BEHAVIORAL MODEL AND PREDISTORTER FOR MODELING AND REDUCING NONLINEAR EFFECTS IN POWER AMPLIFIERS

Patent №

US 9,837,970

Granted

2017-12-05

Filed 2016

Owner

KING FAHD UNIVERSITY OF PETROLEUM AND MINERALS

Lab

AI components

4

ml · planning · evo · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

15061954

The behavioral model and predistorter for modeling and reducing nonlinear effects in power amplifiers addresses the model size estimation problem. The GMP model is replaced by the hybrid memory polynomial/envelope memory polynomial (HMEM) model within a twin nonlinear two-box structure to reduce the number of variables involved in the model size estimation problem, without compromising model accuracy and digital predistorter performance. A sequential approach is presented to efficiently estimate the model size. Experimental validation is carried out to evaluate the performance of the size estimation and the accuracy of the HMEM-based twin-nonlinear two-box model with respect to that of the GMP-based twin-nonlinear two-box model.

Machine learningPlanningEvolutionary computationAI hardwareH03F 1/3258H03F 3/24H04B 1/0475H03F 2200/102H03F 2201/3224H03F 2201/3233H04B 2001/0408

AI classification

AI hardware0.94
Evolutionary computation0.88
Machine learning0.77
Planning0.71
Speech0.17
Vision0.01
Natural language0.00
Knowledge representation0.00

Ownership

KING FAHD UNIVERSITY OF PETROLEUM AND MINERALS

assignment · 385680892

Assignors

HAMMI, OUALID, DR., KHAN, MOHAMMED HANZALA SULEMAN

On an employer assignment, the assignors are typically the inventors.

From the same owner

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