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5G cellular networks are designed to address the need for increased bandwidth of end users (eMBB services), high-reliability and low-latency of critical industrial use cases (URLLC), and long-range, low-power connectivity of machine-type IoT applications (mMTC). To meet such contrasting requirements, 5G networks rely on its new radio interface (5G-NR) to address eMBB and URLLC services and on LTE-M and NB-IoT for mMTC services. As of Release 16, 5G networks effectively support the extreme ends of key performance indicators, namely bandwidth, reliability, latency, coverage, and autonomy. This article analyzes the gap between those capabilities and the requirements of use cases as discussed in the NR-REDCAP 3GPP Study Item of Release 17: video surveillance, industrial IoT, and wearables, to name a few. This article further discusses the challenges driving the design of this new air interface for reduced-capability 5G devices in the sub-6 GHz band and key enablers to fulfill those use case requirements. [ABSTRACT FROM AUTHOR]

The virtualization of the fifth generation radio access network (RAN), which distributes the next generation Node B functions between a central unit (CU) and a distributed unit (DU), along with the emergence of slicing as a corner-stone of mobile communications networks, pose new challenges. One of these challenges is the management of the joint slicing and allocation of appropriate distribution of functions between CU and DU, known as functional split. In this work, a discussion on the challenges and open issues of joint slicing and functional splitting is presented, taking into account the additional complexity resulting from instantiating multiple slices per OU, each one with a different functional split. It is shown that the additional complexity, which is translated into higher cost, is worthwhile depending on the RAN deployment density. [ABSTRACT FROM AUTHOR]

Augmented reality (AR) has been presented lately as one of the key technology fields in which 5G networks can become a disruptive tool, raising interest from both industry and academia. The main goal of this article is to extend the current state of the art of distributed AR studies and implementations by extracting the main AR algorithms' offloading requirements individually. This extension is further achieved by depicting the data flow between these algorithms and their hardware requirements. From the obtained results, we estimate a preliminary set of network key performance indicators (KPIs) for a subset of three examples of distributed AR implementations highlighting the necessity of 5G technologies and their ecosystem to unveil the full potential of AR. Finally, based on these KPls, we propose a set of 5G configuration parameters for a successful distributed AR implementation. As most of the described algorithms are also used in virtual reality (VR) applications, our contributions can facilitate future distributed implementations of both AR and VR applications. [ABSTRACT FROM AUTHOR]

Next generation (NextG) cellular networks will be natively cloud-based and built on programmable, virtualized, and disaggregated architectures. The separation of control functions from the hardware fabric and the introduction of standardized control interfaces will enable the definition of custom closed-control loops, which will ultimately enable embedded intelligence and real-time analytics, thus effectively realizing the vision of autonomous and self-optimizing networks. This article explores the disaggregated network architecture proposed by the O-RAN Alliance as a key enabler of NextG networks. Within this architectural context, we discuss the potential, the challenges, and the limitations of data-driven optimization approaches to network control over different timescales. We also present the first large-scale integration of O-RAN-compliant software components with an open source full-stack softwarized cellular network. Experiments conducted on Colosseum, the world's largest wireless network emulator, demonstrate closed-loop integration of real-time analytics and control through deep reinforcement learning agents. We also show the feasibility of radio access network (RAN) control through xApps running on the near-real-time RAN intelligent controller to optimize the scheduling policies of coexisting network slices, leveraging the O-RAN open interfaces to collect data at the edge of the network. [ABSTRACT FROM AUTHOR]

The rapid development of communication technologies in the past decades has provided immense vertical opportunities for individuals and enterprises. However, conventional terrestrial cellular networks have unfortunately neglected the huge geographical digital divide, since high-bandwidth wireless coverage is concentrated in urban areas. To meet the goal of “connecting the unconnected,” integrating low Earth orbit (LEO) satellites with the terrestrial cellular networks has been widely considered as a promising solution. In this article, we first introduce the development roadmap of LEO satellite constellations (SatCons), including early attempts in LEO satellites with the emerging LEO constellations. Further, we discuss the unique opportunities of employing LEO SatCons for the delivery of integrating 5G networks. Specifically, we present their key performance indicators, which offer important guidelines for the design of associated enabling techniques, and then discuss the potential impact of integrating LEO SatCons with typical 5G use cases, where we engrave our vision of various vertical domains reshaped by LEO SatCons. Technical challenges are finally provided to specify future research directions. [ABSTRACT FROM AUTHOR]

