados de la evaluación presentados muestran que un modelo de aprendizaje automático bien entrenado puede ser una herramienta muy útil a la hora de obtener una utilización eficiente del espectro de frecuencias.Postprint (published version

Security enhancement in passive optical networks through wavelength hopping and sequences cycling technique

Growth in the telecommunication industry continues to expand with requirements evolving around increased bandwidth and security. Advances in networking technologies have introduced low cost optical components that has made passive optical networks (PON) the choice for providing huge bandwidth to end users. PON are covered by established standards such as IEEE 802.3ah and ITU-T G.983.1/984.1, with star topology of broadcast and select (B&S) on shared fiber links that poses security vulnerability in terms of confidentiality and privacy;Research and reports in the literature focus around increasing cardinality via coding schemes that lack in addressing security, which was left for implementation in application layers via cryptography. This dissertation presents an approach on security in PON at the network level using slow wavelength hopping techniques and diffusion of data packets among dense wave division multiplex (DWDM). Orthogonal wavelength sequences are generated by mapping an ITU-T G694.1 based wavelength grid matrix and code matrices. The arrangement of wavelengths in the wavelength grid matrix, which can be changed frequently (i.e, hourly) serves as the first key of secure operation. Allocation of generated wavelength sequences distributed in multiple quantities to nodes based on their security level serve as second individual keys for the nodes. In addition, an improved level of security provided via the cycling order of those allocated wavelength sequences to nodes is the third key between the central office (CO) and a node. The proposed approach to PON security provides three new keys available outside the world of cryptography;Various coding techniques are used, and results show that even time spreading/wavelength hopping based on symmetric prime numbers provided the least wavelength sequences; however, it provided excellent correlation properties and level of security. A PON simulation model was implemented to investigate channel impairments in DWDM with 64 channels spaced at 25GHz carried over a 25 km ITU-T G.655 compliant shared fiber cable. Security performance evaluation included analytical studies in classical probabilities to capture the correct order of wavelength hopping sequence using exhaustive searching and reverse construction of matrices from monitored channels. Encouraging results obtained support the feasibility of this proposed technical approach for security

