An EFOM for Cross-Layer Optimization towards Low-Power
and High-Performance Wireless Networks
Xia Li, Peter Baltus, Dusan Milosevic,
Arthur van Roermund
Mixed-Signal Microelectronics, Electrical Engineering
Eindhoven University of Technology
Paul van Zeijl
Electronic Systems and Silicon Integration
Philips Research Eindhoven
Abstract—This paper presents an Equivalent-Figure-of-Merit
(EFOM) for designing and evaluating a wireless system towards
low power and high performance. Relevant factors like delay,
minimum latency, overhead length of a package, package length,
data rate, bit-error-rate (BER), pre-receiving time of the
receiver, average duty cycle and electronics performance factor
are synthesized within a unique model. Comparing to other
FOMs like energy per bit Ebit, this EFOM is able to rank the
overall performance of a wireless network concerning the
information not only power efficiency but also about
communication quality (speed, BER, wake-up time, etc.),
communication effectiveness and user’s satisfaction. Applying
this model to the system design, a 60 GHz self-demodulating
receiver is designed and optimized, which obtains high-speed
versatile performance in a low-traffic wireless network with
better power efficiency comparing to other low-power wireless
interface, e.g. Bluetooth and so on.
Key Words—EFOM, Cross-layer, 60 GHz, Self-demodulating.
Wireless electronic devices become quite indispensible in
one’s daily life. For example, people may enjoy watching
movies from a laptop or music from the mp3 players.
Moreover, these devices can be connected with each other via
a wireless link, e.g. the Bluetooth interface, in which
complicated wires and cables are eliminated. Consequently,
the data loading process becomes much more convenient and
limitless with the environment. However, the extra power
consumed by such a wireless interface turns out to be very
critical. As always heard, “turn off the Bluetooth when one do
not really need it, otherwise the battery will go empty soon”.
The situation is even worse when these wireless connections
are used frequently and people will have to re-charge the
batteries of these mobile devices several times per week. In a
room, several wireless nodes may form into a wireless
network, and the data is shared, relayed and transferred within
it. In order to maximize the effective working time of this
network, the power consumption of the network should be
minimized while on the other hand the communication quality
should also be guaranteed.
Fig. 1 Cross-layer parameters of a wireless system.
Low power performance is not a straightforward task. A
low power in the PHY layer would mean that the burden is
shifted to the MAC or other layers. In other words, one may
need a much more complicated protocol to transfer the data
among some ultra-simple “non-smart” physical nodes. The
overall power consumption is not necessarily optimized.
Therefore, the cross-layer optimization on the power
consumption becomes important and useful. Unfortunately,
there are too many changeable parameters for each layer and
they are more or less dependant on each other, which makes
the optimization unobvious and indirect, as shown in Fig. 1.
As a result, a cross-layer EFOM is crucial to indicate the
direction for the optimization as well as to evaluate the
effectiveness of it.
In Section II, an EFOM is proposed for the cross-layer
optimization. In Section III, applications of the EFOM and the
accordingly and the comparison of this work and other
equivalent low-power systems is given afterwards. The final
conclusions are drawn in Section IV
architecture is discussed
Based on the above discussion, the cross-layer EFOM is
derived and analyzed in this section. The power-related key
978-1-4244-5309-2/10/$26.00 ©2010 IEEE 2263
parameters of the PHY, MAC and network layers are
presented and their relationships are discussed.
A. Key parameters of different layers
The total delay of a single node in a wireless network can
be expressed as
where τPropagation is the propagation delay, defined by distance
over wave propagation speed; τSerialization is the serialization
delay, which is defined as the time of starting to ending of
reception; τQueuing is the time consumed by waiting for
forwarding, and τProcessing is the time for intermitting nodes to
processing the package.
When a network is established with a certain carrier
frequency, communication distance, and package forwarding
mechanism, the total delay τtot can be re-written as
where τC is the minimum latency, or the summation of
propagation, queuing and processing delays, which can be
taken as a constant for a certain type of networking
configuration, and τSerialization can be calculated by the receiver
(Rx) overhead tRx,overhead plus the package length L over the
data rate R, i.e.
totC Rx overhead
t L R
From the previous research , it is known that data rate is
sub-linear to the power consumption of a front-end circuit as
PPP k R
+ ⋅ (4)
where PDC is the total DC power consumption of a node, Ppr
is the power consumption of a receiver (Rx) for pre-receiving
activities (e.g. listening, synchronization or settling the Rx),
PRx is the Rx power consumption, which has no direct relation
with R, and k is the electronics factor, which implies the
circuit performance of the front-end.
Solving for R from (3), we obtain
totC Rx overhead
Substituting (5) into (4), the PDC can be expressed as
DC pr Rx
According to the definition of the energy per bit (Ebit), the
system energy efficiency can be evaluated by the power
consumption over the data rate. It is a fair FOM to evaluate the
energy efficiency of an always-on communication system.
