4 accepted papers
Gaussian Mixture Models (GMMs) commonly arise in communication systems, particularly in bilinear joint estimation and detection problems. Although the product of GMMs is still a GMM, as the number of factors increases, the number of components in the resulting product GMM grows exponentially. To obt…
In this work, we study uplink communication in cell-free (CF) massive multiple-input multiple-output (MaMIMO) systems, a promising architecture for next-generation networks. To address the challenge of pilot contamination, we employ semi-blind transmission structures that enable joint channel and da…
When derived from the Bethe Free Energy (BFE) of the Generalized Linear Model (GLM), Approximate Message Passing (AMP) algorithms combine two asymptotic Large System Limit (LSL) simplifications which are asymptotic Gaussianity of extrinsics and large random matrix theory based asymptotic variance co…
Many signal processing problems involve a Generalized Linear Model (GLM), which is a type of linear model where the unknowns may be non-identically independently distributed (n.i.i.d.). Vector Approximate Message Passing for Generalized Linear Models (GVAMP) is a computationally efficient belief pro…