5G Spectrum: enabling the future mobile landscape [Guest Editorial

5G-Flow: A unified Multi-RAT RAN architecture for beyond 5G networks

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.

The current radio environment is characterized by its heterogeneity. Different aspects of this heterogeneity include multiple operators and services, various radio access technologies, different network topologies, a broad range of radio equipment, and multiple frequency bands. Such an environment has a lot of technical and business opportunities. Examples are joint management of several radio access networks within one operator to balance load of these networks, detecting and using unused spectrum in the allocated frequency bands without interrupting the operation of the primary users of such frequency bands, and spectrum trading between several operators. To exploit such opportunities, the concept of cognitive radio system has been developed. Many CRS usage scenarios and business cases are possible. This has triggered a lot of standardization activity at all levels, including in the International Telecommunication Union, IEEE, European Telecommunications Standards Institute, and European Association for Standardizing Information and Communication Systems; each of these organizations is considering multiple CRS deployment scenarios and business directions. This article describes the current concept of the CRS and shows the big picture of international standardization of the CRS. Understanding of these standardization activities is very important for both academia and industry in order to select important research topics and promising business directions.

Caching and virtualization have been considered as the promising techniques in 5G Networks. In 5G networks with virtualization, the caching resources deployed by infrastructure providers (InPs) can be abstracted into isolated slices and transparently shared by mobile virtual network operators (MVNOs). In this case, one of the most important issues is how the MVNOs to share the caching resource. To solve this issue, different from previous works, a hierarchical caching architecture that core network and radio access network (RAN) have the caching capability in 5G networks with virtualization is first considered in this paper. Then, we study the problem of hierarchical caching resource sharing for MVNOs, and a competitive game to maximize their expectation revenue based on the oligopoly market model is formulated. As it is a hard problem to find the optimal solution in the hierarchical caching resource sharing problem, we decompose the optimization problem into two independent caching resource sharing problems in RAN and core network, respectively. Then the local optimal solutions are solved and the global Nash equilibrium solution is achieved. Finally, simulation results are illustrated to demonstrate the performance of the proposed scheme.

The 5G network’s commercialization has revealed challenges in providing customized and personalized deployment and services for diverse vertical industrial use cases, leading to high cost, low resource efficiency and management efficiency, and long time to market. Although the 5G core network (CN) has adopted a service-based architecture (SBA) to enhance agility and elasticity, the radio access network (RAN) keeps the traditional integrated and rigid architecture and suffers the difficulties of customizing and personalizing the functions and capabilities. Open RAN attempted to introduce cloudification, openness, and intelligence to RAN but faced limitations due to 5G RAN specifications. To address this, this paper analyzes the experience and insights from 5G SBA and conducts a systematic study on the service-based RAN, including service definition, interface protocol stacks, impact analysis on the air interface, radio capability exposure, and joint optimization with CN. Performance verification shows significant improvements of service-based user plane design in resource utilization and scalability.

The trials and rollout of the fifth generation (5G) network technologies are gradually intensifying as 5G is positioned as a platform that not only accommodates exploding data traffic but also unlocks a multitude use cases, services and deployment scenarios. However, the need for hyperdense 5G deployments is revealing some of the limitations of planning approaches that hitherto proved adequate for pre-5G systems. The hyperdensification envisioned in 5G networks not only adds complexity to network planning and optimization problems, but underlines need for more realistic data-driven approaches that consider cost, varying demands and other contextual attributes to produce feasible topologies. Furthermore, the quest for network programmability and automation including the 5G radio access network (RAN), as manifested by network slicing technologies and more flexible RAN architectures, are also among other factors that influence planning and optimization frameworks. Collectively, these deployment trends, technological developments and evolving (and diverse) service demands point towards the need for more holistic frameworks. This article proposes a data-driven multiobjective optimization framework for hyperdense 5G network planning with practical case studies used to illustrate added value compared to contemporary network planning and optimization approaches. Comparative results from the case study with real network data reveal potential performance and cost improvements of hyperdense optimized networks produced by the proposed framework due to increased use of contextual data of planning area and focus on objectives that target demand satisfaction.

