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Experimentation in 5G and beyond Networks: State of the Art and the Way Forward

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 37994

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Special Issue Editors

Dr. Giuseppe Caso

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Department of Mathematics and Computer Science, Karlstad University, 65188 Karlstad, Sweden
Interests: wireless communication; mobile systems; Internet of Things; resource allocation; spectrum management
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Özgü Alay

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Department of Informatics, University of Oslo, 0315 Oslo, Norway Department of Mobile Systems and Analytics, Simula Metropolitan Center for Digital Engineering, 0167 Oslo, Norway
Interests: 5G; IoT; low-latency networking; mobile multimedia; multipath transport

Prof. Dr. Anna Brunstrom

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Department of Mathematics and Computer Science, Karlstad University, 65188 Karlstad, Sweden
Interests: internet architectures and protocols; low-latency communication; multipath communication; performance evaluation of mobile systems; 5G; IoT

Dr. Harilaos Koumaras

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Guest Editor

NCSR "Demokritos", Institute of Informatics and Telecommunications, Patriarchou Grigoriou E' & 27 Neapoleos Str., 15341 Agia Paraskevi, Greece
Interests: 5G; mobile communications; virtualization; cloud computing; quality of experience; multimedia; networking
Special Issues, Collections and Topics in MDPI journals

Dr. Almudena Díaz Zayas

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Department of Electronics Technology, University of Malaga, 29016 Malaga, Spain
Interests: mobile communications and protocols; testbeds; testing; quality of service

Dr. Valerio Frascolla

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Guest Editor

Intel Deutschland GmbH, Lilienthalstraße 4, 85579 Neubiberg, Germany
Interests: 5G and beyond system design; business models; dynamic spectrum management; edge technology; artificial intelligence

Special Issue Information

Dear Colleagues,

As defined by the 3rd Generation Partnership Project (3GPP) standards in the Release 15 specifications, only recently has the first phase of the 5th Generation (5G) of cellular systems started to be deployed worldwide. Each country, based on its own needs and local market requests, has decided on its own deployment roadmap of 5G services. For instance, as of August 2020, not all European countries have launched commercial 5G services. This ongoing first phase of deployment will be followed by enhanced versions of the standards in the following years. Therefore, in parallel with the commercial rollout, the capability to experiment and validate the planned new features, thanks to data-driven analyses based on field trials and measurements, is of extreme interest to the whole 5G ecosystem, including researchers, standardization bodies, network operators, small and medium-sized enterprises, technology and equipment providers, and verticals. These analyses make it possible to identify correlations between deployment choices and achievable 5G key performance indicators (KPIs), while guiding towards system optimization and enhancement. The definition of KPIs, as well as measurement and validation methodologies, are complex tasks in 5G scenarios, due to intrinsic dependencies with specific use cases, services, and applications.

Within the above context, this Special Issue aims to collect original contributions on experimental aspects of 5G and beyond networks and systems. Topics of interest include, but are not limited to:

Design, implementation, and usage of 5G and beyond experimental testbeds and platforms (e.g., those in the scopes of EU 5G-PPP and US PAWR programs);
Design, implementation, and usage of 5G open-source tools for automated resource instantiation, management, monitoring, and data analysis;
End-to-end measurement and validation frameworks for 5G KPIs;
Experimental analysis and ML/AI-based modeling and optimization of 5G technologies and paradigms, including:
- 5G New Radio (NR) and 5G Core (5G Core);
- Network slicing, management and orchestration, and SDN/NFV;
- MEC, fog and edge computing;
- 5G multi-access and multi-connectivity at different network layers (e.g., 5GNR-LTE interworking, 5GNR-WiFi aggregation, and multipath transport protocols applied to 5G);
- Spectrum sharing, coexistence, and management mechanisms;
- mmWave communication and networking;
Experimental analysis and ML/AI-based modeling and optimization of 5G vertical-specific applications, including
- High-demanding multimedia applications;
- Smart cities;
- Industrial automation;
- Intelligent transport systems and vehicular applications;
- E-health;
- Mission-critical services;
5G and beyond standardization activities towards KPI measurement and validation;
Description and usage of 5G open datasets.

The Special Issue seeks original, unpublished papers addressing key issues and challenges in 5G and beyond experimentation. Survey, review, and tutorial papers on aspects related to the above topics will also be considered for publication. Papers shall contain original material, not currently submitted elsewhere. All submissions will be judged by their technical merit and relevance to the Special Issue.

