235 citations · 345 across the 30 of their papers we have counts for
30 papers
Deep Unfolded Simulated Bifurcation for Massive MIMO Signal Detection
Satoshi Takabe
Multiple-input multiple-output (MIMO) is a key ingredient of next-generation wireless communications. Recently, various MIMO signal detectors based on deep learning techniques and…
Hubbard-Stratonovich Detector for Simple Trainable MIMO Signal Detection
Satoshi Takabe, Takashi Abe
Massive multiple-input multiple-output (MIMO) is a key technology used in fifth-generation wireless communication networks and beyond. Recently, various MIMO signal detectors based…
Proximal Decoding for LDPC-coded Massive MIMO Channels
Tadashi Wadayama, Satoshi Takabe
We propose a novel optimization-based decoding algorithm for LDPC-coded massive MIMO channels. The proposed decoding algorithm is based on a proximal gradient method for solving an…
Acceleration of Cooperative Least Mean Square via Chebyshev Periodical Successive Over-Relaxation
Tadashi Wadayama, Satoshi Takabe
A distributed algorithm for least mean square (LMS) can be used in distributed signal estimation and in distributed training for multivariate regression models. The convergence spe…
Convergence Acceleration via Chebyshev Step: Plausible Interpretation of Deep-Unfolded Gradient Descent
Satoshi Takabe, Tadashi Wadayama
Deep unfolding is a promising deep-learning technique, whose network architecture is based on expanding the recursive structure of existing iterative algorithms. Although convergen…
Deep Unfolded Multicast Beamforming
Satoshi Takabe, Tadashi Wadayama
Multicast beamforming is a promising technique for multicast communication. Providing an efficient and powerful beamforming design algorithm is a crucial issue because multicast be…