Analog radio over fiber solutions for multi-band 5g systems

This study presents radio over fiber (RoF) solutions for the fifth-generation (5G) of wireless networks. After the state of the art and a technical background review, four main contributions are reported. The first one is proposing and investigating a RoF technique based on a dual-drive Mach-Zehnder modulator (DD-MZM) for multi-band mobile fronthauls, in which two radiofrequency (RF) signals in the predicted 5G bands individually feed an arm of the optical modulator. Experimental results demonstrate the approach enhances the RF interference mitigation and can prevail over traditional methods. The second contribution comprises the integration of a 5G transceiver, previously developed by our group, in a passive optical network (PON) using RoF technology and wavelength division multiplexing (WDM) overlay. The proposed architecture innovates by employing DD-MZM and enables to simultaneously transport baseband and 5G candidate RF signals in the same PON infrastructure. The proof-of-concept includes the transmission of a generalized frequency division multiplexing (GFDM) signal generated by the 5G transceiver in the 700 MHz band, a 26 GHz digitally modulated signal as a millimeter-waves 5G band, and a baseband signal from an gigabit PON (GPON). Experimental results demonstrate the 5G transceiver digital performance when using RoF technology for distributing the GFDM signal, as well as Gbit/s throughput at 26 GHz. The third contribution is the implementation of a flexible-waveform and multi-application fiber-wireless (FiWi) system toward 5G. Such system includes the FiWi transmission of the GFDM and filtered orthogonal frequency division multiplexing (F-OFDM) signals at 788 MHz, toward long-range cells for remote or rural mobile access, as well as the recently launched 5G NR standard in microwave and mm-waves, aiming enhanced mobile broadband indoor and outdoor applications. Digital signal processing (DSP) is used for selecting the waveform and linearizing the RoF link. Experimental results demonstrate the suitability of the proposed solution to address 5G scenarios and requirements, besides the applicability of using existent fiber-to-the-home (FTTH) networks from Internet service providers for implementing 5G systems. Finally, the fourth contribution is the implementation of a multi-band 5G NR system with photonic-assisted RF amplification (PAA). The approach takes advantage of a novel PAA technique, based on RoF technology and four-wave mixing effect, that allows straightforward integration to the transport networks. Experimental results demonstrate iv uniform and stable 15 dB wideband gain for Long Term Evolution (LTE) and three 5G signals, distributed in the frequency range from 780 MHz to 26 GHz and coexisting in the mobile fronthaul. The obtained digital performance has efficiently met the Third-Generation Partnership Project (3GPP) requirements, demonstrating the applicability of the proposed approach for using fiber-optic links to distribute and jointly amplify LTE and 5G signals in the optical domain.Agência 1Este trabalho apresenta soluções de rádio sobre fibra (RoF) para aplicações em redes sem fio de quinta geração (5G), e inclui quatro contribuições principais. A primeira delas refere-se à proposta e investigação de uma técnica de RoF baseada no modulador eletroóptico de braço duplo, dual-drive Mach-Zehnder (DD-MZM), para a transmissão simultânea de sinais de radiofrequência (RF) em bandas previstas para redes 5G. Resultados experimentais demonstram que o uso do DD-MZM favorece a ausência de interferência entre os sinais de RF transmitidos. A segunda contribuição trata da integração de um transceptor de RF, desenvolvido para aplicações 5G e apto a prover a forma de onda conhecida como generalized frequency division multiplexing (GFDM), em uma rede óptica passiva (PON) ao utilizar RoF e multiplexação por divisão de comprimento de onda (WDM). A arquitetura proposta permite transportar, na mesma infraestrutura de rede, sinais em banda base e de radiofrequência nas faixas do espectro candidatas para 5G. A prova de conceito inclui a distribuição conjunta de três tipos de sinais: um sinal GFDM na banda de 700 MHz, proveniente do transceptor desenvolvido; um sinal digital na frequência de 26 GHz, assumindo a faixa de ondas milimétricas; sinais em banda base provenientes de uma PON dedicada ao serviço de Internet. Resultados experimentais demonstram o desempenho do transceptor de RF ao utilizar a referida arquitetura para distribuir sinais GFDM, além de taxas de transmissão de dados da ordem de Gbit/s na faixa de 26 GHz. A terceira contribuição corresponde à implementação de um sistema fibra/rádio potencial para redes 5G, operando inclusive com o padrão ―5G New Radio (5G NR)‖ nas faixas de micro-ondas e ondas milimétricas. Tal sistema é capaz de prover macro células na banda de 700 MHz para aplicações de longo alcance e/ou rurais, utilizando sinais GFDM ou filtered orthogonal frequency division multiplexing (F-OFDM), assim como femto células na banda de 26 GHz, destinada a altas taxas de transmissão de dados para comunicações de curto alcance. Resultados experimentais demonstram a aplicabilidade da solução proposta para redes 5G, além da viabilidade de utilizar redes ópticas pertencentes a provedores de Internet para favorecer sistemas de nova geração. Por fim, a quarta contribuição trata da implementação de um sistema 5G NR multibanda, assistido por amplificação de RF no domínio óptico. Esse sistema faz uso de um novo método de amplificação, baseado no efeito não linear da mistura de quatro ondas, que vi permite integração direta em redes de transporte envolvendo rádio sobre fibra. Resultados experimentais demonstram ganho de RF igual a 15 dB em uma ampla faixa de frequências (700 MHz até 26 GHz), atendendo simultaneamente tecnologias de quarta e quinta geração. O desempenho digital obtido atendeu aos requisitos estabelecidos pela 3GPP (Third-Generation Partnership Project), indicando a aplicabilidade da solução em questão para distribuir e conjuntamente amplificar sinais de RF em enlaces de fibra óptica

