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20162023
most citedTheoretical Interpretation of Learned Step Size in Deep-Unfolded Gradient Descent

9 citations · 30 across the 14 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.IT2019★ 1 cited

Trainable Projected Gradient Detector for Sparsely Spread Code Division Multiple Access

Satoshi Takabe, Yuki Yamauchi, Tadashi Wadayama

Sparsely spread code division multiple access (SCDMA) is a promising non-orthogonal multiple access technique for future wireless communications. In this paper, we propose a novel…

cs.IT2019

Compute-and-forward relaying with LDPC codes over QPSK scheme

Satoshi Takabe, Tadashi Wadayama, Ángeles Vazquez-Castro +1

In this paper, we study a compute-and-forward (CAF) relaying scheme with low-density parity-check (LDPC) codes, a special case of physical layer network coding, under the quadratur…

cs.IT2019

Complex Trainable ISTA for Linear and Nonlinear Inverse Problems

Satoshi Takabe, Tadashi Wadayama, Yonina C. Eldar

Complex-field signal recovery problems from noisy linear/nonlinear measurements appear in many areas of signal processing and wireless communications. In this paper, we propose a t…

cs.IT2019

Asymptotic Analysis on LDPC-BICM Scheme for Compute-and-Forward Relaying

Satoshi Takabe, Tadashi Wadayama, Masahito Hayashi

The compute-and-forward (CAF) scheme has attracted great interests due to its high band-width efficiency on two-way relay channels. In the CAF scheme, a relay attempts to decode a…

cs.IT2019★ 6 cited

Deep Learning-Aided Trainable Projected Gradient Decoding for LDPC Codes

Tadashi Wadayama, Satoshi Takabe

We present a novel optimization-based decoding algorithm for LDPC codes that is suitable for hardware architectures specialized to feed-forward neural networks. The algorithm is ba…