pith. sign in

arxiv: 2410.23378 · v3 · submitted 2024-10-30 · 📡 eess.SP

Channel-Aware Behavioral Power Modeling of CMOS OOK Transceivers for Wireless Network-on-Chip Systems

Mohammad Shahmoradi , Ahmet Yelbo\u{g}a , Eduard Alarc\'on , Korkut Kaan Tokg\"oz , Sergi Abadal This is my paper

Pith reviewed 2026-05-23 18:24 UTC · model grok-4.3

classification 📡 eess.SP
keywords wireless network-on-chipOOK transceiverpower modelingchannel-awareenergy efficiencyCMOS RFfrequency dependenceenergy-per-bit
0
0 comments X

The pith

A channel-aware power model of OOK transceivers shows the energy-per-bit global minimum occurs only when transmitter and receiver are tuned jointly.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper builds a channel-aware behavioral modeling framework for CMOS OOK transceivers used in wireless network-on-chip. It derives frequency-dependent power models for key sub-blocks from existing implementation surveys and folds in channel loss to compute overall energy per bit. The resulting landscape shows sweet spots where power dominance moves from the oscillator and envelope detector at low frequencies to the power amplifier and low-noise amplifier at high frequencies. A sympathetic reader would care because the model indicates that the lowest energy operation requires joint optimization of the full transmitter-receiver chain rather than tuning either side alone.

Core claim

The channel-aware behavioral modeling framework, built from survey data on CMOS OOK implementations, derives frequency-dependent power consumption for the PA, oscillator, mixer, LNA, and ED. When channel loss is folded into the power budget, the model produces an energy-per-bit landscape with sweet spots and a model-based global minimum. This demonstrates that optimal operation points require simultaneous consideration of transmitter and receiver performance rather than independent optimization of either.

What carries the argument

The channel-aware behavioral power model that incorporates frequency-dependent sub-block power from survey data and channel loss to map energy-per-bit across frequencies.

If this is right

  • Power dominance shifts from oscillator- and ED-dominated regimes at lower frequencies to PA- and LNA-dominated behavior at higher frequencies.
  • The energy-per-bit landscape exhibits sweet spots and a model-based global minimum.
  • Optimal operation cannot be achieved by optimizing transmitter or receiver independently.
  • The framework enables rapid exploration of power scaling with frequency and channel conditions for WNoC design.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same survey-driven method could be reused for other short-range wireless links if comparable sub-block data become available.
  • A silicon prototype measured at the predicted minimum frequency would directly test whether real hardware follows the modeled energy curve.
  • Changing the assumed channel-loss values could show how sensitive the location of the minimum is to different many-core floorplans.

Load-bearing premise

Survey data from existing CMOS OOK implementations accurately capture the frequency dependence of power consumption in the PA, oscillator, mixer, LNA, and ED sub-blocks over the wide frequency range considered.

What would settle it

Fabricate and measure OOK transceivers at the model's predicted global-minimum frequency and check whether the measured energy-per-bit is lower than at nearby frequencies or whether a lower value exists elsewhere.

Figures

Figures reproduced from arXiv: 2410.23378 by Ahmet Yelbo\u{g}a, Eduard Alarc\'on, Korkut Kaan Tokg\"oz, Mohammad Shahmoradi, Sergi Abadal.

Figure 1
Figure 1. Figure 1: Wireless Network-on-Chip (WNoC) architecture in a [PITH_FULL_IMAGE:figures/full_fig_p001_1.png] view at source ↗
Figure 3
Figure 3. Figure 3: PA power model as a function of frequency. [PITH_FULL_IMAGE:figures/full_fig_p003_3.png] view at source ↗
Figure 2
Figure 2. Figure 2: PAE versus frequency based on survey’s data [22] [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 6
Figure 6. Figure 6: DC power contribution of the TX front-end across [PITH_FULL_IMAGE:figures/full_fig_p004_6.png] view at source ↗
Figure 5
Figure 5. Figure 5: Mixer power consumption model as a function of [PITH_FULL_IMAGE:figures/full_fig_p004_5.png] view at source ↗
read the original abstract

