Oscillators Phase Noise

Phase Noise Definition

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Eq. (3.25) is widely adopted by industry and academia

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using the narrow angle assumption, the two definitions above are equivalent

If the narrow angle condition is not satisfied, however, the two definitions differ

PM vs. FM jitter

Deog-Kyoon Jeong. Topics in IC Design: 1.1 Introduction to Jitter [https://ocw.snu.ac.kr/sites/default/files/NOTE/Lec%201%20-%20Jitter%20and%20Phase%20Noise.pdf]

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Phase Noise Profile

Power Spectral Density of Brownian Motion despite non-stationary [https://dsp.stackexchange.com/a/75043/59253]

white noise

\(1/f^2\) Phase Noise Profile

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Sudhakar Pamarti. CICC 2020 ES2-2: Basics of Closed- and Open-Loop Fractional Frequency Synthesis [https://youtu.be/t1TY-D95CY8?si=tbav3J2yag38HyZx]

flicker noise

\(1/f^3\) Phase Noise Profile

\[ S_{\phi n} = \frac{K}{f}\left(\frac{K_{VCO}}{2\pi f}\right)^2 \propto \frac{1}{f^3} \]


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[https://dsp.stackexchange.com/a/75152/59253]

Free-running Oscillator

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Note that \(f_{min}\) is related to the observation time. The longer we observe the device under test, the smaller \(f_{min}\) must be

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Ali Sheikholeslami ISSCC 2008 T5: Basics of Chip-to-Chip and Backplane Signaling [https://www.nishanchettri.com/isscc-slides/2008%20ISSCC/Tutorials/T10_Pres.pdf]


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B. Casper and F. O'Mahony, "Clocking Analysis, Implementation and Measurement Techniques for High-Speed Data Links-A Tutorial," in IEEE Transactions on Circuits and Systems I. [https://people.engr.tamu.edu/spalermo/ecen689/clocking_analysis_hs_links_casper_tcas1_2009.pdf]

Lorentzian spectrum

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We typically use the two spectra, \(S_{\phi n}(f)\) and \(S_{out}(f)\), interchangeably, but we must resolve these inconsistencies. voltage spectrum is called Lorentzian spectrum


The periodic signal \(x(t)\) can be expanded in Fourier series as:

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Assume that the signal is subject to excess phase noise, which is modeled by adding a time-dependent noise component \(\alpha(t)\). The noisy signal can be written \(x(t+\alpha(t))\), the added excess phase \(\phi(t)= \frac{\alpha(t)}{\omega_0}\)

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The autocorrelation of the noisy signal is by definition:

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The autocorrelation averaged over time results in:

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By taking the Fourier transform of the autocorrelation, the spectrum of the signal \(x(t + \alpha(t))\)​ can be expressed as

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It is also interesting to note how the integral in Equation 9.80 around each harmonic is equal to the power of the harmonic itself \(|X_n|^2\)

The integral \(S_x(f)\) around harmonic is \[\begin{align} P_{x,n} &= \int_{f=-\infty}^{\infty} |X_n|^2\frac{\omega_0^2n^2c}{\frac{1}{4}\omega_0^4n^4c^2+(\omega +n\omega_0)^2}df \\ &= |X_n|^2\int_{\Delta f=-\infty}^{\infty}\frac{2\beta}{\beta^2+(2\pi\cdot\Delta f)^2}d\Delta f \\ &= |X_n|^2\frac{1}{\pi}\arctan(\frac{2\pi \Delta f}{\beta})|_{-\infty}^{\infty} \\ &= |X_n|^2 \end{align}\]

The phase noise does not affect the total power in the signal, it only affects its distribution

  • Without phase noise, \(S_v(f)\) is a series of impulse functions at the harmonics of \(f_o\).
  • With phase noise, the impulse functions spread, becoming fatter and shorter but retaining the same total power

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[https://community.cadence.com/cadence_technology_forums/f/rf-design/51484/comparing-transient-noise-pnoise-and-pnoise-with-lorentian-approximation-of-a-ring-oscillator/1382911]


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Phase perturbed by a stationary noise with Gaussian PDF