Dr. Giuseppe Caso
Prof. Dr. Özgü Alay
Prof. Dr. Anna Brunstrom
Dr. Harilaos Koumaras
Dr. Almudena Díaz Zayas
Dr. Valerio Frascolla
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

5G
5G and beyond
KPI measurement and validation
Testbed design and usage
Empirical analysis
ML/AI-based optimization
Experimentation
Open source tools

Published Papers (11 papers)

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Editorial

Jump to: Research

5 pages, 191 KiB

Open AccessEditorial

Experimentation in 5G and beyond Networks: State of the Art and the Way Forward

by Giuseppe Caso, Özgü Alay, Anna Brunstrom, Harilaos Koumaras, Almudena Díaz Zayas and Valerio Frascolla

Sensors 2023, 23(24), 9671; https://doi.org/10.3390/s23249671 - 07 Dec 2023

Viewed by 847

Abstract

After first being standardized by the 3rd Generation Partnership Project (3GPP) in Release 15, 5th Generation (5G) mobile systems have been rapidly deployed worldwide [...] Full article

(This article belongs to the Special Issue Experimentation in 5G and beyond Networks: State of the Art and the Way Forward)

Research

Jump to: Editorial

30 pages, 2418 KiB

Open AccessArticle

Machine Learning-Based Methods for Enhancement of UAV-NOMA and D2D Cooperative Networks

by Lefteris Tsipi, Michail Karavolos, Petros S. Bithas and Demosthenes Vouyioukas

Sensors 2023, 23(6), 3014; https://doi.org/10.3390/s23063014 - 10 Mar 2023

Cited by 5 | Viewed by 1740

Abstract

The cooperative aerial and device-to-device (D2D) networks employing non-orthogonal multiple access (NOMA) are expected to play an essential role in next-generation wireless networks. Moreover, machine learning (ML) techniques, such as artificial neural networks (ANN), can significantly enhance network performance and efficiency in fifth-generation (5G) wireless networks and beyond. This paper studies an ANN-based unmanned aerial vehicle (UAV) placement scheme to enhance an integrated UAV-D2D NOMA cooperative network.The proposed placement scheme selection (PSS) method for integrating the UAV into the cooperative network combines supervised and unsupervised ML techniques. Specifically, a supervised classification approach is employed utilizing a two-hidden layered ANN with 63 neurons evenly distributed among the layers. The output class of the ANN is utilized to determine the appropriate unsupervised learning method—either k-means or k-medoids—to be employed. This specific ANN layout has been observed to exhibit an accuracy of 94.12%, the highest accuracy among the ANN models evaluated, making it highly recommended for accurate PSS predictions in urban locations. Furthermore, the proposed cooperative scheme allows pairs of users to be simultaneously served through NOMA from the UAV, which acts as an aerial base station. At the same time, the D2D cooperative transmission for each NOMA pair is activated to improve the overall communication quality. Comparisons with conventional orthogonal multiple access (OMA) and alternative unsupervised machine-learning based-UAV-D2D NOMA cooperative networks show that significant sum rate and spectral efficiency gains can be harvested through the proposed method under varying D2D bandwidth allocations. Full article

(This article belongs to the Special Issue Experimentation in 5G and beyond Networks: State of the Art and the Way Forward)

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30 pages, 6316 KiB

Open AccessArticle

OpenCare5G: O-RAN in Private Network for Digital Health Applications

by Wagner de Oliveira, José Olimpio Rodrigues Batista, Jr., Tiago Novais, Silvio Toshiyuki Takashima, Leonardo Roccon Stange, Moacyr Martucci, Jr., Carlos Eduardo Cugnasca and Graça Bressan

