11 citations · 15 across the 4 of their papers we have counts for
6 papers · 1 filter
Guaranteed blind deconvolution and demixing via hierarchically sparse reconstruction
Axel Flinth, Ingo Roth, Benedikt Groß +2
The blind deconvolution problem amounts to reconstructing both a signal and a filter from the convolution of these two. It constitutes a prominent topic in mathematical and enginee…
Hierarchical sparse recovery from hierarchically structured measurements with application to massive random access
Benedikt Groß, Axel Flinth, Ingo Roth +2
A new family of operators, coined hierarchical measurement operators, is introduced and discussed within the well-known hierarchical sparse recovery framework. Such operator is a c…
Performance of Hierarchical Sparse Detectors for Massive MTC
Gerhard Wunder, Ingo Roth, Rick Fritschek +1
Recently, a new class of so-called \emph{hierarchical thresholding algorithms} was introduced to optimally exploit the sparsity structure in joint user activity and channel detecti…
Low-Overhead Hierarchically-Sparse Channel Estimation for Multiuser Wideband Massive MIMO
Gerhard Wunder, Stelios Stefanatos, Axel Flinth +2
The problem of excessive pilot overhead required for uplink massive MIMO channel estimation is well known, let alone when it is considered along with wideband (OFDM) transmissions.…
Hierarchical Sparse Channel Estimation for Massive MIMO
Gerhard Wunder, Ingo Roth, Axel Flinth +4
The problem of wideband massive MIMO channel estimation is considered. Targeting for low complexity algorithms as well as small training overhead, a compressive sensing (CS) approa…
Hierarchical restricted isometry property for Kronecker product measurements
I. Roth, A. Flinth, R. Kueng +2
Hierarchically sparse signals and Kronecker product structured measurements arise naturally in a variety of applications. The simplest example of a hierarchical sparsity structure…