However, some important information is missing in this FOM,
e.g. the type of the device operation (duty-cycled or always-
on) and the quality of the communication (the BER).
Consequently, it does not directly indicate the level of the
system average power consumption, which is the parameter
determining the battery life. Therefore we define another
FOM average energy per bit of correctly received bits
where Reffect is the effective data rate, which is calculated by
the data rate times (1-BER), ton is the on time and the ttot is the
total observing time.
Substituting (6) into (7), the EFOM can be expressed as
totC Rx overhead
where τmax is the maximum user-happy delay, which can be
obtained from the quality-of-experience (QoE) experiments.
The coefficient k can be calculated as following: from ,
it is known that the system noise factor increases sub-linearly
with frequency in certain technology when the system
architecture is similar. Taking  as the benchmark of deep
submicron CMOS, the receiver noise factor is estimated as
where ω is the frequency and 5·109 is the technology- and
The pathloss PL is calculated by
where d is the communication distance, λ is the carrier wave
length and c is the speed of light.
The receiver sensitivity S can be calculated as
S KTB F
where K is the Boltzmann’s constant, T is the temperature in
Kelvin, Eb/N0 is the signal-to-noise-ratio per bit, and B is the
bandwidth. The maximum output power Pout of the transmitter
(Tx) can be estimated by
(1 ) (
tx rx txrx
where PL is the path-loss and Gtx, Grx are the antenna gains of
the Tx and Rx, respectively.
The power consumption of the Tx is calculated as output
power over electronics efficiency η, which is preferably
decided by the power amplifier (PA). Comparing (4) and (12),
the expression of k can be obtained.
2 5 10
η ⋅ ⋅
where smaller k would indicate more efficient PHY system.
Fig. 3 A self-demodulating receiver.
B. Further discussion
From (13), it can be seen that the electronics factor k is a
good FOM to evaluate the PHY-layer performance. Overall
speaking, comparing (12) and (13), smaller k means lower Tx
power consumption at the same data rate and with same output
power of the Tx. To improve k, some techniques are
investigated. For example, using n-path phase array
beamsteering technique can introduce an extra power gain
from antenna as 20·log10n dB (or 10·log10n dB if single local
oscillator (LO) is used). Since the power gain is generated by
the antenna (gain of the equivalent isotropically radiated
power, or EIRP) instead of the drivers or PA, the total power
consumption is decreasing almost linearly with the same total
output power. In other words, the electronics efficiency is
improved by 2n/(n+1) with LO is at the same power
consumption level as the following stage in one path, as
shown in Fig. 2.
Trade-offs and transforms among parameters can be found
by the EFOM equation. For example, when the duty-cycle of a
node becomes higher, or the ratio ton/ttot increases, in order to
maintain a certain EFOM level, we should either need a better
front-end circuit (decrease k), or reduce the pre-receiving time
of the receiver, or increase the data rate at certain BER by
improving the bandwidth efficiency. These methods can be
treated (partially) orthogonal during system design, which
simplifies the whole process.
Recalling (8), the following analyses can be made: for a
better EFOM, (1) smaller τC is preferred, which in turn
reflecting to the network configuration, means that the
communication distance of the each node should be kept small
and data forwarding time should be minimized. As a result,
the self-configured ad hoc network with multi-hop routing
would be a reasonable choice; (2) ton/ttot, tRx,overhead and Ppr have
to be minimized, which implies that in the MAC layer, the
duty-cycle should be sufficiently low and the settling of the
nodes should be fast, especially for short packages. A PLL-
less receiver would be a realistic choice for saving of the start-
up time; (3) in the PHY layer, Reffect should be increased and k
has to be decreased. High data rate can be realized in a wide
band system, e.g. in the 60 GHz ISM band, which offers 7
GHz license-free spectrum to support several Gbps data rate.
To decrease k, constant-envelope modulation scheme is
preferred, because it des not require linear PA in the Tx so the
PA efficiency is improved and the signal can be simply
demodulated by e.g. amplitude detector in the receiver side,
which makes the circuits simple and thus low in power
Based on the above discussion, a 60 GHz radio system is
designed with its application targeting at medium to high data
rate wireless personal-area network (WPAN). At this moment,
the real-time communication or high-definition data streaming
are not included, which, on the other hand, normally do not
require a wireless link. Deep submicron CMOS technology,
e.g. 65 nm CMOS with a unity-gain frequency fT as up to 200
GHz, is used for the PHY circuitry design .
