A State-Space Modeling Approach for Dynamic Nonlinear Microwave System Based on Large Signal Time Domain Measurements

Cidronali, Alessandro; Accillaro, C.; Myslinski, Maciej; Schreurs, Dominique; Manes, G.

doi:10.1109/mwsym.2005.1516633

Cited by 3 publications

(5 citation statements)

References 4 publications

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“…After being converted into dBm, the signal is fed into the Step-Up/Down Function blocks that implement the DGE, the dc normalized average current, and the gain compression terms as functions of the instantaneous input power, P in , as stated by eqs. (4)- (6). The total gain term G t that is generated next depends on P in and contains spectral components at frequencies 0, 6f m , 62f m , 63f m , etc.…”

Section: Figure 4 Illustrates the Implementation Of Eqs (4)-(8) As Amentioning

confidence: 99%

“…4). Next, gain compression term is modeled through (6). Corresponding parameters listed in Table I are extracted.…”

Section: Model Extraction and Experimental Validationmentioning

confidence: 99%

“…In [2][3][4], nonlinear models have been extracted using vectorial large signal measurements, whereas Schreurs et al [5] and Cidronali et al [6] proposed a state space modeling approach for capturing dynamic nonlinear memory effects by performing time domain vector measurements. de Carvalho and Pedro in [7][8][9] and Fager et al in [10] performed an analysis on assessing and modeling the behavior of small and large signal IMD (IMD sweet spot), as well as memory effects, which they attributed to load termination at the baseband, using two-and multi-tone excitations.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Behavioral modeling of power amplifiers for wireless applications

Vryssas

Samelis

2007

Int J RF and Microwave Comp Aid Eng

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In this paper, an improved empirical behavioral model for radio-frequency power amplifiers (RF-PAs) is presented. The model was implemented in a commercial nonlinear microwave simulator. It belongs to the category of bandpass PA models, which exhibits memory effects due to the low frequency dependence of bias and temperature. Additionally, it facilitates accurate and efficient system level simulations of RF-PA large-signal behaviors such as self-bias, AM-AM, AM-PM, gain expansion effects, and intermodulation distortion (IMD) sweet-spots. The model was validated using measurement data obtained from a commercial CDMA PA at 1.88 GHz.

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Section: Figure 4 Illustrates the Implementation Of Eqs (4)-(8) As Amentioning

confidence: 99%

“…4). Next, gain compression term is modeled through (6). Corresponding parameters listed in Table I are extracted.…”

Section: Model Extraction and Experimental Validationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Behavioral modeling of power amplifiers for wireless applications

Vryssas

Samelis

2007

Int J RF and Microwave Comp Aid Eng

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“…State space modeling techniques provide an efficient approach to modeling system dynamics, and are readily adapted to electrically larger microwave frequency circuits [5], [6]. While state space analysis can can be used to characterise dispersive systems, more sophisticated techniques are required when the systems component values are frequency dependent [4].…”

Section: Introductionmentioning

confidence: 99%

State-space analysis of left-handed transmission lines

Milford

2014

2014 1st Australian Microwave Symposium (AMS)

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In this paper we illustrate the use of a state space approach for the analysis of left-handed transmission lines, where an RLC equivalent circuit model is used to represent the transmission line. Steady state S-parameter frequency responses can be obtained directly from the state matrices, whereas the temporal response for arbitrary input excitations requires solu tion of the state equation. Validation using conventional methods is demonstrated.

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“…Although the RF bandwidth is up to 50 GHz, the instrument relies on sub-sampling techniques requiring the modulation to be periodic and have a bandwidth below 8 MHz [2]. A traditional vector network analyzer was modified in [3] to achieve an extremely wide modulation bandwidth and large dynamic range.…”

Section: Introductionmentioning

confidence: 99%

Improvement of Oscilloscope Based RF Measurements by Statistical Averaging Techniques

Fager

Andersson

2006

2006 IEEE MTT-S International Microwave Symposium Digest

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This paper demonstrates a method for accurate characterization of modulated microwave signals using a digital storage oscilloscope (DSO). Repeated measurements of the modulated signal are used with statistical averaging techniques to significantly improve the dynamic range. The performance of the method is evaluated by residual EVM and RF spectrum measurements. AM/AM measurements using two DSO channels are used to demonstrate the ability to perform synchronous input/output PA characterization.Index Terms -Statistical signal processing, digital storage oscilloscope, time domain measurement, base-band.

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A State-Space Modeling Approach for Dynamic Nonlinear Microwave System Based on Large Signal Time Domain Measurements

Cited by 3 publications

References 4 publications

Behavioral modeling of power amplifiers for wireless applications

Behavioral modeling of power amplifiers for wireless applications

State-space analysis of left-handed transmission lines

Improvement of Oscilloscope Based RF Measurements by Statistical Averaging Techniques

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