Poster 1

Tuesday, 16 June 2020, 12:15-14:30 CEST, Recommended re-viewing, https://www.youtube.com/playlist?list=PLjQu6nB1DfNCf5S2O4-apCLd3lIy83cFK

Tuesday, 16 June 2020, 12:15-17:00 CEST, Non-Live interaction (Chat),  link sent only to Registered people

 

Experimental Assessment of Electromagnetic Fields in a Commercial 5G Network

Chrysanthi Chountala, Jean Marc Chareau, Pravir K Chawdhry, Philippe Viaud, James Bishop and Tiziano P Pinato (European Commission – Joint Research Centre, Italy)
Reliable estimation of electromagnetic fields (EMFs) generated by mobile phone signals is crucial for the roll out of fifth generation (5G) networks and public trust in its safety. An experimental approach using a low cost portable testbed was developed for the evaluation of EMFs of 5G signals. Measurements were carried out on a live 5G commercial network operating in IMT band n78 and radiofrequency (RF) signals were analysed off-line to characterize EMF levels in the network. Results show that a baseline of the EMF level can be determined using standard spectrum analysers and post-processing and that the level of the electric field generated by the 5G signal depends on the downlink/uplink (DL/UL) traffic.

 

CRAN Option 7-3 Splitting: A Novel Comparative Real-time Study

Shahriar Basiri (Sharif University of Technology, Iran); Azad Ravanshid (NOMOR, Germany); Babak Hossein Khalaj (Sharif University of Technology, Iran)
Cloud-Radio Access Network (C-RAN) is a well-known promising technology to support requirements of future 5G mobile networks where evolved NodeB (eNB) functions can be split between a Distributed Unit (DU) and Central Unit (CU). Several functional splits have been introduced in order to mitigate fronthaul requirements of C-RAN. This study experimentally evaluates option 7-3 functional splitting introduced by 3GPP. We will test some main key performance indicators (KPIs) to evaluate this option and we will compare the results to some other lower layer splits. Obtained results show that option 7-3 is an advantageous C-RAN candidate specially when cell traffic is low.

 

Data-driven UAV Trajectory Optimization

Hajar El Hammouti (KAUST, Saudi Arabia); Abdulkadir Celik (King Abdullah University of Science & Technology, Saudi Arabia); Basem Shihada (KAUST, Saudi Arabia); Mohamed-Slim Alouini (King Abdullah University of Science and Technology (KAUST), Saudi Arabia)
Unmanned aerial vehicles (UAVs) have received lots of attention as a promising technology to assist future wireless networks. One of the key use cases is deploying UAVs to enhance network performance by offloading traffic from hotspot areas. However, in a dynamic data traffic environment, it is crucial to design the UAV trajectory to maximize the number of offloaded base stations while taking the UAV’s limited energy budget into account
In this paper, the trajectory of a UAV that provides connectivity to the ground users is studied. In order to maximize the system’s sum-rate under energy constraints, we adopt a Markov decision process framework that we solve using a reinforcement learning approach. Simulation results demonstrate that incorporating reinforcement learning into UAV’s trajectory planning enhances the network performance.

 

5GCroCo Use Cases and Key Performance Indicators for Cross-border Trials

Dirk Hetzer (T-Systems, Germany); Maciej Muehleisen (Ericsson GmbH, Germany); Apostolos Kousaridas (Huawei Technologies, Germany); Jesus Alonso-Zarate (Centre Tecnologic de Telecomunicacions de Catalunya – CTTC, Spain)
The provision of Cooperative, Connected, and Automated Mobility (CCAM) services across different countries when vehicles traverse various national borders has a huge innovative business potential. However, the seamless provision of connectivity and the uninterrupted delivery of real-time services across borders also pose technical challenges which 5G technologies promise to solve. The situation is challenging given the multi-country, multi-operator, multi-telco-vendor, multi-car manufacturer, and cross-generation scenario of any cross-border layout. The 5GCroCo project is piloting use cases for Automated Driving (AD) in 1) Tele-operated Driving, 2) High Definition (HD) map generation and distribution for automated vehicles, and 3) Anticipated Cooperative Collision Avoidance (ACCA). The results will help reduce the uncertainties associated with enhanced Vehicle-to-Anything (eV2X communications) across borders in Europe in preparation for commercial 5G deployment.

