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学术活动
Leveraging A Variety of Anchors in Cellular Network for Ubiquitous Sensing
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报告人:
Liang Liu, Professor, The Hong Kong Polytechnic University
邀请人:
Yafeng Liu, Associate Professor
题目:
Leveraging A Variety of Anchors in Cellular Network for Ubiquitous Sensing
时间地点:
15:00-16:00 May 9 (Thursday) , Z311
摘要:

Integrated sensing and communication (ISAC) has recently attracted tremendous attention from both academia and industry, being envisioned as a key part of the standards for the sixth-generation (6G) cellular network. A key challenge of 6G-oriented ISAC lies in how to perform ubiquitous sensing based on the communication signals and devices. Previous works have made great progresses on studying the signal waveform design that leads to optimal communication-sensing performance tradeoff. In this talk, we aim to focus on issues arising from the exploitation of the communication devices for sensing in 6G network. Particularly, we will discuss about how to leverage various nodes available in the cellular network, including base stations, reconfigurable intelligent surfaces, and user equipments, as anchors to perform ubiquitous sensing. The advantages and disadvantages of each type of anchors will be discussed, and the possible solutions to overcome these disadvantages will be outlined.  

Bio: Liang Liu is currently an Assistant Professor with the Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University. He was a recipient of the 2021 IEEE Signal Processing Society Best Paper Award, the 2017 IEEE Signal Processing Society Young Author Best Paper Award, the Best Student Award of of 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), and the Best Paper Award of the 2011 International Conference on Wireless Communications and Signal Processing. He was recognized by Clarivate Analytics as a Highly Cited Researcher in 2018. He is an Editor of IEEE Transactions on Wireless Communications. He was a Leading Guest Editor of IEEE Wireless Communications Special Issue on Massive Machine-Type Communications for IoT.