Using a Passive Oscilloscope Probe with a Spectrum Analyser

Solution: Spectrum Analysers are typically used to measure radio frequency (RF) signals. The signals are usually delivered to the RF input of the analyser with an antenna, magnetic probe, or using a cable with a matched impedance. This minimises impedance mismatching which lowers reflected power and provides the cleanest measurement. This is not always an acceptable connection scheme. Especially in circuits that are highly susceptible to loading when attached to low impedance inputs, like those on most Spectrum Analysers.
This application note covers using a passive probe, typically used with an oscilloscope, with a spectrum analyser. We highlight some of the advantages and trade-offs with this technique as well.
Most analysers feature a 50 Ohm input impedance. In fact, many oscilloscopes with analogue bandwidths above a few hundred MHz also feature a 50 Ohm impedance setting. This lower impedance enables better performance at higher frequencies but can significantly load a circuit with higher impedance.
In this application note, we will use an RF signal source to deliver a -10dBm signal at 1GHz (CW Sine Wave) to a spectrum analyser, using a passive 1.5GHz oscilloscope probe.

Here is a screen capture of the signal directly connected to the input of the spectrum analyser using coaxial cable and BNC adapters:

Note that the marker above shows the peak at 1GHz with an amplitude of -10dBm. Now, we connect a 1.5GHz Passive Probe (Rigol RP6150 Passive probe) to the input of the spectrum analyser. The RP6150 is designed to be a 10:1 probe when connected to 50 ohms.
Using a probe with an impedance greater than 50 ohms acts as a voltage divider for signals being delivered to the spectrum analyser. This decreases the voltage to the input and effectively acts as an attenuator. It also has the advantage of lessening the circuit loading that can be caused by connecting the 50 ohm spectrum analyser input directly to the circuit.

Here is the same signal but instead of a direct connection to the RF input, we are using an RP6150 probe to detect the signal.

Note that the marker now shows -30dBm for the amplitude. This is due to the probe attenuation factor.
Let’s take a closer look at that probe. Recall that power is the square of the amplitude. Therefore, you can calculate the probe power ratio by simply squaring the probe attenuation factor.

Some common probe attenuation ratios can be found using Table 1.

Table 1: Probe Impedance to dB
*With 50 Ohm Input to Spectrum Analyser

Now, we can easily calculate the expected measured power using the equation below: Measured Power (dBm) = Signal Source Power (dBm) – Probe Attenuation ratio (dB)
So, if our Signal Source Power is -10dBm, and the probe attenuation ratio for our RP6150 Passive Probe is 20dB, we would expect to read -30dB on the spectrum analyser as we see in the above screen capture.
For convenience, we can then use the spectrum analysers internal reference setting to adjust for the attenuation of the probe.
Simply press AMPT and set the Ref Level to the probe attenuation ratio in dB. This is a scalar factor that will remove the additional attenuation from the displayed value and give the corrected power value.

Products Mentioned In This Article:

• RP6150 please see HERE

RIGOL Technologies extended the RF test system of DSA800 spectrum analyser with additional tests for passive key less entry systems. RIGOL’s test solution is very comfortable to use and much cheaper than other available test systems on the market.
Passive keyless entry [PKE] communication is an electronic lock system mainly used to open cars or buildings without a mechanical key. This lock system works with a passive component (key) which will be activated by a device (e.g. a car) sending a periodical signal to its environment. One most common example is the keyless entry system in a car. The car sends always a constant low frequency [LF] signal around 130 kHz to its environment. If the correct key is closed to the car (~1.5 to 5 meter) then the key recognizes the LF signal and sends back the correct ID with an ASK or FSK modulated RF signal (UHF1). With opening the car door it will be unlocked. With some keys it is also possible to start the car via a button when the key is internally the drivers cab or to open the door of rear trunk. The used frequency of UHF signal depends of location. Mainly ISM2 bandwidth for carrier frequency of 433 MHz will be used in Europe. This application uses also a carrier frequency of 868 MHz in Europe but this frequency range is not part of an ISM bandwidth. USA and Japan use mainly the frequency band of 315 MHz.
Two kinds of procedures are possible3:
1.) Car sends a LF signal with a short wake up signal