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If keep \(\phi_{rms}\) in \(R_x(\tau)\), i.e. \[ R_x(\tau)=\frac{A^2}{2}e^{-\phi_{rms}^2}\cos(2\pi f_0 \tau)e^{R_\phi(\tau)}\approx \frac{A^2}{2}e^{-\phi_{rms}^2}\cos(2\pi f_0 \tau)(1+R_\phi(\tau)) \] The PSD of the signal is \[ S_x(f) = \mathcal{F} \{ R_x(\tau) \} = \frac{P_c}{2}e^{-\phi_{rms}^2}\left[S_\phi(f+f_0)+S_\phi(f-f_0)\right] + \frac{P_c}{2}e^{-\phi_{rms}^2}\left[\delta(f+f_0)+\delta(f-f_0)\right] \] ❗❗above Eq isn't consistent with stationary white noise process - the following section

Phase perturbed by a stationary WHITE noise process

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Assuming that the delay line is noiseless

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Expanding the cosine function we get \[\begin{align} R_y(t,\tau) &= \frac{A^2}{2}\left\{\cos(2\pi f_0\tau)E[\cos(\phi(t)-\phi(t-\tau))] - \sin(2\pi f_0\tau)E[\sin(\phi(t)-\phi(t-\tau))]\right\} \\ &+ \frac{A^2}{2}\left\{\cos(4\pi f_0(t+\tau/2-T_D))E[\cos(\phi(t)+\phi(t-\tau))] - \sin(4\pi f_0(t+\tau/2-T_D))E[\sin(\phi(t)+\phi(t-\tau))] \right\} \end{align}\]

where, both the process \(\phi(t)-\phi(t-\tau)\) and \(\phi(t)+\phi(t-\tau)\) are independent of time \(t\), i.e. \(E[\cos(\phi(t)+\phi(t-\tau))] = m_{\cos+}(\tau)\), \(E[\cos(\phi(t)-\phi(t-\tau))] = m_{\cos-}(\tau)\), \(E[\sin(\phi(t)+\phi(t-\tau))] = m_{\sin+}(\tau)\) and \(E[\sin(\phi(t)-\phi(t-\tau))] = m_{\sin-}(\tau)\)

we obtain \[\begin{align} R_y(t,\tau) &= \frac{A^2}{2}\left\{\cos(2\pi f_0\tau)m_{\cos-}(\tau) - \sin(2\pi f_0\tau)m_{\sin-}(\tau)\right\} \\ &+ \frac{A^2}{2}\left\{\cos(4\pi f_0(t+\tau/2-T_D))m_{\cos+}(\tau) - \sin(4\pi f_0(t+\tau/2-T_D))m_{\sin+}(\tau) \right\} \end{align}\]

The second term in the above expression is periodic in \(t\) and to estimate its PSD, we compute the time-averaged autocorrelation function \[ R_y(\tau) = \frac{A^2}{2}\left\{\cos(2\pi f_0\tau)m_{\cos-}(\tau) - \sin(2\pi f_0\tau)m_{\sin-}(\tau)\right\} \] image-20241207095906575

After nontrivial derivation

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Phase perturbed by a Weiner process

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The phase process \(\phi(t)\) is also gaussian but with an increasing variance which grows linearly with time \(t\)

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\[\begin{align} R_y(t,\tau) &= \frac{A^2}{2}\left\{\cos(2\pi f_0\tau)E[\cos(\phi(t)-\phi(t-\tau))] - \sin(2\pi f_0\tau)E[\sin(\phi(t)-\phi(t-\tau))]\right\} \\ &+ \frac{A^2}{2}\left\{\cos(4\pi f_0(t+\tau/2-T_D)E[\cos(\phi(t)+\phi(t-\tau))] - \sin(4\pi f_0(t+\tau/2-T_D)E[\sin(\phi(t)+\phi(t-\tau))] \right\} \end{align}\]

The spectrum of \(y(t)\) is determined by the asymptotic behavior of \(R_y(t,\tau)\) as \(t\to \infty\)

❗❗ \(\lim_{t\to\infty}R_y(t,\tau)\) rather than time-averaged autocorrelation function of cyclostationary process, ref. Demir's paper

We define \(\zeta(t, \tau)=\phi(t)+\phi(t-\tau) = \phi(t)-\phi(t-\tau) + 2\phi(t-\tau)\), the expected value of \(\zeta(t,\tau)\) is 0, the variance is \(\sigma_{\zeta}^2=(k\sigma)^2(\tau + 4(t-\tau))=(k\sigma)^2(4t-3\tau)\) \[ E[\cos(\zeta(t,\tau))]=\frac{1}{\sqrt{2\pi \sigma_{\zeta}^2}}\int_{-\infty}^{\infty}e^{-\zeta^2/2\sigma_{\zeta}^2}\cos(\zeta)d\zeta = e^{-\sigma_{\zeta}^2/2}=e^{-(k\sigma)^2(4t-\tau)} \] i.e., \(\lim _{t\to \infty} E[\cos(\zeta(t,\tau))] = \lim_{t\to \infty}e^{-(k\sigma)^2(4t-\tau)} = 0\)

