5G Services Research Articles

An Optimal Resource Allocation Scheme with Carrier Aggregation in 5G Network under Unlicensed Band

Carrier aggregation (CA) technology in the Fifth-Generation (5G) network can be considered as a major feature for high-rate data services, which can be combined with the concept of 5G in unlicensed band (5G-U) for data offloading to further enhance the efficiency of the scarce licensed spectral resource. However, the introduction of cellular services in an unlicensed spectrum can force unlicensed band users to silent mode. Meanwhile, the coexistence among different radio access technologies operating on the same frequency band is a complex issue, especially considering the requirement diversity of quality of service (QoS) in networking. In this paper, we propose an optimal resource allocation mechanism to maximize system performance satisfaction for multiple types of services with different QoS requirements in the 5G-U network with a CA feature to address the challenge. Additionally, the performance of services in Wi-Fi system is protected by reserving the minimum spectrum resource when offloading for the 5G-U network. Analytical results on the mean ergodic achievable rate of Wi-Fi services and the mean packet delay of 5G services are provided to maximize the system performance satisfaction. Numerical results demonstrate the effectiveness of the proposed algorithm, wherein optimal spectrum and power allocation can contribute to the maximum system satisfaction in a 5G-U network with a CA feature.

An intelligent scheduling for 5G user plane function placement and chaining reconfiguration

Services and use cases in 5G and beyond networks are characterized by strict requirements such as ultra-low latency, increased capacity, and high user mobility. Moreover, these networks must be capable of satisfying these ambitious demands as well as anticipating and adapting to dynamically changing conditions in a quick and feasible manner. This study deals with the problem of determining the best time to readjust the user plane function (UPF) placement and session mapping configuration to avoid quality of service (QoS) degradation in the system due to user mobility. To this aim, we rely on machine learning (ML) techniques to anticipate poor QoS events and decide whether a reconfiguration procedure is required based on a pre-established QoS tolerance threshold. Specifically, an ML-based framework, called intelligent scheduling of the reconfiguration (ISR), is proposed to automate the reconfiguration process. This framework applies supervised ML methods, either regressors or classifiers, to predict the QoS values/status at a given time horizon. The simulation experiments revealed the proposed mechanism’s superiority compared to the established scheduling baseline. The ISR solution could not only keep the system QoS under desired values most of the time but also reduce the number of readjustment events by at least 50% compared to the baselines.

A Contract-Theory-Based Incentive Mechanism for UAV-Enabled VR-Based Services in 5G and Beyond

The proliferation of novel infotainment services such as Virtual Reality(VR)-based services has fundamentally changed the existing mobile networks. These bandwidth-hungry services expanded at a tremendously rapid pace, thus, generating a burden of data traffic in the mobile networks. To cope with this issue, one can use Multi-access Edge Computing (MEC) to bring the resource to the edge. By doing so, we can release the burden of the core network by taking the communication, computation, and caching resources nearby the end-users (UEs). Nevertheless, due to the vast adoption of VR-enabled devices, MEC resources might be insufficient in peak times or dense settings. To overcome these challenges, we propose a system model where the service provider (SP) might rent Unmanned Area Vehicles (UAVs) from UAV service providers (USPs) to serve as micro-based stations (UBSs) that expand the service area and improve the spectrum efficiency. In which, UAV can pre-cached certain sets of VR-based contents and serve UEs via air-to-ground (A2G) communication. Furthermore, future intelligent devices are capable of 5G and B5G communication interfaces, and thus, they can communicate with UAVs via A2G links. By doing so, we can significantly reduce a considerable amount of data traffic in mobile networks. In order to successfully enable such kinds of services, an attractive incentive mechanism is required. Therefore, we propose a contract theory-based incentive mechanism for UAV-assisted MEC in VR-based infotainment services, in which the MEC offers an amount reward to a UAV for serving as a UBS in a specific location for certain time slots. We then derive an optimal contract-based scheme with individual rationality and incentive compatibility conditions. The numerical findings show that our proposed approach outperforms the Linear Pricing (LP) technique and is close to the optimal solution in terms of social welfare. Additionally, our proposed scheme significantly enhanced the fairness of utility for UAVs in asymmetric information problems.

