A transmission line based technique for de-embedding noise parameters

A Transmission-Line Based Technique for De-Embedding Noise Parameters
Kenneth H. K. Yau∗, Alain M. Mangan∗, Pascal Chevalier†, Peter Schvan‡, and Sorin P. Voinigescu∗
∗Department of Electrical and Computer Engineering,
University of Toronto, 10 King’s College Rd., Toronto ON, M5S 3G4, Canada
†STMicroelectronics, 850 rue Jean Monnet, F-38926 Crolles, France
‡NORTEL, 3500 Carling Ave., Ottawa ON, K2H 8E9, Canada
Abstract— A transmission line-based de-embedding technique
for on-wafer S parameter measurements is extended to the
noise parameters of MOSFETs and HBTs. Since it accounts
for the distributed effects of interconnect lines and for the pad-
interconnect discontinuity, it is expected to yield more accurate
results at high frequencies than existing approaches. Further-
more, by requiring only two transmission line test structures to
de-embed all test structures in a (Bi)CMOS process, it is one
of the most area-efficient. Experimental validation is provided
on 90 nm and 130 nm n-MOSFETs and SiGe HBTs and its
accuracy is compared with that of other lumped or distributed
de-embedding techniques.
I. INTRODUCTION
Accurate characterization of the noise parameters of active
devices relies on the complete removal of test structure par-
asitics from the measured data. The limitations of a lumped-
element approach and the need to account for the distributed
nature of the interconnect linking the pads with the device have
been recognized and different techniques have recently been
developed based on a cascade configuration [1], [2] and a four-
port parasitic model [3]. Although the techniques in [1], [3]
account for the distributed effects, they require, respectively,
three and five de-embedding structures for each device to be
characterized. This results in a large area overhead, long test-
ing times and becomes very expensive in nano-scale CMOS
technologies. This paper expands on a recently proposed
transmission line characterization technique [4], [5], to present
a noise parameter de-embedding method that requires only two
dummy structures to characterize the noise parameters of all
the test structures fabricated on a wafer. The new technique
differs from that in [2] in the method employed to obtain the
characteristic impedance (ZC) and the propagation constant
(γ) of the transmission line. It is experimentally validated on
130 nm and 90 nm n-MOSFETs and on SiGe HBTs with fT ’s
of 150 GHz and 230 GHz, respectively, from two generations
of 130 nm SiGe BiCMOS processes [6], [7].
II. THEORY
A transistor test structure can be represented as a cascade
of three two-port networks as shown in Fig. 1. The electrical
and noise properties of the input and output networks, which
are composed of the probe pads and the interconnects leading
to the transistor, are described by their two-port network
parameters and noise correlation matrices [8], with the notation
defined in Fig. 1. The transistor is represented by its own
two-port parameters and noise correlation matrix, Ci
T. Two-
Input
Device
Output
Network Network
Electrical:
Noise:
YIN YT YOUT
Ci
IN Ci
T Ci
OUT
YDUT Ci
DUT
Fig. 1. A test structure modelled as a cascade of two-port networks. The
superscript “i” denotes the representation (A: chain, Y : admittance, etc.) of
the noise correlation matrix.
GSG
GSG
GSG
GSG
(a) (b)
(c)
GSG
GSG
DEVICE
lS
lL
l1 l2
YLEFT YRIGHT
Fig. 2. Test structures required for noise parameter de-embedding. (a) short
transmission line, (b) transistor test structure utilizing interconnects with the
same width at the in the input and output ports, and (c) long transmission
line.
port parameter and noise correlation matrix conversions are
assumed implicitly for a concise presentation. For instance,
both YT and AT represent the transistor, but one is a Y -
parameter representation and the other is an ABCD parameter
representation, likewise for CY
T and CA
T. Noise correlation
matrix conversions are accomplished using the formulae in [8].
Figure2 describes the dummy structures required for de-
embedding and defines relevant symbols.
The noise parameter de-embedding technique can be sep-
arated into three major steps: (1) de-embedding the probe

pads from the transmission line test structures to obtain the
characteristic impedance (ZC) and propagation constant (γ),
(2) splitting the short transmission line into two halves as
illustrated in Fig. 2(a) and determining the matrices YLEFT
and YRIGHT, and (3) calculate the electrical and noise
matrices of the input and output networks (i.e. YIN/OUT
and CY
IN/OUT) and de-embed their contributions from the
measured noise parameters. The remainder of this section shall
describe each of the three steps in sequence.
A. De-embedding the Transmission Line Test Structures
For simplicity, the interconnects at the input and output of
the transistor are assumed to have the same width. A method
to remove this restriction will be illustrated at the end of the
last subsection.
In this work, the interconnects from the probe pads to the
transistor are characterized as transmission lines. ZC and γ of
the interconnects are determined from two transmission line
test structures of different lengths, but having the same width
as the interconnects, using the technique described in [4].
