High-efficient adaptive predistortion scheme for nonlinear power amplifier with memory
Liu Fu-qiang
Abstract
Liu Fu-qiang
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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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