Placing Timely Refreshing Services at the Network Edge

Accommodating services at the network edge is favorable for time-sensitive applications. However, maintaining service usability is resource-consuming in terms of pulling service images to the edge, synchronizing databases of service containers, and hot updates of service modules. Accordingly, it is critical to determine which service to place based on the received user requests and service refreshing (maintaining) cost, which is usually neglected in existing studies. In this work, we study how to cooperatively place timely refreshing services and offload user requests among edge servers to minimize the backhaul transmission costs. We formulate an integer non-linear programming problem and prove its NP-hardness. This problem is highly non-tractable due to the complex spatial-and-temporal coupling effect among service placement, offloading, and refreshing costs. We first decouple the problem in the temporal domain by transforming it into a Markov shortest-path problem. We then propose a light-weighted Discounted Value Approximation (DVA) method, which further decouples the problem in the spatial domain by estimating the offloading costs among edge servers. The worst performance of DVA is proved to be bounded. 5G service placement testbed experiments and real-trace simulations show that DVA reduces the total transmission cost by up to 59.1% compared with the state-of-the-art baselines.

Efficient Network Slicing for 5G Services in Cloud Fog-RAN Deployment Over WDM Network

Network slicing in fifth generation (5G) radio access network (RAN) enables serving massive network traffic with diverse and stringent quality of service (QoS) requirements. Multiple logical networks can be built using RAN slicing over a single RAN infrastructure. This paper considers three different types of slices that are standardized by third generation partner project (3GPP): ultra-reliable low-latency communication (URLLC), enhanced mobile broadband (eMBB), and massive machine type communication (mMTC). Each slice type has unique requirements for data rate, latency, and reliability. Cloud RAN (C-RAN) was proposed to address the requirements of 5G services, which involves physical separation between the remote radio head (RRH) and baseband unit (BBU) in 2-layers. While C-RAN enables more efficient resource utilization and energy consumption, it limits network scalability. Furthermore, C-RAN is unable to meet the stringent latency demands of URLLC services, as well as the massive fronthaul capacity required for eMBB requests. To address this issue, we propose a novel cloud fog RAN (CF-RAN) over wavelength division multiplexing (WDM) architecture. In CF-RAN over WDM the RAN functions are divided into 3 layers, which include the RRH at layer 1, fog nodes at layer 2, and BBU hotels at layer 3. We employ the emerging fog computing paradigm in optical and wireless networks in this suggested architecture. To facilitate low latency URLLC requests, the fog nodes are located closer to the cell site (CS). We propose an integer linear programming (ILP)-based mathematical model. The model's objective is to decrease the number of active BBU hotels and fog nodes while remaining compliant with practical network restrictions. Furthermore, a low complexity greedy heuristic algorithm is proposed to solve the problem and is compared to the branch & bound (B&B) algorithm, which is assumed to provide an optimal solution with exponential complexity. The proposed 3-layer CF-RAN over WDM architecture achieves a 70% improvement in BBU centralization and a 50% reduction in request blocking when compared to the standard 2-layer architecture.

Analisis Performansi Jaringan 4G Telkomsel Menggunakan Metode Drive Test

Availability and quality of the network is very important considering the needs of people who are all connected to internet services. Kuma Hamlet, which is in Sarudu District, West Celebes, has gained access to the 4G service network through the Telkomsel operator, but problems still occur such as a slow network or weak network connection. This study aims to analyze the performance of the Telkomsel 4G network in Dusun Kuma using the Drive Test Method. The research results obtained were Telkomsel's 4G network performance results using the Drive Test Method in Kuma hamlet carried out at 15 Location Points with the help of the Gnet Track Pro Application which were obtained at 3.0 (Normal), with Maximum Performance reaching 4.0 (Good), and Minimum Performance reaching 2.3 (Bad).

Hybrid Chaos Particle Swarm Optimization algorithm for smart Cloud Service System based on optimization resource scheduling and allocation

<p>To enhance the smart Cloud Service System for diverse user requirements in 5G and other service networks, this study leverages resource utilization and multi-tenancy network slicing operation costs. Specifically, we propose a multi-tenancy network resource allocation strategy based on the Chaos Particle Swarm Optimization (CPSO) algorithm. In a multi-tenancy network (MTN), we lease the wireless spectrum resources of the infrastructure provider’s base station, construct access service slices as network slice services, and offer network access services to users. Introduce detailed formulation of the relationship between MTN and users, represented as a multi-master and multi-slave construct that defines the strategy space and profit function after MTN decision-making. Reverse induction is used to analyze the proposed model, and a distributed iterative algorithm is proposed to obtain the optimal throughput demand of users and the optimal slice cost of MTN. Simulation results demonstrate that the proposed strategy can effectively enhance resource utilization and user satisfaction while reducing energy consumption.</p>

Literature review: visible light communication system business model scheme for telecommunication business in Indonesia

