most citedExplicit CSI Feedback Compression via Learned Approximate Message Passing

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.IT2021

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…

eess.SP20211 cited

Explicit CSI Feedback Compression via Learned Approximate Message Passing

Benedikt Groß, Rana Ahmed Salem, Thorsten Wild +1

Explicit channel state information at the transmitter side is helpful to improve downlink precoding performance for multi-user MIMO systems. In order to reduce feedback signalling…

cs.IT2021

Measure Concentration on the OFDM-based Random Access Channel

Gerhard Wunder, Axel Flinth, Benedikt Groß

It is well known that CS can boost massive random access protocols. Usually, the protocols operate in some overloaded regime where the sparsity can be exploited. In this paper, we…

cs.IT2021

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…

cs.IT2020

WiFi-Based Channel Impulse Response Estimation and Localization via Multi-Band Splicing

Mahdi Barzegar Khalilsarai, Benedikt Gross, Stelios Stefanatos +2

Using commodity WiFi data for applications such as indoor localization, object identification and tracking and channel sounding has recently gained considerable attention. We study…