For \(E[\sin(\zeta(t,\tau))]\), we have \[ E[\sin(\zeta(t,\tau))] = \frac{1}{\sqrt{2\pi \sigma_{\zeta}^2}}\int_{-\infty}^{\infty}e^{-\zeta^2/2\sigma_{\zeta}^2}\sin(\zeta)d\zeta \] i.e., \(E[\sin(\zeta(t,\tau))]\) is odd function, therefore \(E[\sin(\zeta(t,\tau))]=0\)

Finally, we obtain

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Amplitude Noise

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P.E. Allen - 2003. ECE 6440 - Frequency Synthesizers: Lecture 160 – Phase Noise - II [https://pallen.ece.gatech.edu/Academic/ECE_6440/Summer_2003/L160-PhNoII(2UP).pdf]

reference

A. Hajimiri and T. H. Lee, "A general theory of phase noise in electrical oscillators," in IEEE Journal of Solid-State Circuits, vol. 33, no. 2, pp. 179-194, Feb. 1998 [paper], [slides]

—, "Corrections to "A General Theory of Phase Noise in Electrical Oscillators"" [https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=678662]

—, RFIC2024 "Noise in Oscillators from Understanding to Design"

Carlo Samori, "Phase Noise in LC Oscillators: From Basic Concepts to Advanced Topologies" [https://www.ieeetoronto.ca/wp-content/uploads/2020/06/DL-VCO-short.pdf]

—, "Understanding Phase Noise in LC VCOs: A Key Problem in RF Integrated Circuits," in IEEE Solid-State Circuits Magazine, vol. 8, no. 4, pp. 81-91, Fall 2016 [https://picture.iczhiku.com/resource/eetop/whIgTikLswaaTVBv.pdf]

—, ISSCC2016, "Understanding Phase Noise in LC VCOs"

Antonio Liscidini, ESSCIRC 2019 Tutorials: Phase Noise in Wireless Applications [https://youtu.be/nGmQ0JdoSE4]

A. Demir, A. Mehrotra and J. Roychowdhury, "Phase noise in oscillators: a unifying theory and numerical methods for characterization," in IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol. 47, no. 5, pp. 655-674, May 2000 [https://sci-hub.se/10.1109/81.847872]

Dalt, Nicola Da and Ali Sheikholeslami. "Understanding Jitter and Phase Noise: A Circuits and Systems Perspective." (2018) [https://picture.iczhiku.com/resource/eetop/WykRGJJoHQLaSCMv.pdf]

F. L. Traversa, M. Bonnin and F. Bonani, "The Complex World of Oscillator Noise: Modern Approaches to Oscillator (Phase and Amplitude) Noise Analysis," in IEEE Microwave Magazine, vol. 22, no. 7, pp. 24-32, July 2021 [https://iris.polito.it/retrieve/handle/11583/2903596/e384c433-b8f5-d4b2-e053-9f05fe0a1d67/MM%20noise%20-%20v5.pdf]

Poddar, Ajay & Rohde, Ulrich & Apte, Anisha. (2013). How Low Can They Go?: Oscillator Phase Noise Model, Theoretical, Experimental Validation, and Phase Noise Measurements. Microwave Magazine, IEEE. [http://time.kinali.ch/rohde/noise/how_low_can_they_go-2013-poddar_rohde_apte.pdf]

Pietro Andreani, "RF Harmonic Oscillators Integrated in Silicon Technologies" [https://www.ieeetoronto.ca/wp-content/uploads/2020/06/DL-Toronto.pdf]

Chembiyan T, "Brownian Motion And The Oscillator Phase Noise" [link]

—, "Jitter and Phase Noise in Oscillators" [link]

—, "Jitter and Phase Noise in Phase Locked Loops" [link]

—, "PLLs and reference spurs" [link]

Godone, A. & Micalizio, Salvatore & Levi, Filippo. (2008). RF spectrum of a carrier with a random phase modulation of arbitrary slope. [https://sci-hub.se/10.1088/0026-1394/45/3/008]

Bae, Woorham; Jeong, Deog-Kyoon: 'Analysis and Design of CMOS Clocking Circuits for Low Phase Noise' (Materials, Circuits and Devices, 2020)