spectrum analyzer training - intranet...
TRANSCRIPT
Page 1
www.agilent.com
April 2009
Spectrum Analyzer Training
Roberto Sacchi
Application Engineer
www.agilent.com
April 2009
Agenda
• Introduction
• Overview:
• What is Signal Analysis?
• What Measurements are available?
• Theory of Operation
• Specifications
• Modern Signal Analyzer Designs & Capabilities
• Wide Bandwidth Vector Measurements
• Basics on digital modulation
• Measurements on digital modulation
Slide 2
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April 2009
OverviewWhat is Signal, Vector and Spectrum Analysis?
•Display and measure amplitude versus frequency for RF & MW signals
•Separate or demodulate complex signals into their base components (sine waves)
Spectrum Analysis
Slide 3
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April 2009
OverviewFrequency versus Time Domain
Time domain
Measurements(Oscilloscope)
Frequency Domain
Measurements(Spectrum Analyzer)
Amplitude
(power)
Slide 4
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April 2009
OverviewTypes of Tests Made
Modulation
Noise
Distortion
Slide 5
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April 2009
OverviewDifferent Types of Analyzers
A
ff1 f2
Filter 'sweeps' over range of
interest
LCD shows full
spectral display
Swept Analyzer
Slide 6
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April 2009
OverviewDifferent Types of Analyzers
Parallel filters measured
simultaneously
LCD shows full
spectral display
A
ff1 f2
FFT Analyzer
Slide 7
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April 2009
Agenda
• Introduction
• Overview
• Theory of Operation
• Specifications
• Modern spectrum analyzer designs & capabilities
– Wide Bandwidth Vector Measurements
• Basics on digital modulation
• Measurements on digital modulation
Slide 8
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April 2009
Theory of OperationSwept Spectrum Analyzer Block Diagram
Pre-Selector
Or Low Pass
Input Filter
Crystal
Reference
Oscillator
Log
Amp
RF input
attenuator
mixer
IF filter
(RBW)envelope
detector
video
filterlocal
oscillator
sweep
generator
IF gain
Input
signal
ADC, Display
& Video
Processing
Slide 9
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April 2009
Theory of OperationMixer
MIXER
fsig
LOf
fsig LO
f
LOf f
sig- LOf f
sig+RF
LO
IF
1.5 GHz
3,6 GHz 6.5 GHz
Slide 10
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April 2009
Theory of OperationIF Filter
(Resolution Bandwidth – RBW)
IF Filter
Display
Input
Spectrum
IF Bandwidth
(RBW)
A B C
Slide 11
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April 2009
Theory of OperationEnvelope Detector
Envelope
Detector
Before detector After detector
Slide 12
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April 2009
Theory of OperationEnvelope Detector
and Detection Types
Envelope
Detector
Negative detection: smallest value
in bin displayed
Positive detection: largest value
in bin displayed
Sample detection: middle value in bin
displayed
bins/buckets*
Other Detectors: Normal (Rosenfell),
Average (RMS Power)
Digitally Implemented Detection TypesADC, Display &
Video Processing
*Sweep points
Slide 13
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April 2009
Theory of OperationAverage Detector Type
Envelope
Detector
Time
Volts
bin Sample
detection
Power Average Detection (rms) = Square root of the sum of the
squares of ALL of the voltage data values in the bin /50Ω
x
Neg Peak
detectionx
x
Pos Peak
detection
ADC, Display &
Video Processing
Slide 14
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April 2009
Theory of OperationVideo Filter
(Video Bandwidth – VBW)
Video
Filter
Slide 15
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April 2009
Theory of OperationOther Components
LCD Display, ADC
& Video processing
SWEEP
GEN
LO
IF GAINRF INPUT
ATTENUATOR
Slide 16
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April 2009
Theory of OperationHow it All Works Together - 3 GHz spectrum analyzer
3.6
(GHz)
(GHz)
0 3 61 2 4 5
0 31 2
3 64 5
3.6 GHz
(GHz)0 31 2
fIF
Signal Range LO Range
sweep generator
LO
LCD display
input
mixer
IF filter
detector
A
f
fLO
fs
fs
fs
fLO
-f
sf
LO+
fLO
3.6 6.5
6.5
Slide 17
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April 2009
Agenda
• Introduction
• Overview
• Theory of Operation
• Specifications
• Modern spectrum analyzer designs & capabilities
– Wide Bandwidth Vector Measurements
• Basics on digital modulation
• Measurements on digital modulation
Slide 18
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April 2009
Key Specifications
8563ASPECTRUM ANALYZER 9 kHz - 26.5 GHz
• Safe spectrum analysis
• Frequency Range
• Accuracy: Frequency & Amplitude
• Resolution
• Sensitivity
• Distortion
• Dynamic Range
Slide 19
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April 2009
Specifications
Resolution
Resolution Bandwidth
Noise Sidebands
What Determines Resolution?
