The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 26, 2023

Filed:

Sep. 19, 2022
Applicant:

The Research Foundation for the State University of New York, Binghamton, NY (US);

Inventors:

Xiaohua Li, Johnson City, NY (US);

Robert Thompson, Quakertown, PA (US);

Assignee:

The Research Foundation for SUNY, Binghamton, NY (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
H03H 7/30 (2006.01); H03H 7/40 (2006.01); H03K 5/159 (2006.01); H04L 25/03 (2006.01); H04B 1/16 (2006.01); H03F 3/20 (2006.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); H03F 1/32 (2006.01);
U.S. Cl.
CPC ...
H04L 25/03165 (2013.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); H03F 1/32 (2013.01); H03F 3/20 (2013.01); H04B 1/16 (2013.01); H03F 2200/451 (2013.01);
Abstract

The nonlinearity of power amplifiers (PAs) has been a severe constraint in performance of modern wireless transceivers. This problem is even more challenging for the fifth generation (5G) cellular system since 5G signals have extremely high peak to average power ratio. Nonlinear equalizers that exploit both deep neural networks (DNNs) and Volterra series models are provided to mitigate PA nonlinear distortions. The DNN equalizer architecture consists of multiple convolutional layers. The input features are designed according to the Volterra series model of nonlinear PAs. This enables the DNN equalizer to effectively mitigate nonlinear PA distortions while avoiding over-fitting under limited training data. The non-linear equalizers demonstrate superior performance over conventional nonlinear equalization approaches.


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