Virtual network function development for NG-PON Access Network Architecture

Dissertação de mestrado em Engenharia de Redes e Serviços TelemáticosThe access to Internet services on a large scale, high throughput and low latency has grown at a very high pace over time, with a growing demand for media content and applications increasingly oriented towards data consumption. This fact about the use of data at the edge of the network requires the Central Offices (CO) of telecommunication providers, to be pre pared to absorb these demands. COs generally offer data from various access methods, such as Passive Optical Network (PON) technologies, mobile networks, copper wired and oth ers. For each of these technologies there may be different manufacturers that support only their respective hardware and software solutions, although they all share different network resources and have management, configuration and monitoring tools (Fault, Configuration, Accounting, Performance, and Security management - FCAPS) similar, but being distinct and isolated from each other, which produces huge investment in Capital Expenditure (CAPEX) and Operational Expenditure (OPEX) and can cause barriers to innovation. Such panora mas forced the development of more flexible, scalable solutions that share platforms and net work architectures that can meet this need and enable the evolution of networks. It is then proposed the architecture of Software-Defined Network (SDN) which has in its proposal to abstract the control plane from the data plane, in addition to the virtualization of several Net work Function Virtualization (NFV). The SDN architecture allows APIs and protocols such as Openflow, NETCONF / YANG, RESTCONF, gRPC and others to be used so that there is communication between the various hardware and software elements that compose the net work and consume network resources, such as services AAA, DHCP, routing, orchestration, management or various applications that may exist in this context. This work then aims at the development of a virtualized network function, namely a VNF in the context of network security to be integrated as a component of an architecture guided by the SDN paradigm applied to broadband networks, and also adherent to the architecture OB-BAA promoted by the Broadband Forum. Such OB-BAA architecture fits into the initia tive to modernize the Information Technology (IT) components of broadband networks, more specifically the Central Offices. With such development, it was intended to explore the con cepts of network security, such as the IEEE 802.1X protocol applied in NG-PON networks for authentication and authorization of new network equipment. To achieve this goal, the development of the applications was based on the Golang language combined with gRPC programmable interfaces for communication between the various elements of the architec ture. Network emulators were initially used, and then the components were ”containerized” and inserted in the Docker and Kubernetes virtualization frameworks. Finally, performance metrics were analyzed in the usage tests, namely computational resource usage metrics (CPU, memory and network I/O), in addition to the execution time of several processes performed by the developed applications.O acesso aos serviços de Internet em larga escala, alto débito e baixa latência têm crescido em um ritmo bastante elevado ao longo dos tempos, com uma demanda crescente por conteúdos de media e aplicações cada vez mais orientadas ao consumo de dados. Tal fato acerca da uti lização de dados na periferia da rede, obriga a que os Central Offices (CO) dos provedores de telecomunicações estejam preparados para absorver estas demandas. Os CO geralmente re cebem dados de diversos métodos de acesso, como tecnologias Passive Optical Network (PON), redes móveis, cabladas em cobre, entre outros. Para cada uma destas tecnologias pode haver diferentes fabricantes que suportam somente suas respetivas soluções de hardware e software, apesar de todas compartilharem diversos recursos de rede e possuírem ferramentas de gestão, configuração e monitoração (Fault-management, Configuration, Accounting, Performance e Segurança - FCAPS) similares, mas serem distintas e isoladas entre si, o que se traduz em um enorme investimento em Capital Expenditure (CAPEX) e Operational Expenditure (OPEX) e pode causar barreiras à inovação. Tais panoramas forçaram o desenvolvimento de soluções mais flexíveis, escaláveis e que compartilhem plataformas e arquiteturas de redes que pos sam suprir tal necessidade e possibilitar a evolução das redes. Propõe-se então a arquitetura de redes definidas por software (Software-Defined Network - SDN) que tem em sua proposta abstrair o plano de controle do plano de dados, além da virtualização de diversas funções de rede (Network Function Virtualization - NFV). A arquitetura SDN possibilita que API’s e pro tocolos como Openflow, NETCONF/YANG, RESTCONF, gRPC e outros, sejam utilizados para que haja comunicação entre os diversos elementos de hardware e software que estejam a compor a rede e a consumir recursos de redes, como serviços de AAA, DHCP, roteamento, orquestração, gestão ou diversas outras aplicações que possam existir neste contexto. Este trabalho visa então o desenvolvimento de uma função de rede virtualizada nomeada mente uma (Virtual Network Function - VNF) no âmbito de segurança de redes a ser integrada como um componente de uma arquitetura orientada pelo paradigma de SDN aplicado a re des de banda larga, e aderente também à arquitetura OB-BAA promovida pelo Broadband Fo rum. Tal arquitetura OB-BAA se enquadra na iniciativa de modernização dos componentes de Tecnologia da Informação (TI) das redes de banda larga, mais especificamente dos Cen tral Offices. Com tal desenvolvimento pretende-se explorar conceitos de segurança de redes, como o protocolo IEEE 802.1X aplicado em redes NG-PON para autenticação e autorização de novos equipamentos de rede. Para atingir tal objetivo, utilizou-se desenvolvimento de aplicações baseadas na linguagem Golang aliado com interfaces programáveis gRPC para comunicação entre os diversos elementos da arquitetura. Para emular tais componentes, utilizou-se inicialmente emuladores de rede, e em um segundo momento os componentes foram ”containerizados” e inseridos nos frameworks de virtualização Docker e Kubernetes.Por fim, foram analisadas métricas de desempenho nos testes executados, nomeadamente métricas de utilização de recursos computacionais (CPU, memória e tráfego de rede), além do tempo de execução de diversos processos desempenhados pelas aplicações desenvolvidas