RBW Type and
Selectivity
Slide 20
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April 2009
Specifications
Resolution: Resolution Bandwidth
3 dB3 dB BW
LO
Mixer
IF Filter/
Resolution Bandwidth Filter (RBW)
Sweep
Envelope
Detector
Input
Spectrum
Display
RBW
Slide 21
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April 2009
Specifications
Resolution: Resolution BW
3 dB
10 kHz
10 kHz RBW
Determines resolvability of equal amplitude signals
Slide 22
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April 2009
Specifications
Resolution BW Selectivity or Shape Factor
3 dB
60 dB
60 dBBW
60 dB BW
3 dB BW
3 dB BW
Selectivity =
Determines resolvability of unequal amplitude signals
Slide 23
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April 2009
Specifications
Resolution BW Selectivity or Shape Factor
10 kHz
RBW = 10 kHzRBW = 1 kHz
Selectivity 15:1
10 kHz
distortion
products
60 dB BW =
15 kHz
7.5 kHz
3 dB
60 dB
Slide 24
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April 2009
Specifications
Resolution: RBW Type and Selectivity
DIGITAL FILTER
ANALOG FILTER
SPAN 3 kHzRES BW 100 Hz
Typical Selectivity
Analog 15:1
Digital ≤5:1
Slide 25
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April 2009
Specifications
Sensitivity/DANL
Sweep
LO
MixerRF
Input
RES BWFilter
Detector
A Spectrum Analyzer Generates and Amplifies Noise Just
Like Any Active Circuit
Slide 26
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April 2009
Specifications
Sensitivity/DANL
10 dB
Attenuation = 10 dB Attenuation = 20 dB
signal level
Effective Level of Displayed Noise is a Function
of RF Input Attenuation
Signal To Noise Ratio Decreases as
RF Input Attenuation is Increased
Slide 27
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April 2009
Specifications
Sensitivity/DANL: IF Filter(RBW)
Decreased BW = Decreased Noise
100 kHz RBW
10 kHz RBW
1 kHz RBW
10 dB
10 dB
Displayed Noise is a Function of IF Filter
Bandwidth
Slide 28
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April 2009
Specifications
Sensitivity/DANL: Summary
Narrowest Resolution BW
Minimum RF Input Attenuation
Sufficient Averaging (video or trace)
For Best Sensitivity Use:
Slide 29
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April 2009
Specifications
Spectrum Analyzer Dynamic Range
Dynamic
Range
The ratio, expressed in dB, of the largest to the smallest
signals simultaneously present at the input of the spectrum
analyzer that allows measurement of the smaller signal to a
given degree of uncertainty.
Slide 30
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April 2009
Agenda
• Introduction
• Overview
• Theory of Operation
• Specifications
• Modern spectrum analyzer designs & capabilities
– Wide Bandwidth Vector Measurements
• Basics on digital modulation
• Measurements on digital modulation
Slide 31
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April 2009
Modern Spectrum Analyzer Block Diagram
YIGADC
Analog IF
FilterDigital IF Filter
Digital Log Amp
Digital Detectors
FFT
Sweep vs . FFTAttenuation
Pre-amp
Slide 32
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April 2009
Wide Band Block Diagram of the PSA option 122
Third Converter WB Analog IF WB Digital IF
1st LO 2nd LO
HB
Low Band
NB IF
FPGACalibrator
3rd LO
3rd LO
UPHB*
*Un-preselected High Band
Slide 33
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April 2009
Simplified Block Diagram
2nd LO
3.6 GHz
PMYO
RF
INPUT
Input
Attenuator
0 - 70 dB
2 dB Step
1st LO
3 - 7 GHz
1st LO
3 - 7 GHz
1st LO
3 - 7 GHz
Highband Preselected Mixer
321.4 MHz
IF
Digital Demod Option
Unpreselected
Highband
Mixer
A
321.4 MHz
IF
B
3Hz - 3GHz
3 GHz
Preamp Option
Lowband
ACP Module Option
321.4 MHz
IF
C
21.4 MHz
IF
D
3.9214 GHz
1st IF3.9 GHz
B
A
C
300 MHz
LO
D
28.9 MHz
LO
ADC ASIC CPU
fs = 30 MHz
321.4 MHz
Out
21.4 MHz
3rd IF
IF
Processing
Slide 34
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April 2009
IF Processing Past
Log Amp/Detector ADC
Bits
ADC
ADC
Cos(wt)
Sin (wt)
Bits
Bits
Amplitude Only - Spectrum Analyzer (HP856x)
Quadrature - Network Analyzer (HP8510A,..)
