SS-11.2
SYMBOL-LEVEL ONLINE CHANNEL TRACKING FOR DEEP RECEIVERS
Ron Aharon Finish, Yoav Cohen, Tomer Raviv, Nir Shlezinger, Ben-Gurion University of the Negev, Israel
Session:
Graph-based Deep Learning for Communications
Track:
Special Sessions
Location:
Gather Area A
Presentation Time:
Wed, 11 May, 21:00 - 21:45 China Time (UTC +8)
Wed, 11 May, 13:00 - 13:45 UTC
Wed, 11 May, 13:00 - 13:45 UTC
Session Co-Chairs:
Santiago Segarra, Rice University and Mark Eisen, Intel Corporation
Session SS-11
SS-11.1: USER SCHEDULING USING GRAPH NEURAL NETWORKS FOR RECONFIGURABLE INTELLIGENT SURFACE ASSISTED MULTIUSER DOWNLINK COMMUNICATIONS
Zhongze Zhang, Tao Jiang, Wei Yu, University of Toronto (St. George), Canada
SS-11.2: SYMBOL-LEVEL ONLINE CHANNEL TRACKING FOR DEEP RECEIVERS
Ron Aharon Finish, Yoav Cohen, Tomer Raviv, Nir Shlezinger, Ben-Gurion University of the Negev, Israel
SS-11.3: DELAY-ORIENTED DISTRIBUTED SCHEDULING USING GRAPH NEURAL NETWORKS
Zhongyuan Zhao, Santiago Segarra, Rice University, United States of America; Gunjan Verma, Ananthram Swami, US Army’s DEVCOM Army Research Laboratory, United States of America
SS-11.4: FLOWDT: A FLOW-AWARE DIGITAL TWIN FOR COMPUTER NETWORKS
Miquel Ferriol-Galmés, Pere Barlet-Ros, Albert Cabellos-Aparicio, Universitat Politècnica de Catalunya, Spain; Xiangle Cheng, University of Exeter, United Kingdom of Great Britain and Northern Ireland; Xiang Shi, Shihan Xiao, Huawei Technologies, China
SS-11.5: STABLE AND TRANSFERABLE WIRELESS RESOURCE ALLOCATION POLICIES VIA MANIFOLD NEURAL NETWORKS
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro, University of Pennsylvania, United States of America; Mark Eisen, Intel Labs, United States of America
SS-11.6: Joint Source-Channel Coding for Semantics-Aware Grant-Free Radio Access in IoT Fog Networks
Johannes Dommel, Zoran Utkovski, Slawomir Stanczak, Fraunhofer Heinrich-Hertz-Institute, Germany; Osvaldo Simeone, King’s College London, Germany