A comprehensive survey on radio resource management in 5G HetNets: current solutions, future trends and open issues

The 5G network technologies are intended to accommodate innovative services with a large influx of data traffic with lower energy consumption and increased quality of service and user quality of experience levels. In order to meet 5G expectations, heterogeneous networks (HetNets) have been introduced. They involve deployment of additional low power nodes within the coverage area of conventional high power nodes and their placement closer to user underlay HetNets. Due to the increased density of small-cell networks and radio access technologies, radio resource management (RRM) for potential 5G HetNets has emerged as a critical avenue. It plays a pivotal role in enhancing spectrum utilization, load balancing, and network energy efficiency. In this paper, we summarize the key challenges i.e., cross-tier interference, co-tier interference, and user association-resource-power allocation (UA-RA-PA) emerging in 5G HetNets and highlight their significance. In addition, we present a comprehensive survey of RRM schemes based on interference management (IM), UA-RA-PA and combined approaches (UA-RA-PA + IM). We introduce a taxonomy for individual (IM, UA-RA-PA) and combined approaches as a framework for systematically studying the existing schemes. These schemes are also qualitatively analyzed and compared to each other. Finally, challenges and opportunities for RRM in 5G are outlined, and design guidelines along with possible solutions for advanced mechanisms are presented

A survey of multi-access edge computing in 5G and beyond : fundamentals, technology integration, and state-of-the-art

Driven by the emergence of new compute-intensive applications and the vision of the Internet of Things (IoT), it is foreseen that the emerging 5G network will face an unprecedented increase in traffic volume and computation demands. However, end users mostly have limited storage capacities and finite processing capabilities, thus how to run compute-intensive applications on resource-constrained users has recently become a natural concern. Mobile edge computing (MEC), a key technology in the emerging fifth generation (5G) network, can optimize mobile resources by hosting compute-intensive applications, process large data before sending to the cloud, provide the cloud-computing capabilities within the radio access network (RAN) in close proximity to mobile users, and offer context-aware services with the help of RAN information. Therefore, MEC enables a wide variety of applications, where the real-time response is strictly required, e.g., driverless vehicles, augmented reality, robotics, and immerse media. Indeed, the paradigm shift from 4G to 5G could become a reality with the advent of new technological concepts. The successful realization of MEC in the 5G network is still in its infancy and demands for constant efforts from both academic and industry communities. In this survey, we first provide a holistic overview of MEC technology and its potential use cases and applications. Then, we outline up-to-date researches on the integration of MEC with the new technologies that will be deployed in 5G and beyond. We also summarize testbeds and experimental evaluations, and open source activities, for edge computing. We further summarize lessons learned from state-of-the-art research works as well as discuss challenges and potential future directions for MEC research

Analysis and Design of Millimeter Wave Cellular Networks

Millimeter wave (mmWave) communications has been widely acknowledged as an attractive strategy for the rapidly growing data rate requirements of cellular user equipments (UEs), due to the vast amounts of available frequencies at the mmWave band. However, the unique propagation characteristics of mmWave, including 1) high path loss, 2) extreme sensitivity to blockage, and 3) rapid channel fluctuations, bring serious challenges to the deployment of mmWave cellular networks. Against this background, this thesis focuses on the analysis and design of mmWave cellular networks. In Chapter 1, the motivation of the studies presented in this thesis is described. Moreover, a literature review of several key research topics is presented, including mmWave channel models, mmWave-enabled heterogeneous networks (HetNets), mmWave precoding, mmWave-based non-orthogonal multiple access (NOMA), and mmWave prototypes. Furthermore, an overview of this thesis is provided. In Chapter 2, a two-tier mmWave cellular HetNet is considered. As pointed out by the 3rd Generation Partnership Project (3GPP), a major issue in the HetNet is that high-power BSs are often heavily loaded, while low-power BSs are always lightly loaded and therefore not fully exploited. This load disparity inevitably leads to suboptimal resource allocation across the network, where a large number of UEs may be associated with one high-power BS but experience poor date rates. To increase the load of low-power BSs and strike a load balance between high-power BSs and low-power BSs, an association bias factor needs to be added to increase the possibility that UEs are associated with low-power BSs. In this chapter, we conduct novel analysis to assess the impact of the bias factor on the rate coverage performance of the considered network. In order to obtain tractable analytical results on the rate coverage probability, we model the considered network using a stochastic geometry based approach. We first analyze the loads of high-power BSs and low-power BSs, based on which we derive a new expression for the rate coverage probability of the network. Through numerical results, we demonstrate the correctness of our analysis. In addition, we thoroughly examine the impact of load balancing and various network parameters on the rate coverage probability, offering valuable guidelines on the design of practical mmWave HetNets. In Chapter 3, a relay assisted mmWave cellular network is considered. In this network, the BS adopts either the direct mode to transmit to the destination UE, or the relay mode if the direct mode fails, where the BS transmits to the relay and then the relay transmits to the destination UE. To address the drastic rotational movements of destination UEs in practice, we propose to adopt selection combining at destination UEs. Similar to Chapter 2, in order to obtain tractable analytical results on the system-level coverage probability, we model the system using a stochastic geometry based approach. New expression is derived for the signal-to-interference-plus-noise ratio (SINR) coverage probability of the network. Using numerical results, we first demonstrate the accuracy of our new expression. Then we show that ignoring spatial correlation, which has been commonly adopted in the literature, leads to severe overestimation of the SINR coverage probability. Furthermore, we show that introducing relays into a mmWave cellular network vastly improves the coverage performance. In addition, we show that the optimal BS density maximizing the SINR coverage probability can be determined by using our analysis. In Chapter 4, a summary of the conclusions drawn from this thesis is presented. Moreover, a number of future research directions are identified, including integrated mmWave/sub-6 GHz cellular networks, the mobility support in mmWave cellular networks, ultra-low latency mmWave cellular networks, and the transport layer design of mmWave cellular networks

