Small-signal and noise model extraction technique for heterojunction bipolar transistor at microwave frequencies

Noise parameters of InP-based double heterojunction base-collector self-aligned bipolar transistors

“…This is in agreement with the high of the device ( 100 GHz) at large current densities. Indeed, a high limits the noise figure variations at microwave frequencies [6]. Then and are predicted to remain, respectively, below 5 dB and above 10 dB up to 25-30 GHz, which makes these devices attractive for large bandwidth applications.…”

A method to simultaneously extract the small‐signal equivalent circuit and noise parameters of heterojunction bipolar transistors

“…However, measurement uncertainties, local minima of the error function to be minimized (in optimization methods), and the approximations (assumed in the direct-extraction methods) will compromise the accuracy of the small-signal circuit elements' extraction, thus producing a misleading estimation of the noise sources, and therefore the four NPs, that is, minimum noise figure F min , equivalent noise resistance R n , and magnitude ͉⌫ opt ͉ and phase opt of the optimum source reflection coefficient ⌫ opt . To overcome this drawback, other works [22,23] have proposed fitting the S-parameters and the NPs simultaneously. However, the measurement of NPs in [22,23] requires an input tuner [24] to synthesize the multiple source impedances required at the HBT input (base) port (typically, 10 source states or more at each frequency).…”

“…To overcome this drawback, other works [22,23] have proposed fitting the S-parameters and the NPs simultaneously. However, the measurement of NPs in [22,23] requires an input tuner [24] to synthesize the multiple source impedances required at the HBT input (base) port (typically, 10 source states or more at each frequency). In [25] an intrinsic noise model (admittance noise-matrix configuration) was proposed to extract the NPs using new analytical expressions; however, the accuracy of the method still depends on the extraction quality of the smallsignal parameters.…”

A fuzzy-neural approach for the characterisation of the active microwave devices

“…The fact that neural networks can learn totally different things, led to their use in diverse fields such as pattern recognition, speech processing, control, medical applications and more. Recently, microwave researchers developed techniques in which neural networks are trained from microwave data, and then used to enhance microwave design [5-81. In particular, researchers have successfully used ANNs to model micro-strip via [9], packaging and interconnects [lo], spiral inductors [l 11, MESFET devices [12], and CPW circuit components [13], to name just a few.…”

“…Besides, published literature is concerned with the equivalent circuit for the single-bias which are only either small-signal models or the noise behavior descriptions based on existing signal equivalent circuits that have nothing to do with the device noise characteristics. In [12] and [13] these two behaviors are combined in an unified classical circuit model for only a single-bias. A recent work [7] combines the signal and noise parameters in a neural network model over the fairly large operation band at a single bias point.…”