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Capacity of Interference-Limited Channels with Memory

Ron Dabora (Ben-Gurion University)

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.