5G Non-Standalone Research Articles

A hybrid SDN solution for mobile networks

The adoption of Software Defined Networking (SDN) has encountered resistance mainly due to its disruptive nature for current deployed networks. In order to allow a smoother transition of SDN into production networks and take advantage of SDN’s characteristics, a mix of SDN with traditional networks, or Hybrid SDN Networks, can be deployed, paving the path to fully SDN-capable networks. The introduction of SDN allows for new and more efficient network optimization methods. This paper presents a Hybrid SDN Mobile Core Network for 4G and Non-Standalone 5G, which integrates support for Wi-Fi access, traffic offloading capabilities from 3GPP to non-3GPP Access and dynamic non-3GPP network slice instantiation, while still being flexible enough to be used in Standalone 5G. Results showed that the virtualization of the Mobile Core Network and the introduction of SDN in its architecture (making it a hybrid SDN solution) presented no significant impact in latency, attachment time and throughput in the mobile network when compared with a traditional deployment, coupling it with all the flexibility that SDN provides. Furthermore, benefits of traffic offloading for both the end user and the network operator are also shown.

Non-Standalone 5G NR FiWi System Based on a Photonic Integrated Multi-Wavelength Transmitter

This letter presents a non-standalone 5G new radio (NR) multiband fiber-wireless (FiWi) system implemented using an integrated multi-wavelength transmitter with direct modulation. In this system, three 4G/5G RF signals are simultaneously transported over a 12.5-km long radio over fiber (RoF) link, before being amplified and radiated: a 20-MHz 5G NR signal at 788 MHz; five 20-MHz LTE subcarriers at 2.6 GHz; a 100-MHz 5G NR signal at 3.5 GHz. Wireless transmissions through a 10-m long indoor picocell-like link and a 115-m long realistic outdoor wireless link are demonstrated. All 4G and 5G received signals comply with the 3GPP Release 15 requirements, in terms of EVM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RMS</sub> , except for 16 QAM at 3.5 GHz on the 115-m link. Experimental results demonstrate a total throughput of 1.36 Gbit/s and 230 Mbit/s on the 10-m and 115-m scenarios, respectively.

Towards 5G-based IoT security analysis against Vo5G eavesdropping

With the advent of 5G technology, the enhanced Mobile Broadband technology is translating 5G-based Internet of Things (IoT) such as smart home/building into reality. With such advances, security must mitigate greater risks associated with faster and more accessible technology. The 5G-based IoT security analysis is crucial to IoT Technology, which will eventually expand extensively into massive machine-type communications and Ultra-Reliable Low Latency Communications. This paper analyses the countermeasures and verification methods of eavesdropping vulnerabilities within IoT devices that use the current 5G Non-Standalone (NSA) network system. The network hierarchical structure of 5G-based IoT was evaluated for vulnerability analysis, performed separately for 5G Access Stratum (AS), Non-Access Stratum (NAS), and Internet Protocol (IP) Multimedia Subsystem (IMS). AS keystream reuse, NAS null-ciphering, and IMS IPsec off vulnerabilities were tested on mobile carrier networks to validate it on the 5G NSA network as well. A countermeasure against each vulnerability was presented, and our Intrusion Detection System based on these countermeasures successfully detected the presented controlled attacks.

5G Campus Networks: A First Measurement Study

A 5G campus network is a 5G network for the users affiliated with the campus organization, e.g., an industrial campus, covering a prescribed geographical area. A 5G campus network can operate as a so-called 5G non-standalone (NSA) network (which requires 4G Long-Term Evolution (LTE) spectrum access) or as a 5G standalone (SA) network (without 4G LTE spectrum access). 5G campus networks are envisioned to enable new use cases, which require cyclic delay-sensitive industrial communication, such as robot control. We design a rigorous testbed for measuring the one-way packet delays between a 5G end device via a radio access network (RAN) to a packet core with sub-microsecond precision as well as for measuring the packet core delay with nanosecond precision. With our testbed design, we conduct detailed measurements of the one-way download (downstream, i.e., core to end device) as well as one-way upload (upstream, i.e., end device to core) packet delays and losses for both 5G SA and 5G NSA hardware and network operation. We also measure the corresponding 5G SA and 5G NSA packet core processing delays for download and upload. We find that typically 95% of the SA download packet delays are in the range from 4–10 ms, indicating a fairly wide spread of the packet delays. Also, existing packet core implementations regularly incur packet processing latencies up to 0.4 ms, with outliers above one millisecond. Our measurement results inform the further development and refinement of 5G SA and 5G NSA campus networks for industrial use cases. We make the measurement data traces publicly available as the IEEE DataPort 5G Campus Networks: Measurement Traces dataset (DOI 10.21227/xe3c-e968).