Referring to the parameters in EFOM, an overall
optimization would be achieved in the following aspects. First
of all, the radio should operate in a discontinuous mode to
reduce the factor ton/ttot and so as the average power
consumption. For the further minimizing of ton/ttot without
missed alarms, a sophisticated MAC protocol is required. In
, a duty-cycled wake-up scheme is proposed, which pushes
the average “on” time of the main radio to the real minimum
by using an extra very power-efficient duty-cycled wake-up
radio for event detection. Besides, the nodes in the network
work in a time-division multiple access (TDMA) mode so that
the collision problem is not an issue. Due to the similar
network features, e.g. node density, maximum distance and
burst-mode transmission, this scheme is also suitable for the
pre-receiving activities of our system.
In order to minimize Ppr and tRx,overhead in the pre-receiving
phase, e.g. in the switching-on or switch-off mode, a self-
demodulating receiver is designed, as shown in Fig. 3.
Comparing to the conventional voltage-controlled oscillator
(VCO) with a phase-locked-loop (PLL) which normally would
need 40 to 200 µs to be settled , the self-demodulation
receiver only need less than maximally 3 µs to be settled,
which is determined by the settling of high-gain stage, e.g. an
injection-locked oscillator (IJLO) . The incoming RF signal
is divided into two paths. One is captured and amplified
though the IJLO and then sent to a passive mixer as the
driving voltage, and the other is sent to the mixer as the RF
signal. In other words, the signal is down-converted by itself
through the mixer to the DC baseband directly. The settling
time of the receiver is then much shorter than a PLL because it
does not require a low-frequency feedback loop and there is
no frequency pulling behavior in an IJLO. The system
sensitivity is further improved by using a frequency-sweeping
1 10 100
kk n( )
Normalized k factor
Fig. 2 Antenna number vs. k factor.
EFOM (dB) Download full-text
Fig. 4 The comparison of EFOM.
technique in the IJLO and the basic idea behind is to reduce
the locking range of single-step locking action while still
maintaining a 7 GHz locking range in total after sweeping the
whole band. This operation has negative effect on the receiver
pre-receiving time and increases the minimum latency due to
the sweeping time. However, in the worst case, the total
sweeping and locking time is below 10 µs, which is still better
than a state-of-the-art PLL.
The data rate is chosen as 1 Gbps at 10-3 BER to support
the applications like wireless point-to-point communication
and video files transmission and so on. On-off-keying (OOK)
modulation is used to reduce the system complexity as well as
the power consumption . However, since OOK modulation
is vulnerable to interference and has a relatively poor Eb/N0,
the improvement of the k factor is not significant.
Consequently, an n-path phase-array beamforming module is
added to increase the antenna gain to combat the extra
pathloss at high frequency and improve the k factor as
discussed in Section II B. A phase shifter is inserted between
the mixer and the gain stage. Combining n identical paths at
the output of the mixer, the antenna gain is improved by
10·log10n. The k factor and so as EFOM are improved too. In
order not to increase additional complexity to train the pencil-
beam antenna, an asymmetrical master node, e.g. an access
point is needed to update the position information of the entire
network to all the nodes, and the factor tRx,overhead is minimized
in such a way too.
EFOM can also be used to compare the overall
performance of different wireless standards. Though some of
these systems target at very different applications and have
very different specifications, it would still be useful to
evaluate them by the overall power efficiency and
communication quality, which on the other hand, to some
extent also indicates the overall design complexity. When the
systems are used for the same applications, e.g. a Bluetooth
WPAN and a 60 GHz WPAN, this comparison would become
more fair and important. In Fig. 4, the EFOM’s of biosensor,
ZigBee radio, Bluetooth Radio, 17 GHz ULP and this work
are compared, and it shows a linear increase of the system
overall performance . Qualitively speaking, the system
power efficiency and communication quality is improved
while the system throughput is also increased, which verifies
This paper derives an EFOM for the design and
optimization of a low-power, high-performance wireless
system. This EFOM reveals some relationships and trade-offs
of parameters on different layers, e.g. the relationship among
the average duty-cycle, the latency, the overhead length of a
package, the pre-receiving power, BER, the PHY parameters
and user satisfaction delay. Based on the EFOM, a 60 GHz
low-power self-demodulating receiver is proposed, which
removes the slow turn-on PLL module while using the RF
signal to down-convert itself. In this way, a normal settling
time as hundreds to thousands of µs is eliminated and this is
very efficient in power saving for a burst-mode operation
system. Finally, different prevalent low-power communication
systems like Bluetooth, ZigBee or 17 GHz WSN and UWB
WPAN are compared with this 60 GHz WPAN system based
on the EFOM. It is found that for short-range WPAN
communications, the overall performance of ZigBee or
Bluetooth are low, and the 60 GHz low-power system is much
more power-efficient and has high performance at the highest
data rate, i.e. in a level of several Gbps, so it would be a
promising future direction for the next generation of high-
speed and low-power WPANs.
The authors wish to acknowledge the assistance and
support of Eindhoven University of Technology and Philips
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