Adaptive modulation techniques for passive optical networks

Smart use of fiber networks to increase capacity to the hom

Data-driven visual quality estimation using machine learning

Heutzutage werden viele visuelle Inhalte erstellt und sind zugänglich, was auf Verbesserungen der Technologie wie Smartphones und das Internet zurückzuführen ist. Es ist daher notwendig, die von den Nutzern wahrgenommene Qualität zu bewerten, um das Erlebnis weiter zu verbessern. Allerdings sind nur wenige der aktuellen Qualitätsmodelle speziell für höhere Auflösungen konzipiert, sagen mehr als nur den Mean Opinion Score vorher oder nutzen maschinelles Lernen. Ein Ziel dieser Arbeit ist es, solche maschinellen Modelle für höhere Auflösungen mit verschiedenen Datensätzen zu trainieren und zu evaluieren. Als Erstes wird eine objektive Analyse der Bildqualität bei höheren Auflösungen durchgeführt. Die Bilder wurden mit Video-Encodern komprimiert, hierbei weist AV1 die beste Qualität und Kompression auf. Anschließend werden die Ergebnisse eines Crowd-Sourcing-Tests mit einem Labortest bezüglich Bildqualität verglichen. Weiterhin werden auf Deep Learning basierende Modelle für die Vorhersage von Bild- und Videoqualität beschrieben. Das auf Deep Learning basierende Modell ist aufgrund der benötigten Ressourcen für die Vorhersage der Videoqualität in der Praxis nicht anwendbar. Aus diesem Grund werden pixelbasierte Videoqualitätsmodelle vorgeschlagen und ausgewertet, die aussagekräftige Features verwenden, welche Bild- und Bewegungsaspekte abdecken. Diese Modelle können zur Vorhersage von Mean Opinion Scores für Videos oder sogar für anderer Werte im Zusammenhang mit der Videoqualität verwendet werden, wie z.B. einer Bewertungsverteilung. Die vorgestellte Modellarchitektur kann auf andere Videoprobleme angewandt werden, wie z.B. Videoklassifizierung, Vorhersage der Qualität von Spielevideos, Klassifikation von Spielegenres oder der Klassifikation von Kodierungsparametern. Ein wichtiger Aspekt ist auch die Verarbeitungszeit solcher Modelle. Daher wird ein allgemeiner Ansatz zur Beschleunigung von State-of-the-Art-Videoqualitätsmodellen vorgestellt, der zeigt, dass ein erheblicher Teil der Verarbeitungszeit eingespart werden kann, während eine ähnliche Vorhersagegenauigkeit erhalten bleibt. Die Modelle sind als Open Source veröffentlicht, so dass die entwickelten Frameworks für weitere Forschungsarbeiten genutzt werden können. Außerdem können die vorgestellten Ansätze als Bausteine für neuere Medienformate verwendet werden.Today a lot of visual content is accessible and produced, due to improvements in technology such as smartphones and the internet. This results in a need to assess the quality perceived by users to further improve the experience. However, only a few of the state-of-the-art quality models are specifically designed for higher resolutions, predict more than mean opinion score, or use machine learning. One goal of the thesis is to train and evaluate such machine learning models of higher resolutions with several datasets. At first, an objective evaluation of image quality in case of higher resolutions is performed. The images are compressed using video encoders, and it is shown that AV1 is best considering quality and compression. This evaluation is followed by the analysis of a crowdsourcing test in comparison with a lab test investigating image quality. Afterward, deep learning-based models for image quality prediction and an extension for video quality are proposed. However, the deep learning-based video quality model is not practically usable because of performance constrains. For this reason, pixel-based video quality models using well-motivated features covering image and motion aspects are proposed and evaluated. These models can be used to predict mean opinion scores for videos, or even to predict other video quality-related information, such as a rating distributions. The introduced model architecture can be applied to other video problems, such as video classification, gaming video quality prediction, gaming genre classification or encoding parameter estimation. Furthermore, one important aspect is the processing time of such models. Hence, a generic approach to speed up state-of-the-art video quality models is introduced, which shows that a significant amount of processing time can be saved, while achieving similar prediction accuracy. The models have been made publicly available as open source so that the developed frameworks can be used for further research. Moreover, the presented approaches may be usable as building blocks for newer media formats

An Innovative RAN Architecture for Emerging Heterogeneous Networks: The Road to the 5G Era

