5.2.noise types
DESCRIPTION
+ D x. Matching. Influence. 5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.Noise types. In order to reduce errors, the measurement object and the measurement system should be matched not only in terms of output and input impedances, but also in terms of noise. x. Measurement Object. - PowerPoint PPT PresentationTRANSCRIPT
1
In order to reduce errors, the measurement object and the
measurement system should be matched not only in terms of
output and input impedances, but also in terms of noise.
5.2. Noise types
5. SOURCES OF ERRORS. 5.2. Noise types
The purpose of noise matching is to let the measurement
system add as little noise as possible to the measurand.
We will treat the subject of noise matching in Section 5.4.
Before that, we have to describe in Sections 5.2 and 5.3 the
most fundamental types of noise and its characteristics.
Influence
Measurement System
Measurement Object
Mat
chin
g
+ xx
2MEASUREMENT THEORY FUNDAMENTALS. Contents
5. Sources of errors
5.1. Impedance matching
5.4.1. Anenergetic matching
5.4.2. Energic matching
5.4.3. Non-reflective matching
5.4.4. To match or not to match?
5.2. Noise types
5.2.1. Thermal noise
5.2.2. Shot noise
5.2.3. 1/f noise
5.3. Noise characteristics
5.3.1. Signal-to-noise ratio, SNR
5.3.2. Noise factor, F, and noise figure, NF
5.3.3. Calculating SNR and input noise voltage from NF
5.3.4. VnIn noise model
5.4. Noise matching5.4.1. Optimum source resistance
5.4.2. Methods for the increasing of SNR
5.4.3. SNR of cascaded noisy amplifiers
3
Reference: [1]
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
5.2.1. Thermal noise
Thermal noise is observed in any system having thermal losses
and is caused by thermal agitation of charge carriers.
Thermal noise is also called Johnson-Nyquist noise. (Johnson,
Nyquist: 1928, Schottky: 1918).
An example of thermal noise can be thermal noise in resistors.
4
vn(t)
tf (vn)
vn(t)
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
R V
6
Vn
Example: Resistor thermal noise
T 0
2R()
0
White (uncorrelated) noise
en2
f0
Normal distribution according to thecentral limit theorem
5
C
T
enC
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
To calculate the thermal noise power density, enR2( f ), of a
resistor, which is in thermal equilibrium with its surrounding, we
temporarily connect a capacitor to the resistor.
R
Ideal, noiseless resistor
Noise source
Real resistor
A. Noise description based on the principles of
thermodynamics and statistical mechanics (Nyquist, 1828)
From the point of view of thermodynamics, the resistor and the
capacitor interchange energy:
enR
T
65. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
m v
2
2
Each particle has three degrees of freedom
mivi 2
2
mi vi 2
2=
m v 2
2= 3
k T2
In thermal equilibrium:
x
z
Illustration: The law of the equipartition of energy
y
75. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
Illustration: Resistor thermal noise pumps energy into the capacitor
Each particle (mechanical equivalents of electrons in the resistor) has three degrees of freedom
CV
2
2
mivi 2
2
C VC 2
2=
k T2
In thermal equilibrium:
The particle (a mechanical equivalent of the capacitor) has a single degree of freedom
x
y
z
85. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
Since the obtained dynamic first-order circuit has a single
degree of freedom, its average energy is kT/2.
This energy will be stored in the capacitor:
H( f )= enC ( f )
enR ( f )
C VC 2
2=
k T2
In thermal equilibrium:
C
T
enC
R
Ideal, noiseless resistor
Noise source
Real resistor
enR
T
9
kTC
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
= =nC 2 =
C nC 2
2
kT
2
kT
C
C vnC (t) 2
2
0
According to the Wiener–Khinchin theorem (1934), Einstein
(1914),
enR 2( f ) H(j2 f)2
e j 2 f d f
nC 2 RnC () =
1 d f0
enR2( f )
1) +2 f RC(2
enR2( f )
4 RC
enR2( f ) = 4 k T R [V2/Hz].
Power spectral density of resistor noise:
C VC 2
2=
10
SHF EHF IR R
10 GHz 100 GHz 1 THz 10 THz 100 THz 1 GHz
1
0.2
0.4
0.6
0.8
enR P( f )2
enR( f )2
f
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
enR P 2( f ) = 4 R [V2/Hz] .
