MCM OFDM using sparse signals

We describe our initial approach to MCM OFDM that uses entropy-based signal models to provide a sparse, efficient set of codes. Specifically, we consider applying a set of sparse orthogonal signals developed precisely to solve the space-time uncertainty of the Hirschman Uncertainty (itself a generalization of the Heisenberg Uncertainty) for finite-duration discrete time signals. These signals were in part developed by one of the authors, and primarily used in both linear and non-linear adaptive filtering. Recently, that author has begun to use those elements to develop high-resolution spectral estimation methods for the stationary environment. In this paper, we begin to apply these results to one of the most basic communications strategies.