Signal Design for Future Wireless Communications: Green, Multi-Functional, and AI Native
Overview
Future wireless communication systems are equipping more and more antennas for high spectral efficiency with increasing the number of power-hungry radio frequency (RF) chains. Can we increase the number of antennas with a fixed number of RF chains? How much performance gain can it achieve and how to design the signals to achieve its limit? Integrated sensing is expected to be featuring technology and enabling technology for 6G wireless communication networks. The waveform representing different bits needs to be as separable as possible, while that for sensing targets needs to be as deterministic as possible. How to characterize the conflict and trade-off between communications and sensing when they are integrated within the same waveform? Existing wireless communications are originally designated for signal/data recovery, not for signal/data specific usage. The fast development of artificial intelligence (AI) enables diverse data usage for various tasks. How can we design signals for task-oriented and data-aware wireless communications? How can we design more efficient communication signals between a human and an AI agent, and between two AI agents? In this talk, the speaker will give his research on signal designs for green multiple-antenna communication systems with a limited number of RF chains, signal designs for future wireless communications integrating sensing, and signal designs for benefiting remote AI inference beyond signal recovery.
Presenters
Shuaishuai Guo, Shandong University, China
Brief Biography
Shuaishuai Guo was born in 1990 in the hometown of Confucius and Mencius. He received his B.E. and Ph.D. degrees in Communication and Information Systems from the School of Information Science and Engineering, Shandong University, Jinan, China, in 2011 and 2017, respectively. From 2016 to 2017, he was a visiting scholar at the University of Tennessee at Chattanooga (UTC), USA. He subsequently worked as a postdoctoral research fellow at King Abdullah University of Science and Technology (KAUST), Saudi Arabia, from 2017 to 2019. In 2024, he was a visiting scholar at EURECOM, France. Currently, he is a full professor at Shandong University. Dr. Guo’s research interests encompass LLM-enabled AI agent, intelligent communications, and integrated sensing and communications. He has published more than 80 research papers, including over 40 articles in IEEE journals. He serves as an Associate Editor for the IEEE Open Journal of Vehicular Technology and Frontiers in Communication and Networking. Additionally, he is a Youth Editorial Board Member of the Journal of Communications.