B. Noise description based on Planck’s law for blackbody
radiation (Nyquist, 1828)
h f
eh f /k T 1
A comparison between the two Nyquist equations:
R = 50 ,C f 0.04 = F
= R 50 ,C = 0.04 f F
115. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
The Nyquist equation was extended to a general class of
dissipative systems other than merely electrical systems:
eqn2( f ) = 4 R + [V2/Hz]
h f
eh f / k T 1
Zero-point energy f(T)
h f
2
C. Noise description based on quantum mechanics
(Callen and Welton, 1951)
eqn ( f )2
enR ( f )2
SHF EHF IR R
10 GHz 100 GHz 1 THz 10 THz 100 THz 1 GHz f0
2
4
6
8
Quantum noise
12
The ratio of the temperature dependent and temperature
independent parts of the Callen-Welton equation shows that at 0
K and f 0 there still exists some noise compared to the Nyquist
noise level at T0 = 290 K (standard temperature: k T0 =
4.001021)
10 Log [dB]2
eh f / k Tstd 1
f, Hz
Remnant noise at 0 K, dB
103 106 109
-20
-40
-60
-80
-100
-120
0
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
100
13
An equivalent noise bandwidth, B , is defined as the bandwidth
of an equivalent-gain ideal rectangular filter that would pass as
much power of white noise as the filter in question:
D. Equivalent noise bandwidth, B
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
B d
f.
0
IA( f )I2
IAmax I2
IA( f )I2
IAmax I2
f
1
0.5
B
ff
B
linear scale
Equal areas Equal areas
Lowpass Bandpass
0
14
R
C
en o( f )
fc = = f3dB 1
2 RC
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
=en in2 0.5 fc
Vn o 2 = en o
2( f ) d f 0
= en in2H( f )2 d f
0
Example: Equivalent noise bandwidth of an RC filter
=en in2
1
1) + f / fc (2d f
0
Vn o 2 = en in
2 B
enR
15
fc
2 4 6 8 10
1
Equal areas
1
0.5
f /fc
B = 0.5 fc 1.57 fc R
C
en o
0
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
en o2
en in2
0.01 0.1 1 10 100
0.1
1
f /fc
fc
B
0.5 Equal areas
en o2
en in2
fc = = f3dB 1
2 RC
Example: Equivalent noise bandwidth of an RC filter
en in
16
Two first-order independent stages B = 1.22 fc.
Butterworth filters:
H( f )2= 1
1 ) +f / fc (2n
Example: Equivalent noise bandwidth of higher-order filters
First-order RC low-pass filterB = 1.57 fc.
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
second order B = 1.11 fc.
third order B = 1.05 fc.
fourth order B = 1.025 fc.
17
Amplitude spectral density of noise, rms/Hz0.5:
en = 4 k T R [V/Hz].
Noise voltage, rms:
Vn = 4 k T R [V].
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
en = 0.13R [nV/Hz].
At room temperature:
18
Vn = 4 k T 1k 1Hz 4 nV
Vn = 4 k T 50 1Hz 0.9 nV
Vn = 4 k T 1M 1MHz 128 V
Examples:
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
19
1) First-order filtering of the Gaussian white noise.
Input noise pdf Input and output noise spectra
Output noise pdf Input and output noise vs. time
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
E. Normalization of the noise pdf by dynamic networks
20
Input noise pdf Input noise autocorrelation
Output noise pdf Output noise autocorrelation
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
1) First-order filtering of the Gaussian white noise.
21
Input noise pdf Input and output noise spectra
Output noise pdf Input and output noise vs. time
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
2) First-order filtering of the uniform white noise.
22
Input noise pdf Input noise autocorrelation
Output noise pdf Output noise autocorrelation
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
2) First-order filtering of the uniform white noise.
23
Different units can be chosen to describe the spectral density of
noise: mean square voltage (for the equivalent Thévenin noise
source), mean square current (for the equivalent Norton noise
source), and available power.