The telecommunication sector mainly comprises operators, vendors, and regulators. In Indonesia, tele- communications operator companies tend to decrease profits from the first quarter of 2017 to the third quarter of 2018. This condition is due to the tight competition of telecommunication service providers, high operational costs, and digital transformation that does not provide substantial revenue for the company. Telecommunica- tions operators need other service options that can expand target market segmentation. It aims to open up a new blue ocean as a new source of income. The world is getting closer to massive communication technology, so high-speed communication is needed. Therefore, telecommunications operators can open new service options based on the visible light spectrum as their communication resources. This option can be integrated with ambient lighting, a wide spectrum ranging from radio waves, and greater bandwidth, making visible light suitable for IoT- 5G services. This research aims to design a wireless visible light communication business model. Several frame- works are used, such as the magic triangle of St. Gallen, Osterwalder Business Model Canvas, and PESTLE analysis. The business model design results in a business model with B2B market segmentation being the main focus and B2C market segmentation to acquire retail customers.

Remote Bridge Inspection and Actual Bridge Verification Based on 4G/5G Communication Environments

The close-up visual inspection of bridges faces several problems, including a lack of financial resources and human personnel. Hence, there has been increasing use of artificial intelligence (AI) and information and communications technology (ICT) to solve them. We previously investigated remote inspection—in which skilled engineers provided on-site support from a remote location—with the aim of reducing the labor required for on-site work and addressing the lack of personnel through the use of AI and ICT. Sharing images of bridges from inspection sites to remote locations via the Internet enables remote assessment of the sites and the ability to consider and diagnose damage. Mobile communications can be used to upload images, although the volume of image data required for inspection can be enormous and take considerable time to upload. Consequently, in this study, we investigated image uploads using 5G communication—that is, the fifth-generation technology standard for broadband cellular networks. Moreover, we measured the upload times when using 4G and 5G services and examined their operation based on differences in the communication environments. We concluded that the simulated remote inspection can be efficiently performed by adjusting the inspection method to the communication environment.

Korea's leadership in 5G and beyond: Footprints and futures

The Korean government has played a crucial role in the development of advanced mobile networks, including 5G. Korea became the first country in the world to not only launch a nationwide 5G network but also to commercialize 5G services. In addition to looking at the steps toward 5G-related developments in Korea, this study used Latent Dirichlet Allocation (LDA) topic modeling analysis to examine how 5G-related discourse was formed in the media after its commercialization. As a result of analyzing news articles in the Korean press with 5G as the main keyword, a total of five topics were derived. Intriguingly, most topics contained several new articles related to government policies. Considering the characteristics of the mobile network industry—e.g. as an industry that receives licenses from the government—this result suggests that 5G-related issues are closely related to government policies. Our topic modeling results confirm that the interventionist promotion policy of the Korean government which acted as a catalyst for technology and business innovation played an important role in Korea's 5G leadership.

Empirical evaluation of 5G and Wi-Fi mesh interworking for Integrated Access and Backhaul networking paradigm

The Fifth Generation (5G) of mobile networks and beyond have emerged with ambitions to facilitate the deployment and evolution of a wide spectrum of applications such as Industry 4.0 and 5.0 use cases. Despite this trend of increasing importance to upgrade the networked applications to the next generation, the use of 5G and beyond technologies can be a prohibitive barrier for some business sectors due to the high deployment costs that it can incur. To overcome this obstacle, more cost-effective approaches in networking are entailed. In this work, an innovative approach coupling 5G and Wi-Fi mesh networking is proposed and developed as a promising solution to extend 5G services to the indoor use case scenarios whilst being capable of keeping the capital expenditure of the network infrastructure significantly lower. In order to empirically validate and evaluate this new networking paradigm, a number of experiments have been performed over a testbed with a demanding video application as a representative use case. The experimental results prove the gained benefits from this new approach, especially, video users can be more than twice as far away without compromising the quality of the video consumption experience. Specifically, the results show that users can be 29% further away using a single router, and 100% further away if a second router is added.

Evaluation of 5G and Fixed-Satellite Service Earth Station (FSS-ES) Downlink Interference Based on Artificial Neural Network Learning Models (ANN-LMS).

Fifth-generation (5G) networks have been deployed alongside fourth-generation networks in high-traffic areas. The most recent 5G mobile communication access technology includes mmWave and sub-6 GHz C-bands. However, 5G signals possibly interfere with existing radio systems because they are using adjacent and co-channel frequencies. Therefore, the minimisation of the interference of 5G with other signals already deployed for other services, such as fixed-satellite service Earth stations (FSS-Ess), is urgently needed. The novelty of this paper is that it addresses issues using measurements from 5G base stations (5G-BS) and FSS-ES, simulation analysis, and prediction modelling based on artificial neural network learning models (ANN-LMs). The ANN-LMs models are used to classify interference events into two classes, namely, adjacent and co-channel interference. In particular, ANN-LMs incorporating the radial basis function neural network (RBFNN) and general regression neural network (GRNN) are implemented. Numerical results considering real measurements carried out in Malaysia show that RBFNN evidences better accuracy with respect to its GRNN counterpart. The outcomes of this work can be exploited in the future as a baseline for coexistence and/or mitigation techniques.

