Abstract: In this talk we study the capacity of interference-limited channels with memory. These channels model non-orthogonal communications scenarios, such as the non-orthogonal multiple access (NOMA) scenario and underlay cognitive communications, in which the interference from other communications signals is much stronger than the thermal noise. As communications signals are inherently cyclostationary in continuous time (CT), then, after sampling at the receiver, the discrete-time (DT) received signal model contains the sampled desired information signal with additive sampled CT cyclostationary noise. We first explain why the sampled noise can be modeled either as a DT cyclostationary process with memory or a DT almost-cyclostationary process with memory, where the latter case results in a channel which is not information-stable. Thus, analyzing this model requires the development of a new approach for channels with additive non-stationary noise which has memory. Our results show, for the first time, the relationship between memory, sampling frequency synchronization and capacity, for interference-limited communications. The insights from our work provide a link between the analog and digital time domains, which has been missing in most previous works on capacity analysis. We also discuss related results on NN-aided network clock synchronization motivated by these results, and subsequent work on source coding for such processes.
Bio: Ron Dabora received the B.Sc. and M.Sc. degrees in electrical engineering from Tel-Aviv University in 1994 and 2000, respectively, and the Ph.D. degree in electrical engineering from Cornell University, USA, in 2007. From 1994 to 2000, he was with the Ministry of Defense of Israel, and from 2000 to 2003, he was with the Algorithms Group, Millimetrix Broadband Networks, Israel. From 2007 to 2009, he was a Post-Doctoral Researcher with the Department of Electrical Engineering, Stanford University, USA. Since 2009, he has been with the School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Israel, where he is currently an Associate Professor. From 2022 he has been a Visiting Fellow with the Department of Electrical Engineering, Princeton University, USA. His research interests include network information theory, wireless communications, power line communications, and machine learning. He served as a TPC Member for several international conferences, including WCNC, PIMRC, and ICC. From 2012 to 2014, he served as an Associate Editor for the IEEE Signal Processing Letters. From 2014 to 2019, he served as a Senior Area Editor for the IEEE Signal Processing Letters.