F. Noise temperature, Tn
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
R
en( f )
R in( f )
R na( f )
en2 = 4 k T R [V2/Hz],
in2 = 4 k T/ R [A2/Hz],
na k T [W/Hz] . en
2
4 R en( f )
24
Any thermal noise source has available power spectral density
na( f ) k T , where T is defined as the noise temperature, T Tn.
It is a common practice to characterize other, nonthermal
sources of noise, having available power that is unrelated to a
physical temperature, in terms of an equivalent noise
temperature Tn:
Tn ( f ) .
na ( f )
k
Then, given a source's noise temperature Tn,
na ( f ) kTn ( f ) .
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
na( f )
en( f )
Nonthermal sources of noise
25
l
Example A: Noise temperatures of nonthermal noise sources
1. Environmental noise: Tn(1 MHz) can be as great as 3108 K.
2. Antenna noise temperature:
T
vn2( f ) = 320 2(l/)2
k T [J/Hz]= 4 k Ta R[V2/Hz]
l
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
R= 80 2(l/)2 [] is the radiation resistance.
Reference: S. I. Baskakov.
26
Example B: Antenna noise temperature, Ta (sky contribution only)
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
101 103 105 107100 102 104 106 108 109
Frequency, MHz
A
nten
na
noi
se t
empe
ratu
re, T a
(K)
100
101
102
103
104
300
Quantum noise limitTQ h f / k
O2
H2O
S. Okwit, “An historical view of the evolution of low-noise concepts and techniques,” IEEE Trans. MT&T, vol. 32, pp. 1068-1082, 1984.
Galactic noise limitTG 100 2.4
275. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
Example C: Noise performance of any antenna/receiving system, Top
l
Ta RS
vS
ReceiverAntenna
G
Noiseless
Ta + Te
Tais the antenna noise temperature, K,
Teis the effective input receiver temperature, K,
Top= Ta+Teis the operating noise temperature, K.
Compare: a 75 K receiver versus a 80 K receiver, vis-à-vis
a 0.999dBreceiver versus a 1.058dB receiver.
S. Okwit, “An historical view of the evolution of low-noise concepts and techniques,” IEEE Trans. MT&T, vol. 32, pp. 1068-1082, 1984.
28
We will show in this section that in thermal equilibrium any
system that dissipates power generates thermal noise; and
vice versa, any system that does not dissipate power does not
generate thermal noise.
For example, ideal capacitors and inductors do not dissipate
power and then do not generate thermal noise.
To prove the above, we will show that the following circuit can
only be in thermal equilibrium if enC = 0.
G. Thermal noise in capacitors and inductors
R C
Reference: [2], pp. 230-231
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
enR enC
T T
29
Reference: [2], p. 230
In thermal equilibrium, the average power that the resistor
delivers to the capacitor, PRC, must equal the average power that
the capacitor delivers to the resistor, PCR. Otherwise, the
temperature of one component increases and the temperature of
the other component decreases.
PRC is zero, since the capacitor cannot dissipate power. Hence,
PCR should also be zero: PCR [enC( f ) HCR( f ) ]2/R where
HCR( f ) R /(1/j2f+R). Since HCR( f ) , enC ( f ) .
R C
f f
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
enR enC
PRC
PCR
T T
30
Ideal capacitors and inductors do not generate any thermal
noise. However, they do accumulate noise generated by
other sources.
For example, the noise power at a capacitor that is connected to
an arbitrary resistor value equals kT/C:
Reference: [5], p. 202
R
C VnC
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
H. Noise power at a capacitor
VnC 2
= enR2H( f )2 d f
0
4 k T RB
4 k T R 0.5 1
2 RC
VnC 2
k T
C
enR
T
31
The rms voltage VnC across the capacitor does not depend on
the value of the resistor because small resistances have less
noise spectral density but result in a wide bandwidth, compared
to large resistances, which have reduced bandwidth but larger
noise spectral density.
To lower the rms noise level across a capacitors, either
capacitor value should be increased or temperature should be
decreased.
Reference: [5], p. 203
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.1. Thermal noise
VnC 2
kT
C
R
C VnC
enR
T
33
Shot noise (Schottky, 1918) results
from the fact that the current is not a
continuous flow but the sum of
discrete pulses, each corresponding
to the transfer of an electron through
the conductor. Its spectral density is
proportional to the average current
and is characterized by a white
noise spectrum up to a certain
frequency, which is related to the
time taken for an electron to travel
through the conductor.
