New Predistortion Method for RF Power Amplifier Linearization
Kaiyu Qin
Abstract
Kaiyu Qin
Abstract
This paper proves that the sequence of two memoryless nonlinear systems,predistorter and RF power amplifier,is commutative through theoretical derivation.For the disadvantages of frequently used predistortion structures,this paper proposes a new predistortion structure combining direct learning structure with indirect learning structure,which is simple and easy to implement.The RF power amplifier predistortion linearization method is extended to the situation with memory effect.Simulation results show the correctness of this predistortion linearization method.Its linearization performance is better than that using the direct inverse indirect learning structure.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
This paper proves that the sequence of two memoryless nonlinear systems,predistorter and RF power amplifier,is commutative through theoretical derivation.For the disadvantages of frequently used predistortion structures,this paper proposes a new predistortion structure combining direct learning structure with indirect learning structure,which is simple and easy to implement.The RF power amplifier predistortion linearization method is extended to the situation with memory effect.Simulation results show the correctness of this predistortion linearization method.Its linearization performance is better than that using the direct inverse indirect learning structure.
Key concepts: Predistortion, Linearization, Amplifier, Computer science, Control theory (sociology), Correctness, Power (physics), Electronic engineering