Enhancing NextG with ML-based Multi-User Resource Scheduling
0Massive MIMO base stations, with their large number of antennas, can use beamforming to communicate with multiple users simultaneously on the same time and frequency resource. However, when user channels are highly correlated, this advantage can be diminished, significantly impacting the spectral efficiency of multi-user beamforming. As users move within a network cell, their channels vary across both time and frequency, which in turn affects their correlation with other users, leading to different optimal groupings of users depending on the specific time-frequency resource. Thus, to maximize spectral efficiency while maintaining fairness among users, the base station must carefully schedule users during each transmission interval. \n\nThe goal of this challenge is to develop machine learning-based algorithms to address the multi-user beamforming scheduling problem in practical settings. Given the considerable overhead associated with constantly measuring user channels in mobile environments, an efficient solution may need to work with partial or even stale channel data to schedule users effectively in upcoming periods. Thus, machine learning algorithms can be ideal for managing incomplete or old channel data and deriving effective user scheduling strategies that aim to maximize network throughput and fairness. \n\nIn this webinar, we will discuss this challenge in greater detail. We will present a baseline solution that assumes full channel knowledge, outline the available datasets, and explain the evaluation criteria for the challenge. This discussion aims to foster innovation in developing robust solutions for multi-user scheduling in massive MIMO systems. \n\nThe AI for Good Global Summit is the leading action-oriented United Nations platform promoting AI to advance health, climate, gender, inclusive prosperity, sustainable infrastructure, and other global development priorities. AI for Good is organized by the International Telecommunication Union (ITU) β the UN specialized agency for information and communication technology β in partnership with 40 UN sister agencies and co-convened with the government of Switzerland.\n\nJoin the Neural Network!\nπ https://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\nπ΄ Watch the latest #AIforGood videos!\n\n\nπ© Stay updated and join our weekly AI for Good newsletter:\nhttp://eepurl.com/gI2kJ5\n\nπ Check out the latest AI for Good news:\nhttps://aiforgood.itu.int/newsroom/\n\nπ± Explore the AI for Good blog:\nhttps://aiforgood.itu.int/ai-for-good-blog/\n\nπ Connect on our social media:\nWebsite: https://aiforgood.itu.int/\nTwitter: https://twitter.com/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\nDisclaimer:\nThe views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.