1 UHF = Ultra High Frequency (range: 300 MHz to 1000 MHz)
2 ISM = Industrial Scientific and Medical Band are bandwidth which can be used with a defined maximum power in industry, scientific, medical or private applications. ISM defines two types: Type A and Type B. Type B bandwidth can be used without requesting an official license. The most popular ISM band is 2.4 GHz to 2.5 GHz, used for WIFI.
Systems in Modern Cars, Aur´elien Francillon, Boris Danev, Srdjan Capkun Department of Computer Science ETH Zurich 8092 Zurich, Switzerland, §2.2

• In a defined period a car sends a LF signal with short information to its environment (wake up signal).
• If a keyless entry key is closed to the car, the key sends an acknowledgement (UHF) to the car.
• The key and the car starting a data communication with ID check.
• Car sends an ID to the key. If the ID is correct, the key sends the correct key code. If this key code is correct, then car let you open the door.
  2.) Car sends a LF signal with car ID
• In a defined period the car sends a LF signal with the car ID to its environment.
• If a keyless entry key is closed to the car and ID is correct, the key sends the correct key code. If this key code is correct, the car can be opened.
  FSK – Frequency Shift Keying
  Frequency Shift Keying (FSK) is a digital modulation form. The principle of shift keying is to modulate a digital signal to a carrier and the changes are discrete in nature. The basis form is 2FSK. 2FSK is used e.g. in keyless entry systems like a car key or a tire pressure monitoring system. In simplest form of 2FSK modulation two digital state “0” and “1” (2FSK with 1 bit/symbol) will be transmitted with two different frequencies. These two frequencies are modulated to a carrier frequency and both have the same distance to the carrier. The difference to analogue frequency modulation (FM) is that the two transmitted frequency changes in the rhythm of binary data. In FM the frequency changes according to the analogue modulation frequency.
  The distance of both frequencies to carrier is defined as FSK deviation:
• FSK deviation = Δf
• fcarrier ± Δf
  Example:
  2FSK with Δf = 40 kHz and fcarrier = 866 MHz is visible in figure 1

Figure 1: 2FSK Signal with FSK deviation of 40 kHz, fcarrier = 866 MHz, tested with DSA832E

The frequency shift of both frequencies is 80 kHz:

• fmax = fcarrier +Δf = 866 MHz + 40kHz
• fmin = fcarrier – Δf = 866 MHz – 40kHz
• fmax – fmin = 80kHz
  Frequency shift is 2 x FSK deviation:
• Δ(f2-f1) = 2 x Δf
  In constellation diagram of a 2FSK signal is visible in figure 2.
  The tests performed in figure 3 and figure 4 show different kind of important measurement:
• Signal shall not be higher than customer defined pass / fail curve (see figure 3). Test can be performed with a DSA832, DSA832E or DSA875.
• Absolute power values of these two frequencies can be analysed (figure 4, marker 2R and 3D)
• Information of carrier offset can be checked with marker function (figure 4, marker 1D)
• Difference of power values of two frequencies can be measured (figure 4, marker 2R and 2D)
  Another measurement is the analysis of occupied bandwidth (OCP). OCP measures the frequency range which contains 99% of spectral power of signal. The carrier frequency is centered in the middle of this frequency range (see figure 5). OCP can be measured with DSA800 with the option DSA800-AMK.
  Calculation of OCP for 2FSK is defined as follow:
• OCPBW6 = Data rate + 2 x Δf

Figure 2: Constellation diagram of 2 FSK, carrier frequency is in the middle

Figure 3: pass / fail mask for curve analysis

Figure 4: Measurement values of 2FSK signal (see marker table)

Figure 5: Measurement of occupied bandwidth with a 2FSK signal

4 Speed of DSA832, DSA832E and DSA875 (sweep time of 10 msec: processing time is 30-40 msec.): measure speed of ~50 msec. is possible in normal mode.
5 Following tests can be performed with the option DSA800-AMK: Time Power, Adjacent Channel Power, Channel Power, Occupied Bandwidth, Emission Bandwidth, Signal to Noise Ratio, Harmonic Distortion, Third Order Intercept Point
6 With influence of a roll off factor e.g. with 0.35, OCP will be lower than the calculation.