 

D-band Point to Multipoint Wireless Testbed

Antonio Ramirez (Fibernova Systems, Spain); Viktor Krozer (Goethe University of Frankfurt am Main, Germany); Quang Trung Le (HF Systems Engineering GmbH & Co. KG, Germany); Rupa Basu, Jeevan Rao and Rosa Letizia (Lancaster University, United Kingdom (Great Britain)); Ernesto Limiti (University of Rome Tor Vergata, Italy); François Magne (WHEN-AB & SARL, France); Marc Marilier (OMMIC, France); Giacomo Ulisse (Johann Wolfgang Goethe-Universität, Germany); Hadi Yacob (9 Ferdinand-Braun-Institut, Leibniz-Institut für Höchstfrequenztechnik, Germany); Borja Vidal (Universidad Politecnica de Valencia, Spain); Roberto Llorente (Universitat Politècnica de València, Spain); Claudio Paoloni (Lancaster University, United Kingdom (Great Britain))
The paper presents the first ever testbed of a D-band (141 – 148.5 GHz) point to multipoint wireless system, developed in the framework of H2020 ULTRAWAVE project. The testbed for the mentioned D-band system has been implemented in the campus of the Universitat Politecnica de Valencia (Valencia, Spain). One Transmission Hub, including a novel D-band Traveling Wave Tube high power amplifier, is employed to provide coverage in a 30º sector to three D-band terminals deployed at 300 m, 450 m and 500 m. The objective of the testbed is to provide performance assessment based on the most critical Key Parameter Indicators of the wireless links established between the TH and each Terminal using ULTRAWAVE technology. Such parameters will be collected using an underlying GbE network allowing undisturbed out-of-band monitoring and configuration.

 

Inter-Numerology Interference in Filtered-OFDM Waveforms

Chrysanthi Chountala (European Commission – Joint Research Center, Italy); Jean Marc Chareau and James Bishop (Joint Research Centre of the European Commission, Italy); Fausto Bonavitacola (Fincons Italia S.p.A., Milan, Italy)
Mixed numerologies will be used in 5G systems to support diverse services. In the present paper, filtered orthogonal frequency division multiplexing (f-OFDM) waveforms were implemented in the field programmable gate array (FPGA) of software defined radio (SDR) transceivers. The setup was capable of implementing different numerologies with variable sub-carrier frequency separation. Measurements were performed in conducted mode operating at 3.6GHz, having 40MHz channel width and using quadrature phase-shift keying (QPSK) modulation scheme. With a 4K video stream as payload, the link allowed us to experiment with 5G New Radio (NR) mixed numerologies when applying different filtering on the transmitter and the receiver. Error vector magnitude (EVM) was quantified as the quality factor. Results suggest that the application of filtering on the receiver improves the quality of the f-OFDM waveforms.

 

Autonomous Vehicles Impact on 5G Network Base Station Inter-Site Distance

António Serrador (Polytechnic Institute of Lisbon & ISEL, Portugal); Grazielle Bonaldi Teixeira (Lisbon High Institute of Engineering – ISEL, Portugal); Mirtes Lima and Rafael Fernandes (ISEL, Portugal)
Future 5G networks will support new mobile services and applications. A good example is autonomous vehicles applications, which in relevant cases will use 5G network access capabilities to increase their security and available information to enable, or help, perform different manoeuvres. This work proposes a tool useful for Mobile Network Operators (MNO) to compute Base Stations (BS) Inter-Site Distance (ISD) based on the average traffic generated by connected autonomous vehicles and roadside sensors. To achieve this goal, vehicles foreseen generated data traffic and 5G cell capacity is modelled. ISD results are computed based on 2020/30 forecast autonomous vehicles data traffic, identifying propagation conditions when 5G cells in urban and rural areas reach their capacity. Main results show that ISD range from 400 up to 4000 m, in urban and rural environments, respectively. Compared with current ISD configurations, rural areas will need more investments by reducing ISD in these areas.

