Design of predistorter based on parallel particle swarm optimization algorithm

Zheng Dai Li; Nan Wu; Jing Ming Kuang; Hua Wang

doi:10.15918/j.tbit1001-0645.2015.07.012

Design of predistorter based on parallel particle swarm optimization algorithm

Zheng Dai Li, Nan Wu^*, Jing Ming Kuang, Hua Wang

^*Corresponding author for this work

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

High power amplifier (HPA) is one of the main sources of nonlinear distortion in wireless communication systems. Digital baseband predistortion technology can effectively reduce the nonlinear distortion and improve the system transmission performance. In this paper, a particle swarm optimization (PSO) algorithm was used directly to estimate the parameters of Hammerstein predsitorter model and to solve the local maximum problem of gradient algorithms. The predistortion algorithm was optimized into a parallel computing structure which could lead to the maximum acceleration rate of the algorithm greater than 3. Simulation results show that the proposed algorithm can effectively suppress the spectrum regrowth outside band and reduce ACPR about 25 dB.

Original language	English
Pages (from-to)	715-719 and 770
Journal	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume	35
Issue number	7
DOIs	https://doi.org/10.15918/j.tbit1001-0645.2015.07.012
Publication status	Published - 1 Jul 2015

Keywords

Hammerstein model
Parallel optimization algorithm
Particle swarm optimization
Predistortion

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10.15918/j.tbit1001-0645.2015.07.012

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title = "Design of predistorter based on parallel particle swarm optimization algorithm",

abstract = "High power amplifier (HPA) is one of the main sources of nonlinear distortion in wireless communication systems. Digital baseband predistortion technology can effectively reduce the nonlinear distortion and improve the system transmission performance. In this paper, a particle swarm optimization (PSO) algorithm was used directly to estimate the parameters of Hammerstein predsitorter model and to solve the local maximum problem of gradient algorithms. The predistortion algorithm was optimized into a parallel computing structure which could lead to the maximum acceleration rate of the algorithm greater than 3. Simulation results show that the proposed algorithm can effectively suppress the spectrum regrowth outside band and reduce ACPR about 25 dB.",

keywords = "Hammerstein model, Parallel optimization algorithm, Particle swarm optimization, Predistortion",

author = "Li, {Zheng Dai} and Nan Wu and Kuang, {Jing Ming} and Hua Wang",

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T1 - Design of predistorter based on parallel particle swarm optimization algorithm

AU - Li, Zheng Dai

AU - Wu, Nan

AU - Kuang, Jing Ming

AU - Wang, Hua

PY - 2015/7/1

Y1 - 2015/7/1

N2 - High power amplifier (HPA) is one of the main sources of nonlinear distortion in wireless communication systems. Digital baseband predistortion technology can effectively reduce the nonlinear distortion and improve the system transmission performance. In this paper, a particle swarm optimization (PSO) algorithm was used directly to estimate the parameters of Hammerstein predsitorter model and to solve the local maximum problem of gradient algorithms. The predistortion algorithm was optimized into a parallel computing structure which could lead to the maximum acceleration rate of the algorithm greater than 3. Simulation results show that the proposed algorithm can effectively suppress the spectrum regrowth outside band and reduce ACPR about 25 dB.

AB - High power amplifier (HPA) is one of the main sources of nonlinear distortion in wireless communication systems. Digital baseband predistortion technology can effectively reduce the nonlinear distortion and improve the system transmission performance. In this paper, a particle swarm optimization (PSO) algorithm was used directly to estimate the parameters of Hammerstein predsitorter model and to solve the local maximum problem of gradient algorithms. The predistortion algorithm was optimized into a parallel computing structure which could lead to the maximum acceleration rate of the algorithm greater than 3. Simulation results show that the proposed algorithm can effectively suppress the spectrum regrowth outside band and reduce ACPR about 25 dB.

KW - Hammerstein model

KW - Parallel optimization algorithm

KW - Particle swarm optimization

KW - Predistortion

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DO - 10.15918/j.tbit1001-0645.2015.07.012

M3 - Article

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SN - 1001-0645

VL - 35

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JO - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

JF - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

IS - 7

ER -

Design of predistorter based on parallel particle swarm optimization algorithm

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Keywords

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