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signal processing Signal processing is an electrical engineering subfield that focuses on analyzing, modifying and synthesizing ''signals'', such as audio signal processing, sound, image processing, images, Scalar potential, potential fields, Seismic tomograph ...
, phase noise is the frequency-domain representation of random fluctuations in the phase of a
waveform In electronics, acoustics, and related fields, the waveform of a signal is the shape of its Graph of a function, graph as a function of time, independent of its time and Magnitude (mathematics), magnitude Scale (ratio), scales and of any dis ...
, corresponding to
time-domain In mathematics and signal processing, the time domain is a representation of how a signal, function, or data set varies with time. It is used for the analysis of function (mathematics), mathematical functions, physical signal (information theory), ...
deviations from perfect periodicity (
jitter In electronics and telecommunications, jitter is the deviation from true periodicity of a presumably periodic signal, often in relation to a reference clock signal. In clock recovery applications it is called timing jitter. Jitter is a signifi ...
). Generally speaking,
radio-frequency Radio frequency (RF) is the oscillation rate of an alternating electric current or voltage or of a magnetic, electric or electromagnetic field or mechanical system in the frequency range from around to around . This is roughly between the ...
engineers speak of the phase noise of an oscillator, whereas digital-system engineers work with the jitter of a clock.


Definitions

An ideal oscillator would generate a pure
sine wave A sine wave, sinusoidal wave, or sinusoid (symbol: ∿) is a periodic function, periodic wave whose waveform (shape) is the trigonometric function, trigonometric sine, sine function. In mechanics, as a linear motion over time, this is ''simple ...
. In the frequency domain, this would be represented as a single pair of
Dirac delta function In mathematical analysis, the Dirac delta function (or distribution), also known as the unit impulse, is a generalized function on the real numbers, whose value is zero everywhere except at zero, and whose integral over the entire real line ...
s (positive and negative conjugates) at the oscillator's frequency; i.e., all the signal's power is at a single frequency. All real oscillators have phase modulated
noise Noise is sound, chiefly unwanted, unintentional, or harmful sound considered unpleasant, loud, or disruptive to mental or hearing faculties. From a physics standpoint, there is no distinction between noise and desired sound, as both are vibrat ...
components. The phase noise components spread the power of a signal to adjacent frequencies, resulting in noise sidebands. Consider the following noise-free signal: :x(t)= A\cos(2 \pi f_0 t) Phase noise is added to this signal by adding a
stochastic process In probability theory and related fields, a stochastic () or random process is a mathematical object usually defined as a family of random variables in a probability space, where the index of the family often has the interpretation of time. Sto ...
represented by \phi(t) to the signal as follows: :x(t)= A\cos(2 \pi f_0 t + \phi (t)) Different phase noise processes, \phi(t), possess different power Spectral density (PSD). For example, a white noise PSD follows a f^0 trend, a pink noise PSD follows a f^ trend, and a brown noise PSD follows a f^ trend. \operatorname_(f) is the single-sided (f>0) phase noise PSD \left \frac \right, given by the
Fourier transform In mathematics, the Fourier transform (FT) is an integral transform that takes a function as input then outputs another function that describes the extent to which various frequencies are present in the original function. The output of the tr ...
of the Autocorrelation of the phase noise. : \operatorname_(f) = \mathcal\left \operatorname \left[ \phi(t)\overline \rightright">\phi(t)\overline_\right.html" ;"title="\operatorname \left[ \phi(t)\overline \right">\operatorname \left[ \phi(t)\overline \rightright The noise can also be represented at the single-sided (f>0) frequency noise PSD, \operatorname_(f) \left \frac \right, or the fractional frequency stability PSD, \operatorname_(f) \left \frac \right, which defines the frequency fluctuations in terms of the deviation from the carrier frequency, f_0. : \operatorname_(f) = f^2\operatorname_(f) : \operatorname_(f) = \frac = \frac The phase noise can also be given as the spectral purity, \mathcal\left(f\right) \left[ \frac \right], the single-sideband power in a 1Hz bandwidth at a frequency offset, f, from the carrier frequency, f_0, referenced to the carrier power. : \mathcal\left(f\right) = 10\log_ \left( \frac \right)


Jitter conversions

Phase noise is sometimes also measured and expressed as a power obtained by integrating over a certain range of offset frequencies. For example, the phase noise may be −40 dBc integrated over the range of 1 kHz to 100 kHz. This integrated phase noise (expressed in degrees) can be converted to jitter (expressed in seconds) using the following formula: :\text) = \frac In the absence of 1/f noise in a region where the phase noise displays a –20dBc/decade slope ( Leeson's equation), the RMS cycle jitter can be related to the phase noise by: : \sigma^2_c = \frac Likewise: : \mathcal\left(f\right) = \frac


Measurement

Phase noise can be measured using a spectrum analyzer if the phase noise of the device under test (DUT) is large with respect to the spectrum analyzer's
local oscillator In electronics, the term local oscillator (LO) refers to an electronic oscillator when used in conjunction with a Frequency mixer, mixer to change the frequency of a signal. This frequency conversion process, also called Heterodyne, heterodyning ...
. Care should be taken that observed values are due to the measured signal and not the shape factor of the spectrum analyzer's filters. Spectrum analyzer based measurement can show the phase-noise power over many decades of frequency; e.g., 1 Hz to 10 MHz. The slope with offset frequency in various offset frequency regions can provide clues as to the source of the noise; e.g., low frequency flicker noise decreasing at 30 dB per decade (= 9 dB per octave). Phase noise measurement systems are alternatives to spectrum analyzers. These systems may use internal and external references and allow measurement of both residual (additive) and absolute noise. Additionally, these systems can make low-noise, close-to-the-carrier, measurements.


