I/Q-based Beam Classification with the DeepBeam Dataset | AI/ML IN 5G CHALLENGE
0This talk introduces the problem statement “I/Q-based Beam Classification with the DeepBeam Dataset” for the 2022 ITU AI/ML in 5G Challenge. Learn how to leverage the DeepBeam dataset and (if needed) the DeepBeam codebase to develop ML/DL models that improve the classification accuracy, while reducing the number of samples that are required for the classification. \n\nHighly directional millimeter wave (mmWave) radios need to perform beam management to establish and maintain reliable links. To achieve this objective, existing solutions mostly rely on explicit coordination between the transmitter (TX) and the receiver (RX), which significantly reduces the airtime available for communication and further complicates the network protocol design. In previous work, we proposed a new approach based on convolutional neural networks (CNNs) for the detection of the transmit beam used by the TX, and the angle of arrival at the RX side. In this way, the RX can associate Signal-to-Noise-Ratio (SNR) levels to beams without explicit coordination with the TX. DeepBeam thus does not require pilot sequences from the TX, nor any beam sweeping or synchronization from the RX. This is possible because different beam patterns introduce different “impairments” to the waveform, which can be subsequently learned by a CNN.\n\nOpening remarks:\nThomas Basikolo, Young Expert - AI/ML, International Telecommunication Union (ITU)\n\nModerator:\nVishnu Ram OV, Independent Research Consultant, International Telecommunication Union (ITU)\n\nSpeaker:\nMichele Polese, Principal Research Scientist, Northeastern University\n\n\nJoin the Neural Network! \nhttps://aiforgood.itu.int/neural-network/\nThe AI for Good networking community platform powered by AI. \nDesigned to help users build connections with innovators and experts, link innovative ideas with social impact opportunities, and bring the community together to advance the SDGs using AI.\n\n Watch the latest #AIforGood videos!\n\n\nExplore more #AIforGood content:\n AI for Good Top Hits\n • Top Hits \n\n AI for Good Webinars\n • AI for Good Webinars \n\n AI for Good Keynotes\n • AI for Good Keynotes \n\n Stay updated and join our weekly AI for Good newsletter:\nhttp://eepurl.com/gI2kJ5\n\n Discover what's next on our programme!\nhttps://aiforgood.itu.int/programme/\n\nCheck out the latest AI for Good news:\nhttps://aiforgood.itu.int/newsroom/\n\nExplore the AI for Good blog:\nhttps://aiforgood.itu.int/ai-for-good-blog/\n\n Connect on our social media:\nWebsite: https://aiforgood.itu.int/\nTwitter: https://twitter.com/ITU_AIForGood\nLinkedIn Page: https://www.linkedin.com/company/26511907 \nLinkedIn Group: https://www.linkedin.com/groups/8567748 \nInstagram: https://www.instagram.com/aiforgood \nFacebook: https://www.facebook.com/AIforGood\n\nWhat is AI for Good?\nThe AI for Good series is the leading action-oriented, global & inclusive United Nations platform on AI. The Summit is organized all year, always online, in Geneva by the ITU with XPRIZE Foundation in partnership with over 35 sister United Nations agencies, Switzerland and ACM. The goal is to identify practical applications of AI and scale those solutions for global impact.\n\nDisclaimer:\nThe views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.\n\n#5gnetworks #machinelearning