D6.3 Intermediate system evaluation results

The overall purpose of METIS is to develop a 5G system concept that fulfil s the requirements of the beyond-2020 connected information society and to extend today’s wireless communication systems for new usage cases. First, in this deliverable an updated view on the overall METIS 5G system concept is presented. Thereafter, simulation results for the most promising technology components supporting the METIS 5G system concept are reported. Finally, s imulation results are presented for one relevant aspect of each Horizontal Topic: Direct Device - to - Device Communication, Massive Machine Communication, Moving Networks, Ultra - Dense Networks, and Ultra - Reliable Communication.Popovski, P.; Mange, G.; Fertl, P.; Gozálvez - Serrano, D.; Droste, H.; Bayer, N.; Roos, A.... (2014). D6.3 Intermediate system evaluation results. http://hdl.handle.net/10251/7676

A Survey on Energy Optimization Techniques in UAV-Based Cellular Networks: From Conventional to Machine Learning Approaches

Wireless communication networks have been witnessing an unprecedented demand due to the increasing number of connected devices and emerging bandwidth-hungry applications. Albeit many competent technologies for capacity enhancement purposes, such as millimeter wave communications and network densification, there is still room and need for further capacity enhancement in wireless communication networks, especially for the cases of unusual people gatherings, such as sport competitions, musical concerts, etc. Unmanned aerial vehicles (UAVs) have been identified as one of the promising options to enhance the capacity due to their easy implementation, pop up fashion operation, and cost-effective nature. The main idea is to deploy base stations on UAVs and operate them as flying base stations, thereby bringing additional capacity to where it is needed. However, because the UAVs mostly have limited energy storage, their energy consumption must be optimized to increase flight time. In this survey, we investigate different energy optimization techniques with a top-level classification in terms of the optimization algorithm employed; conventional and machine learning (ML). Such classification helps understand the state of the art and the current trend in terms of methodology. In this regard, various optimization techniques are identified from the related literature, and they are presented under the above mentioned classes of employed optimization methods. In addition, for the purpose of completeness, we include a brief tutorial on the optimization methods and power supply and charging mechanisms of UAVs. Moreover, novel concepts, such as reflective intelligent surfaces and landing spot optimization, are also covered to capture the latest trend in the literature.Comment: 41 pages, 5 Figures, 6 Tables. Submitted to Open Journal of Communications Society (OJ-COMS

