Wideband compact model of inductors for RF-SOP applications

Tsai, Yu-Shiuan; Wu, Jiming; Fan, Chieh-jung; Chiu, Chi-Tsung

doi:10.1109/apmc.2012.6421889

Cited by 2 publications

(4 citation statements)

References 6 publications

(6 reference statements)

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“…R loss accounts the eddy current induced loss. The T model is made up of 4 dash blocks, Z 1 , Z 2 , Z 3 , and Z 4 , where

Z_{1} = \frac{1}{\frac{1}{R_{normalp}} + \frac{1}{italicjω L_{s} + R_{s}}},

Z_{2} = Z_{3} = \frac{1}{italicjω C_{ox}},

Z_{4} = R_{loss} + \frac{R {}_{sub}}{1 + italicjω R_{sub} C_{sub}} .

When operating in the lower frequency, Z 4 and R p can be neglected . Then the series resistance R s and series inductance L s can be extracted as

R_{s} = real ((),, - \frac{2}{Y_{21} + Y_{12}}),

L_{s} = ([],, \frac{1}{ω} imag ((),, - \frac{2}{Y_{12} + Y_{12}})) .

…”

Section: Modeling Methodology Of Smnnmentioning

confidence: 99%

“…High‐accuracy inductor model is vital for the success of radio‐frequency (RF) and millimeter‐wave circuit design . Considerable study works on this topic have been reported in the literature . These modeling methods of spiral inductors are generally described as numerical techniques, behavioral macromodels, and compact circuit models .…”

Section: Introductionmentioning

confidence: 99%

“…1 Considerable study works on this topic have been reported in the literature. [2][3][4][5][6] These modeling methods of spiral inductors are generally described as numerical techniques, behavioral macromodels, 7,8 and compact circuit models. 9 Numerical techniques have a large computational load, and a small change in geometrical or process parameters could require a completely new simulation.…”

Section: Introductionmentioning

confidence: 99%

“…When operating in the lower frequency, Z 4 and R p can be neglected. 6 Then the series resistance R s and series inductance L s can be extracted as…”

Section: Introductionmentioning

confidence: 99%

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Broadband scalable compact circuit model for on‐chip spiral inductors by neural network

Han

Shi

2016

Int J Numerical Modelling

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A scalable model combining the advantages of the compact model and space‐mapping neural network (SMNN) has been presented to characterize radio‐frequency behaviors of on‐chip spiral inductors. The physics‐based T equivalent circuit model has been used for constructing the proposed scalable SMNN model. All values of the T model elements are fast and accurately extracted based on the mathematical formulations derived by analyzing the resonant responses. A 4‐layer perceptron neural network has been applied for the space mapping of the T model and the measurement data. Compared with the conventional models of on‐chip spiral inductors, the proposed SMNN model not only preserves the accuracy of measurement data but also runs as fast as an approximate compact model. The presented SMNN model has been verified by a series of octagon spiral inductors fabricated by 130‐nm BiCMOS process of HHNEC. Excellent agreements are obtained between the measurement and simulation of the proposed SMNN model up to 40 GHz.

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“…R loss accounts the eddy current induced loss. The T model is made up of 4 dash blocks, Z 1 , Z 2 , Z 3 , and Z 4 , where

Z_{1} = \frac{1}{\frac{1}{R_{normalp}} + \frac{1}{italicjω L_{s} + R_{s}}},

Z_{2} = Z_{3} = \frac{1}{italicjω C_{ox}},

Z_{4} = R_{loss} + \frac{R {}_{sub}}{1 + italicjω R_{sub} C_{sub}} .

When operating in the lower frequency, Z 4 and R p can be neglected . Then the series resistance R s and series inductance L s can be extracted as

R_{s} = real ((),, - \frac{2}{Y_{21} + Y_{12}}),

L_{s} = ([],, \frac{1}{ω} imag ((),, - \frac{2}{Y_{12} + Y_{12}})) .

…”

Section: Modeling Methodology Of Smnnmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…When operating in the lower frequency, Z 4 and R p can be neglected. 6 Then the series resistance R s and series inductance L s can be extracted as…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations