[Design FAQs]
FPGA Improves Basestation Design Sponsored by Xilinx
Louis E. Frenzel
ED Online ID #20123
November 25, 2008
Copyright © 2006 Penton Media, Inc., All rights reserved. Printing of this document is for personal use only.
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What are some of the challenges facing basestation designers today?
The five biggest are the numerous
wireless standards that must be accommodated,
increased and complex
frequency assignments, increased operating
efficiency, capital expenditures
(CAPEX), and scalability.
Why must designers deal with so
many standards?
Most new basestations benefit from
being able to handle multiple air interfaces.
New basestations that implement
Long Term Evolution (LTE) or WiMAX
that can also support past air interfaces
like WCDMA, cdma2000, and GSM
will be in strong demand. A typical
basestation will still have to support
single-channel and multiple-channel
GSM as well as, say, LTE.
What are the frequency issues?
Basestations will still use their assignments
in the 800- to 950-MHz, 1800- to
1950-MHz, and 2110- to 2170-MHz
range but will extend to new frequencies
like 1.7, 2.3, 2.6, and 3.5 GHz and
even 700 MHz. A basestation must
be flexible enough to change as new
subscribers and services are added.
Why is operating efficiency so vital?
Power amplifiers (PAs) in a basestation
typically constitute up to 70%
of the overall site power consumption.
This is due to the poor efficiency
inherent with supporting higher modulated
signals. Deployment of efficiency
improvement algorithms in the digital
domain significantly improves the efficiency
of the PAs.
Lowering power consumption greatly
reduces the operating expenses (OPEX)
of a network operator. Furthermore,
with the green movement demanding
less power usage and a lower carbon
footprint, carriers not only can help the
environment but also cut many millions
of dollars from their bottom line.
What is the issue with CAPEX?
CAPEX increases as new standards
and systems are implemented. Carriers
are constantly under the gun to reduce
CAPEX. However, new FPGA-based
equipment featuring a new multimode
design using digital pre-distortion and
other technologies is smaller, lower in
cost, and more power efficient.
What does scalability mean?
It means designs should be able to be
used in a variety of configurations, not
only the macrocell. Today, microcell,
picocell, and femtocell basestations are
more common than ever, and great
savings accrue if a single design can be
used for all or most configurations.
What are some of the major objectives
in a new basestation design?
Besides the usual lower development
costs and faster time-to-market, new
designs must be more flexible so new
air interface standards may be quickly
changed or updated. The design also
must be more reliable. A big objective
is to reduce both the initial CAPEX and
OPEX associated with the equipment.
What part of the basestation design
will yield the greatest benefits?
The transmitter is the primary target,
as many functions now implemented
with ASICs and other individual ICs can
be combined in an FPGA, with lower
costs and higher reliability. Of course,
any circuitry associated with the PAs
will yield major gains in efficiency and
lower power consumption and heat.
What does the transmitter architecture
look like?
The figure shows a typical UMTS
WCDMA transmit chain. Note the individual
segments with their approximate
costs and power consumption levels.
This design uses receive diversity and
digital pre-distortion in the PA.
Yet these sections can be implemented
in a single FPGA. Six chips become one,
cost is cut to less than a third, and the
power consumption is almost halved, all
improving reliability. And, the FPGA’s
programmability provides the flexibility
to handle multiple frequencies for different
air interfaces.
How does digital pre-distortion
(DPD) improve performance?
It improves the efficiency of the PAs.
All modern cell-phone standards use
air interfaces that need a linear PA.
WCDMA and LTE are both broadband
techniques to achieve greater capacity
and increased spectral efficiency.
Higher-level modulation techniques
like QAM demand the linearity.
Most PAs are LDMOS class AB designs
that rarely achieve an efficiency greater
than 10%, so 90% of the total power
used ends up as excessive heat. The
reason for the inefficiency is inherent
in the class AB design, but it’s also the
result of having to reduce the amplifier
output to deal with signals that exhibit
high peak to average (PAR) power and
to prevent distortion, which results in
adjacent channel power leakage.
Continued on page 2
How does the DPD fix that?
The solution is to drive the amplifier
harder to get more power, which introduces
some signal distortion. But if you
can predict the type of distortion and
then pre-distort the signal in a reverse
manner, the distortion is cancelled out.
This extends the linear region of the
operation range and produces more
output power at an efficiency approaching
40%. A smaller amplifier at higher
efficiency then can be used with DPD to
achieve the desired output power.
To implement the DPD function, the
transmitter develops the signal to be
transmitted. It is then upconverted and
put through a crest factor reduction
process before being sent to a DPD
process—an algorithm implemented in
the FPGA using a combination of DSP
elements and a soft processor. But for
the algorithm to know how to predistort
the signal, it must know what the
actual transmitter output looks like.
The PA output is sampled with a
directional coupler, amplified, and
downconverted to an IF, where it is
digitized. The ADC output becomes
the feedback the predistortion circuit
uses to compute the output signal.
This signal then goes to the DAC to
be converted to analog and upconverted
to the final frequency before it is
applied to the PA. The result is a clean,
undistorted signal at high power and
improved efficiency.
The distortion compensation algorithm
is very intricate, as it has to
compensate for complex nonlinear
interactions and memory effects. The
key is to simplify the implementation
process as much as possible. This lets
engineers achieve the results they need
without becoming too embroiled in
the algorithmic complexities and saves
many hours of development time.
Product Q&A
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