Example: Data rate: 10kSymbols/sec. and frequency deviation: 40 kHz

• OCPBW = 10 kSymbols/sec. + 2 x 40kHz = 90 kHz
  Filtering:
  The target of filtering is, that the digital pulses will get a smoother rounded pulse form (according a gauss clock) to get better spectral results and reduce the bandwidth. In RIGOL’s software ULTRA IQ STATION it is possible to select different filter types. A special Gauss Filter for FSK modulation is available to reduce the bandwidth before transmission. Filtering of FSK modulation with that kind of filter results this modulation form into a GFSK modulation. In this software it is possible to adjust the roll off factor (α = B*T), the impulse length (amount of samples per pulse with duration of one bit) and oversampling (additional sampling to be better compliant of sampling theorem to use a simpler reconstruction filter). A gauss characteristic is visible in figure 6. The length of filter is the product of Impulse length and oversampling values. Roll-off factor α is calculated with:
• the bandwidth (@-3 dB) of gauss characteristic: B
• the duration of one bit: TBit
  2FSK Signal can be generated with Software ULTRA IQ STATION and can be downloaded to an RF signal generator with IQ option (DSG3030-IQ or DSG3060-IQ7).
  The clock frequency in the generator will set the wavetable output clock rate. This clock frequency will be calculated from oversampling value and symbol rate (One symbol contains one bit in this 2FSK modulation example).
  Clock frequency = oversampling value * symbol rate

Figure 6: Gauss characteristic

Software S1220 for 2FSK demodulation

DSG3030-IQ: 9 kHz to 3 GHz; DSG3060-IQ: 9 kHz to 6 GHz; IQ Modulator is an Option and contains also external analogue I and Q in-, and outputs

RIGOL provides (option) a demodulation software solution for ASK / FSK demodulation with software S1220. This software works with spectrum analyser DSA832, DSA832E and DSA8758. ASK demodulation will be described at the end of this document.

• This software displays the symbol waveforms of modulation
• Eye diagram can be analysed. This is important to see to analyse jitter effects.
• Specific pattern can be set as reference. Each time the pattern will be transmitted, it will be marked in yellow.
• Carrier Power, Frequency deviation and Carrier frequency offset will be measured.
• Manchester encoding is supported.
• Load and save configuration data

FSK Measurement with DSA815 / DSA705 / DSA710
Software S1220 is usable for
DSA832(E)/DSA875. The measurement speed of
DSA815 / DSA705 and DSA710 is lower than
DSA832(E)/DSA875 and their speed for 2FSK signals are too slow. RIGOL solve this problem with a new option for signal seamless capture (SSC-DSA)9. With the option SSC-DSA 2FSK analysis is also possible to do the FSK measurement with DSA815 / DSA705 and DSA710. With this option the analyser switches into a FFT mode with faster capturing speed. FSK signal measurement (up to three different 2FSK signals) can be performed with that option (see figure 10) in parallel up to 1.5 MHz directly with the device without additional software.
This option has three different main features:

• Real time trace (RT Trace)
• Maximum hold function
• 2FSK signal capture analysis which includes

8 Analyser will be set into a DMA mode (FFT Mode). The analyser can only be controlled with S1220 in DMA mode. 9 This option is only valid for DSA705, DSA710 and
DSA815

o also a maximum hold function parallel to continuous test
o pass/fail measurement according to limit lines to be set
o activation of two mark lines
o measurement of two frequencies from 2FSK signal, amplitude of both frequencies, frequency deviation and carrier offset

Figure 7: 2FSK Signal generation with ULTRA IQ STATION

Figure 8: Software S1220 for ASK / FSK demodulation

Figure 9: FSK configuration in S1220

Figure 10: 2FSK measurement with DSA815 and SSC option

ASK – Amplitude Shift Keying
ASK is also a digital modulation form used in e.g. keyless entry or radio beacon in navigation. In simplest form, the characters one “1” and “0” of digital signal will be multiplied with a carrier frequency (see figure 12 to figure 14). On/Off Keying is used in keyless entry systems using ASK modulation.
On/Off Keying (OOK):