Analog -- Digital
rf
rf/IF
IF2
LO1 LO2
Gain/Phase match errors
Detected and logged levelcalled video, mostly dc or slow moving
RBW
AnalogRBW filterset here
AnalogRBW filterset here
Slide 35
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April 2009
IF Digitizers Now
ADC
Bits
Amplitude or Vector Analyzer
Analog -- Digital
Cos(wt)
Sin (wt)
IF
rf
I
Q
I
QLO
Fs
Sample Rate
MHz
ASICPush the digitizers up the rf chain
RBW filters
done digitally
• ADC digitizes IF - not detected amplitude
• Fewer analog adjustments• No temperature dependence• Cheaper to manufacture• Fewer components• More flexible processing
Slide 36
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April 2009
•With narrow band measurements some
information can be gained, such as amplitude
and frequency range occupied by signal.
• Information contained within the signal will be
lost because of the reduced BW.
Swept tuned measurements of broadband signals
Swept
LO
RF
In
IF
out
BPF
Detectors
Display
processor
Slide 37
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April 2009
Digitization and FFT of broadband signals
RF
In
IF
out
WBF
Display
processor
Fixed or step
tuned
ADC
All information is captured using
a fast digitizer. An FFT is then
performed to view signal in the
frequency domain
Slide 38
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April 2009
Types of wideband measurements
There are basically two types of wide
BW measurements:
1. Signal amplitude and lobe width
for very narrow pulse radar
measured in the pulse mode.
2. Phase and amplitude are needed
for complete evaluation such as
Chirp Radar 200 MHz
linear chirp
Slide 39
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April 2009
Instrument and System Calibration
Calibration
Amplitude Flatness Phase linearity
Minimum Error Vector MagnitudeEVM
I
Q
Ideal Signal
Measured signal
θ
Amplitude error
Phase linearity error
The goal is to measure the EVM of the DUT not the EVM introduced by the measuring system
Slide 40
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April 2009
Signal used to calibrate IF path
Amplitude and phase characterized comb covering the entire 80 MHz information BW
Slide 41
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April 2009
Three loops of calibration
Third Converter WB Analog IF WB Digital IF
1st LO 2nd LO
HB
Low Band
UPHB
NB IF
FPGACalibrato
r
3rd LO
3rd LO
Inner Loop IF cal
Outer Loop IF cal
ADC cal
Slide 42
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April 2009
Modern Spectrum Analyzer Block Diagram
Digital Detectors
•Normal
•Peak
•Minimum Peak
•Sample
•RMS
•Quasi Peak
FFT
Digital IF Filter
• 160 Settings
• 1 Hz to 8 MHz RBW
• 1 Hz to 50 MHz VBW
• Min Switching
Uncertainty
Digital Log Amp
• Min Linearity
Contribution
• > 100 dB
Dynamic Range
Sweep vs FFT
• Fast Sweep
• Narrow BW
• High Selectivity14 Bit ADC
• Autoranging
• Dither on/off
VCO
• Fast Tune
• Stepped for FFT
• Optimization for
Close in PhaseNoise
Far out PhaseNoise
Analog IF Filter
(Single Pole)
3 GHz PreAmp
• Improve 1GHz
DANL from –153
dBm to –167 dBm
Attenuator
2 dB Step
Slide 43
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April 2009
Agenda
• Introduction
• Overview
• Theory of Operation
• Specifications
• Modern spectrum analyzer designs & capabilities
• Basics on digital modulation
• Measurements on digital modulation
Slide 44
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April 2009
Transmitting Information
(Analog or Digital)
Modify a Signal
"Modulate"
Detect the Modifications
"Demodulate"
Any reliably detectable change in signal
characteristics can carry information
Slide 45
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April 2009
The Communications Hierarchy
The OSI Model:
Application
Presentation
Session
Transport
Network
Data Link
Physical
e.g. Microsoft Exchange
Encrypt/cross format translation
E to E dialogue, billing etc.