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial

Network virtualization in next generation cellular networks

The complexity of operation and management of emerging cellular networks significantly increases, as they evolve to correspond to increasing QoS needs, data rates and diversity of offered services. Thus critical challenges appear regarding their performance. At the same time, network sustainability pushes toward the utilization of haring Radio Access Network (RAN) infrastructure between Mobile Network Operators (MNOs). This requires advanced network management techniques which have to be developed based on characteristics of these networks and traffic demands. Therefore it is necessary to provide solutions enabling the creation of logically isolated network partitions over shared physical network infrastructure. Multiple heterogeneous virtual networks should simultaneously coexist and support resource aggregation so as to appear as a single resource to serve different traffic types on demand. Hence in this thesis, we study RAN virtualization and slicing solutions destined to tackle these challenges. In the first part, we present our approach to map virtual network elements onto radio resources of the substrate physical network, in a dense multi-tier LTE-A scenario owned by a MNO. We propose a virtualization solution at BS level, where baseband modules of distributed BSs, interconnected via logical point-to-point X2 interface, cooperate to reallocate radio resources on a traffic need basis. Our proposal enhances system performance by achieving 53% throughput gain compared with benchmark schemes without substantial signaling overhead. In the second part of the thesis, we concentrate on facilitating resource provisioning between multiple Virtual MNOs (MVNOs), by integrating the capacity broker in the 3GPP network management architecture with minimum set of enhancements. A MNO owns the network and provides RAN access on demand to several MVNOs. Furthermore we propose an algorithm for on-demand resource allocation considering two types of traffic. Our proposal achieves 50% more admitted requests without Service Level Agreement (SLA) violation compared with benchmark schemes. In the third part, we devise and study a solution for BS agnostic network slicing leveraging BS virtualization in a multi-tenant scenario. This scenario is composed of different traffic types (e.g., tight latency requirements and high data rate demands) along with BSs characterized by different access and transport capabilities (i.e., Remote Radio Heads, RRHs, Small Cells, SCs and future 5G NodeBs, gNBs with various functional splits having ideal and non-ideal transport network). Our solution achieves 67% average spectrum usage gain and 16.6% Baseband Unit processing load reduction compared with baseline scenarios. Finally, we conclude the thesis by providing insightful research challenges for future works.La complejidad de la operación y la gestión de las emergentes redes celulares aumenta a medida que evolucionan para hacer frente a las crecientes necesidades de calidad de servicio (QoS), las tasas de datos y la diversidad de los servicios ofrecidos. De esta forma aparecen desafíos críticos con respecto a su rendimiento. Al mismo tiempo, la sostenibilidad de la red empuja hacia la utilización de la infraestructura de red de acceso radio (RAN) compartida entre operadores de redes móviles (MNO). Esto requiere técnicas avanzadas de gestión de redes que deben desarrollarse en función de las características especiales de estas redes y las demandas de tráfico. Por lo tanto, es necesario proporcionar soluciones que permitan la creación de particiones de red aisladas lógicamente sobre la infraestructura de red física compartida. Para ello, en esta tesis, estudiamos las soluciones de virtualización de la RAN destinadas a abordar estos desafíos. En la primera parte de la tesis, nos centramos en mapear elementos de red virtual en recursos de radio de la red física, en un escenario LTE-A de múltiples niveles que es propiedad de un solo MNO. Proponemos una solución de virtualización a nivel de estación base (BS), donde los módulos de banda base de BSs distribuidas, interconectadas a través de la interfaz lógica X2, cooperan para reasignar los recursos radio en función de las necesidades de tráfico. Nuestra propuesta mejora el rendimiento del sistema al obtener un rendimiento 53% en comparación con esquemas de referencia. En la segunda parte de la tesis, nos concentramos en facilitar el aprovisionamiento de recursos entre muchos operadores de redes virtuales móviles (MVNO), al integrar el capacity broker en la arquitectura de administración de red 3GPP con un conjunto míinimo de mejoras. En este escenario, un MNO es el propietario de la red y proporciona acceso bajo demanda (en inglés on-demand) a varios MVNOs. Además, para aprovechar al máximo las capacidades del capacity broker, proponemos un algoritmo para la asignación de recursos bajo demanda, considerando dos tipos de tráfico con distintas características. Nuestra propuesta alcanza 50% más de solicitudes admitidas sin violación del Acuerdo de Nivel de Servicio (SLA) en comparación con otros esquemas. En la tercera parte de la tesis, estudiamos una solución para el slicing de red independiente del tipo de BS, considerando la virtualización de BS en un escenario de múltiples MVNOs (multi-tenants). Este escenario se compone de diferentes tipos de tráfico (por ejemplo, usuarios con requisitos de latencia estrictos y usuarios con altas demandas de velocidad de datos) junto con BSs caracterizadas por diferentes capacidades de acceso y transporte (por ejemplo, Remote Radio Heads, RRHs, Small cells, SC y 5G NodeBs, gNBs con varias divisiones funcionales que tienen una red de transporte ideal y no ideal). Nuestra solución logra una ganancia promedio de uso de espectro de 67% y una reducción de la carga de procesamiento de la banda base de 16.6% en comparación con escenarios de referencia. Finalmente, concluimos la tesis al proporcionando los desafíos y retos de investigación para trabajos futuros.Postprint (published version

Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services

This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book