1
ANALYSIS OF SWITCHING ACTIVITY IN DSP SIGNALS IN THE PRESENCE OF NOISE
Asghar Havashki
1
, Lars Lundheim
1
, Per Gunnar Kjeldsberg
1
, Oscar Gustafsson
2
, Geir E. Øien
1
Abstract—Input switching activity is one of the deciding
factors for power consumption in digital signal processing
components. For accurate power estimation, it is essential
to have knowledge about the switching activity in the input
signal, including how this activity changes in different
environments, e.g., in the presence of noise. The Dual
Bit Type (DBT) method aims at characterizing the bit-
level switching activity in a signal, using signal statistics.
However, the DBT method requires that the correlation
coefficient and switching activity for the most significant
bit of the signal are available. In this paper we give
an expression for direct calculation of the correlation
coefficient for the most significant bit in a signal, using the
word-level correlation coefficient. Using simulation results
we examine the accuracy of the given method to calculate
the switching activity and correlation coefficient for the
most significant bit. Furthermore, we derive expressions
for accurately calculating the variance and word-level
correlation coefficient for a correlated signal, when an
additional noise of a given variance is added to the signal.
This can be used to estimate the bit-level switching activity
in a signal in the presence of noise. Finally, based on this we
study the impact the additional noise has on the switching
activity of the resulting signal.
Index Terms—switching activity, DSP signals, dual bit
type, bit-level switching activity
I. I NTRODUCTION
Through the last decade, power consumption in
CMOS VLSI circuits has become a major design con-
straint. In order to design circuits for low power, it is
now essential to be able to accurately estimate power
consumption at different design stages, at circuit and
logic level as well as at architectural level. Since dy-
namic power consumption in a CMOS VLSI circuit
depends on the number of signal transitions at its capaci-
tive nodes, accurate estimation of the bit-level switching
activity at the primary inputs is a key requirement in var-
ious power estimation techniques. The input switching
activity can subsequently be used directly or indirectly
to calculate the number of transitions of all nodes in the
circuit [1].
The Dual Bit Type method introduced in [2] aims
at characterizing the bit-level switching activity in a
data word, using the word-level statistics of data, i.e.,
mean, μ, variance, σ
2
, and temporal correlation, ρ. The
1: Norwegian University of Science and
Technology, Trondheim, Norway. E-mail:
havashki,lundheim,Per.Gunnar.Kjeldsberg,Geir.Oien@iet.ntnu.no.
2: Department of Electrical Engineering, Link¨ oping University,
Link¨ oping, Sweeden. E-mail: oscarg@isy.liu.se.
method is based on the assumption that the binary
representation of real world signals can be divided into a
few regions, with well defined switching activity for the
bits in each region. In [2] the binary representation of a
word is divided into three regions: the most significant
bit (MSB) region or sign region (S), the uniform white
noise (UWN) region, and an intermediate region. The
bits in the UWN region, which are defined to last
from the least significant bit to a certain breakpoint P
0
,
exhibit random switching with switching activity equal
to α
UWN
=0.5. Switching activity for the bits in the
S-region, which lasts from the most significant bit to
another breakpoint P
1
, is a constant, while the switching
activity in the intermediate region is assumed to decrease
in a linear manner from α
UWN
to α
MSB
, where α
UWN
and α
MSB
are the switching activities in the UWN and
S regions, respectively.
Experiments have shown that the method presented
in [2] to calculate the regions boundaries, P
0
and
P
1
, is not accurate for highly correlated signals. The
work in [3], which builds on the principles of [2], has
however developed expressions which take correlation of
data into account when defining the mentioned regions.
Accurate estimation of bit-level switching activity, using
expressions in [3], requires accurate estimation of ρ
MSB
and α
MSB
, where ρ
MSB
and α
MSB
are the temporal
correlation and the switching activity for the most sig-
nificant bit, respectively. In [3] the method presented to
calculate α
MSB
and ρ
MSB
is based on knowledge of
a signal generation model. ρ
MSB
in [2] was acquired
using simulation.
An exact method to calculate the bit-level correlation
factor ρ
MSB
was presented in [4]. It is again based on
knowledge of a signal generation model. The estimation
method calculating α
MSB
assumes, however, that ρ
MSB
is equal to the word-level correlation ρ. This is not
accurate in many cases. In [5] an accurate analytical
expression for calculating α
MSB
using the word-level
correlation ρ is presented. In this paper we use this
expression for α
MSB
to derive an expression for direct
calculation of ρ
MSB
. We also use simulation to examine
the accuracy of this method to estimate α
MSB
and
ρ
MSB
.
Furthermore, signals are often subjected to noise from
different sources, e.g., quantization noise from fixed
point DPS realization, wired and wireless communica-
tion channel noise. This changes the word-level signal
statistics, σ
2
and ρ. As mentioned above, the methods
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