With the emergence of virtualization and software automation for mobile networks, network slicing is enabling operators to dynamically provision network resources tuned to suit heterogeneous service requirements. This article investigates the architectures of the fifth generation (5G) of mobile networks experimental prototypes with a focus on network slicing. We present some existing 5G prototypes and identify their gaps. We then propose an architecture and a design of a 5G micro-service-based prototype. This prototype has the ability to auto-con-figure radio resources for network slices using machine-learning-powered decisions based on real-time acquired performance metrics. Finally, we discuss some use cases on top of this prototype and their related results before concluding. [ABSTRACT FROM AUTHOR]

The fifth generation (5G) of cellular networks aims at providing very high data rates, ultra-reliable low latency, and massive connection density. As one of the fundamental design trends toward these objectives, 5G exploits multi-connectivity (i.e., the concurrent use of multiple access networks), where multipath transport protocols have emerged as key technology enablers. The scheduler of a multipath transport protocol determines how to distribute the data packets onto different paths and has a critical impact on the protocol performance. Within this context, we present in this article the first empirical evaluation of state-of-the-art multipath schedulers based on real 5G data, for both static and mobile scenarios. Furthermore, we introduce M-Peekaboo, which builds on a state-of-the-art learning-based multipath scheduler and extends its usage to 5G networks. Our results illustrate the benefits of employing a learning-based multipath scheduler for 5G networks and motivate further studies of advanced learning schemes that can adapt more quickly to the path conditions, and take into account the emerging features and requirements of 5G and beyond networks. [ABSTRACT FROM AUTHOR]

The seven articles in this special section focus on agile radio resource management technologies for use in 5G mobile communications (5G). 5G networks will support a wide range of frequency bands, features, and use cases, with native support for efficient operation. 5G is considered as a significant disruptor to traditional mobile networks. Some of the main motivations behind the design, standardization, and deployment of the new generation of mobile networks include: significant increase of the supported data rates for enhanced mobile broadband, support for ultra-reliable and low-latency communications (URLLC), and support for massive machine type communications (mMTC). The combination of these 5G pillars can further enable new use cases, such as virtual or augmented reality (VR/AR), enabled by combining eMBB and URLLC. [ABSTRACT FROM AUTHOR]

The initial components of New Radio (NR) technology are being discussed within the 3GPP with the aim of not only satisfying the urgent needs of the 5G market but also the long-term requirements that network operators want to provide to customers. An expected solution to start delivering value immediately for the 5G systems is represented by LTE-NR tight-interworking, also known in the 3GPP specifications as EN-DC. With this new network architecture, existing LTE radio and core networks are used as a master entity for mobility management and coverage while adding a new secondary 5G carrier. In this article, we will illustrate the concepts and key features that 3GPP has specified for LTE-NR tight-interworking regarding the control and user plane domains. Our supporting performance evaluations highlight that EN-DC, at least in certain scenarios expected to exist in early deployments, is able to deliver better coverage and capacity compared to standalone LTE and NR technologies deployed alone. [ABSTRACT FROM AUTHOR]

The heterogeneity of the requirements for 5G necessitate a versatile 5G radio access network (RAN); slicing offers a way of realizing a flexible RAN through customized virtual subnetworks. In this article, we focus on how enabling lower-layer flexibility in the RAN affects the development of RAN slicing, particularly in relation to ensuring isolation between RAN slices. We first examine how RAN slices may be individually tailored for different services. We follow this up with an examination of the potential time-frequency resource structure of the RAN, focusing on the trade-off between flexibility and the overhead related to ensuring coexistence between contrasting RAN slices. Based on this analysis, we suggest an approach that permits the allocation of resources to a service-type to be performed separately to resource allocation for individual services belonging to that type. [ABSTRACT FROM AUTHOR]

