2007Computer Engineering and Applications JournalRequires access

High-efficient adaptive predistortion scheme for nonlinear power amplifier with memory

Liu Fu-qiang

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Abstract

Predistortion for nonlinear amplifier with memory always is very difficult.Traditional method using Volterra,Hammerstein and neural network model is not only complex,but their adaptation also not easy.High-efficient predistortion structure based on polynomial in memoryless predistortion is extended to memory predistortion by adding two-delay lines,and a simple polynomial model with tapped delay linear is used as the memory predistorter model.Combined the extended structure and the simple memory predistorter model can realize the linearization of the amplifier with memory.Simulation results demonstrated that the proposed scheme posses faster convergence and better linearization performance.

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What this paper is about

Predistortion for nonlinear amplifier with memory always is very difficult.Traditional method using Volterra,Hammerstein and neural network model is not only complex,but their adaptation also not easy.High-efficient predistortion structure based on polynomial in memoryless predistortion is extended to memory predistortion by adding two-delay lines,and a simple polynomial model with tapped delay linear is used as the memory predistorter model.Combined the extended structure and the simple memory predistorter model can realize the linearization of the amplifier with memory.Simulation results demonstrated that the proposed scheme posses faster convergence and better linearization performance.

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Available abstract

Predistortion for nonlinear amplifier with memory always is very difficult.Traditional method using Volterra,Hammerstein and neural network model is not only complex,but their adaptation also not easy.High-efficient predistortion structure based on polynomial in memoryless predistortion is extended to memory predistortion by adding two-delay lines,and a simple polynomial model with tapped delay linear is used as the memory predistorter model.Combined the extended structure and the simple memory predistorter model can realize the linearization of the amplifier with memory.Simulation results demonstrated that the proposed scheme posses faster convergence and better linearization performance.

Key concepts: Predistortion, Linearization, Amplifier, Computer science, Control theory (sociology), Nonlinear system, Convergence (economics), Polynomial

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