7 citations · 16 across the 5 of their papers we have counts for
5 papers
Bias Compensation in Iterative Soft-Feedback Algorithms with Application to (Discrete) Compressed Sensing
Susanne Sparrer, Robert F. H. Fischer
In all applications in digital communications, it is crucial for an estimator to be unbiased. Although so-called soft feedback is widely employed in many different fields of engine…
Low-Complexity Iterative Algorithms for (Discrete) Compressed Sensing
Robert F. H. Fischer, Susanne Sparrer
We consider iterative (`turbo') algorithms for compressed sensing. First, a unified exposition of the different approaches available in the literature is given, thereby enlightenin…
Unveiling Bias Compensation in Turbo-Based Algorithms for (Discrete) Compressed Sensing
Susanne Sparrer, Robert F. H. Fischer
In Compressed Sensing, a real-valued sparse vector has to be recovered from an underdetermined system of linear equations. In many applications, however, the elements of the sparse…
Algorithms for the Iterative Estimation of Discrete-Valued Sparse Vectors
Susanne Sparrer, Robert F. H. Fischer
In Compressed Sensing, a real-valued sparse vector has to be estimated from an underdetermined system of linear equations. In many applications, however, the elements of the sparse…
Discrete Sparse Signals: Compressed Sensing by Combining OMP and the Sphere Decoder
Susanne Sparrer, Robert F. H. Fischer
We study the reconstruction of discrete-valued sparse signals from underdetermined systems of linear equations. On the one hand, classical compressed sensing (CS) is designed to de…