报告人简介：Zilong Liu is a Lecturer (tenured Assistant Professor) at the School of Computer Science and Electronics Engineering, University of Essex. He received his PhD (2014) from School of Electrical and Electronic Engineering, Nanyang Technological University (Singapore), and Master Degree (2007) in the Department of Electronic Engineering from Tsinghua University (China). From Jan. 2018 to Nov. 2019, he was a Senior Research Fellow at the Institute for Communication Systems (ICS), Home of the 5G Innovation Centre (5GIC), University of Surrey, where he studied the air-interface design of 5G communication networks (e.g., machine-type communications, V2X communications, 5G New Radio). His research lies in the interplay of coding, signal processing, and communications, with a major objective of bridging theory and practice.
He is a Senior Member of IEEE and an Associate Editor of IEEE TVT, WCL, TNNLS and Access. He has published 95 peer-reviewed journal papers including over 50 IEEE full papers (i.e., TIT, TSP, TCOM, TWC, TVT, JSAC, JSTSP). His research is/was generously supported by EPSRC, Royal Society, EU-H2020, Research Council of Norway and so on.
报告主题简介：Among many emerging vertical industries, connected autonomous vehicles (CAVs) building upon vehicle-to-everything (V2X) communication and networking are deemed to transform our travel experience with numerous far-reaching societal and economic benefits. In the first part of this talk, I will share our vision to 6G V2X communications by emphasizing enabling technologies, major challenges and significant opportunities. In particular, 6G V2X is expected to support reliable & massive vehicular connectivity at the moving speeds of 1000 km/h or higher and this, however, cannot be supported by the legacy communication systems. I will present a solution in the second part by a novel downlink vehicular communication system that combines orthogonal-time-frequency-space (OTFS) modulation and sparse code multiple access (SCMA). With the aid of orthogonal approximate message passing (OAMP), our key innovation is an iterative receiver with orthogonal estimation/decoding errors of two different signal domains.