Throughput Prediction using Machine Learning in LTE and 5G Networks

The emergence of novel cellular network technologies, within 5G, are envisioned as key enablers of a new set of use-cases, including industrial automation, intelligent transportation, and tactile internet. The critical nature of the traffic requirements ranges from ultra-reliable communications, massive connectivity, and enhanced mobile broadband. Thus, the growing research on cellular network monitoring and prediction aims for ensuring a satisfied user-base and fulfillment of service level agreements. The scope of this study is to develop an approach for predicting the cellular link throughput of end-users, with a goal to benchmark the performance of network slices. First, we report and analyze a measurement study involving real-life cases, such as driving in urban, sub-urban, and rural areas, as well as tests in large crowded areas. Second, we develop machine learning models using lower-layer metrics, describing the radio environment, to predict the available throughput. The models are initially validated on the LTE network and then applied to a non-standalone 5G network. Finally, we suggest scaling the proposed model into the future standalone 5G network. We have achieved 93% and 84% R^2 accuracy, with 0.06 and 0.17 mean squared error, in predicting the end-user's throughput in LTE and non-standalone 5G network, respectively.

5G-Enabled Autonomous Driving Demonstration with a V2X Scenario-in-the-Loop Approach.

Autonomous vehicles are at the forefront of interest due to the expectations of changing transportation for the better. In order to make better decisions on the road, vehicles use information from various sources: their own sensors, messages arriving from surrounding vehicles and objects, as well as from centralized entities—including their own Digital Twin. Certain decisions require the information to arrive with low latency and some of this information (such as video) requires broadband communication. Furthermore, the vehicles can populate an area, so they can represent mass communication endpoints that still need low latency and massive broadband. The mobility of the vehicles obviously requires the complete coverage of the roads with reliable wireless communication technologies fulfilling the previously mentioned needs. The fifth generation of cellular mobile technologies, 5G, addresses these requirements. The current paper presents real-life scenarios—on the M86 highway and the ZalaZONE proving ground in Hungary—for the demonstration of vehicular communication with 5G support, where the cars exchange sensor and control information with each other, their environment, and their Digital Twins. The demonstrations were carried out through the Scenario-in-the-Loop (SciL) methodology, where some of the actionable triggers were not physically present around the vehicles, but sensed or simulated around their Digital Twin. The measurements around the demonstrations aim to reveal the feasibility of the 5G Non-Standalone Architecture for certain communication scenarios, and they mainly aim to reveal the current latency and throughput limitations under real-life conditions.

A Modular Experimentation Methodology for 5G Deployments: The 5GENESIS Approach.

The high heterogeneity of 5G use cases requires the extension of the traditional per-component testing procedures provided by certification organizations, in order to devise and incorporate methodologies that cover the testing requirements from vertical applications and services. In this paper, we introduce an experimentation methodology that is defined in the context of the 5GENESIS project, which aims at enabling both the testing of network components and validation of E2E KPIs. The most important contributions of this methodology are its modularity and flexibility, as well as the open-source software that was developed for its application, which enable lightweight adoption of the methodology in any 5G testbed. We also demonstrate how the methodology can be used, by executing and analyzing different experiments in a 5G Non-Standalone (NSA) deployment at the University of Malaga. The key findings of the paper are an initial 5G performance assessment and KPI analysis and the detection of under-performance issues at the application level. Those findings highlight the need for reliable testing and validation procedures towards a fair benchmarking of generic 5G services and applications.

5G Nonstandalone Fusion Networks Based on the Intelligent Transplant Immune Tolerance

Fifth-generation (5G) nonstandalone (NSA) uses the 4G infrastructure to realize the rapid deployment of 5G, which will challenge the convergence of network architecture, signaling recognition, and editing capabilities of the next generation of mobile communications systems. Inspired by the immune technology of allograft transplantation, this article proposes for the first time the mechanism of antirejection induced by immune tolerance (IT) to solve the problem of signaling recognition and fusion between the heterogeneous mobile communication systems. First, with transplantation immunity as the technical background, a 5G NSA fusion architecture based on the adaptive IT mechanism was constructed. Then, the deep learning (DL) algorithm is used to efficiently identify the type of donor protocol, and the affinity calculation between the recipient and the donor is used to further enhance the correctness of the model recognition results. Meanwhile, the antibody concentration calculation was used to maintain the diversity of antibodies, which realized the complementarity between the IT mechanism and the DL algorithm. Finally, the donor signaling is decoded based on xor and encoded again based on the gene bit field. Simulation results show that the proposed method can effectively identify donor signaling, improve the affinity between the heterogeneous signaling and the efficiency of encoding and decoding, and broaden the research boundary of artificial immunity.

Performance Evaluation of 5G Access Technologies and SDN Transport Network on an NS3 Simulator

In this article, we deal with the enhanced Mobile Broadband (eMBB) service class, defined within the new 5G communication paradigm, to evaluate the impact of the transition from 4G to 5G access technology on the Radio Access Network and on the Transport Network. Simulation results are obtained with ns3 and performance analyses are focused on 6 GHz radio scenarios for the Radio Access Network, where an Non-Standalone 5G configuration has been assumed, and on SDN-based scenarios for the Transport Network. Inspired by the 5G Transformer model, we describe and simulate each single element of the three main functional plains of the proposed architecture to aim a preliminary evaluation of the end-to-end system performances.

