… decoding reducesmuch complexity on the low-rate codes compared with the existing sphere
decoding … At high signal-to-noise ratios, the latency of the proposed decoding is comparable …

… of a deep learning approach. This paper presents a deep learning based sphere decoder
to … A deep learning-based sphere decoder is presented using 16 × 16 MIMO system for 16 …

… Since the deep learning is employed on top of the proposed NC-RD algorithm, in the following,
we will firstly introduce the NC-RD algorithm. Specifically, compared to the conventional …

… new approach that combines effective machine learning tools from persistent homology and
convolutional neural networks (CNNs) is proposed to decode the OAM modes. A Gaussian …

… MIMO decoding schemes are complex, impractical, and perform poorly for massive multiple-input
multiple-output (M-MIMO) systems. Deep learning (… MIMO decoder using a deep neural …

… Recent works [30], [31] exploit deep learning in order to compute the IR in … on sphere
decoding are described. For constant throughput and complexity, fixed-complexity sphere decoder (…

… In this paper, an efficient software stack sphere decoder (ESSD) based on synchronous
determination is firstly proposed to reduce complexity. The ESSD limits the growth of …

… designed before being processed by the decoder (example: intersymbol equalization in
cable modems, beamforming and sphere decoding in multiple antenna wireless systems); again …

… decoder (example: intersymbol equalization in cable modems, beamforming and sphere
decoding … Deep learning is fast emerging as capable of learning sophisticated algorithms from …

… sphere decoders using urn:x-wiley:10745351:media:dac5081:dac5081-math-0003 best
algorithm by modifying the conventional sphere decoders … deep learning aided sphere decoder (…