OPE2 – Beyond 5G and 6G trials and experiments

Wednesday, 7 June 2023, 16:00-17:30, Room R24-R25

Session Chair: Tero Jokela (Turku University of Applied Sciences, Finland)

Experimental Assessment of Electromagnetic Field Exposure from 5G Terminal Devices
Chrysanthi Chountala (European Commission – Joint Research Centre, Italy); Isabella Cerutti (Joint Research Centre, Italy); Jean Marc Chareau and Philippe Viaud (Joint Research Centre of the European Commission, Italy); Fausto Bonavitacola (Energy Security, Distribution and Markets Unit, Joint Research Centre, EC, Italy)
Electromagnetic field (EMF) exposure from mobile networks is raising discussions not only on their safety levels but also on the assessment methods, since the evolution of technology among the various generations requires different measurement techniques. This paper describes an experimental study for measuring the 5G EMF emissions caused by mobile terminals. To consider a realistic worst-case scenario, the measurements were taken in the direction of maximum antenna gain of the devices while inducing maximum uplink traffic in the mobile channel. The results provide valuable feedback on the exposure assessment of the mobile terminals connected to 5G networks. Moreover the measurement setup and methodology can provide useful insights in developing exposure setups for future studies analyzing biological interactions with EMFs.

Drone Interference in Geographically Limited Local Mobile TDD Networks
Pekka Talmola, Juha Kalliovaara, Tero Jokela, Jani Auranen, Juhani Hallio, Juho Koskinen and Antti Arajärvi (Turku University of Applied Sciences, Finland); Heidi Himmanen (Traficom, Finland)
Local wireless mobile networks using LTE or 5G technology have recently gained interest in many industrial applications. Using drones opens up possibilities for many novel services to be deployed in local networks. From the network point of view, having a mobile User Equipment (UE) in the air poses additional source of interference towards neighbouring local networks. This paper develops a calculation model for the interference and verifies the model with a field measurement campaign.

Data Collection from LoRaWAN Sensor Network by UAV Gateway: Design, Empirical Results and Dataset
Gianmarco Canello (University of Oulu, Finland); Silvia Mignardi (University of Bologna, Italy); Konstantin Mikhaylov (University of Oulu, Finland); Chiara Buratti (University of Bologna, Italy); Tuomo Hänninen (University of Oulu, Finland)
Collecting data from Internet-of-Things (IoT) devices, especially the variety of sensors dispersed in the environment, is an increasingly important and difficult task. Several long-range radio-access technologies, such as low-power widearea networks (LPWAN) and specifically LoRaWAN, have been proposed to address this challenge. However, until now, the key focus of the related studies has been on static terrestrial LPWAN deployments. In this study, we depart from this vision and investigate the practical feasibility and performance of a LoRaWAN gateway (GW) on a flying platform, specifically – an unmanned aerial vehicle (UAV). The key contributions of this study are (i) the design and field-testing of a packet-sniffer-based mobile LoRaWAN GW prototype, allowing collection of the data from LoRaWAN networks, including the already deployed ones; (ii) the open-publication of the data collected during our experimental campaign in the 426 LoRaWAN sensor node network of the University of Oulu illustrating the performance of different drone trajectories; (iii) the initial results of the system’s performance analysis, revealing some interesting trends and setting goals for further studies, and pinpointing the lessons learned during the experimental campaign. Our empirical findings suggest that the Travelling Salesman Problem (TSP) trajectory is the most effective moving trajectory for the number of packets collected and the average energy consumed per packet collected.

Experiments with Industrial Robotics Systems over an Indoor 5G-NSA mmWave Deployment
Vicknesan Ayadurai and Revathy Narayanan (Ericsson Research, Sweden); Bengt-Erik Olsson (Ericsson AB, Sweden)
Use of high frequency millimeter wave (mmWave) bands as the communication solution for a variety of new verticals has been of interest over the past several years. While the inherent range limitation of mmWave bands make them the perfect candidate for building localized private indoor networks, transmissions at these high frequencies are also susceptible to absorption losses. Hence, despite the availability of large bandwidths, there has been a relatively slow uptake of these bands for licensed services. To address this, we explore the feasibility of mmWave by experimentally validating the performance of closedloop control applications with indoor mobility requirements over hybrid combinations of wired and 5G networks. Our experiments, executed over an indoor non-standalone (NSA) 5G deployment at 28GHz, revealed comparable performance of industrial robotics systems when communicating over 5G mmWave or Ethernet.

Investigating the Impact of Variables on Handover Performance in 5G Ultra-Dense Networks
Donglin Wang (Technical University of Kaiserslautern, Germany); Anjie Qiu (University of Kaiserslautern, Germany); Qiuheng Zhou (German Research Center for Artificial Intelligence (DFKI GmbH), Germany); Sanket Partani and Hans D. Schotten (University of Kaiserslautern, Germany)
The advent of 5G New Radio (NR) technology has revolutionized the landscape of wireless communication, offering various enhancements such as elevated system capacity, improved spectrum efficiency, and higher data transmission rates. To achieve these benefits, 5G has implemented the UltraDense Network (UDN) architecture, characterized by the deployment of numerous small general Node B (gNB) units. While this approach boosts system capacity and frequency reuse, it also raises concerns such as increased signal interference, longer handover times, and higher handover failure rates. To address these challenges, the critical factor of Time to Trigger (TTT) in handover management must be accurately determined. Furthermore, the density of gNBs has a significant impact on handover performance. This study provides a comprehensive analysis of 5G handover management. Through the development and utilization of a downlink system-level simulator, the effects of various TTT values and gNB densities on 5G handover were evaluated, taking into consideration the movement of Traffic Users (TUs) with varying velocities. Simulation results showed that the handover performance can be optimized by adjusting the TTT under different gNB densities, providing valuable insights into the proper selection of TTT, UDN, and TU velocity to enhance 5G handover performance.

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