mmWave radio, although instrumental for achieving the required 5G capacity KPIs, necessitates the need for a very large number of access points, which places an immense strain on the current network infrastructure. In this article, we try to identify the major challenges that inhibit the design of the Next Generation Fronthaul Interface in two upcoming distinctively highly dense environments: in Urban 5G deployments in metropolitan areas, and in ultra-dense Hotspot scenarios. Second, we propose a novel centralized and converged analog Fiber-Wireless Fronthaul architecture, specifically designed to facilitate mmWave access in the above scenarios. The proposed architecture leverages optical transceivers, optical add/drop multiplexers and optical beamforming integrated photonics towards a Digital Signal Processing analog fronthaul. The functional administration of the fronthaul infrastructure is achieved by means of a packetized Medium Transparent Dynamic Bandwidth Allocation protocol. Preliminary results show that the protocol can facilitate Gb/s-enabled data transport while abiding to the 5G low-latency KPIs in various network traffic conditions. [ABSTRACT FROM AUTHOR]

This article reviews state of the art channel coding techniques for URLLC. The stringent requirements of URLLC services, such as ultrahigh reliability and low latency, have made it the most challenging feature of 5G of mobile networks. The problem is even more challenging for services beyond the 5G promise, such as tele-surgery and factory automation, which require latencies less than 1ms and packet error rates as low as 10-9. This article provides an overview of channel coding techniques for URLLC and compares them in terms of performance and complexity. Several important research directions are identified and discussed in more detail. [ABSTRACT FROM AUTHOR]

This article investigates the slicing concept in the 5G RAN with the related challenges and research problems. The objective is to identify the plausible options for implementing the slicing concept at the RAN level by the mobile network operator to respond to the needs of verticals. We start by identifying the different slice granularity options, that is, how to define slices by combining customer and service needs. We then present how the 5G NR features can be used for facilitating slice implementation and provide typical configurations for different slice types from technology and RAN architecture perspectives. The main challenges for RAN slicing are then discussed, with special attention to the resource allocation problem between slices sharing the same spectrum band. We also investigate the multi-tenant slicing implementation in terms of the openness of the network to third parties, which is regarded as a key issue that may encourage vertical players to use operators' networks rather than deploying their own infrastructure. [ABSTRACT FROM AUTHOR]

The requirement of high data rates, low latency, efficient use of spectrum, and coexistence of different network technologies are major considerations in Internet of Things (IoT)-based fifth generation (5G) networks. To achieve the above requirements, the incorporation of artificial intelligence (AI) is required to make efficient decisions based on the massive data generated by the large number of IoT devices. AI methods analyze the data to extract patterns and make sense of the data to prescribe action to the end devices. In this work, we first give an overview, discussing the challenges and relevant solutions of the 5G and IoT technologies including the IoT-based 5G enabling technologies. We discuss the need for AI in future IoT-based 5G networks from the perspective of Kipling's method. In addition, we review the intelligent use of spectrum through full duplex and cognitive radio technologies. [ABSTRACT FROM AUTHOR]

5G networks are expected to be able to satisfy users' different QoS requirements. Network slicing is a promising technology for 5G networks to provide services tailored for users' specific QoS demands. Driven by the increased massive wireless data traffic from different application scenarios, efficient resource allocation schemes should be exploited to improve the flexibility of network resource allocation and capacity of 5G networks based on network slicing. Due to the diversity of 5G application scenarios, new mobility management schemes are greatly needed to guarantee seamless handover in network-slicing-based 5G systems. In this article, we introduce a logical architecture for network-slicing-based 5G systems, and present a scheme for managing mobility between different access networks, as well as a joint power and subchannel allocation scheme in spectrum-sharing two-tier systems based on network slicing, where both the co-tier interference and cross-tier interference are taken into account. Simulation results demonstrate that the proposed resource allocation scheme can flexibly allocate network resources between different slices in 5G systems. Finally, several open issues and challenges in network-slicing-based 5G networks are discussed, including network reconstruction, network slicing management, and cooperation with other 5G technologies. [ABSTRACT FROM PUBLISHER]