Wireless Network-on-Chip (WNoC) systems enable low-latency communication in many-core platforms through short-range wireless links. However, the power consumption of integrated transceivers (TRXs), dominated by that of the RF front-end circuitry, remains a major challenge. Moreover, the optimal operating frequency is still unclear, as bandwidth, energy efficiency, and technology maturity must be balanced. This work presents a channel-aware behavioral modeling framework to estimate power consumption and identify energy-efficient operating points in non-coherent On-Off Keying (OOK) TRXs over a wide frequency range. The approach leverages survey data from CMOS implementations to derive frequency-dependent power models for key TRX sub-blocks, including the power amplifier (PA), oscillator, mixer, low noise amplifier (LNA), and envelope detector (ED). By incorporating the frequency-dependent channel loss into the TRX power budget, the model captures system-level power trade-offs across operating regimes. The analysis reveals a frequency-dependent shift in power dominance between the transmitter and receiver: oscillator- and ED-dominated regimes at lower frequencies transition to PA- and LNA-dominated behavior at higher frequencies. Furthermore, the energy-per-bit landscape exhibits sweet spots and a model-based global minimum, indicating that optimal operation cannot be achieved by optimizing transmitter or receiver independently. Overall, the proposed framework enables rapid and physically grounded exploration of power scaling with frequency and channel conditions, providing practical guidelines for energy-efficient design of high-frequency wireless links for WNoC systems and beyond.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 0 minor

Summary. The manuscript presents a channel-aware behavioral modeling framework for non-coherent OOK transceivers in Wireless Network-on-Chip systems. It derives frequency-dependent power models for the PA, oscillator, mixer, LNA, and ED sub-blocks from survey data on existing CMOS implementations, folds in frequency-dependent channel loss, and reports a shift from oscillator/ED-dominated to PA/LNA-dominated regimes together with sweet spots and a global minimum in the energy-per-bit landscape, from which it concludes that transmitter and receiver must be optimized jointly.

Significance. If the survey-derived frequency scalings prove accurate and the resulting E_b(f) surface is reproducible, the framework would supply a practical, system-level tool for identifying energy-efficient operating points in short-range WNoC links and for quantifying the necessity of joint TX/RX design. The approach is conceptually attractive because it couples sub-block power models to channel loss without requiring full circuit simulation; however, the absence of any raw survey points, fitting equations, frequency span, or validation metrics in the provided text prevents assessment of whether the reported dominance transitions and global minimum are physically grounded or artifacts of the modeling choices.

major comments (1)
  1. [Abstract] Abstract: The headline claims of a frequency-dependent power-dominance shift and a model-based global minimum in the energy-per-bit landscape rest entirely on the accuracy of the frequency-dependent power models for PA, oscillator, mixer, LNA, and ED. The abstract states only that these models are “derived” from “survey data from CMOS implementations” but supplies neither the underlying data points, the functional form or fitting procedure used, the covered frequency range, nor any cross-validation or residual-error statistics. Without this information it is impossible to determine whether the computed sweet spots and global minimum reflect measured device behavior or are imposed by the chosen parametrization.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for highlighting the need for greater transparency regarding our survey-derived models. We address this point directly below and propose a targeted revision to the abstract.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The headline claims of a frequency-dependent power-dominance shift and a model-based global minimum in the energy-per-bit landscape rest entirely on the accuracy of the frequency-dependent power models for PA, oscillator, mixer, LNA, and ED. The abstract states only that these models are “derived” from “survey data from CMOS implementations” but supplies neither the underlying data points, the functional form or fitting procedure used, the covered frequency range, nor any cross-validation or residual-error statistics. Without this information it is impossible to determine whether the computed sweet spots and global minimum reflect measured device behavior or are imposed by the chosen parametrization.

    Authors: We agree that the abstract, as a concise summary, does not include the raw survey data points, explicit fitting equations, frequency span, or validation metrics. The full manuscript supplies these details in the sections describing the behavioral modeling framework. To directly address the concern and allow readers to better assess the grounding of the reported dominance shifts and energy minimum, we will revise the abstract to add a brief clause specifying the frequency range examined and noting that the sub-block models were fitted to survey data with reported goodness-of-fit metrics. revision: yes

Circularity Check

0 steps flagged

No significant circularity; models derived from external survey data

full rationale

The abstract states that frequency-dependent power models for PA, oscillator, mixer, LNA, and ED are derived from survey data from CMOS implementations, an external source. The energy-per-bit landscape, sweet spots, and global minimum are obtained by incorporating frequency-dependent channel loss into the TRX power budget. No equations, self-citations, uniqueness theorems, or fitted inputs called predictions are present in the provided text that would reduce any result to its inputs by construction. The derivation is self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