Stable Service Caching in MECs of Hierarchical Service Markets With Uncertain Request Rates

A 5G hierarchical service market is emerging with both large-scale and small-scale network service providers competing the computing and network bandwidth resources of an infrastructure provider. In this paper, we investigate the problem of caching services originally deployed in remote clouds to cloudlets in an MEC network of a hierarchical service market. We first propose a novel approximation-restricted framework that guarantees the stability of the 5G service market. Under the proposed framework, we first propose an approximation algorithm with an approximation ratio for the problem with non-selfish network service providers. We then design an efficient Stackelberg congestion game with selfish network service providers, and analyze the Price of Anarchy (PoA) of the proposed game to measure its efficiency loss due to selfishness of players. When the request rates of services are not given in advance, we study the service caching problem with request rate uncertainty, and propose an approximation algorithm and a Stackelberg game via leveraging the randomized rounding technique. We finally evaluate the performance of the proposed algorithms and mechanisms by both simulations and implementations in a real test-bed. Results show that the performance of our proposed mechanisms achieve around 9.2% less cost than those of existing approaches.

Design of a Microstrip Filtering Antenna for 4G and 5G Wireless Networks

The filtering antenna provides both radiation and filtering features and is an important component for the RF front-end of wireless devices. The main function of a filtering antenna is to reject out-of-band signals, thus reducing the interference from adjacent channels. The aim of the present work is to design a 2.6 GHz microstrip filtering antenna for 4G and 5G global mobile services. The filtering antenna is designed using a hairpin bandpass filter integrated with an elliptical microstrip aerial. Good impedance matching is obtained by using appropriate dimensions of the hairpin bandpass filter. The 10 dB return loss bandwidth of the filtering antenna is approx. 5.7%, with the maximum gain for the elliptical filtering antenna of approx. 2.2 dB. Good agreements between the measured and simulated results are obtained for the proposed filtering antenna and the bandwidth covers almost the entire 2.6 GHz band.

Performance analysis of a RIS-assisted RoFSO communication system over Malaga distribution for smart city applications.

Radio over free space optics (RoFSO) is one of the potential technologies that can satisfy the requirements of 5G services in a smart city. However, as RoFSO is line-of-sight (LOS) communication, one of its limitations is the occurrence of a skip zone in the targeted areas. In this work, a reconfigurable intelligent surface (RIS) is proposed as the solution to overcome this connection difficulty, which prevents signal blocking by generating LOS connections. These RIS modules extend the communication channel coverage, making it more intelligent and controllable. The performance analysis based on outage probability, ergodic channel capacity, and bit error rate has been performed using heterodyne detection. Malaga distribution has been used to model atmospheric turbulence. The exact closed-form expressions of the probability density function and cumulative distribution function of the end-to-end signal-to-noise ratio are derived. Exploiting these derived statistics, system performance is investigated through the ergodic channel capacity, outage probability, and average bit error rate for M-ary quadrature amplitude modulation and two binary modulation schemes: non-coherent binary frequency-shift keying and coherent binary phase-shift keying. Numerical results are compared among different turbulence conditions, link lengths, and scattering errors. The results show that the proposed RIS-assisted RoFSO technology has the potential to be effective for 5G smart city applications.

Designing a high-fidelity testbed for 5G-based Industrial IoT

With the rise of the Industrial IoT (Internet of Things) and Industry 4.0 paradigms, many control and sensor systems used for IACS (Industrial Automation and Control Systems) have become more complex, due to the increasing number of interconnected field devices, sensors and actuators often being geographically spread across large areas. Supporting these increasingly sophisticated networked scenarios calls for the involvement of telecommunications and utility providers to better support Machine-to-Machine (M2M) communications and infrastructure orchestration, for which 5G technology is considered a perfect match. Nowadays, such 5G networks empower solutions both for consumer and for industrial IoT scenarios, providing the capacity and the means to seamlessly connect a massive number of gadgets and sensors, with diverse data rate requirements, low latency, and low power consumption. Part of this flexibility is also due to the nature of the 5G Service Architecture (SA), which is based on a microservice concept, dividing its core through multiple functions, allowing it to horizontally scale in a flexible way. Furthermore, the 3GPP specifications encompass specific support for verticals by means of slicing and 5G LANs, paving the way for a paradigm shift in terms of the relationship between service, telecom, and operational infrastructure tenants. However, such benefits come at the cost of extra complexity and, consequently, an increased vulnerability surface. This calls for further research focused on improving 5G infrastructure management, service integration and security, which cannot be safely undertaken in production environments, thus motivating the development of suitable 5G testbeds. This research work, which was developed in the scope of the POWER and Smart5Grid P2020 projects, addresses the creation of a high-fidelity environment for 5G-related research, which encompasses a gNodeB and 5G core, together with emulated User Elements (terminal devices) and IoT nodes (in this specific case, Programmable Logic Controllers), constituting a 5G Industrial IoT scenario designed for development and validation of new solutions, security research, or even advanced training purposes. The entire infrastructure is supported via container orchestration technology, providing enhanced scalability and resilience characteristics.

