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US12126467B2

Low resolution OFDM receivers via deep learning

University of Texas System

Abstract

Various embodiments provide for deep learning-based architectures and design methodologies for an orthogonal frequency division multiplexing (OFDM) receiver under the constraint of one-bit complex quantization. Single bit quantization greatly reduces complexity and power consumption in the …

University
University of Texas System
Assignee
Board Of Regents, The University Of Texas System
Inventor
Jeffrey Andrews
Priority date
October 29, 2018
Filing date
February 03, 2023
Grant date
October 22, 2024
Publication date
October 22, 2024
Language
en
Metadata fetched
August 29, 2026 00:31