| Paper ID | SPTM-24.6 |
| Paper Title |
A PARALLEL ALGORITHM FOR PHASE RETRIEVAL WITH DICTIONARY LEARNING |
| Authors |
Tianyi Liu, Technische Universitaet Darmstadt, Germany; Andreas M. Tillmann, Technische Universität Braunschweig, Germany; Yang Yang, Fraunhofer ITWM, Germany; Yonina C. Eldar, Weizmann Institute of Science, Israel; Marius Pesavento, Technische Universitaet Darmstadt, Germany |
| Session | SPTM-24: Sparsity-aware Processing |
| Location | Gather.Town |
| Session Time: | Friday, 11 June, 14:00 - 14:45 |
| Presentation Time: | Friday, 11 June, 14:00 - 14:45 |
| Presentation |
Poster
|
| Topic |
Signal Processing Theory and Methods: [SMDSP-SAP] Sparsity-aware Processing |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
We propose a new formulation for the joint phase retrieval and dictionary learning problem with a reduced number of regularization parameters to be tuned. A parallel algorithm based on the block successive convex approximation framework is developed for the proposed formulation. The performance of the algorithm is evaluated when applied to sparse channel estimation in a multi-antenna random access network. Simulation results on synthetic data show the efficiency of the proposed technique compared to the state-of-the-art method. |
