Fronthaul-Constrained Cloud Radio Access Networks: Insights and Challenges

As a promising paradigm for fifth generation (5G) wireless communication systems, cloud radio access networks (C-RANs) have been shown to reduce both capital and operating expenditures, as well as to provide high spectral efficiency (SE) and energy efficiency (EE). The fronthaul in such networks, defined as the transmission link between a baseband unit (BBU) and a remote radio head (RRH), requires high capacity, but is often constrained. This article comprehensively surveys recent advances in fronthaul-constrained C-RANs, including system architectures and key techniques. In particular, key techniques for alleviating the impact of constrained fronthaul on SE/EE and quality of service for users, including compression and quantization, large-scale coordinated processing and clustering, and resource allocation optimization, are discussed. Open issues in terms of software-defined networking, network function virtualization, and partial centralization are also identified.Comment: 5 Figures, accepted by IEEE Wireless Communications. arXiv admin note: text overlap with arXiv:1407.3855 by other author

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

A Comprehensive Survey on Resource Allocation for CRAN in 5G and Beyond Networks

The diverse service requirements coming with the advent of sophisticated applications as well as a large number of connected devices demand for revolutionary changes in the traditional distributed radio access network (RAN). To this end, Cloud-RAN (CRAN) is considered as an important paradigm to enhance the performance of the upcoming fifth generation (5G) and beyond wireless networks in terms of capacity, latency, and connectivity to a large number of devices. Out of several potential enablers, efficient resource allocation can mitigate various challenges related to user assignment, power allocation, and spectrum management in a CRAN, and is the focus of this paper. Herein, we provide a comprehensive review of resource allocation schemes in a CRAN along with a detailed optimization taxonomy on various aspects of resource allocation. More importantly, we identity and discuss the key elements for efficient resource allocation and management in CRAN, namely: user assignment, remote radio heads (RRH) selection, throughput maximization, spectrum management, network utility, and power allocation. Furthermore, we present emerging use-cases including heterogeneous CRAN, millimeter-wave CRAN, virtualized CRAN, Non- Orthogonal Multiple Access (NoMA)-based CRAN and fullduplex enabled CRAN to illustrate how their performance can be enhanced by adopting CRAN technology. We then classify and discuss objectives and constraints involved in CRAN-based 5G and beyond networks. Moreover, a detailed taxonomy of optimization methods and solution approaches with different objectives is presented and discussed. Finally, we conclude the paper with several open research issues and future directions

Will SDN be part of 5G?

For many, this is no longer a valid question and the case is considered settled with SDN/NFV (Software Defined Networking/Network Function Virtualization) providing the inevitable innovation enablers solving many outstanding management issues regarding 5G. However, given the monumental task of softwarization of radio access network (RAN) while 5G is just around the corner and some companies have started unveiling their 5G equipment already, the concern is very realistic that we may only see some point solutions involving SDN technology instead of a fully SDN-enabled RAN. This survey paper identifies all important obstacles in the way and looks at the state of the art of the relevant solutions. This survey is different from the previous surveys on SDN-based RAN as it focuses on the salient problems and discusses solutions proposed within and outside SDN literature. Our main focus is on fronthaul, backward compatibility, supposedly disruptive nature of SDN deployment, business cases and monetization of SDN related upgrades, latency of general purpose processors (GPP), and additional security vulnerabilities, softwarization brings along to the RAN. We have also provided a summary of the architectural developments in SDN-based RAN landscape as not all work can be covered under the focused issues. This paper provides a comprehensive survey on the state of the art of SDN-based RAN and clearly points out the gaps in the technology.Comment: 33 pages, 10 figure