In contrast to thermal noise, shot
noise cannot be reduced by lowering
the temperature.
Reference: Physics World, August 1996, page 22
5.2.2. Shot noise
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
D
I
ii
www.discountcutlery.net
34
D
Reference: [1]
I
t
i
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
Illustration: Shot noise in a diode
35
D
Reference: [1]
I
t
i
Illustration: Shot noise in a diode
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
I
36
A. Statistical description of shot noise
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
We start from defining n as the average number of electrons
passing the pn junction of a diode during one second, hence,
the average electron current I = q n.
We assume that the probability of passing two or more
electrons simultaneously is negligibly small, P>1(d t) 0. This
allows us to define the probability that an electron passes the
junction in the time interval d t = (t, t + d t) as P1(d t) n d t
(d t is approaching the time taken for an electron to travel
over the junction, < 1 ns).
v t
37
Next, we derive the probability that no electrons pass the
junction in the time interval (0, t + d t):
P0(t + d t ) = P0(t) P0(d t) = P0(t) [1 P1(d t)] = P0(t) P0(t) n d t.
This yields:
with the obvious initiate state P0(0) = 1.
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
= n P0
d P0
d t
38
This yields
with the obvious initiate state P1(0) = 0.
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
The probability that an electron passes the junction in the time
interval (0, t + d t)
P1(t + d t ) = P1(t) P0(d t) + P0(t) P1(d t)
= P1(t) (1 n d t) + P0(t) n d t .
= n P1 + n P0
d P1
d t
39
In the same way, one can obtain the probability of passing the
junction electrons:
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
= n PN + n PN 1
d PN
d t
PN (0) = 0
.
which corresponds to the Poisson probability distribution.
PN (t) = e n t ,)n t( N
N !
By substitution, one can verify that
40
0 5 10 15 20
0.02
0.04
0.06
0.08
0.1
0.12
0.14
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
Illustration: Poisson probability distribution
PN (t) e nt)nt( N
N !
N
n = 10t = 1
v t
41
0 5 10 15 20
0.02
0.04
0.06
0.08
0.1
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
Illustration: Poisson probability distribution
PN (t) e nt)nt( N
N !
N
n = 10t = 0.01
v t
42
The average number of electrons passing the junction during a
time interval (0,) can be found as follows:
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
N = N e n = n e n = n,
)n( N
N !
and the average squared number can be found as follows:
N = 0
)n( N 1
)N 1( !N = 1
N 2
= N 2 e n = [N (N 1) + N ] e n
)n( N
N !N = 0
N = 0
)n( N
N !
=ne n n= nn. N = 2
)n ( N 2
)N 2( !
=e n
43
We now can find the average current of the electrons, I, and its
variance, irms2:
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
I = = q n,
in rms2 .
The variance of the electron flow during the time interval can
be found as follows:
N2 = N
2 N)2 = n.
q N
q N
2 q
2 n
2
q I
44
i
t
?
The highest noise frequency waveform
The maximum measurement time ?
21/B
Let us suppose that we measure the shot noise at the
output of an ideal low-pass filter. Then according to the
Nyquist criterion:
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
IA( f )I
fB
Illustration: The relationship between and B
1/2B
Noise bandwidth
I = q n
q I
in rms
in z-p
45
Hence, the spectral density of the shot noise
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
in rms2 = 2 q B.
in( f ) = 2 q .
B. Spectral density of shot noise
Assuming = 1/( 2 B), we finally obtain the Schottky equation
for shot noise rms current
465. SOURCES OF ERRORS. 5.2. Noise types. 5.2.2. Shot noise
C. Shot noise in resistors and semiconductor devices
Through a pn junction (or any other potential barrier), the
electrons are transmitted randomly and independently of each
other. Thus the transfer of electrons can be described by Poisson
statistics. In this case, the shot noise has its maximum value at
in2( f ) = 2 q I.