 

MAC-agnostic Swarm-Based Directional Antenna Control for Wireless Sensor Networks

Tim van der Lee and George Exarchakos (Eindhoven University of Technology, The Netherlands); Sonia Heemstra de Groot (Eindhoven Technical University, The Netherlands)
In recent years, we observe an emergence of large-scale and dense mesh wireless network deployments. Interference caused by such deployments leads to re-transmissions, avoidable energy waste. To solve this issue, directional antennas are considered as it makes a more efficient use of the wireless medium, by only using the required wireless space when unicast messages have to be sent or received. Inspired from swarming behavior present in nature, this algorithm distributively assigns to each neighbor, a dynamic direction probability distribution. In this way, device mobility is addressed. Similarly, inactive or faulty devices are forgotten, which leads to an efficient use of the wireless medium.

 

5G-CLARITY: Integrating 5GNR, WiFi and LiFi in Private Networks with Slicing Support

Daniel Camps (i2CAT, Spain); Mir Ghoraishi (Gigasys Solutions, United Kingdom (Great Britain)); Jesús Gutiérrez (IHP – Leibniz-Institut für Innovative Mikroelektronik, Germany); Jose Ordonez-Lucena (Telefonica I+D, Spain); Tezcan Cogalan (University of Edinburgh, United Kingdom (Great Britain)); Harald Haas (The University of Edinburgh, United Kingdom (Great Britain)); Antonio Garcia (Accelleran, Belgium); Vladica Sark (IHP – Leibniz-Institut für Innovative Mikroelektronik, Germany); Erik Aumayr and Sven van der Meer (Ericsson, Ireland); Shuangyi Yan (University of Bristol, United Kingdom (Great Britain)); Alain Abdel-Majid Mourad (Interdigital Europe Ltd, United Kingdom (Great Britain)); Oscar Adamuz-Hinojosa (University of Granada, Spain); Jordi Pérez-Romero (Universitat Politècnica de Catalunya (UPC), Spain); Miguel Granda (BOSCH, Spain); Rui Bian (University of Edinburgh, United Kingdom (Great Britain))
Some vertical users, e.g. industrial environments, demand customized private 5G networks that address their technological and business needs. These networks present challenges that differ from those of traditional mobile network operators(MNOs), and that should be addressed through innovations in the user, control and management planes. This paper introduces 5G-CLARITY, a 5G-PPP project exploring beyond B5G private networks integrating heterogeneous wireless access including Cellular (5GNR beyond Rel. 16), WiFi, and LiFi. The project targets enhancements to current 5GNR performance including multi-connectivity and indoor positioning accuracy. 5G-CLARITY also develops novel management enablers that allow to operate the private network with a high level intent interface, while being able to natively embed machine learning (ML) functions.

 

Joint 5G-LTE-WiFi Prototyping Platform for RAT Interworking Experiments

Walter Nitzold and Clemens Felber (National Instruments, Germany)
The coordination and coexistence of heterogeneous wireless technologies such as 5G, LTE and WiFi have become a growing area of research these days due to an increased number of connected devices and related communication requirements. This poster presents a prototyping system for joint real-time experimentation of LTE, WiFi and 5G systems with software defined radio hardware that involves real-time FPGA PHY implementations. This platform allows holistic experiments of these communication systems and related interworking functionalities that will lead to a better insight into trade-offs for using these radio access technologies jointly as it is foreseen in practical wireless network deployments.