Measurement and simulation of memory effects in predistortion linearizers

Bösch, Wolfgang; Gatti, G.

doi:10.1109/22.44098

Cited by 212 publications

(76 citation statements)

References 3 publications

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“…It is reported in literature that the nonlinearity due to software program and hardware system of the instrument are deteriorate the measurement results [2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Effect of the Base-band Measurement Setup Errors on DPD Performance and Elimination Procedure

Yüzer

Şanlı

2017

AEM

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In this study, the effect of base-band measurement setup errors on DPD performance was investigated and a calibration procedure is developed to eliminate the measurement errors. A base-band measurement setup is prepared at laboratory with instruments and then the data which is measured and the deteriorating effect of errors on Digital Predistortion (DPD) linearization performance are investigated. In order to eliminate deteriorating effect of this error a three steps calibration procedure is developed. Before and after calibration application DPD performance is measured. It is showed both in simulation and experimentally that the calibration procedure improved the DPD system linearization performance from 10 dB to 26dB and 13dB to 20dB, respectively.

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“…It is reported in literature that the nonlinearity due to software program and hardware system of the instrument are deteriorate the measurement results [2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Effect of the Base-band Measurement Setup Errors on DPD Performance and Elimination Procedure

Yüzer

Şanlı

2017

AEM

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“…The models are valid when the device Òmemory timeÓ (amplitude-and frequency-dependent time delay between the transmitted and received RF signal) is much smaller than the reciprocal of the input signal bandwidth [16]. In other words, these characteristics can be used only when the nonlinear system is treated as a quasi-memoryless system [17]. As a rule of thumb, the AM-AM/PM models are used when the memory of the nonlinear system is at least twice less than the reciprocal of the envelope frequency [16,18].…”

Section: B Optical Subsystemmentioning

confidence: 99%

Pilot‐aided estimation and equalisation of a Radio‐over‐Fibre system in Wideband Code Division Multiple Access

Baghersalimi¹,

O’Farrell²

2013

IET Communications

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AbstractÑIn this paper the impact of a Radio over Fibre (RoF) subsystem on the capacity performance of Wideband Code Division Multiple Access (WCDMA) is evaluated. The study investigates the use of pilot aided channel estimation to compensate for the optical subsystem nonlinearities for different channel conditions, estimation intervals, and coding schemes. The results show that pilot aided channel estimation is an effective method for compensating the composite impairments of the optical subsystem and the RF channel. It is found that there is always a suitable pilot power level which maximises the system capacity performance regardless of coding scheme and channel condition. Also, the peak capacity is only slightly affected by a decrease in the estimation interval.

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“…The most evident nonlinear behavior is the gain compression that occurs when the PA is driven at higher power levels. Besides, different kinds of dynamic effects are also observable, including low-frequency memory effects (on the order of the envelope bandwidth) associated to active-device self-heating, biasing circuitry and trapping effects [17,18], as well as high-frequency memory effects (on the order of the carrier frequency) attributed to non-uniform frequency response of the matching networks [6].…”

Section: Power Amplifier Behavioral Modelingmentioning

confidence: 99%

Low-Pass Equivalent Behavioral Modeling of Rf Power Amplifiers Using Two Independent Real-Valued Feed-Forward Neural Networks

Freire¹,

França²,

Lima³

2014

PIER C

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Abstract-Feed-forward artificial neural networks (ANNs) can provide the adequate model required for the linearization of power amplifiers (PAs) used in wireless communication systems. A common characteristic of previously available ANN-based models for linearization purposes is the use of a single real-valued ANN having two outputs. The contribution of this work is to report the benefits of performing such behavioral modeling based on two independent real-valued ANNs, where each network has a unique output. The proposed ANN-based model is applied to the behavioral modeling of a GaN HEMT class AB PA, and its accuracy is compared to previous approaches in two different scenarios. First, in case of similar number of network parameters, it is observed that the proposed ANN-based model can reduce the normalized mean-square error (NMSE) by up to 1.3 dB. Second, in a situation of comparable modeling accuracy (NMSE = −40 dB), it is observed that the proposed ANN-based model can reduce the number of network parameters by up to 40% (from 62 to 38 real-valued parameters).

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Measurement and simulation of memory effects in predistortion linearizers

Cited by 212 publications

References 3 publications

Effect of the Base-band Measurement Setup Errors on DPD Performance and Elimination Procedure

Effect of the Base-band Measurement Setup Errors on DPD Performance and Elimination Procedure

Pilot‐aided estimation and equalisation of a Radio‐over‐Fibre system in Wideband Code Division Multiple Access

Low-Pass Equivalent Behavioral Modeling of Rf Power Amplifiers Using Two Independent Real-Valued Feed-Forward Neural Networks

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