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X-WR-CALNAME:Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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TZID:Asia/Hong_Kong
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DTSTART;TZID=Asia/Hong_Kong:20260416T100000
DTEND;TZID=Asia/Hong_Kong:20260416T110000
DTSTAMP:20260511T035356
CREATED:20260323T025207Z
LAST-MODIFIED:20260323T025207Z
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SUMMARY:RPG Seminar – Evolving LEO Satellite Constellations into Multi-Service Platforms
DESCRIPTION:Abstract\nLow Earth orbit (LEO) satellite constellations offer global communication capabilities\, yet fundamental system challenges restrict their full utility. Specifically\, under increasing user demands\, these networks face difficulties in optimizing internal traffic distribution and efficiently delivering advanced content services. Furthermore\, seamlessly integrating space-based infrastructure with terrestrial systems to ensure resilient operations remains an unresolved issue. Solving these challenges is required to transition LEO constellations from basic connectivity relays into integrated service platforms. \nThis presentation explores optimization and extension strategies for evolving LEO satellite networks. Focusing first on the internal constellation network\, we begin with Matchmaker to address traffic distribution challenges through effective load balancing to enhance network performance. To ensure quality of service (QoS) in large-scale constellations\, an efficient heuristic algorithm that minimizes maximum satellite utilization and handovers is proposed. With this optimized network foundation\, we elevate the constellation’s capabilities through SpaceCache+\, transforming it into a space-based content delivery network (CDN). SpaceCache+ deploys cache-equipped satellites and optimizes cache replacement by managing dynamic coverage and regional preferences through zero-shot meta-learning and spatial-temporal mixing. Having expanded the constellation’s internal capacity\, we finally project its utility outward to assist terrestrial infrastructure via SpaceHelper. This work integrates satellite resources with terrestrial software-defined wide area networks (SD-WANs) to construct a resilient out-of-band control plane\, ensuring rapid reconnection during terrestrial link failures. Together\, these works illustrate a continuous system evolution\, advancing LEO networks from basic Internet access to comprehensive space-based multi-service platforms. \nSpeaker\nMr Dou Songshi\nDepartment of Electrical and Computer Engineering\nThe University of Hong Kong \nBiography of the Speaker\nSongshi Dou received B.E. degree from North China Electric Power University\, Beijing\, China\, in 2019\, and M.E. degree from Beijing Institute of Technology\, Beijing\, China\, in 2022. He is currently pursuing Ph.D. degree at The University of Hong Kong\, Hong Kong SAR\, China. His research interests cover satellite Internet\, software-defined networking\, and traffic engineering. \nOrganiser\nProf. Lawrence K. Yeung\nDepartment of Electrical and Computer Engineering\, The University of Hong Kong \nAll are welcome.
URL:https://ece.hku.hk/events/20260416/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/11/rpg-seminar.jpg
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DTSTART;TZID=Asia/Hong_Kong:20260416T110000
DTEND;TZID=Asia/Hong_Kong:20260416T120000
DTSTAMP:20260511T035356
CREATED:20260413T041830Z
LAST-MODIFIED:20260413T042149Z
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SUMMARY:Seminar on Machine Learning for Integrated Sensing and Communication
DESCRIPTION:Abstract\nIntegrated sensing and communication (ISAC) is a key technology for the sixth-generation (6G) wireless networks\, where the same spectral and hardware resources are used for both communication and environmental sensing. Many optimization problems in ISAC require accurate sensing and communication channel models\, which are often difficult to obtain. Machine learning (ML) is a powerful tool for solving ISAC problems by enabling data-driven solutions that can bypass the reliance on explicit models. This talk will explore how ML techniques can improve ISAC performance beyond traditional optimisation approaches. Two case studies will be discussed: sensing-assisted predictive beamforming and cooperative sensing through ML. These examples will demonstrate the potential of ML to enable end-to-end signal processing for ISAC in 6G wireless networks. \nSpeaker\nProf. Vincent WONG\nProfessor\,\nDepartment of Electrical and Computer Engineering\,\nUniversity of British Columbia\, Vancouver\, Canada \nSpeaker’s Biography\nVincent WONG is a Professor in the Department of Electrical and Computer Engineering at the University of British Columbia\, Vancouver\, Canada. His research areas include protocol design\, optimisation\, and resource management of communication networks\, with applications to the Internet\, wireless networks\, smart grid\, mobile edge computing\, and Internet of Things. Dr. Wong is the Editor-in-Chief of the IEEE Transactions on Wireless Communications. He is a Fellow of the IEEE\, Canadian Academy of Engineering\, and the Engineering Institute of Canada. \nOrganisers\nProf. Kaibin HUANG & Prof. Xianhao CHEN\nDepartment of Electrical and Computer Engineering\,\nThe University of Hong Kong\n\nAll are welcome!
URL:https://ece.hku.hk/events/20260416-2/
LOCATION:Room CB-601J\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2026/04/1280-2.jpg
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