1 free parameters · 2 axioms · 0 invented entities

Abstract-only view limits visibility; the framework rests on survey-derived frequency-dependent power expressions for five sub-blocks and the assumption that channel loss can be directly added to the power budget.

free parameters (1)
  • frequency-dependent power scaling factors for PA, oscillator, mixer, LNA, ED
    Extracted from survey of CMOS implementations; exact functional forms and fitting details not visible in abstract
axioms (2)
  • domain assumption Non-coherent OOK modulation allows simple envelope detection whose power scales predictably with frequency
    Implicit in the choice of TRX architecture and sub-block modeling
  • domain assumption Channel loss is a known frequency-dependent quantity that can be folded into the total power budget without additional circuit effects
    Used to produce system-level trade-off curves

pith-pipeline@v0.9.0 · 5798 in / 1371 out tokens · 46532 ms · 2026-05-23T18:24:25.321881+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

41 extracted references · 41 canonical work pages

  1. [1]

    Edholm’s law of bandwidth,

    S. Cherry, “Edholm’s law of bandwidth,” IEEE spectrum, vol. 41, no. 7, pp. 58–60, 2004

    work page 2004

  2. [2]

    Wireless communications and applications above 100 ghz: Opportunities and challenges for 6g and beyond,

    T. S. Rappaport, Y . Xing, O. Kanhere, S. Ju, A. Madanayake, S. Mandal, A. Alkhateeb, and G. C. Trichopoulos, “Wireless communications and applications above 100 ghz: Opportunities and challenges for 6g and beyond,” IEEE access, vol. 7, pp. 78 729–78 757, 2019

    work page 2019

  3. [3]

    New trends and advancement in next generation mobile wireless communication (6g): a survey,

    S. Ali, M. Sohail, S. B. H. Shah, D. Koundal, M. A. Hassan, A. Abdol- lahi, and I. U. Khan, “New trends and advancement in next generation mobile wireless communication (6g): a survey,” Wireless Communica- tions and Mobile Computing , vol. 2021, no. 1, p. 9614520, 2021

    work page 2021

  4. [4]

    Special issue on 6g wireless systems,

    P. Chatzimisios, D. Soldani, A. Jamalipour, A. Manzalini, and S. K. Das, “Special issue on 6g wireless systems,” Journal of Communications and Networks, vol. 22, no. 6, pp. 440–443, 2020

    work page 2020

  5. [5]

    Crols and M

    J. Crols and M. Steyaert, CMOS wireless transceiver design . Springer Science & Business Media, 2013, vol. 411

    work page 2013

  6. [6]

    Sige and cmos technology for state-of-the-art millimeter-wave transceivers,

    J. Du Preez, S. Sinha, and K. Sengupta, “Sige and cmos technology for state-of-the-art millimeter-wave transceivers,” IEEE Access, 2023

    work page 2023

  7. [7]

    Terahertz fre- quency sensing and imaging: A time of reckoning future applications?

    D. L. Woolard, R. Brown, M. Pepper, and M. Kemp, “Terahertz fre- quency sensing and imaging: A time of reckoning future applications?” Proceedings of the IEEE , vol. 93, no. 10, pp. 1722–1743, 2005

    work page 2005

  8. [8]

    Electromagnetic nanonetworks beyond 6g: From wearable and implantable networks to on-chip and quantum communication,

    S. Abadal, C. Han, V . Petrov, L. Galluccio, I. F. Akyildiz, and J. M. Jornet, “Electromagnetic nanonetworks beyond 6g: From wearable and implantable networks to on-chip and quantum communication,” IEEE Journal on Selected Areas in Communications , 2024

    work page 2024

  9. [9]

    Graphene- based wireless agile interconnects for massive heterogeneous multi-chip processors,

    S. Abadal, R. Guirado, H. Taghvaee, A. Jain, E. P. de Santana, P. H. Bol´ıvar, M. Saeed, R. Negra, Z. Wang, K.-T. Wang et al. , “Graphene- based wireless agile interconnects for massive heterogeneous multi-chip processors,” IEEE Wireless Communications, 2022

    work page 2022

  10. [10]

    Hywin: Hybrid wireless noc with sandboxed sub-networks for cpu/gpu architectures,