Mux, Flow and sequencing
Switch, route and order packets
Error detection/correction and Frames
Raw bits/ Electrical specificationsWe are here
Slide 46
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April 2009
Why do we modulate?
to move the signal to a frequency band where the
medium has best transmitting properties
radio transmission: to reduce antenna physical dimensions (f= 30 KHz = 10 Km)
to multiplex multiple users in a given bandwidth
Slide 47
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April 2009
Electromagnetic Spectrum
Wave length
(Velocity)
(Wave length)=f (Frequency)
10 mm 1 mm
Slide 48
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April 2009
mmWaves’ Atmospheric Windows
Automotive
RADAR
Scientific
Research
National
Security
(imaging)
Satellite
Millimeter waves (30-300 GHz) have unique transmission channel characteristics of great interest for:• Communications• Transportation• Scientific Research• National Security
Minimum attenuation bands35, 94, 140, 220 GHz
Maximum absorption bands60, 120, 182 GHz
Slide 49
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April 2009
Atmospheric Windows for Satellite
Communications
O2/H2O
Minimum attenuation band: 35, 94,
140, 220 GHz
• Most effective for the satellite-earth
signal transmissions ?
Maximum absorption band: 60,
120, 182 GHz
• Hard to be intercepted
• Effective for secured inter-
satellite transmissions
Slide 50
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April 2009
Digital vs. Analog
0 2 4 6 8 10 12 14-1.5
-1
-0.5
0
0.5
1
1.5
Time
Vo
lta
ge
0 2 4 6 8 10 12 14-1.5
-1
-0.5
0
0.5
1
1.5
Time
Vo
lta
ge
Analog: Faithful reproduction of
signal at RX
Digital: Decide which symbol was
sent from a pre-defined alphabet
Slide 51
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April 2009
Bandwidth of a Signal
-4 -3 -2 -1 0 1 2 3 40
0.2
0.4
0.6
0.8
1
Re
sp
on
se
Time (t/Tb)
0 1 2 3 4 5 6 7 8
0
0.5
1
Re
sp
on
se
0 1 2 3 4 5 6 7 8-50
-40
-30
-20
-10
0
Re
sp
on
se
(d
B)
Normalised Frequency (f.Tb)
• Bandwidth of pulse of duration Tb is infinite• Spectrum has sinc(x) shape extending from - to +
• First sidelobe -13 dB down, rolls off at 20 dB/dec
• Some form of filtering is required
Slide 52
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April 2009
Nyquist Brickwall Filter
• Nyquist filter - achieves zero crossings at integer multiples of symbol period
• e.g. „brickwall‟ filter with cut-off at RS/2
• Zero crossings at symbol interval - no ISI at sample point
-6 -4 -2 0 2 4 6-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Normalised Time (t/Tb)
Imp
uls
e R
esp
on
se
0 0.5 1 1.5 2 2.5 3 3.5 4-50
-45
-40
-35
-30
-25
-20
-15
-10
-5
0
5
Re
sp
on
se
(d
B)
Normalised Frequency (f/Rb)
Pulse Response Nyquist Brickwall Filter
Slide 53
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April 2009
The Nyquist Bandwidth
fn= Nyquist Frequency
= Symbol Rate/2
This condition gives zero ISI (Inter Symbol Interference)
Ideal “brick-wall” filter at the minimum bandwidth
frequency
In a radio transmitter the filtering
is done at baseband.
Envelope of digital baseband spectrum.
Slide 54
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April 2009
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1
= 0.3
= 0.5
= 0
= 1.0
Fs : Symbol Rate
Alpha describes the "sharpness" of the filter.
Occupied bandwidth is approximately: Symbol rate X (1 + )
Filter Bandwidth Parameter " “
Practical Filter Shapes
brickwall
Slide 55
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April 2009
Single Carrier ModulationFrequency Domain View
1 carrier
BW = SymRate(1+ )
Slide 56
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April 2009
0 deg
"I"
"Q"
Q-Value
I-Value
Polar vs. "I-Q" Format
Project signal to "I" and "Q" axes
• Polar to Rectangular Conversion
Slide 57
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April 2009
Creating Digital Modulation
We have used the concept of Signal
Space to view our modulations.
We can use the same idea to
engineer these modulations.
90º
I
Q
I
Q
(1,1)
(0,0)
(0,1)
(1,0)
+1volt1volt
+1volt
1volt
(0,1)
+1v
1v
fC
Slide 58
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April 2009
How Does this Work?