Shot noise is absent in a macroscopic, metallic resistor because
the ubiquitous inelastic electron-phonon scattering smoothes out
current fluctuations that result from the discreteness of the
electrons, leaving only thermal noise.
Shot noise does exist in mesoscopic (nm) resistors, although at
lower levels than in a diode junction. For these devices the length
of the conductor is short enough for the electron to become
correlated, a result of the Pauli exclusion principle. This means
that the electrons are no longer transmitted randomly, but
according to sub-Poissonian statistics.
Reference: Physics World, August 1996, page 22
47
The most general type of excess noise is 1/f or flicker noise.
This noise has approximately 1/f power spectrum (equal power
per decade of frequency) and is sometimes also called pink
noise.
1/f noise is usually related to the fluctuations of the device
properties caused, for example, by electric current in resistors
and semiconductor devices.
Curiously enough, 1/f noise is present in nature in unexpected
places, e.g., the speed of ocean currents, the flow of traffic on
an expressway, the loudness of a piece of classical music
versus time, and the flow of sand in an hourglass.
Reference: [3]
5.2.3. 1/f noise
Thermal noise and shot noise are irreducible (ever present)
forms of noise. They define the minimum noise level or the
‘noise floor’. Many devices generate additional or excess noise.
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.3. 1/f noise
No unifying principle has been found for all the 1/f noise sources.
48
References: [4] and [5]
In electrical and electronic devices, flicker noise occurs only
when electric current is flowing.
In semiconductors, flicker noise usually arises due to traps,
where the carriers that would normally constitute dc current
flow are held for some time and then released.
Although bipolar, JFET, and MOSFET transistors have flicker
noise, it is a significant noise source in MOS transistors,
whereas it can often be ignored in bipolar transistors (and some
modern JFETs).
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.3. 1/f noise
49
An important parameter of 1/f noise is its corner frequency, fc,
where the power spectral density equals the white noise level.
A typical value of ff is 100 Hz to 1 kHz (MOSFET: 100 kHz).
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.3. 1/f noise
f, decades
in ( f ), dB
ff
White noise
Pink noise
10 dB/decade
50
References: [4] and [5]
Flicker noise is directly proportional to the dc (or average)
current flowing through the device:
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.3. 1/f noise
in2( f )
where Kf is a constant that depends on the type of material,
1 < m < 3, and 1 < n < 3.
Kf m
I m
f n
515. SOURCES OF ERRORS. 5.2. Noise types. 5.2.3. 1/f noise
For example, the spectral power density of 1/f noise in resistors
is in inverse proportion to their power dissipating rating. This is
so, because the resistor current density decreases with square
root of its power dissipating rating.
in 1W ( f )
Kf I
f 0.5
Example: Let us compare 1/f noise in 1 , 1 W and 1 , 9 W resistors
for the same dc current:
1 9 W
1 Ain 9W
( f ) ?
1 1 W
1 A
525. SOURCES OF ERRORS. 5.2. Noise types. 5.2.3. 1/f noise
1 9 W
1 Ain 9W
( f ) ?
1/3 A1 A
in 1W / 3 {3)]in 1W/ 3·(1[2}0.5 in 1W/ 30.5
3
53
{3)]in 1W/ 30.5/( 3[2}0.5 in 1W/( 30.5·3)
5. SOURCES OF ERRORS. 5.2. Noise types. 5.2.3. 1/f noise
3
1 9 W
1 A
in 9W ( f ) = }3[(in 1W/( 30.5·3)]2{0.5 in 1W/3
in 9W 2( f ) = in 1W
2( f )/9
f, decadesff (9 W)
White noise
in 1W2( f ), dB
Pink noise1 1 W
1 9 W
ff (1 W)
545. SOURCES OF ERRORS. 5.2. Noise types. 5.2.3. 1/f noise
Example: A simulation of 1/f noise
Input Gaussian white noise Input noise PSD
Output 1/f noise Output noise PSD
555. SOURCES OF ERRORS. 5.2. Noise types. 5.2.3. 1/f noise
Example: A simulation of 1/f noise
Filter
0 +1 ij
1kR
10kfc C
1/(2*pi*x) RC
j(2 pi i ) j(2 pi i )RC
1u
1
0
Real
0
100000
2 1
20
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