Efficient Management of Flexible Functional Splits in 5G Second Phase Networks

The fifth mobile network generation (5G), which offers better data speeds, reduced latency, and a huge number of network connections, promises to improve the performance of the cellular network in practically every way available. A portion of the network operations are deployed in a centralized unit in the 5G radio access network (RAN) partially centralized design. By centralizing these functions, operational expenses are decreased and coordinating strategies are made possible. To link centralized units (CU) and distributed units (DU), and the DU to remote radio units (RRU), both the midhaul and fronthaul networks must have higher capacity. The necessary fronthaul capacity is also influenced by the fluctuating instantaneous user traffic. Consequently, the 5G RAN must be able to dynamically change its centralization level to the user traffic to maximize its performance. To try to relieve this fronthaul capacity it has been considered a more flexible distribution between the base band unit (BBU) (or CU and DU if enhanced common public radio interface (eCPRI) is considered) and the RRU. It may be challenging to provide high-speed data services in crowded areas, particularly when there is imperfect coverage or significant interference. Because of this, the macrocell deployment is insufficient. This problem for outdoor users could be resolved by the introduction of low-power nodes with a limited coverage area. In this context, this MSc dissertation explores, in an urban micro cell scenario model A (UMi_A) for three frequency bands (2.6 GHz, 3.5 GHz, and 5.62 GHz), the highest data rate achievable when a numerology zero is used. For this, it was necessary the implementation of the UMi_A in the 5G-air-simulator. Allowing the determination of the saturation level using the results for the packet loss ratio (PLR=2%). By assuming Open RAN (O-RAN) and functional splitting, the performance of two schedulers in terms of quality-of-service (QoS) were also studied. The QoS-aware modified largest weighted delay first (M-LWDF) scheduler and the QoS-unaware proportional fair (PF) scheduler. PLR was evaluated for both schedulers, whilst analyzing the impact of break point distance while changing the frequency band. The costs, revenues, profit in percentage terms, and other metrics were also estimated for the PF and M-LWDF schedulers when used video (VID) and video plus best effort (VID+BE), with or without consideration of the functional splits 7.2 and 6, for the three frequency bands. One concluded that the profit in percentage terms with functional split option 7.2 applied is always slightly higher than with functional split option 6. It reaches a maximum profit of 366.92% in the case of the M-LWDF scheduler, and 305.51% in the case of the PF scheduler, at a cell radius of 0.4 km for the 2.6 GHz frequency band, considering a price of the traffic of 0.0002 €/min.A quinta geração de redes móveis (5G), oferece ritmos de transmissão melhorados, atraso extremo-a-extremo reduzido, e um vasto número de ligações de rede. A 5G promete melhorar o desempenho das redes celulares em praticamente todos os aspectos relevantes. Uma parte da operação da rede é colocada numa unidade centralizada na rede de acesso de rádio (RAN) 5G com dimensionamento parcialmente centralizado. Ao centralizar estas funções, os custos operacionais decrescem, viabilizando-se as estratégias de coordenação. Para ligar as unidades centralizadas e unidades distribuídas, e por sua vez, unidades distribuidas e unidades de rádio remotas, ambos os midhaul e fronthaul devem ter uma capacidade mais elevada. A capacidade da fronthaul necessária é também influenciada pela flutuação do tráfego instantâneo dos utilizadores. Consequentemente, a RAN 5G deve ser capaz de alterar dinamicamente o seu nível de centralização para o tráfego de utilizadores, com objetivo de maximizar o seu desempenho. Para tentar aliviar o aumento da capacidade suportada pelo fronthaul, tem sido considerada uma distribuição mais flexível entre a unidade de banda base, BBU (ou unidade central e unidade distribuída se a interface de rádio pública comum melhorada, eCPRI, for considerada), e a unidade de rádio remota, RRU. Em áreas densamente povoadas, pode ser um desafio fornecer serviços de dados de elevada velocidade, particularmente quando existe uma cobertura deficiente ou interferência significativa. Por este motivo, o desenvolvimento de macrocélulas pode ser insuficiente, mas este problema para utilizadores em ambiente de exterior pode ser mitigado com a introdução de nós de potência reduzida com uma área de cobertura limitada. Neste contexto, esta dissertação de mestrado explora, num cenário urbano de microcélulas caracterizado pelo modelo A (UMi_A) para três bandas de frequência (2.6 GHz, 3.5 GHz, e 5.62 GHz), o débito binário máximo que se pode alcançar quando se utiliza numerologia zero. Para tal, foi necessária a implementação do UMi_A no 5G - air - simulator. Determinou-se o nivel de saturação, considerandose os resultados para a taxa de perda de pacotes (PLR=2%). Estudou-se o desempenho de dois escalonadores de pacotes em termos de qualidade de serviço (QoS), assumindo-se o OpenRAN (O-RAN) e as divisões funcionais (functionalsplitting). Um dos escalonadores é ciente da QoS, e é de atraso máximo-superior ponderado primeiro (M-LWDF), enquanto que o outro não é ciente da QoS, e é de justiça proporcional (PF). Avaliou-se o PLR para ambos os escalonadores de pacotes, estudando-se o impacto da distância de ponto de quebra (breakpointdistance), variando-se a banda de frequências. Foram também estimados os custos, proveitos, o lucro (em percentagem), e outras metricas, para os escalonadores PF e M-LWDF, considerando o vídeo (VID) e vídeo mais besteffort (VID+BE) como aplicações, com ou sem a consideração das divisões funcionais 7.2 e 6, para as três bandas de frequência. Concluiu-se que o lucro em termos percentuais, com a escolha da opção de divisão funcional 7.2, é sempre ligeiramente mais elevado do que com a opção de divisão funcional 6. Atingese um lucro máximo de 366,92% no caso do escalonador M-LWDF, e de 305,51% no caso do escalonador PF, para um raio de célula de 0,4 km, para a banda de frequência de 2,6 GHz, considerando-se um preço do tráfego de 0,0002 €/min