B. Splitting Short Transmission Line Test Structure
Splitting the short transmission line test structure and calcu-
lating the electrical matrices of the two halves form the basis
of the noise parameter de-embedding technique. The method
used was presented in [5] and summarized in the remainder
of this subsection.
From transmission line theory, the Y -parameters of a trans-
mission line of length l are given by [9]
Y =
1
ZC
coth γl −cschγl
−cschγl coth γl
. (1)
If the transmission line is short such that |γl| 1, then the
hyperbolic functions can be approximated by the ﬁrst non-zero
term of their Maclaurin series expansion [5]. By approximating
the probe pads as lumped elements (YP ) and accounting for
the pad-line discontinuity through (ZD) as illustrated in Fig. 3,
it can be shown that the Y -parameter matrix of the left half of
the short transmission line, including the probe pads, is given
by [5]
YLEFT =
yS
11 − yS
12 − γlS
4ZC
2yS
12
2yS
12
γlS
4ZC
− 2yS
12
, (2)
where yS
ij are the measured Y -parameters of the short
transmission line test structure before de-embedding and lS
is the length of the short transmission line. Since the left
and right halves are mirror images of each other, YRIGHT
can be obtained by simultaneously interchanging the rows and
columns of YLEFT as
YRIGHT = P × YLEFT × P, (3)
where P is the permutation matrix
P =
0 1
1 0
. (4)
TRANSMISSION LINE
Y1 Y2
Y3
YPYP ZDZD
Fig. 3. Equivalent circuit model of a transmission line test structure. Note that
the lumped pad approximation is the only assumption made. Any transmission
line can be represented exactly by the π-network inside the dashed box
by frequency dependent impedances, although the impedances may not be
realizable with physical R, L, and C elements.
Since the short transmission line test structure is symmetric,
its S-parameter matrix should also be symmetric. However,
because of measurement errors, this is strictly not the case. In
this work, the measurement error is handled by averaging the
measured S-parameter matrix according to
s11 = s22 =
s11 + s22
2
(5)
s12 = s21 =
s12 + s21
2
, (6)
where the quantities without primes are the measured values.
The averaged S-parameter matrices are used in (2) to calculate
YLEFT.
C. De-embedding Noise Parameters
The Y -parameter matrices of the input (YIN) and output
networks (YOUT) have to be determined in order to de-embed
the measured noise parameters. Based on the transmission
line de-embedding technique summarized in section II-A, the
input network is obtained by appending (or subtracting) a
transmission line of length |l1 − lS/2| to the network repre-
sented YLEFT. Likewise, the matrix of the output network
is calculated by appending (or subtracting) a |l2 − lS/2| long
line to YRIGHT. Mathematically,
AIN = ALEFT × Al1−lS /2 (7)
AOUT = Al2−lS /2 × ARIGHT, (8)
where Al1−lS /2 and Al2−lS /2, respectively, are ABCD ma-
trices of intrinsic transmission lines of lengths l1 − lS/2
and l2 − lS/2 obtained from (1). Note that if l1 − lS/2
and/or l2 − lS/2 is negative, the above equations elegantly
subtract the appropriate transmission length from ALEFT
and/or ARIGHT.
Since the input and output networks are passive, their noise
correlation matrices can be determined from their Y -parameter
matrices as in [10]
CY
IN/OUT = kBT YIN/OUT + Y†
IN/OUT , (9)
where †
represents the conjugate-transpose (adjoint) operation.
This equation, which reduces to 2kBT {Y} if the real part

of the Y -parameter matrix is symmetric, ensures that the noise
matrix is also symmetric even in the presence of measurement
errors.
Having determined both the electrical and noise matrices
of the input and output networks, the chain noise correlation
matrix of the transistor from which the de-embedded noise
parameters are calculated can be isolated as [8], [11]
CA
T = A−1
IN CA
DUT − CA
IN A†
IN
−1
− ATCA
OUTA†
T.
(10)
AT is the ABCD parameter matrix of the transistor and can
be calculated as
AT = A−1
INADUTA−1
OUT (11)
and CA
DUT is reconstructed from the measured noise param-
eters of the test structure using the formulae in [8], [11].
An additional pair of long and short transmission line
test structures is necessary to remove the restriction that the
interconnects at the input and output of the transistor have
identical widths. AIN and CY
IN are determined from the pair
of transmission line test structures that have the same line
width as the input interconnect. Likewise, AOUT and CY
OUT
are obtained from the lines whose width is identical to that
of the output interconnect. The de-embedding technique will
otherwise remain unchanged.