Putting two different messages into one signal space. (These
could be independent messages.)
–90ºcos( t)
I(t)
Q(t)
S(t)
S(t) = I(t)cos( t) – Q(t)sin( t) = A(t)[cos ( t + (t))]
22 QIAI
Qtan 1
Slide 59
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April 2009
Separating the Components: The Receiver
S(t) = I(t)cos( t) – Q(t)sin( t)
• The composite signal is separated by multiplying (mixing) by sin( t)
and cos ( t), the resulting sin2 and cos2 terms become
[I(t) or Q(t)] × ½[1 ± cos(2 t)] terms - the 2 t’s are removed by LPF.
+90ºcos( t)
I(t)
Q(t)
S(t)
LPF
LPF
Slide 60
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April 2009
Agenda
• Introduction
• Overview
• Theory of Operation
• Specifications
• Modern spectrum analyzer designs & capabilities
• Basics on digital modulation
• Measurements on digital modulation
Slide 61
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April 2009
Measurements on digital radios
Time Domain
(CCDF, pulse shaping, timing)Frequency Domain
(Channel Power, spectrum mask,…)
Modulation Domain
• Overall Modulation Quality,
• Modulation Quality on individual carriers
• Channel Response, Group Delay
• In Channel Spurious Search
Swept Spectrum Analyzer
(with span zero and enough ResBW)
Vector Signal Analyzer
Slide 62
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April 2009
FFT Analyzer Block Diagram
Anti-alaising and
Sampling
Input
SignalADC
Fs
ADC Assembly
(time)
Re-Sampling90o
phase
shift
Digital Filter assembly
Real Part (I)
Imaginary Part
D
e
m
o
d
W
i
n
d
o
w
F
F
T
D
I
S
P
L
A
Y
DSP
(freq)
(demod time)
Digital Data Flow
(Q) Quadrature
Decimation
Slide 63
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April 2009
Measurements in the frequency domain:
- Channel power
and occupied bandwidth
- Adjacent channel power ratio (ACPR)
Slide 64
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April 2009
Measurements in the frequency domain:Spurious signals
Out of bandIn band
Slide 65
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April 2009
- time domain
Slide 66
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April 2009
Power Amplifier (PA) Compression
How to verify?
Useful measurements: ACP, CCDF
Compare these measurements performed:
- at the input and output of the PA
- at the output for decreasing values of the input level
With compression
Without compression
Slide 67
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April 2009
Modulation Quality Analysis
Modulation Error
Basic Concept:Ideal point
Measured point
Measured Signalat decision time
Ideal Signalat decision time
I
Q
Error Vector
Measured signal is never equal to ideal signal, due to noise, transmitter
impairments, propagation phenomena,…
EVM[%] MER[dB]
Error Vector Magnitude
Slide 68
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April 2009
Effect of Noise
Noise adds vectorially to a signal. Noise on a QPSK constellation.
Slide 69
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April 2009
Overlapping Probabilities
There is a finite probability that adjacent states could be
confused.
A measure of the functioning of the system is BER (Bit Error
Ratio)
e.g. if 100 bits are in error in 108 bits. Then the BER is 10-6
Slide 70
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April 2009
I/Q Impairments:
I/Q gain imbalance, Quadrature errors, I/Q offsets
Significant measurements: constellation and EVM metrics
I/Q impairments are typically cause by matching problems due to
component differences between the I side and Q side of the block diagram
Slide 71
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April 2009
Signal B: Demodulation
Demod
EVM High (3.6%)
Points are not
randomly
distributed
Mag & Phase Errors
High and comparable
Spectrum B
Slide 72
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April 2009
Signal B: EVM Spectrum Shows Spur
Spurious Signal
Spectrum B
EVM Spectrum
-36dBc spur was
buried under the
modulated carrier
Slide 73
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April 2009
Clock impairments
Incorrect symbol rate
The effect of symbol rate errors on the different measurements depends
on the the magnitude of the errors:
- different methods to verify small or large symbol errors
Slide 74
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April 2009
Incorrect Symbol Rate
+
Symbol Clock Recovered
Symbol Clock
Transmitter and Receiver
operate with different clocks
Symbol Rate Error = 0.1%
Slide 75
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April 2009
Detection and troubleshooting hint:
• Verify the “V” shape of the magnitude of the error vector versus time display
Incorrect symbol rate: small errors (2)Measurement: EVM vs time
Slide 76
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April 2009
Troubleshooting examples:
QPSK transmitter with symbol rate errors
Slide 77