Sensors 2023, 23(2), 1047; https://doi.org/10.3390/s23021047 - 16 Jan 2023

Cited by 4 | Viewed by 4363

Abstract

Digital Health is a new way for medicine to work together with computer engineering and ICT to carry out tests and obtain reliable information about the health status of citizens in the most remote places in Brazil in near-real time, applying new technologies and digital tools in the process. InovaHC is the technological innovation core of the Clinics Hospital of the Faculty of Medicine of the University of São Paulo (HCFMUSP). It is the first national medical institution to seek new opportunities offered by 5G technology and test its application in the first private network for Digital Health in the largest hospital complex in Latin America through the OpenCare5G Project. This project uses an Open RAN concept and network disaggregation with lower costs than the traditional concept used by the telecommunications industry. The technological project connected to the 5G network was divided into two phases for proof-of-concept testing: the first with an initial focus on carrying out examinations with portable ultrasound equipment in different locations at HCFMUSP, and the second focusing on carrying out remote examinations with health professionals in other states of Brazil, who will be working in remote areas in other states with little or no ICT infrastructure together with a doctor analyzing exams in real time at HCFMUSP in São Paulo. The objective of the project is to evaluate the connectivity and capacity of the 5G private network in these the proof-of-concept tests for transmitting the volume of data from remote exams with higher speed and lower latency. We are in the first phase of the proof of concept testing to achieve the expected success. This project is a catalyst for innovation in health, connecting resources and entrepreneurs to generate solutions for the innovation ecosystem of organizations. It is coordinated by Deloitte with the participation of the Escola Politécnica da USP (The School of Engineering—University of São Paulo), Airspan, Itaú Bank, Siemens Healthineers, NEC, Telecom Infra Projet, ABDI and IDB. The use of 5G Open RAN technology in public health is concluded to be of extreme social, economic, and fundamental importance for HCFMUSP, citizens, and the development of health research to promote great positive impacts ranging from attracting investment in the country to improving the quality of patient care. Full article

(This article belongs to the Special Issue Experimentation in 5G and beyond Networks: State of the Art and the Way Forward)

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21 pages, 814 KiB

Open AccessArticle

Implementation of Deep-Learning-Based CSI Feedback Reporting on 5G NR-Compliant Link-Level Simulator

by Daniel Gaetano Riviello, Riccardo Tuninato, Elisa Zimaglia, Roberto Fantini and Roberto Garello

Sensors 2023, 23(2), 910; https://doi.org/10.3390/s23020910 - 12 Jan 2023

Cited by 4 | Viewed by 3469

Abstract

Advances in machine learning have widened the range of its applications in many fields. In particular, deep learning has attracted much interest for its ability to provide solutions where the derivation of a rigorous mathematical model of the problem is troublesome. Our interest was drawn to the application of deep learning for channel state information feedback reporting, a crucial problem in frequency division duplexing (FDD) 5G networks, where knowledge of the channel characteristics is fundamental to exploiting the full potential of multiple-input multiple-output (MIMO) systems. We designed a framework adopting a 5G New Radio convolutional neural network, called NR-CsiNet, with the aim of compressing the channel matrix experienced by the user at the receiver side and then reconstructing it at the transmitter side. In contrast to similar solutions, our framework is based on a 5G New Radio fully compliant simulator, thus implementing a channel generator based on the latest 3GPP 3-D channel model. Moreover, realistic 5G scenarios are considered by including multi-receiving antenna schemes and noisy downlink channel estimation. Simulations were carried out to analyze and compare the performance with current feedback reporting schemes, showing promising results for this approach from the point of view of the block error rate and throughput of the 5G data channel. Full article

(This article belongs to the Special Issue Experimentation in 5G and beyond Networks: State of the Art and the Way Forward)

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27 pages, 5357 KiB

Open AccessArticle

Multi-Layer Attack Graph Analysis in the 5G Edge Network Using a Dynamic Hexagonal Fuzzy Method

by Hisham A. Kholidy

Sensors 2022, 22(1), 9; https://doi.org/10.3390/s22010009 - 21 Dec 2021

Cited by 15 | Viewed by 4041

Abstract

Overall, 5G networks are expected to become the backbone of many critical IT applications. With 5G, new tech advancements and innovation are expected; 5G currently operates on software-defined networking. This enables 5G to implement network slicing to meet the unique requirements of every application. As a result, 5G is more flexible and scalable than 4G LTE and previous generations. To avoid the growing risks of hacking, 5G cybersecurity needs some significant improvements. Some security concerns involve the network itself, while others focus on the devices connected to 5G. Both aspects present a risk to consumers, governments, and businesses alike. There is currently no real-time vulnerability assessment framework that specifically addresses 5G Edge networks, with regard to their real-time scalability and dynamic nature. This paper studies the vulnerability assessment in the 5G networks and develops an optimized dynamic method that integrates the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with the hexagonal fuzzy numbers to accurately analyze the vulnerabilities in 5G networks. The proposed method considers both the vulnerability and 5G network dynamic factors such as latency and accessibility to find the potential attack graph paths where the attack might propagate in the network and quantifies the attack cost and security level of the network. We test and validate the proposed method using our 5G testbed and we compare the optimized method to the classical TOPSIS and the known vulnerability scanner tool, Nessus. Full article

(This article belongs to the Special Issue Experimentation in 5G and beyond Networks: State of the Art and the Way Forward)

