Intelligent Waveform Design and Channel Modeling Using Group Theoretic Weyl-Heisenberg Frames

This theoretical work presents properties of Weyl-Heisenberg frames as they are used in the characterization of the cross-ambiguity function (CAF) which is an essential tool in the development of integrated wireless sensing and communications techniques. In essence, the work concretely formulates a relation between Weyl-Heisenberg (WH) frames and CAF operators when dealing with multicarrier sensing and communications operations. The work describes how features extracted from WH frames support machine learning (ML) models for intelligent waveform design and wireless channel modeling for emerging integrated sensing and communication (ISAC) systems, sharing the same spectrum, in beyond fifth generation (B5G) wireless networks.