## 4 Conclusions  
This paper presents a broadband LNA design in 22 nm FD-SOI CMOS using bandwidth extension techniques to improve input matching and wide gain bandwidth. We developed a two-stage gain compensation technique by first adjusting the frequency separation and magnitude of the gain peaks in the interstage resonator, followed by using the second stage's gain to supplement the gain droop of the first stage at midband frequencies to cover the key 5G FR2 bands. Resistive feedback was added to the first stage to smoothen the gain peaks at the first stage for improved \(S_{21}\)- bandwidth and to address the problem of narrowband input matching in a conventional cascode LNA with inductive degeneration. The lumped-element-based PEX simulations show the parasitic effects on BW, \(NF\) and linearity from different extraction options (\(R\), \(RC\) or \(RCC\)). PEX \(RCC\) simulations show rather similar results to the full EM PEX simulations but with significantly reduced simulation time. EM PEX simulated data suggest that the \(S_{21}\) 3 dB BW is 17.8-42.4 GHz, with the lowest \(NF=2.9\) dB, a maximum small signal gain of 18.3 dB, \(IP1 dB\) of \(-17.9\) dBm and \(IIP3\) of \(-8.5\) dBm. Table 2 summarizes our LNA from its EM and PEX RCC simulation results and compares them with state-of-the-art mm-Wave and/or Ka-band broadband  
Figure 13: K factor and Mu with (blue) vs. without (red) an 8.2 k\(\Omega\) shunt resistor at the output between 1 MHz and 100 MHz in EM simulations. With an 8.2 k\(\Omega\) shunt resistor, K factor and Mu are greater than 1 which means the LNA is unconditionally stable.  
LNAs. We achieved our initial target specifications, including the \(S_{21}\) 3-dB BW, \(NF\) and \(IIP3\). Our design has obtained one of the highest 3 dB small signal gain bandwidths and fractional bandwidth percentages and a competitive FOM amongst the best in the literature. However, measurement data are needed to validate the PEX simulation data presented. Future endeavors include tuning the EM simulated results as suggested in Section 3.2, as well as applying some well-established linearization techniques such as feedforward or the derivative superposition method [20] to improve \(IIP3\).  
Conceptualization: L.-W.O. and D.Y.C.L.; methodology: L.-W.O. and D.Y.C.L.; validation: L.-W.O., J.C.M. and C.S.; formal analysis: L.-W.O. and D.Y.C.L.; investigation: L.-W.O. and D.Y.C.L.; resources: D.Y.C.L. and J.L.; data curation: L.-W.O.; writing--original draft preparation: L.-W.O.; writing--review and editing: L.-W.O. and D.Y.C.L.; supervision: J.C.M. and D.Y.C.L.; funding acquisition, D.Y.C.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
The authors would like to sincerely thank the excellent GF University Program and all the great support from the GF team. We are deeply indebted to the TTU Keh-Shew Lu Regents Chair Endowment Fund. We also thank the customer support from Siemens Calibre and Cadence EMX.  
Author [PERSON] was employed by the company NoiseFigure Research Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.