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eess.SP2022
GPU-Accelerated Machine Learning in Non-Orthogonal Multiple Access
Daniel Schäufele, Guillermo Marcus, Nikolaus Binder +3
Non-orthogonal multiple access (NOMA) is an interesting technology that enables massive connectivity as required in future 5G and 6G networks. While purely linear processing alread…
eess.SP2022
GPU-accelerated partially linear multiuser detection for 5G and beyond URLLC systems
Matthias Mehlhose, Guillermo Marcus, Daniel Schäufele +6
In this feasibility study, we have implemented a recently proposed partially linear multiuser detection algorithm in reproducing kernel Hilbert spaces (RKHSs) on a GPU-accelerated…