The global demand for mobile-broadband data services has experienced phenomenal growth over the last few years, driven by the rapid proliferation of smart devices such as smartphones and tablets. This growth is expected to continue unabated as mobile data traffic is predicted to grow anywhere from 20 to 50 times over the next 5 years. Exacerbating the problem is that such unprecedented surge in smartphones usage, which is characterized by frequent short on/off connections and mobility, generates heavy signaling traffic load in the network signaling storms . This consumes a disproportion amount of network resources, compromising network throughput and efficiency, and in extreme cases can cause the Third-Generation (3G) or 4G (long-term evolution (LTE) and LTE-Advanced (LTE-A)) cellular networks to crash. As the conventional approaches of improving the spectral efficiency and/or allocation additional spectrum are fast approaching their theoretical limits, there is a growing consensus that current 3G and 4G (LTE/LTE-A) cellular radio access technologies (RATs) won\u27t be able to meet the anticipated growth in mobile traffic demand. To address these challenges, the wireless industry and standardization bodies have initiated a roadmap for transition from 4G to 5G cellular technology with a key objective to increase capacity by 1000Ã? by 2020 . Even though the technology hasn\u27t been invented yet, the hype around 5G networks has begun to bubble. The emerging consensus is that 5G is not a single technology, but rather a synergistic collection of interworking technical innovations and solutions that collectively address the challenge of traffic growth. The core emerging ingredients that are widely considered the key enabling technologies to realize the envisioned 5G era, listed in the order of importance, are: 1) Heterogeneous networks (HetNets); 2) flexible backhauling; 3) efficient traffic offload techniques; and 4) Self Organizing Networks (SONs). The anticipated solutions delivered by efficient interworking/ integration of these enabling technologies are not simply about throwing more resources and /or spectrum at the challenge. The envisioned solution, however, requires radically different cellular RAN and mobile core architectures that efficiently and cost-effectively deploy and manage radio resources as well as offload mobile traffic from the overloaded core network. The main objective of this thesis is to address the key techno-economics challenges facing the transition from current Fourth-Generation (4G) cellular technology to the 5G era in the context of proposing a novel high-risk revolutionary direction to the design and implementation of the envisioned 5G cellular networks. The ultimate goal is to explore the potential and viability of cost-effectively implementing the 1000x capacity challenge while continuing to provide adequate mobile broadband experience to users. Specifically, this work proposes and devises a novel PON-based HetNet mobile backhaul RAN architecture that: 1) holistically addresses the key techno-economics hurdles facing the implementation of the envisioned 5G cellular technology, specifically, the backhauling and signaling challenges; and 2) enables, for the first time to the best of our knowledge, the support of efficient ground-breaking mobile data and signaling offload techniques, which significantly enhance the performance of both the HetNet-based RAN and LTE-A\u27s core network (Evolved Packet Core (EPC) per 3GPP standard), ensure that core network equipment is used more productively, and moderate the evolving 5G\u27s signaling growth and optimize its impact. To address the backhauling challenge, we propose a cost-effective fiber-based small cell backhaul infrastructure, which leverages existing fibered and powered facilities associated with a PON-based fiber-to-the-Node/Home (FTTN/FTTH)) residential access network. Due to the sharing of existing valuable fiber assets, the proposed PON-based backhaul architecture, in which the small cells are collocated with existing FTTN remote terminals (optical network units (ONUs)), is much more economical than conventional point-to-point (PTP) fiber backhaul designs. A fully distributed ring-based EPON architecture is utilized here as the fiber-based HetNet backhaul. The techno-economics merits of utilizing the proposed PON-based FTTx access HetNet RAN architecture versus that of traditional 4G LTE-A\u27s RAN will be thoroughly examined and quantified. Specifically, we quantify the techno-economics merits of the proposed PON-based HetNet backhaul by comparing its performance versus that of a conventional fiber-based PTP backhaul architecture as a benchmark. It is shown that the purposely selected ring-based PON architecture along with the supporting distributed control plane enable the proposed PON-based FTTx RAN architecture to support several key salient networking features that collectively significantly enhance the overall performance of both the HetNet-based RAN and 4G LTE-A\u27s core (EPC) compared to that of the typical fiber-based PTP backhaul architecture in terms of handoff capability, signaling overhead, overall network throughput and latency, and QoS support. It will also been shown that the proposed HetNet-based RAN architecture is not only capable of providing the typical macro-cell offloading gain (RAN gain) but also can provide ground-breaking EPC offloading gain. The simulation results indicate that the overall capacity of the proposed HetNet scales with the number of deployed small cells, thanks to LTE-A\u27s advanced interference management techniques. For example, if there are 10 deployed outdoor small cells for every macrocell in the network, then the overall capacity will be approximately 10-11x capacity gain over a macro-only network. To reach the 1000x capacity goal, numerous small cells including 3G, 4G, and WiFi (femtos, picos, metros, relays, remote radio heads, distributed antenna systems) need to be deployed indoors and outdoors, at all possible venues (residences and enterprises)