The emerging future heterogeneous wireless networks intend to provide a variety of adaptable services to mobile and nomadic users by using integrated heterogeneous network infrastructure. These networks are envisioned as the integration of different existing wireless network technologies such as WLAN, WiMAX, 2G, 2.5G, 3G, Bluetooth, etc., and future wireless network technologies. To integrate different network into a single heterogeneous network, the mobile station/user equipment (MS/UE) must discover all the available radio access networks ahead of time, select the appropriate network from the available radio access networks (RANs) and then seamlessly hand over the session to the desired/chosen network. This research paper presents a novel hybrid approach for network discovery, where the network will broadcast the updated network information using cell broadcast center (CBC) to the MS/UE and the MS/UE may also enquire from the network the additional information regarding the available networks, as opposed to centralized technique used in the existing cellular networks. The proposed solution suggests a network information repository (NIR) embedded in the core network, having the information of all the available radio access networks (RANs) in a specific location. The NIR will be populated and updated by the reporting agents (RAs) which are normal MS/UEs

Neural oscillations are fundamental for brain function and govern various cognitive processes. Recent functional magnetic resonance imaging advances offer the opportunity to study frequency-specific properties of blood-oxygen-level-dependent oscillations at multiple frequency bands. However, most have focused on spontaneous brain activity in the resting state, leaving a gap in direct evidence regarding the specific activations of cognitive tasks across different frequency bands. We aim to address this gap by exploring the role of blood-oxygen-level-dependent oscillations across multiple frequency bands in cognitive processes. We used task-functional magnetic resonance imaging data of 339 healthy young adults from the Human Connectome Project to map the activation patterns of performing seven cognitive tasks at multiple frequency bands (ie slow-1 to slow-6). Our findings revealed that different frequency bands are associated with distinct task-activation patterns. Specifically, slow-1/2/3 oscillations primarily contribute to local sensory information processing, while slow-4 is crucial for various fundamental cognitive functions. Slow-5 is involved in cognitive processes that require greater memory load, integrated cognitive processing, and attention maintenance. This underscores the importance of analyzing a broad frequency range to capture the full spectrum of cognitive function, highlighting the diverse roles of different frequency bands in brain activity, shedding light on the underlying mechanism of brain–behavior associations.

Effective zero-touch management and orchestration (ZSM&O) is crucial for scaling network slicing, particularly transitioning toward Beyond 5G (B5G) and 6G networks. This paper empirically validates the network slicing framework developed under the European Union Horizon 2020 MonB5G project. Building on three years of academia-industry collaboration, MonB5G introduces a flexible slicing model featuring umbrella slices that orchestrate modular, specialized slices across multi-domain environments to address next-generation service demands. For the first time, we evaluate its practicality in a 5G cloud-native testbed through a virtual reality (VR) streaming use case, supported by solutions such as federated learning-based CPU forecasting, anomaly detection, and deep reinforcement learning (DRL) for radio access network (RAN) optimization. The paper offers insights from technically demanding experimental tests and highlights challenges and development paths for managing next-generation mobile networks.

A structure for an underwater sound absorber with subwavelength thickness and a quasi-perfect absorption property at multiple frequency bands is reported. This absorber consists of a viscoelastic coating layer embedded with periodically distributed plate scatterers (PSs). The embedded PSs cannot only slow sound waves in the coating, leading to a down-shifted resonance frequency where the absorption is maximized, but also introduce multiple local bending modes and local longitudinal modes in the coating. Via proper selection of the parameters of the PSs and the PS array, multiple local resonance modes of different types in a coating unit can be excited, resulting in quasi-perfect absorption of incident sound at multiple frequencies whose wavelengths are much longer than the thickness of the coating layer. For example, absorption (89%) of underwater sound at 462.9 Hz is achieved by such a layer with a thickness of 6 cm, which is 1.9% of the wavelength of the incident sound. Broadband quasi-perfect absorption can also be realized by coupling of those multiple local resonant modes. This quasi-perfect absorption property can also be observed for sound waves with different incident angles, because a large number of local intrinsic modes could still be excited.