    S. H. Gade and S. Deb, “Hywin: Hybrid wireless noc with sandboxed sub-networks for cpu/gpu architectures,” IEEE Transactions on comput- ers, vol. 66, no. 7, pp. 1145–1158, 2016

    work page 2016

  11. [11]

    On the area and energy scalability of wireless network-on-chip: A model-based benchmarked design space explo- ration,

    S. Abadal, M. Iannazzo, M. Nemirovsky, A. Cabellos-Aparicio, H. Lee, and E. Alarc ´on, “On the area and energy scalability of wireless network-on-chip: A model-based benchmarked design space explo- ration,” IEEE/ACM Transactions on Networking , vol. 23, no. 5, pp. 1501–1513, 2014

    work page 2014

  12. [12]

    F. M. Ghannouchi, O. Hammi, and M. Helaoui, Behavioral modeling and predistortion of wideband wireless transmitters . John Wiley & Sons, 2015

    work page 2015

  13. [13]

    System-level performance analysis for designing on-chip communication architectures,

    K. Lahiri, A. Raghunathan, and S. Dey, “System-level performance analysis for designing on-chip communication architectures,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 20, no. 6, pp. 768–783, 2001

    work page 2001

  14. [14]

    Bpnn-based behavioral modeling of the s-parameter variation characteristics of pas with frequency at different temperatures,

    Z. He and S. Zhou, “Bpnn-based behavioral modeling of the s-parameter variation characteristics of pas with frequency at different temperatures,” Micromachines, vol. 13, no. 11, p. 1831, 2022

    work page 2022

  15. [15]

    General behavioral thermal modeling and characterization for multi- core microprocessor design,

    T. J. Eguia, S. X.-D. Tan, R. Shen, E. H. Pacheco, and M. Tirumala, “General behavioral thermal modeling and characterization for multi- core microprocessor design,” in 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010). IEEE, 2010, pp. 1136– 1141

    work page 2010

  16. [16]

    Devel- opment of vhdl-ams neuro-fuzzy behavioral models for rf/microwave passive components,

    J. Hinojosa, G. Dom ´enech-Asensi, and J. Mart ´ınez-Alajar´ın, “Devel- opment of vhdl-ams neuro-fuzzy behavioral models for rf/microwave passive components,”Int. J. RF Microwave Comput.-Aided Eng., vol. 17, no. 3, pp. 335–344, 2007

    work page 2007

  17. [17]

    Large-signal characteriza- tion and behavioral modeling of mm-wave gan hemt switches tailored for advanced power amplifier architectures,

    S. U. Ghozati, A. Baddeley, and R. Quaglia, “Large-signal characteriza- tion and behavioral modeling of mm-wave gan hemt switches tailored for advanced power amplifier architectures,” in IEEE Topical Conf. on RF/Microwave Power Amplifiers for Radio and Wireless Applications (PAWR). IEEE, 2024, pp. 21–23

    work page 2024

  18. [18]

    Optimized design of low-noise amplifier based on behavior-level parameter modeling,

    S. Wu, X. Li, T. Tan, and Z. Huang, “Optimized design of low-noise amplifier based on behavior-level parameter modeling,” in 2023 Inter- national Conference on Microwave and Millimeter Wave Technology (ICMMT). IEEE, 2023, pp. 1–3

    work page 2023

  19. [19]

    Taghikhani, Modeling Approaches for Active Antenna Transmitters

    P. Taghikhani, Modeling Approaches for Active Antenna Transmitters . Chalmers Tekniska Hogskola (Sweden), 2021

    work page 2021

  20. [20]

    The evolution of applications, hardware design, and channel modeling for terahertz (thz) band communications and sensing: Ready for 6g?

    J. M. Jornet, V . Petrov, H. Wang, Z. Popovi ´c, D. Shakya, J. V . Siles, and T. S. Rappaport, “The evolution of applications, hardware design, and channel modeling for terahertz (thz) band communications and sensing: Ready for 6g?” Proceedings of the IEEE , 2024

    work page 2024

  21. [21]

    Models, methods, and solutions for multicasting in 5g/6g mmwave and sub-thz systems,

    N. Chukhno, O. Chukhno, D. Moltchanov, S. Pizzi, A. Gaydamaka, A. Samuylov, A. Molinaro, Y . Koucheryavy, A. Iera, and G. Araniti, “Models, methods, and solutions for multicasting in 5g/6g mmwave and sub-thz systems,” IEEE Communications Surveys & Tutorials , 2023

    work page 2023

  22. [22]