Linewidths

The sinusoidal output of an ideal oscillator is a
Dirac delta function In mathematical analysis, the Dirac delta function (or distribution), also known as the unit impulse, is a generalized function on the real numbers, whose value is zero everywhere except at zero, and whose integral over the entire real line ...
in the power spectral density centered at the frequency of the sinusoid. Such perfect spectral purity is not achievable in a practical oscillator. Spreading of the spectrum line caused by phase noise is characterized by the fundamental linewidth and the integral linewidth. The fundamental linewidth, also known as the White noise-limited linewidth or the intrinsic linewidth, is the linewidth of an oscillator's PSD in the presence of only white noise sources (noise with a PSD that follows a f^0 trend, ie. equivalent across all frequencies). The fundamental linewidth takes Lorentzian spectral line shape. White noise provides a 1/\sqrt Allan Deviation plot at small averaging times. The integral linewidth, also known as the effective linewidth or the total linewidth, is the linewidth of an oscillator's PSD in the presence of both white noise sources (noise with a PSD that follows a f^0 trend) and pink noise sources (noise with a PSD that follows a f^ trend). Pink noise is sometimes called Flicker noise, or simply 1/f noise. The integral linewidth takes Voigt lineshape, a convolution of the white noise-induced Lorentzian lineshape and the pink noise-induced Gaussian lineshape. Pink noise provides a \tau^ Allan Deviation plot at moderate averaging times. This flat line on the Allan Deviation plot is also known as the flicker floor. Additionally, the oscillator might experience Frequency drift over long periods of time, slowly moving the center frequency of the Voigt lineshape. This drift is a brown noise source (noise with a PSD that follows a f^ trend), and provides a \sqrt Allan Deviation plot at large averaging times.


Limiting System Performance

A laser is a common oscillator that is characterized by its noise, and thus its Laser linewidth. The laser noise provides fundamental limitations of the systems that the laser is used in, such as loss of sensitivity in radar and communications systems, lack of definition in imaging systems, and a higher bit error rate in digital systems. Lasers with a near-
Infrared Infrared (IR; sometimes called infrared light) is electromagnetic radiation (EMR) with wavelengths longer than that of visible light but shorter than microwaves. The infrared spectral band begins with the waves that are just longer than those ...
center wavelength are used in many
atomic, molecular, and optical physics Atomic, molecular, and optical physics (AMO) is the study of matter–matter and light–matter interactions, at the scale of one or a few atoms and energy scales around several electron volts. The three areas are closely interrelated. AMO th ...
experiments to provide photons that interact with atoms. The requirements for the spectral purity at specific frequency offsets of the lasers used in qubit operation (such as clock transition lasers and state preparation lasers) are highly stringent because the coherence time of the qubit is directly related to the linewidth of the lasers.


See also

*
Allan variance The Allan variance (AVAR), also known as two-sample variance, is a measure of frequency stability in clocks, oscillators and amplifiers. It is named after David W. Allan and expressed mathematically as \sigma_y^2(\tau). The Allan deviation (ADEV ...
* Flicker noise * Leeson's equation * Maximum time interval error * Noise spectral density * Spectral density * Spectral phase * Opto-electronic oscillator


References


Further reading

* * * * * * * * Ulrich L. Rohde, A New and Efficient Method of Designing Low Noise Microwave Oscillators, https://depositonce.tu-berlin.de/bitstream/11303/1306/1/Dokument_16.pdf * Ajay Poddar, Ulrich Rohde, Anisha Apte, “ How Low Can They Go, Oscillator Phase noise model, Theoretical, Experimental Validation, and Phase Noise Measurements”, IEEE Microwave Magazine, Vol. 14, No. 6, pp. 50–72, September/October 2013. * Ulrich Rohde, Ajay Poddar, Anisha Apte, “Getting Its Measure”, IEEE Microwave Magazine, Vol. 14, No. 6, pp. 73–86, September/October 2013 * U. L. Rohde, A. K. Poddar, Anisha Apte, “Phase noise measurement and its limitations”, Microwave Journal, pp. 22–46, May 2013 * A. K. Poddar, U.L. Rohde, “Technique to Minimize Phase Noise of Crystal Oscillators”, Microwave Journal, pp. 132–150, May 2013. * A. K. Poddar, U. L. Rohde, and E. Rubiola, “Phase noise measurement: Challenges and uncertainty”, 2014 IEEE IMaRC, Bangalore, Dec 2014. {{DEFAULTSORT:Phase Noise Oscillators Frequency-domain analysis Telecommunication theory Noise (electronics)