6 accepted papers
In this paper, we propose deep-unfolded versions of the recently proposed superiorized adaptive projected subgradient method for MIMO detection. The proposed methods require a single matrix inverse for initialization, and they have a quadratic per-iteration complexity. Extensive simulations with rea…
In this paper, we propose a set-theoretic framework for MIMO detection. Various low-complexity MIMO detection algorithms achieve excellent performance on i.i.d. Gaussian channels, but they typically incur high performance loss if realistic channel models are considered. Compared to existing low-comp…
Channel charting (CC) is an emerging machine learning framework that aims at learning lower-dimensional representations of the radio geometry from collected channel state information (CSI) in an area of interest, such that spatial relations of the representations in the different domains are preserv…
Consider an Internet-of-Things (IoT) system that monitors a number of multi-valued events through multiple sensors sharing the same bandwidth. Each sensor measures data correlated to one or more events, and communicates to the fusion center at a base station using grant-free random access whenever t…
While most of the theoretical aspects of physical layer security are well understood, practical applications lag substantially behind theoretical advances. As a step towards the integration of physical-layer security aspects in the radio access system design, the concept of secrecy maps has been rec…
This paper presents a Bayesian nonparametric latent feature model specially suitable for exploratory analysis of high-dimensional count data. We perform a non-negative doubly sparse matrix factorization that has two main advantages: not only we are able to better approximate the row input distributi…