Siradel’s 5G Resarch and Development projects

/ Siradel’s 5G Resarch and Development projects

Innovation and research have always been at the core of Siradel’s vision. With a highly-skilled R&D team and strong expertise in radio planning, Siradel is at the forefront of innovation in the telecommunications and data fields.

Working on various projects including fiber-5G convergence, LoRaWAN planning challenges or advanced channel modeling, Siradel has joined numerous research programs and has developped a large network of partners, from academic labs to private companies. In terms of data innovation, we develop new methods to digitize large urban territories in 3D, and automatically extract semantics. We also explore innovative big geodata management systems to share and exploit the considerable amount of heterogeneous geodata generated daily by cities and its stakeholders. Already working on 6G, Siradel is paving the road for next-generation networks and keeps developping new tools and paradygms for understanding and co-designing cities more efficiently.

Find the agenda of our future participations in scientific events on our Events page

Research projects

5Gwireless (H2020)

Its objectives are to optimize network architectures and topologies, design new transmission technologies based on massive MIMO and mmWave, and introduce new methodological approaches for network optimization.

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Brave

Brave is a collaborative research project started in January 2018, that aims at creating new physical-layer (PHY) techniques for beyond-5G wireless communications.

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LEXNET (FP7)

LEXNET objectives was to investigate methods, technologies and architectures to reduce the exposure to electromagnetic fields (EMF) related to wireless networks.

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Probe SIM 3D (RAPID)

SIRADEL developed semi-automatic methods to produce quickly at a large scale 3D cities from heterogeneous data, and to simulate dynamically in Virtual Battlespace 3 the performance of a radio network virtually deployed.

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Partnerships

Alliance 5G

As member of Alliance 5G SIRADEL is contributing to the scientific cooperation within the 5G millimeter channel model Alliance
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FTTH Council Europe

SIRADEL has been supporting the members of the FTTH council thanks to its wireless expertise and through its contribution in the framework of 5G and fiber convergence.

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LoRa Alliance

SIRADEL, member of the LoRa alliance, has been at the forefront of the LoRa deployment, working closely with technology providers and operators.

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PAWR

The US Ignite PAWR program is enabling experimental exploration of new wireless devices, communication techniques, networks, systems, and services that will revolutionize the nation’s wireless ecosystem while sustaining US leadership and economic competitiveness for decades to come.

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Telecom Infra Project

Member of the TIP since 2016, SIRADEL strongly contributes to the mmW channel modeling group, using its experience in channel sounder measurement data collection and comparison to simulations.

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Scientific papers

5G network design

SIRADEL integrates new 5G wireless technologies (beamforming, massive MIMO, mesh backhaul, etc.) in its simulation software for realistic performance assessment and optimal infrastructure design.

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5G and beyond-5G
high frequencies

SIRADEL is enhancing its radio propagation model Volcano for 5G mmW and beyond-5G higher frequencies (above 100 GHz) by supporting highly-accurate 3D GIS data, for both channel modeling and radio planning applications.

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Radio channel modeling

SIRADEL innovations on its leading ray-tracing propagation model Volcano allow academic and industrial research centers to use cutting-edge, reliable radio channel data to design and test their new technologies.

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Electromagnetic-wave (EMF) exposure

SIRADEL develops new simulation solutions for EMF exposure assessment, adapted to mobile networks evolution, and based on its dual expertise in radio propagation and radio network protocols.

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3D GIS Data

SIRADEL Digital Territories R&D teams’ develop tools and algorithms for geometric and semantic modeling of cities Digital Twins from LIDAR and imagery data using methods like Machine Learning and Deep Learning.

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