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**Harvard**

Carlsson, L. och Boklund, H. (2013) *Modelling of Spectral Regrowth*. Göteborg : Chalmers University of Technology

** BibTeX **

@mastersthesis{

Carlsson2013,

author={Carlsson, Ludvig and Boklund, Henrik},

title={Modelling of Spectral Regrowth},

abstract={In modern communication links amplifiers play a crucial role. However the necessity of cost- and power efficient solutions result in amplifiers being used outside their most linear region of operation. When a modulated signal is inserted into a nonlinear element such as an amplifier, the output will be subject to a phenomena referred to as spectral regrowth. The spectral regrowth will contribute to adjacent channel interference if the regrowth from the modulated signal is spread into an adjacent channel. The aim of this thesis is to create a model that can predict the amount of adjacent channel interference generated due to spectral regrowth, when an modulated signal is fed into an amplifier. The investigation include the common mobile communication standards GSM, UMTS and LTE.
To develop a model, both simulations and measurements has been performed. MATLAB, Agilent’s ADS and AWR VSS have all been used during the simulations for cross verification. The measure used to quantify spectral regrowth is adjacent channel power ratio (ACPR). In logarithmic scale, ACPR was confirmed to depend on IIP3 with a factor of 2 dB/dBm while the dependence on input power is a factor of -2 dB/dBm. The model can predict the ACPR for different channel setups with a maximum deviation of 2.3 dB compared to measurements, for the majority of the frequency interval of interest. The deviation depend upon the type of signal, channel setup and simulation program. The only amplifier characteristic inserted into the model is IIP3 which is a figure of merit that is not constant. As the IIP3 of an amplifier will vary, the use of this input variable result in uncertanties in the prediction of ACPR.
However, the model can give a rough estimation of the ACPR in short time, using easily obtainable input parameters.},

publisher={Institutionen för mikroteknologi och nanovetenskap, Chalmers tekniska högskola},

place={Göteborg},

year={2013},

note={88},

}

** RefWorks **

RT Generic

SR Print

ID 179651

A1 Carlsson, Ludvig

A1 Boklund, Henrik

T1 Modelling of Spectral Regrowth

T2 A Study Focused on Different Mobile Communication Standards and Channel Setups

YR 2013

AB In modern communication links amplifiers play a crucial role. However the necessity of cost- and power efficient solutions result in amplifiers being used outside their most linear region of operation. When a modulated signal is inserted into a nonlinear element such as an amplifier, the output will be subject to a phenomena referred to as spectral regrowth. The spectral regrowth will contribute to adjacent channel interference if the regrowth from the modulated signal is spread into an adjacent channel. The aim of this thesis is to create a model that can predict the amount of adjacent channel interference generated due to spectral regrowth, when an modulated signal is fed into an amplifier. The investigation include the common mobile communication standards GSM, UMTS and LTE.
To develop a model, both simulations and measurements has been performed. MATLAB, Agilent’s ADS and AWR VSS have all been used during the simulations for cross verification. The measure used to quantify spectral regrowth is adjacent channel power ratio (ACPR). In logarithmic scale, ACPR was confirmed to depend on IIP3 with a factor of 2 dB/dBm while the dependence on input power is a factor of -2 dB/dBm. The model can predict the ACPR for different channel setups with a maximum deviation of 2.3 dB compared to measurements, for the majority of the frequency interval of interest. The deviation depend upon the type of signal, channel setup and simulation program. The only amplifier characteristic inserted into the model is IIP3 which is a figure of merit that is not constant. As the IIP3 of an amplifier will vary, the use of this input variable result in uncertanties in the prediction of ACPR.
However, the model can give a rough estimation of the ACPR in short time, using easily obtainable input parameters.

PB Institutionen för mikroteknologi och nanovetenskap, Chalmers tekniska högskola,PB Institutionen för mikroteknologi och nanovetenskap, Chalmers tekniska högskola,

LA eng

OL 30