5G technology to help the development of smart grids: A review

The continuous advancement of technology has led to an increase in electricity consumption by residential, industrial, commercial, and other users in all aspects, and the demand for electricity quality is also increasing. In such a context, the smart grid is regarded as a new generation of power systems. The smart grid uses advanced communication and information processing, remote automatic control, and other technologies to achieve precise control of fault removal, three-dimensional monitoring of the system and optimal dispatch of electrical energy; while ensuring that the reliability of the power supply can be maintained even when a variety of uncontrollable renewable energy sources and a large number of new electricity loads are connected. Smart upgrades require strong communication systems to support them, and the characteristics of 5G technology perfectly match the various needs of smart grids for wireless communication, which is why 5G is widely studied. This paper is a review of the use of 5G technology in smart grids. Firstly, an overview of wireless communication in smart grids is given, and then the three main scenarios for the use of 5G and various grid services are adapted. This is followed by a summary of the problems and under-researched areas in the use of 5G in smart grids. In the end, the current advanced solutions are summarised and analyzed, and it is determined that the most urgent issues to be addressed in the use of 5G in smart grids are the confidentiality of critical data, network anti-attack capability, and other security guarantees. There is also further value in the use of big data to calculate the optimization of energy dispatch solutions. In general, its development prospects are quite optimistic.

Performance Evaluation of Slotted Star-Shaped Dual-band Patch Antenna for Satellite Communication and 5G Services

Performance Evaluation of Slotted Star-Shaped Dual-band Patch Antenna for Satellite Communication and 5G Services

Converging Game Theory and Reinforcement Learning For Industrial Internet of Things

The fifth-generation (5G) wireless network provides high-rate, ultra-low latency, and high-reliability connections that can meet the Industrial Internet of Things (IIoT) requirements in factory automation, especially for robot motion control. In this paper, we address 5G service provisioning in an automated warehouse scenario, where swarm robotics is controlled by an industrial controller that provides routing and job instructions over the 5G network. Leveraging the coordinated multipoint (CoMP), we formulate a time-varying joint CoMP clustering and 5G ultra-reliable low-latency communication (URLLC) beamforming design problem to control the robots that move around the automated warehouse for goods storage with the planned reference tracks. Traditional iterative optimization approaches are impractical in such a dynamic wireless environment due to high computational time. We propose a game-theoretic CoMP clustering algorithm combined with the Proximal Policy Optimization method to obtain a stationary solution closed to that of the exhaustive search algorithm considered as the global optimal solution.

Automatic Recognition of Beam Attachment for Massive MIMO System in Densely Distributed Renewable Energy Resources

Several large-scale and distributed systems such as renewable energy systems (RESs) require ubiquitous and reliable communication. RESs are designed to provide efficient power management and improve both energy production and consumption. Decision making in RESs heavily depends on real-time communication. Fifth and sixth-generation (5G, 6G) wireless networks promise to deliver significant communication advantages to RESs including ultra-low latency, high throughput and improved coverage. However, the communication behavior in RESs is categorized as unpredictable due to aspects such as system flexibility and equipment heterogeneity. This may affect the stability of the entire RES, which results in further issues such as signal reliability and degraded coverage. Therefore, precise identification of user equipment’s (UE) location greatly improves the sustainability of 5G and 6G wireless services. In this work, we propose a novel low-complexity technique to automatically recognize UE locations in an area of interest. The approach aims at providing precise identification of UE with minimum memory and feature requirements. We use the lazy learning approach to build a prediction model to construct beam-attachment maps. We then train the model to provide distributed intelligent models to automatically recognize beam-attachment indexes. We compare the proposed approach with instance-based techniques to measure its ability at predicting beam-attachment maps. The results show that the proposed model has the ability to provide an accurate prediction with respect to the beam-attachment index (around 100%) with minimal complexity.