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20 pages, 4822 KiB

Open AccessArticle

Validating a 5G-Enabled Neutral Host Framework in City-Wide Deployments

by Adriana Fernández-Fernández, Carlos Colman-Meixner, Leonardo Ochoa-Aday, August Betzler, Hamzeh Khalili, Muhammad Shuaib Siddiqui, Gino Carrozzo, Sergi Figuerola, Reza Nejabati and Dimitra Simeonidou

Sensors 2021, 21(23), 8103; https://doi.org/10.3390/s21238103 - 03 Dec 2021

Cited by 10 | Viewed by 2849

Abstract

Along with the adoption of 5G, the development of neutral host solutions provides a unique opportunity for mobile networks operators to accommodate the needs of emerging use-cases and in the consolidation of new business models. By exploiting the concept of network slicing, as one key enabler in the transition to 5G, infrastructure and service providers can logically split a shared physical network into multiple isolated and customized networks to flexibly address the specific demands of those tenant slices. Motivated by this reality, the H2020 5GCity project proposed a novel 5G-enabled neutral host framework for three European cities: Barcelona (ESP), Bristol (UK), and Lucca (IT). This article revises the main achievements and contributions of the 5GCity project, focusing on the deployment and validation of the proposed framework. The developed neutral host framework encompasses two main parts: the infrastructure and the software platform. A detailed description of the framework implementation, in terms of functional capabilities and practical implications of city-wide deployments, is provided in this article. This work also presents the performance evaluation of the proposed solution during the implementation of real vertical use cases. Obtained results validate the feasibility of the neutral host model and the proposed framework to be deployed in city-wide 5G infrastructures. Full article

(This article belongs to the Special Issue Experimentation in 5G and beyond Networks: State of the Art and the Way Forward)

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18 pages, 1530 KiB

Open AccessArticle

Low-Latency QC-LDPC Encoder Design for 5G NR

by Yunke Tian, Yong Bai and Dake Liu

Sensors 2021, 21(18), 6266; https://doi.org/10.3390/s21186266 - 18 Sep 2021

Cited by 2 | Viewed by 4277

Abstract

In order to meet the low latency and high throughput requirements of data transmission in 5th generation (5G) New Radio (NR), it is necessary to minimize the low power encoding hardware latency on transmitter and achieve lower base station power consumption within a fixed transmission time interval (TTI). This paper investigates parallel design and implementation of 5G quasi-cyclic low-density parity-check (QC-LDPC) codes encoder. The designed QC-LDPC encoder employs a multi-channel parallel structure to obtain multiple parity check bits and thus reduce encoding latency significantly. The proposed encoder maps high parallelism encoding algorithms to a configurable circuit architecture, achieving flexibility and support for all 5G NR code length and code rate. The experimental results show that under the 800 MHz system frequency, the achieved data throughput ranges from 62 to 257.9 Gbps, and the maximum code length encoding time under base graph 1 (BG1) is only 33.75 ns, which is the critical encoding time of our proposed encoder. Finally, our proposed encoder was synthesized on SMIC 28 nm CMOS technology; the result confirmed the effectiveness and feasibility of our design. Full article

(This article belongs to the Special Issue Experimentation in 5G and beyond Networks: State of the Art and the Way Forward)

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18 pages, 3777 KiB

Open AccessArticle

5G Standalone and 4G Multi-Carrier Network-in-a-Box Using a Software Defined Radio Framework

by Karolis Kiela, Marijan Jurgo, Vytautas Macaitis and Romualdas Navickas

Sensors 2021, 21(16), 5653; https://doi.org/10.3390/s21165653 - 22 Aug 2021

Cited by 5 | Viewed by 4168

Abstract

In this work, an open Radio Access Network (RAN), compatible, scalable and highly flexible Software Defined Radio (SDR)-based Remote Radio Head (RRH) framework is proposed and designed. Such framework can be used to implement flexible wideband radio solutions, which can be deployed in any region, have common radio management features, and support various channel bandwidths. Moreover, it enables easier access for researchers to nonsimulated cellular networks, reduce system development time, provide test and measurement capabilities, and support existing and emerging wireless communication technologies. The performance of the proposed SDR framework is validated by creating a Network-in-a-Box (NIB) that can operate in multiband multicarrier 4G or 5G standalone (SA) configurations, with an output power of up to 33 dBm. Measurement results show, that the 4G and 5G NIB can achieve, respectively, up to 883 Mbps and 765 Mbps downlink data transfer speeds for a 100 MHz aggregated bandwidth. However, if six carriers are used in the 4G NIB, 1062 Mbps downlink data transfer speed can be achieved. When single user equipment (UE) is used, maximum uplink data transfer speed is 65.8 Mbps and 92.6 Mbps in case of 4G and 5G, respectively. The average packet latency in case of 5G is up to 45.1% lower than 4G. CPU load by the eNodeB and gNodeB is proportional to occupied bandwidth, but under the same aggregated DL bandwidth conditions, gNodeB load on the CPU is lower. Moreover, if only 1 UE is active, under same aggregated bandwidth conditions, the EPC CPU load is up to four times lower than the 5GC. Full article

