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Agilent
Vector Signal Analysis Basics
Application Note 150-15
Chapter 1
Vector Signal Analyzer
This application note serves as a primer on the vector signal analyzer (VSA).
This chapter discusses VSA measurement concepts and theory of operation;
Chapter 2 discusses VSA vector-modulation analysis and, specifically,
digital-modulation analysis.
Analog, swept-tuned spectrum analyzers use superheterodyne technology
to cover wide frequency ranges; from audio, through microwave, to millimeter
frequencies. Fast Fourier transform (FFT) analyzers use digital signal
processing (DSP) to provide high-resolution spectrum and network analysis,
but are limited to low frequencies due to the limits of analog-to-digital
conversion (ADC) and signal processing technologies. Today's wide-bandwidth,
vector-modulated (also called complex or digitally modulated), time-varying
signals benefit greatly from the capabilities of FFT analysis and other DSP
techniques. VSAs combine superheterodyne technology with high speed
ADCs and other DSP technologies to offer fast, high-resolution spectrum
measurements, demodulation, and advanced time-domain analysis.
A VSA is especially useful for characterizing complex signals such as
burst, transient, or modulated signals used in communications, video,
broadcast, sonar, and ultrasound imaging applications.
Figure 1-1 shows a simplified block diagram of a VSA analyzer. The VSA
implements a very different measurement approach than traditional
swept analyzers; the analog IF section is replaced by a digital IF section
incorporating FFT technology and digital signal processing. The traditional
swept-tuned spectrum analyzer is an analog system; the VSA is fundamentally
a digital system that uses digital data and mathematical algorithms to
perform data analysis. For example, most traditional hardware functions,
such as mixing, filtering, and demodulation, are accomplished digitally,
as are many measurement operations. The FFT algorithm is used for
spectrum analysis, and the demodulator algorithms are used for vector
analysis applications.
Analog data Digitized data stream
t t
FFT
f
RF ADC LO Time Frequency domain
input 90 degs
Q
IF Anti-alias Demod-
ulator I
input filter Quadrature
detector,
Local digital filtering Modulation domain
oscilator
Digital IF
I
and
DSP techniques t Q
0 code 15
Time domain Code domain
Figure 1-1. The vector signal analyzer digitizes the analog input signal and uses DSP technology
to process and provide data outputs; the FFT algorithm produces frequency domain results,
the demodulator algorithms produce modulation and code domain results
2
A significant characteristic of the VSA is that it is designed to measure and
manipulate complex data. In fact, it is called a vector signal analyzer because
it has the ability to vector detect an input signal (measure the magnitude
and phase of the input signal). You will learn about vector modulation and
detection in Chapter 2. It is basically a measurement receiver with system
architecture that is analogous to, but not identical to, a digital communications
receiver. Though similar to an FFT analyzer, VSAs cover RF and microwave
ranges, plus additional modulation-domain analysis capability. These
advancements are made possible through digital technologies such as
analog-to-digital conversion and DSP that include digital intermediate
frequency (IF) techniques and fast Fourier transform (FFT) analysis.
Because the signals that people must analyze are growing more complex, the
latest generations of spectrum analyzers have moved to a digital architecture
and often include many of the vector signal analysis capabilities previously
found only in VSAs. Some analyzers digitize the signal at the instrument
input, after some amplification, or after one or more downconverter stages.
In any of these cases, phase as well as magnitude is preserved in order to
perform true vector measurements. Capabilities are then determined by
the digital signal processing capability inherent in the spectrum analyzer
firmware or available as add-on software running either internally
(measurement personalities) or externally (vector signal analysis software)
on a computer connected to the analyzer.
VSA measurement advantages
Vector analysis measures dynamic signals and produces complex data results
The VSA offers some distinct advantages over analog swept-tuned analysis.
One of the major advantages of the VSA is its ability to better measure
dynamic signals. Dynamic signals generally fall into one of two categories:
time-varying or complex modulated. Time-varying are signals whose
measured properties change during a measurement sweep (such as burst,
gated, pulsed, or transient). Complex-modulated signals cannot be solely
described in terms of simple AM, FM, or PM modulation, and include most
of those used in digital communications, such as quadrature amplitude
modulation (QAM).
Swept analysis Vector analysis
Time domain Fourier analysis Frequency domain
Carrier
A Time sampled data A Simulated parallel-filter processing
Frequency
resolution
0
bandwidth t
IF filter
Display shows full
f1 f2 spectral display f
f
Sweep span
Start frequency Stop frequency Time record Frequency spectrum
Figure 1-2. Swept-tuned analysis displays the instantaneous time response of a narrowband IF filter
to the input signal. Vector analysis uses FFT analysis to transform a set of time domain samples into
frequency domain spectra.
3
A traditional swept-spectrum analyzer1, in effect, sweeps a narrowband
filter across a range of frequencies, sequentially measuring one frequency at
a time. Unfortunately, sweeping the input works well for stable or repetitive
signals, but will not accurately represent signals that change during the
sweep. Also, this technique only provides scalar (magnitude only) information,
though some other signal characteristics can be derived by further analysis
of spectrum measurements.
The VSA measurement process simulates a parallel bank of filters and
overcomes swept limitations by taking a "snapshot," or time-record, of the
signal; then processing all frequencies simultaneously. For example, if the
input is a transient signal, the entire signal event is captured (meaning all
aspects of the signal at that moment in time are digitized and captured);
then used by the FFT to compute the "instantaneous" complex spectra
versus frequency. This process can be performed in real-time, that is, without
missing any part of the input signal. For these reasons, the VSA is sometimes
referred to as a "dynamic signal analyzer" or a "real-time signal analyzer".
The VSA's ability to track a fast-changing signal isn't unlimited, however; it
depends on the VSA's computational capability.
The VSA decreases measurement time
Parallel processing yields another potential advantage for high-resolution
(narrow resolution bandwidth) measurements; faster measurement time.
If you've used a swept-tuned spectrum analyzer before, you already know
that narrow resolution bandwidth (RBW) measurements of small frequency
spans can be very time-consuming. Swept-tuned analyzers sweep frequencies
from point to point slowly enough to allow the analog resolution bandwidth
filters to settle. By contrast, the VSA measures across the entire frequency
span at one time. However, there is analogous VSA settling time due to the
digital filters and DSP. This means the VSA sweep speed is limited by data
collection and digital processing time rather than analog filters. But this
time is usually negligible when compared to the settling time of analog
filters. For certain narrow bandwidth measurements, the VSA can complete
a measurement up to 1000 times faster than conventional swept-tuned
analyzers.
In a swept-tuned spectrum analyzer, the physical bandwidth of the sweeping
filter limits the frequency resolution. The VSA doesn't have this limitation.
Some VSAs can resolve signals that are spaced less than 100