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X-WR-CALDESC:Events for CENTRIC
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DTSTART:20230101T000000
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20240603
DTEND;VALUE=DATE:20240607
DTSTAMP:20260530T095620
CREATED:20240602T101358Z
LAST-MODIFIED:20240607T102045Z
UID:20161-1717372800-1717718399@centric-sns.eu
SUMMARY:CENTRIC WILL BE PRESENT AT THE EUCNC | 6G SUMMIT 2024 booth 26!
DESCRIPTION:🕒  < 1 minCENTRIC project at the EUCNC | 6G Summit 2024\nDemonstrating Validation setup for Site-Specific Multi-User MIMO Neural Receiver #booth-26\n \nThe CENTRIC project has proposed techniques encompassing AI-based transceiver designs\, AI-emerged protocol stacks and AI-based radio-resource management algorithms. In addition\, the project studies hardware and software enablers\, such as novel computational paradigms or the role of digital twins in supporting the AI-AI techniques. Last\, but not least\, methods for validation and benchmarking of the studied AI-AI techniques are as well in CENTRIC’s scope. \n \n \nThe CENTRIC project has proposed techniques encompassing AI-based transceiver designs\, AI-emerged protocol stacks and AI-based radio-resource management algorithms. In addition\, the project studies hardware and software enablers\, such as novel computational paradigms or the role of digital twins in supporting the AI-AI techniques. Last\, but not least\, methods for validation and benchmarking of the studied AI-AI techniques are as well in CENTRIC’s scope. \nIn the demo at EUCNC 2024 | 6G Summit 2024\, we showcase how the NVIDIA’s Neural receiver concept can be used to produce receiver structures that are specially optimized for a specific site deployment. On the one hand\, we show that the neural receiver structure can be trained with standardized stochastic channel models\, providing significant gains with respect to traditional MIMO receivers. However\, the neural receiver can be fine-tuned with a limited amount of data obtained at the base-station’s deployment site\, boosting its performance beyond that of the generically trained receiver. \nThis demo showcases a hardware-based validation setup for a neural-network based receiver for multi-user MIMO transmissions through a real 5G O-RAN network\, which consist of the following elements: \n \nThe signal generator (1) sends uplink signals of 2 single-antenna. The signal then travels through the channel emulator (2)\, which is fed ray-traced channel impulse responses observed at a particular base station location\, calculated with NVIDIA’s Sionna ray-tracer. The signal is received at an O-RU (3) with 4 antennas which digitizes the signals and delivers them to the O-DU emulator (4)\, which manages the O-RU’s control plane and synchronization. The O-RU’s data is fed to the PC (5) which runs NVIDIA’s 6G Neural Receiver to extract the payload by applying a pretrained neural network. The demo shows the advantage of the Neural receiver over classical benchmark\, as well as demonstrating the performance improvement resulting from fine-tuning the pre-trained network with a small amount of data obtained at the deployment site.
