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US20220416937A1

Autoencoder-based error correction coding for low-resolution communication

University of Texas System

Abstract

Various embodiments of the present technology provide a novel deep learning-based error correction coding scheme for AWGN channels under the constraint of moderate to low bit quantization (e.g., one-bit quantization) in the receiver. Some embodiments of the error correction code minimize the …

University
University of Texas System
Assignee
Board Of Regents, The University Of Texas System
Inventor
Jeffrey G. Andrews
Priority date
August 26, 2019
Filing date
August 26, 2020
Publication date
December 29, 2022
Language
en
Metadata fetched
August 29, 2026 00:29