(This article belongs to the Special Issue Experimentation in 5G and beyond Networks: State of the Art and the Way Forward)

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21 pages, 1301 KiB

Open AccessArticle

Random Access Using Deep Reinforcement Learning in Dense Mobile Networks

by Yared Zerihun Bekele and Young-June Choi

Sensors 2021, 21(9), 3210; https://doi.org/10.3390/s21093210 - 05 May 2021

Cited by 1 | Viewed by 2386

Abstract

5G and Beyond 5G mobile networks use several high-frequency spectrum bands such as the millimeter-wave (mmWave) bands to alleviate the problem of bandwidth scarcity. However high-frequency bands do not cover larger distances. The coverage problem is addressed by using a heterogeneous network which comprises numerous small and macrocells, defined by transmission and reception points (TRxPs). For such a network, random access is considered a challenging function in which users attempt to select an efficient TRxP by random access within a given time. Ideally, an efficient TRxP is less congested, minimizing delays in users’ random access. However, owing to the nature of random access, it is not feasible to deploy a centralized controller estimating the congestion level of each cell and deliver this information back to users during random access. To solve this problem, we establish an optimization problem and employ a reinforcement-learning-based scheme. The proposed scheme estimates congestion of TRxPs in service and selects the optimal access point. Mathematically, this approach is beneficial in approximating and minimizing a random access delay function. Through simulation, we demonstrate that our proposed deep learning-based algorithm improves performance on random access. Notably, the average access delay is improved by 58.89% from the original 3GPP algorithm, and the probability of successful access also improved. Full article

(This article belongs to the Special Issue Experimentation in 5G and beyond Networks: State of the Art and the Way Forward)

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15 pages, 1142 KiB

Open AccessArticle

Deploying an NFV-Based Experimentation Scenario for 5G Solutions in Underserved Areas

by Victor Sanchez-Aguero, Ivan Vidal, Francisco Valera, Borja Nogales, Luciano Leonel Mendes, Wheberth Damascena Dias and Alexandre Carvalho Ferreira

Sensors 2021, 21(5), 1897; https://doi.org/10.3390/s21051897 - 08 Mar 2021

Cited by 8 | Viewed by 2829

Abstract

Presently, a significant part of the world population does not have Internet access. The fifth-generation cellular network technology evolution (5G) is focused on reducing latency, increasing the available bandwidth, and enhancing network performance. However, researchers and companies have not invested enough effort into the deployment of the Internet in remote/rural/undeveloped areas for different techno-economic reasons. This article presents the result of a collaboration between Brazil and the European Union, introducing the steps designed to create a fully operational experimentation scenario with the main purpose of integrating the different achievements of the H2020 5G-RANGE project so that they can be trialed together into a 5G networking use case. The scenario encompasses (i) a novel radio access network that targets a bandwidth of 100 Mb/s in a cell radius of 50 km, and (ii) a network of Small Unmanned Aerial Vehicles (SUAV). This set of SUAVs is NFV-enabled, on top of which Virtual Network Functions (VNF) can be automatically deployed to support occasional network communications beyond the boundaries of the 5G-RANGE radio cells. The whole deployment implies the use of a virtual private overlay network enabling the preliminary validation of the scenario components from their respective remote locations, and simplifying their subsequent integration into a single local demonstrator, the configuration of the required GRE/IPSec tunnels, the integration of the new 5G-RANGE physical, MAC and network layer components and the overall validation with voice and data services. Full article

(This article belongs to the Special Issue Experimentation in 5G and beyond Networks: State of the Art and the Way Forward)

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25 pages, 1252 KiB

Open AccessEditor’s ChoiceArticle

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

by Almudena Díaz Zayas, Giuseppe Caso, Özgü Alay, Pedro Merino, Anna Brunstrom, Dimitris Tsolkas and Harilaos Koumaras

Sensors 2020, 20(22), 6652; https://doi.org/10.3390/s20226652 - 20 Nov 2020

Cited by 17 | Viewed by 4397

Abstract

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. Full article

(This article belongs to the Special Issue Experimentation in 5G and beyond Networks: State of the Art and the Way Forward)

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