III. RESULTS AND DISCUSSION
Verification of the proposed de-embedding technique is
provided in two steps. First, electromagnetic simulations are
employed to assess the accuracy of using (2) to split the short
transmission line test structure. Next, the noise parameter de-
embedding technique is verified experimentally on 90 nm and
130 nm n-MOSFETs and SiGe HBTs and compared to existing
techniques.
A. Three Dimensional Electromagnetic Simulations
The error assoicated with using the approximation in (2)
to split the short transmission line test structure was assessed
using 3-D electromagnetic simulations. The S-parameters of
the long and short transmission line test structures, together
with the pads, were calculated using Ansoft HFSS. The
transmission line de-embedding technique in [4] was applied
to the simulated S-parameters to extract ZC and γ, and (2)
was applied to split the short transmission line test structure.
The simulated test structures have 40 × 40µm2
signal pads.
The length of the long line (lL) is 600µm, while that of the
short line (lS) is 100µm. The transmission lines are 5µm wide
and 0.9µm thick and the dielectric is 7µm thick.
The S-parameters calculated from (2) are compared with
those obtained directly from HFSS simulations in Figs. 4-6.
The errors for the real and imaginary parts of each of the
S-parameters are summarized in Table II. A validation of
this de-embedding technique on the measured Y -parameters
of MOSFETs, SiGe HBTs, inductors and varactors in the up
to 65 GHz range will be presented in [12]. Below, we focus
only on noise parameter measurements.
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
REAL(S11),REAL(S22)
100806040200
FREQUENCY (GHz)
REAL(S11)
REAL(S22)
HFSS SIMULATED
CALCULATED
Fig. 4. Real parts of s11 and s22 of the left half of the splitted short
transmission line test structure as calculated from (2): solid line and directly
from HFSS simulations: symbols.
-0.20
-0.15
-0.10
-0.05
0.00
IMAG(S11),IMAG(S22)
100806040200
FREQUENCY (GHz)
IMAG(S11)
IMAG(S22)
HFSS SIMULATED
CALCULATED
Fig. 5. Imaginary parts of s11 and s22 of the left half of the splitted short
transmission line test structure as calculated from (2): solid line and directly
from HFSS simulations: symbols.
1.00
0.95
0.90
0.85
0.80
REAL(S12)
100806040200
FREQUENCY (GHz)
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
IMAG(S12)
HFSS SIMULATED
CALCULATED
Fig. 6. s12 of the left half of the splitted short transmission line test
structure as calculated from (2): solid line and directly from HFSS simulations:
symbols.
TABLE I
PERCENTAGE ERROR IN THE S-PARAMETERS DUE TO (2)
Real 100 GHz 50 GHz Imag 100 GHz 50 GHz
s11 134.5% 60.2% s11 8.28% 0.48%
s22 19.13% 25.29% s22 4.68% 4.72%
s12 0.48% 0.103% s12 2.26% 1.08%
B. Experimental Verification
Figure 7 is a die photo of the SiGe HBT and n-MOSFET test
structures and the necessary dummy structures fabricated to

TABLE II
ABSOLUTE ERROR IN THE S-PARAMETERS DUE TO (2)
100 GHz 50 GHz 100 GHz 50 GHz
Real (×10−3) (×10−3) Imag (×10−3) (×10−3)
s11 12.8 4.6 s11 9.7 0.3
s22 16.0 4.6 s22 3.1 2.1
s12 4.3 1.0 s12 9.8 2.4
TABLE III
TEST STRUCTURE AND DEVICE GEOMETRIES
WE/lG lE/WF NE/NF l1 l2
Tech./Device (µm) (µm) - (µm) (µm)
90 nm (n-FET) 0.1 1 80 34.935 34.555
130 nm (n-FET) 0.13 1 80 43.83 45.225
HBT [6]/ [13] 0.17/0.13 2.5 3 44.91 42.335
validate the new de-embedding technique. The geometries of
the devices are summarized in Table III. All the test structures
employ a M1 ground shield with abundant substrate PTAPs to
reduce the substrate loss, as indicated by the shaded region in
Fig. 2. The ground planes are slotted to comply with the metal
density rules in nano-scale CMOS technologies.
S-parameters and noise parameters were measured on-wafer
using a Wiltron 360B VNA, a Focus Microwaves tuner and a
HP8971C noise figure test set. The open-short technique [14],
the transmission line-based technique in [2] and the proposed
technique were used to de-embed measured noise parameters.
The measurement results summarized in Figs. 8-11 indicate
that there is negligible difference between the three techniques
for all noise parameters of SiGe HBTs and n-MOSFETs up
to 26 GHz. This is expected, showing that the new technique
agrees with previously published ones at low frequencies
while consuming less silicon area. Note that the same pair
of transmission lines is used to de-embed both the 130 nm
MOSFETs and SiGe HBTs. The difference between the open-
short technique and the new technique is expected to increase
with frequency, since the lumped-element approximation will
gradually fail as distributive effects become important.