Analytical Modeling of Radio Network Performance for 5G (Non-Standalone) and It’s Network Connectivity

The traffic demand and prediction for the next decade would be mostly affiliated with the Internet of Things (IoT). Various challenges with mobile communication industry will be faced as the demand in high capacity, multi mobile devices (users) connected to the network, uplink power consumption on User Equipment (UE), and its effect on the life span of mobile phone. The major features of 5G as per user experience on the network are Ultra-Reliable Low Latency Communication (URLLC), Internet of Things (IoT), sustaining high rate Enhanced Mobile Broadband (eMBB), and connection density Massive Machine Type Communication (mMTC). This research work focuses on Non-Standalone (NSA) 5G New Radio (NR) early deployment on eMBB for achieving the required throughput. The 5G performance requirement is higher than 4G, which includes the capacity to support user experience downlink throughput with target value of 1 Gbps, millisecond-level of end-to-end latency, and high connection density of 1 million per square kilometer. Optimization is a vast topic, and this paper discusses the problems faced by users latching on 5G NSA network on the downlink and 4G Network on the uplink and suggests its solution.

Green Mobile Networks for 5G and Beyond

The heated 5G network deployment race has already begun with the rapid progress in standardization efforts, backed by the current market availability of 5G-enabled network equipment, ongoing 5G spectrum auctions, early launching of non-standalone 5G network services in a few countries, among others. In this paper, we study current and future wireless networks from the viewpoint of energy efficiency (EE) and sustainability to meet the planned network and service evolution toward, along, and beyond 5G, as also inspired by the findings of the EU Celtic-Plus SooGREEN Project. We highlight the opportunities seized by the project efforts to enable and enrich this green nature of the network as compared to existing technologies. In specific, we present innovative means proposed in SooGREEN to monitor and evaluate EE in 5G networks and beyond. Further solutions are presented to reduce energy consumption and carbon footprint in the different network segments. The latter spans proposed virtualized/cloud architectures, efficient polar coding for fronthauling, mobile network powering via renewable energy and smart grid integration, passive cooling, smart sleeping modes in indoor systems, among others. Finally, we shed light on the open opportunities yet to be investigated and leveraged in future developments.

Next Generation New Radio Small Cell Enhancement: Architectural Options, Functionality and Performance Aspects

The 3rd generation partnership project (3GPP) has been engaged in further advancing the evolved universal mobile telecommunications system (UMTS) terrestrial radio access network (E-UTRAN) and UTRAN based radio access network technologies. New radio (NR) is the 3rd generation partnership project (3GPP) endeavor for outlining and standardization of the 5th generation (5G) advanced radio access technology. 3GPP has released the first set of 5G NR standards, i.e., the non-standalone 5G radio specifications. As long-term evolution (LTE) technology is massively deployed and broadly accepted, the transition from LTE to 5G is very critical, and it is of maximal importance that the backward compatibility of 5G with LTE is considered. 3GPP has identified several architecture options for 5G. This article gives an overview of the NR architecture options, their deployment scenarios, and the key migration paths. The LTE-NR dual connectivity (DC) is presented. This DC scenario is unique in the sense that DC is being endowed for two different generations of 3GPP radio access technologies. We, further, present the integration of multipath transmission control protocol (MPTCP) with LTE-NR DC and DC-like aggregation, i.e., 3GPP-non-3GPP interworking to bring in the advantages of MPTCP in terms of link robustness, reliability and dynamic mapping between the traffic flows and the available paths. Finally, we discuss the future research and standardization directions of the next-generation networks.

Exploitation of Mobile Edge Computing in 5G Distributed Mission-Critical Push-to-Talk Service Deployment

There is a growing interest in adapting mission critical public-safety communications from traditional private radio technologies toward 5G. The need for resiliency and strong delay requirements has resulted in mobile edge computing (MEC) emerging as a key technology to improve the deployment of public safety applications over the mobile network. This paper presents a non-standalone 5G ETSI MEC-based architecture for mission-critical push-to-talk (MCPTT) services. The proposal suggests a hierarchical distributed MCPTT architecture that allocates the user plane at the edge, keeping the control plane (CP) centralized for synchronization and assistance purposes. The MEC architecture enables the deployment of low latency services, due to the proximity of functional servers to the end-user, releases user equipment from heavy workloads, and benefits from horizontal scalability to provide dynamic allocation of network resources at specific locations. The proposed architecture is also beneficial in an isolated E-UTRAN operation situation, where in the case of backhaul connection loss, local MCPTT services can be straightforwardly deployed within an isolated group of eNodeBs.