Tareq Y. Al-Naffouri - Associate Professor at the Electrical Engineering Department at King Abdullah University of Science & Technology (KAUST) and jointly at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia Communication systems
Date: - Location: Eurecom
Distribution Agnostic Structured Sparsity Recovery: Algorithms and Applications There has been increased interest in sparse signal reconstruction algorithms (commonly known as compressed sensing) due to their wide applicability in various fields. Recently, focus has shifted to Bayesian based approaches that are able to perform sparse recovery at much lower complexity while invoking constraint and/or a priori information about the data. In this talk we introduce a Bayesian algorithm which is able to deal with sparse signals with non-Gaussian or unknown distributions. The talk will also introduce variants of this algorithm that deal with various sparsity structures. The discussion will be illuminated with various applications including impulse noise cancellation, Narrowband interference cancellation, feedback reduction in Broadcast channels, and massive MIMO.