Although cognitive functions are hypothesized to be mediated by synchronous neuronal interactions in multiple frequency bands among widely distributed cortical areas, we still lack a basic understanding of the distribution and task dependence of oscillatory activity across the cortical map. Here, we ask how the spectral and temporal properties of the local field potential (LFP) vary across the primate cerebral cortex, and how they are modulated during visual short-term memory. We measured the LFP from 55 cortical areas in two macaque monkeys while they performed a visual delayed match to sample task. Analysis of peak frequencies in the LFP power spectra reveals multiple discrete frequency bands between 3–80 Hz that differ between the two monkeys. The LFP power in each band, as well as the Sample Entropy, a measure of signal complexity, display distinct spatial gradients across the cortex, some of which correlate with reported spine counts in layer 3 pyramidal neurons. Cortical areas can be robustly decoded using a small number of spectral and temporal parameters, and significant task dependent increases and decreases in spectral power occur in all cortical areas. These findings reveal pronounced, widespread and spatially organized gradients in the spectral and temporal activity of cortical areas. Task-dependent changes in cortical activity are globally distributed, even for a simple cognitive task.

A fog computing based radio access network (F-RAN) is presented in this article as a promising paradigm for the fifth generation (5G) wireless communication system to provide high spectral and energy efficiency. The core idea is to take full advantages of local radio signal processing, cooperative radio resource management, and distributed storing capabilities in edge devices, which can decrease the heavy burden on fronthaul and avoid large-scale radio signal processing in the centralized baseband unit pool. This article comprehensively presents the system architecture and key techniques of F-RANs. In particular, key techniques and their corresponding solutions, including transmission mode selection and interference suppression, are discussed. Open issues in terms of edge caching, software-defined networking, and network function virtualization, are also identified.

5G network is anticipated to meet the challenging requirements of mobile traffic in the 2020's, which are characterized by super high data rate, low latency, high mobility, high energy efficiency, and high traffic density. This paper provides an overview of China Mobile's 5G vision and potential solutions. Targeting a paradigm shift to user-centric network operation from the traditional cell-centric operation, 5G radio access network (RAN) design considerations are presented, including RAN restructure, Turbo charged edge, core network (CN) and RAN function repartition, and network slice as a service. Adaptive multiple connections in the user-centric operation is further investigated, where the decoupled downlink and uplink, decoupled control and data, and adaptive multiple connections provide sufficient means to achieve a 5G network with "no more cells." Software-defined air interface (SDAI) is presented under a unified framework, in which the frame structure, waveform, multiple access, duplex mode, and antenna configuration can be adaptively configured. New paradigm of 5G network featuring user-centric network (UCN) and SDAI is needed to meet the diverse yet extremely stringent requirements across the broad scope of 5G scenarios.

An important target for 5G networks is to enable resource sharing among network tenants such as Mobile Virtual Network Operators and Service Providers. Several domains of resource sharing have been considered including infrastructure (compute, storage and networking), transport, Radio Access Network (RAN) and Radio Frequency (RF) spectrum. RAN and spectrum sharing are expected to be an integral part of a multi-tenant 5G network. In this paper, a centralized, fine-grained active RAN and spectrum sharing approach has been presented and analyzed using a modified SimuLTE model. The presented model can be used for analyzing active RAN and spectrum sharing models considered in a multi-tenant 5G network. We present the core modules that enable dynamic allocation of RAN slices with dedicated spectrum and resource scheduling functions. We also present preliminary simulation results that give an insight into the actual benefits and trade-offs of active spectrum sharing among RAN tenants at different time-frequency granularities.

Guest editorial IJSCN special issue on 3GPP NTN standards for future satellite communications