    H. Wang, M. Eleraky, B. Abdelaziz, B. Lin, E. Liu, Y . Liu, M. Ghorbanpoor, C. Chu, A. Ruffino, J. Xu, F. Svelto, N. Villaggi, A. Habib, K. Choi, T.-Y . Huang, H. Jalili, N. S. Mannem, J. Park, J. Lee, D. Munzer, S. Li, F. Wang, A. S. Ahmed, C. Snyder, H. T. Nguyen, and M. E. D. Smith. (2020) Power amplifiers performance survey 2000-present. [Online; acce...

    work page 2020

  23. [23]

    Optimal design of cmos mixer: A research review,

    H. Zhang, S. Tang, M. Cai, and Y . Jiang, “Optimal design of cmos mixer: A research review,” International Journal of RF and Microwave Computer-Aided Engineering, vol. 32, no. 12, p. e23531, 2022

    work page 2022

  24. [24]

    A K -band high-gain and low-noise folded cmos mixer using current- reuse and cross-coupled techniques,

    Y . Peng, J. He, H. Hou, H. Wang, S. Chang, Q. Huang, and Y . Zhu, “A K -band high-gain and low-noise folded cmos mixer using current- reuse and cross-coupled techniques,” IEEE Access, vol. 7, pp. 133 218– 133 226, 2019

    work page 2019

  25. [25]

    High linearity wide band passive mixer for ku-band applications in a 180nm cmos technology,

    H. Duan, J. Chen, M. Wang, H. Wei, Q. Zhang, and H. Quan, “High linearity wide band passive mixer for ku-band applications in a 180nm cmos technology,” in 2022 7th International Conference on Integrated Circuits and Microsystems (ICICM) . IEEE, 2022, pp. 565–569

    work page 2022

  26. [26]

    A cmos ku-band 4x subharmonic mixer,

    B. R. Jackson and C. E. Saavedra, “A cmos ku-band 4x subharmonic mixer,” IEEE Journal of Solid-State Circuits , vol. 43, no. 6, pp. 1351– 1359, 2008

    work page 2008

  27. [27]

    A ku-band receiver with 12-to-20-db gain, -14-dbm ipldb in 65-nm cmos technology,

    D. Cheng, L. Li, M. Xie, B. Sheng, and X. You, “A ku-band receiver with 12-to-20-db gain, -14-dbm ipldb in 65-nm cmos technology,” in 2018 Asia-Pacific Microwave Conference (APMC) , 2018, pp. 765–767

    work page 2018

  28. [28]

    260-mw ku-band fmcw transceiver for sar sensor with 1.48- ghz bw in 65-nm cmos,

    Y . Wang, L. Lou, B. Chen, Y . Zhang, K. Tang, L. Qiu, S. Liu, and Y . Zheng, “260-mw ku-band fmcw transceiver for sar sensor with 1.48- ghz bw in 65-nm cmos,” IEEE Trans. Microw. Theory Tech. , vol. 65, no. 11, pp. 4385–4399, 2017

    work page 2017

  29. [29]

    A 60-ghz double-balanced mixer for direct up-conversion transmitter on 130-nm cmos,

    F. Zhang, E. Skafidas, W. Shieh, B. Yang, B. N. Wicks, and Z. Liu, “A 60-ghz double-balanced mixer for direct up-conversion transmitter on 130-nm cmos,” in 2008 IEEE Compound Semiconductor Integrated Circuits Symposium, 2008, pp. 1–4

    work page 2008

  30. [30]

    A low power and high conversion gain 77–81 ghz double-balanced up-conversion mixer with excellent lo-rf isolation in 90 nm cmos,

    Y .-S. Lin, R.-C. Liu, C.-C. Wang, and C.-C. Chen, “A low power and high conversion gain 77–81 ghz double-balanced up-conversion mixer with excellent lo-rf isolation in 90 nm cmos,” in 2015 IEEE Radio and Wireless Symposium (RWS), 2015, pp. 171–173

    work page 2015

  31. [31]

    6.3 mw 94 ghz cmos down-conversion mixer with 11.6 db gain and 54 db lo-rf isolation,