Another observation is that the differences between the
raw data and the de-embedded results are smaller for the
90 nm MOSFETs (Figs. 12-13) than for the 130 nm HBTs
and MOSFETs (Figs. 8-11). In the 90 nm CMOS test chip,
a metal 1 ground plane extends throughout the test structure,
including under the high speed signal pads. In contrast, the
signal pads in the 130 nm designs do not have a metal 1
ground shield directly underneath. This introduces extra losses,
which translate into a higher measured noise figure of the
test structure before de-embedding. While this loss can be de-
embedded, measurement accuracy improves when the parasitic
losses are minimized.
The importance of employing a ground plane is more
evident by comparing the de-embedded NFMIN of two gener-
ations of SiGe HBTs with exactly the same interconnect and
pad layouts. Shown in Fig. 14 are the de-embedded NFMIN
data for two generations of SiGe HBTs [6], [13]. The NFMIN
of the newer generation HBT, [13] remains below 0.6 dB up to
Fig. 7. Die photos of 90 nm CMOS (top) and 130 nm BiCMOS (bottom)
test structures. Note that only one pair of transmission lines is necessary in
each technology.
22 GHz but exhibits significant fluctuations after the pad and
interconnect losses are de-embedded due to a relatively larger
contribution from the parasitics to the measured noise figure.
Finally, Fig. 14 confirms that the optimum noise bias of
an n-MOSFET remains constant across frequencies, consistent
with the results reported in [15]. The minimum noise bias of
the 150 GHz SiGe HBT in [6] shifts to higher current densities
with increasing frequency. However, this trend is drowned in
the relatively larger scatter in NFMIN data for the 230 GHz
SiGe HBT in [13] due to the aforementioned parasitic losses
and due to the device noise figure being lower than 1 dB.

4
3
2
1
0
NFMIN(dB)
262422201816141210
FREQUENCY (GHz)
50
40
30
20
10
Rn(Ω)
RAW DATA
T-LINE
REF [2]
OPEN-SHORT
Fig. 8. NFMIN and Rn of the 130 nm n-FET. JD = 0.15mA/µm and
VDS=1 V
100
80
60
40
20
REAL(ZSOPT)(Ω)
262422201816141210
FREQUENCY
70
60
50
40
30
20
10
0
IMAG(ZSOPT)(Ω)
RAW DATA
T-LINE
REF [2]
OPEN-SHORT
Fig. 9. ZSOP T of the 130 nm n-FET. JD = 0.15mA/µm and VDS=1 V
5
4
3
2
1
0
NFMIN(dB)
262422201816141210
FREQUENCY (GHz)
50
40
30
20
10
0
Rn(Ω)
RAW DATA
T-LINE
REF [2]
OPEN-SHORT
Fig. 10. NFMIN and Rn of the SiGe HBT [6]. IC = 1mA and VCE=1 V
IV. CONCLUSIONS
A transmission line de-embedding technique was extended
to de-embed the noise parameters of FETs and HBTs. Its
accuracy was assessed using electromagnetic simulations and
tested experimentally on 90 nm and 130 nm n-MOSFETs and
on 150 GHz and 230 GHz SiGe HBTs from two generations
of SiGe BiCMOS processes. Measurement results indicate that
this technique agrees with existing ones up to 26 GHz, while
consuming less silicon area and requiring fewer dummy test
structures and fewer S-parameter measurements. Furthermore,
compared to existing lumped element-based de-embedding
techniques, because of its distributed nature, its accuracy
200
150
100
50
0
REAL(ZSOPT)(Ω)
262422201816141210
FREQUENCY (GHz)
80
70
60
50
40
30
20
10
0
IMAG(ZSOPT)(Ω)
RAW DATA
T-LINE
REF [2]
OPEN-SHORT
Fig. 11. ZSOP T of the SiGe HBT [6]. IC = 1mA and VCE=1 V
4
3
2
1
0NF
MIN
(dB)
262422201816141210
FREQUENCY (GHz)
18
16
14
12
10
R
n
(W)
RAW DATA
T-LINE
Fig. 12. NFMIN and Rn of the 90 nm n-FET. JD = 0.15mA/µm and
VDS=0.7 V
70
60
50
40
30
20
10
REAL(Z
SOPT
)(W)
262422201816141210
FREQUENCY (GHz)
60
50
40
30
20
10
0
IMAG(Z
SOPT
)(W)
RAW DATA
T-LINE
Fig. 13. ZSOP T of the 90 nm n-FET. JD = 0.15mA/µm and VDS=0.7 V
is expected to be better at higher frequencies. Finally, the
importance of minimizing the parasitic losses of the test
structures for accurate measurements was also demonstrated.
ACKNOWLEDGEMENTS
The authors would like to acknowledge STMicroelectronics
for fabrication and NORTEL for funding.
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