URL:https://centric-sns.eu/event/centric-will-be-present-at-the-eucnc-6g-summit-2024/
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20240609
DTEND;VALUE=DATE:20240614
DTSTAMP:20260530T095620
CREATED:20240607T095337Z
LAST-MODIFIED:20240610T073257Z
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SUMMARY:IEEE International Conference on Communications 2024
DESCRIPTION:🕒  < 1 minIEEE International Conference on Communications 2024 \nBetween the 9th and 13th of June 2024\, Septimia Sarbu\, Postdoctoral researcher at the University of Oulu and part of the CENTRIC project\, will travel to Denver\, Colorado\, USA to present her paper entitled “On scaling latency-aware MAC communication protocols with a hierarchical network topology”\, authors Septimia Sarbu\, Mateus P. Mota\, Mehdi Bennis\, scheduled in the session WC-6: AI for Communications II on the Tuesday\, June 11\, 2024\, 11:30 MDT until 13:00 (3rd paper) (18 min.) \n  \nAbout the event: \nIEEE ICC 2024 will focus on “Scaling the Peaks of Global Communications“. They will feature a comprehensive high-quality technical program including 13 symposia and a variety of tutorials and workshops.  IEEE ICC 2024 will also include an attractive industry program aimed at practitioners\, with keynotes and panels from prominent research\, industry and government leaders\, business and industry panels\, and technological exhibits. \nKey information:  \n\nDates: 9–13 June 2024\, Denver\, CO\, USA\nSession time: Tuesday 11 June\, 11:30 – 13:00 MDT\nRoom: Director’s Row E\, Lobby Level\nEvent website: https://icc2024.ieee-icc.org/
URL:https://centric-sns.eu/event/ieee-international-conference-on-communications-2024/
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BEGIN:VEVENT
DTSTART;TZID=UTC:20240626T140000
DTEND;TZID=UTC:20240626T150000
DTSTAMP:20260530T095620
CREATED:20240620T080558Z
LAST-MODIFIED:20240620T081547Z
UID:20212-1719410400-1719414000@centric-sns.eu
SUMMARY:CENTRIC & 6G-SHINE participation in the webinar "Radio Resource Management for 6G in-X Subnetworks"
DESCRIPTION:🕒  < 1 min[vc_row][vc_column][vc_column_text css=”.vc_custom_1718871165178{margin-bottom: 0px !important;}”]\n\nDate: 26 June 2024\nTime: at 14:00 CEST Geneva | 08:00-09:00 EDT\, New York | 20:00-21:00 CST\, Beijing\nDuration: 1 hour (including 20 minutes networking)\nProgramme stream: Discovery – AI/ML in 5G\nTopics: 6G\n\n[/vc_column_text][vc_btn title=”REGISTER HERE” color=”warning” align=”center” css=”” link=”url:https%3A%2F%2Faiforgood.itu.int%2Fevent%2Fradio-resource-management-for-6g-in-x-subnetworks%2F|target:_blank”][vc_column_text css=”.vc_custom_1718871043335{margin-bottom: 0px !important;}”]Radio resource management (RRM) involves selecting key transmission parameters—such as transmit power\, frequency resources\, precoder\, and modulation. The complexity of this process is expected to increase significantly with the tenfold densification anticipated in 6G networks compared to 5G. The concept of in-X subnetworks has been introduced as a further leap of heterogeneous network\, with the aim of providing highly localized wireless coverage for use cases such as in-robot\, in-production module\, in-vehicle\, in-room communication. These subnetworks are expected to support diverse services\, possibly extreme requirements in terms of ultra-short control cycle time\, reliability\, and service availability\, surpassing the capabilities of 5G and its evolution.  \nWhile the specific characteristics of in-X subnetworks can offer opportunities for efficient radio design\, interference can be a major limiting factor in dense deployments. Subnetworks may be then characterized by such high density (e.g.\, vehicles in a congested road\, robots in matrix production)\, and they can also be mobile\, leading to rapid interference fluctuations. These aspects may result in wide and rapidly fluctuating interference patterns\, which make the RRM problem more challenging than in traditional wireless setups\, characterized by static base stations/access points and lower cell densities.  \nThe radio resource management problem is usually non-convex with NP-hardness\, while traditional optimization methods and heuristics have shown efficacy in certain scenarios\, these algorithms have exponential computational complexity and typically require many iterations. The dynamic and complex environment of In-X subnetworks\, coupled with stringent low latency requirements\, calls for more adaptive solutions with lower computational complexity. This necessity is driving the adoption of advanced artificial intelligence (AI) solutions. This challenge\, supported by two EU SNS JU projects\, 6G-SHINE and CENTRIC\, focuses on developing machine learning-based solutions for optimizing sub-band allocation and power control within dense in-factory subnetworks.  \nThis live event includes a 20-minute networking event hosted on the AI for Good Neural Network. This is your opportunity to ask questions\, interact with the panelists and participants and build connections with the AI for Good community.[/vc_column_text][/vc_column][/vc_row]
URL:https://centric-sns.eu/event/centric-6g-shine-participation-in-the-webinar-radio-resource-management-for-6g-in-x-subnetworks/
LOCATION:Online
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