    Y .-S. Lin, K.-S. Lan, C.-C. Wang, C.-C. Chi, and S.-S. Lu, “6.3 mw 94 ghz cmos down-conversion mixer with 11.6 db gain and 54 db lo-rf isolation,” IEEE Microwave and Wireless Components Letters , vol. 26, no. 8, pp. 604–606, 2016

    work page 2016

  32. [32]

    A k-band cmos standing wave oscillator using digital-controlled artificial dielectric differential transmission lines,

    Y . Li, X. Wu, J. Gu, Q. J. Gu, Z. Xu, and X. Yu, “A k-band cmos standing wave oscillator using digital-controlled artificial dielectric differential transmission lines,” IEEE Microwave and Wireless Components Letters , vol. 32, no. 10, pp. 1195–1198, 2022

    work page 2022

  33. [33]

    Design of low phase noise k-band vco using high quality factor resonator in 0.18 µm cmos technology,

    I. Mansour, M. Mansour, M. Aboualalaa, and R. K. Pokharel, “Design of low phase noise k-band vco using high quality factor resonator in 0.18 µm cmos technology,” International Journal of RF and Microwave Computer-Aided Engineering, vol. 32, no. 4, p. e23045, 2022

    work page 2022

  34. [34]

    A 2.2- mw 23 ghz cmos vco using high-quality factor complementary split ring resonator with a- 195dbc/hz fom,

    I. Mansour, M. Mansour, A. Allam, and A. B. Abdel-Rahman, “A 2.2- mw 23 ghz cmos vco using high-quality factor complementary split ring resonator with a- 195dbc/hz fom,” AEU-International Journal of Electronics and Communications , vol. 155, p. 154356, 2022

    work page 2022

  35. [35]

    A 3.3- mw 25.2-to-29.4-ghz current-reuse vco using a single-turn multi-tap inductor and differential-only switched-capacitor arrays with a 187.6- dbc/hz fom,

    Y . Huang, Y . Chen, H. Guo, P.-I. Mak, and R. P. Martins, “A 3.3- mw 25.2-to-29.4-ghz current-reuse vco using a single-turn multi-tap inductor and differential-only switched-capacitor arrays with a 187.6- dbc/hz fom,” IEEE Trans. Circuits Syst. I: Reg. Papers , vol. 67, no. 11, pp. 3704–3717, 2020

    work page 2020

  36. [36]

    A- 193.6 dbc/hz fom t 28.6-to- 36.2 ghz dual-core cmos vco for 5g applications,

    Y . Fu, L. Li, D. Wang, and X. Wang, “A- 193.6 dbc/hz fom t 28.6-to- 36.2 ghz dual-core cmos vco for 5g applications,” IEEE Access, vol. 8, pp. 62 191–62 196, 2020

    work page 2020

  37. [37]

    77.3-ghz standing-wave oscillator using an asymmetrical tunable slow-wave resonator,

    L. Gomes, E. Sharma, A. A. L. Souza, A. L. C. Serrano, G. P. Rheder, E. Pistono, P. Ferrari, and S. Bourdel, “77.3-ghz standing-wave oscillator using an asymmetrical tunable slow-wave resonator,” IEEE Trans. Circuits Syst. I: Reg. Papers , vol. 68, no. 8, pp. 3158–3169, 2021

    work page 2021

  38. [38]

    A 126 ghz, 22.5% tuning, 191 dbc/hz fomt 3rd harmonic extracted class-f oscillator for d-band applications in 16nm finfet,

    B. Philippe and P. Reynaert, “A 126 ghz, 22.5% tuning, 191 dbc/hz fomt 3rd harmonic extracted class-f oscillator for d-band applications in 16nm finfet,” in 2020 IEEE Radio Frequency Integrated Circuits Symposium (RFIC). IEEE, 2020, pp. 263–266

    work page 2020

  39. [39]

    Enhancing the phase-noise-figure-of- merit of a resonator using frequency transformations,

    S. Poolakkal and N. Nallam, “Enhancing the phase-noise-figure-of- merit of a resonator using frequency transformations,” in 2020 33rd International Conference on VLSI Design and 2020 19th International Conference on Embedded Systems (VLSID) . IEEE, 2020, pp. 67–71

    work page 2020

  40. [40]

    T. H. Lee, The design of CMOS radio-frequency integrated circuits . Cambridge university press, 2003

    work page 2003

  41. [41]

    Razavi, Fundamentals of microelectronics

    B. Razavi, Fundamentals of microelectronics . John Wiley & Sons, 2021

    work page 2021