• Carrier will be on with “1”; carrier will be off with “0”.
• ASK modulation is 100% (see figure 14) ASK can also be transmitted with a constant carrier. In this case zero “0” will be transmitted with a lower frequency than one “1”. ASK modulation could be e.g. 10% (e.g. for near field communication [NFC] with a bit rate of 424 kbps).
  ASK modulation index will be calculated as follow:
• m = (A-B)/(A+B) * 100
• If m = 8-14% then ASK modulation is ~10%.
• Modulation depth is B/A

Figure 11: 2FSK measurement with three parallel 2 FSK signals with max hold measurement

Figure 12: Pulse train with “1” and “0” (digital signal)

Figure 13: Carrier of ASK (sine signal))

Figure 14: ASK modulation (digital signal * carrier)

ASK bandwidth is defined with:

• B = 2 x Symbol Rate
  ASK signals can also be generated in RF signal generator DSG3000-IQ (e.g. DSG3060) together with software ULTRA IQ STATION (see figure 16).
  The frequency range is visible in figure 17. ASK Spectrum shows the bandwidth of 2 x sample rate. This spectrum is visible with different signal lines. This makes sense because the expectation of spectrum is not only an on/off cw signal of this modulation form.
• A pulse in time range is a SI (sinx/x) function in frequency range.
• A (constant 0101..) pulse train in time range is a SI function multiplied with a dirac train (like a train of pulses with very small pulse width) in frequency range.
• The multiplication with a carrier results into a shift of this function to the frequency of carrier.

Figure 15: ASK modulation of 10%

Figure 16: ULTRA IQ STATION settings for ASK generation

Figure 17: Spectrum of ASK

Digital Signal is visible in zero span mode (see figure 18). The pulse train in time range can be analysed in this mode.
ASK signal can also be analysed with RIGOL’s S1220 ASK-FSK demodulation software. Settings and analysis form are the same like for 2FSK analysis.

Figure 18: Zero Span analysis of ASK Signal

Figure 19: S1220

Products Mentioned In This Article:

• DSG3000 Series has been discontinued, please see DSG3000B series HERE
• DSA700 Series please see HERE
• DSA800 Series please see HERE

Reading Rigol DP800 Record (*.ROF) Files with Excel 
Solution: The Rigol DP800 series of power supplies have the option to data log the output voltage and current using the Record feature.

This application note covers how to convert the binary file format native to the record file type (*ROF) to decimal using HxD (A hex-to-decimal software package) and the ReadDPROF file, a worksheet created using Microsoft Excel 2010.
The end of this document describes the format of the data in the *ROF file and the Excel functions that were used to convert each data point to decimal.
Steps:
1) Configure the DP800 outputs and Devices (DUTs) for your experiment
2) Insert a USB stick (FAT32 format) into the USB slot on the back panel of the instrument

3) Enable the record feature by pressing the (…) button on the front panel

– Set the time per sample to record by pressing Period and use the keypad or wheel to increment the time

– Select the destination by pressing Det > Select Browser to highlight the external USB (D:) drive

– Press Browser to enter the D: > Press Save and input the file name

– Press OK when finished entering the filename

4) Enable the Recording by pressing SwitchOff. It will turn to SwitchOn when recording is active.

NOTE: The instrument is collecting data as soon as the Recording is enabled.
5) Enable the outputs or run the output profile using the Timer function

6) Once the test is completed, press (…), and disable the Recorder. As soon as it is disabled, the Record mode will ask if you wish to save the data. Press OK to save.

7) In this experiment, I had the following static output values for the duration of the test:
CH1V = 2.00V CH1A = 0.02A CH2V = 2.08V CH2A = 0.18A CH3V = 1.50V CH3A = 0.33A

8) Remove the USB stick and insert it into a computer. If you open the *ROF file (res1.ROF is use d in this example) you will see the binary values:

9) Open the ROF file using hex to decimal conversion software. In this example, I am using HxD, as shareware program from http://mh- exus.de/en/hxd/
10) Here is the data in HxD

11) Configure HxD bytes-per-row to 4:
Before:

After:

12) Set Visible Columns to Text

13) Now the data should show the Offset and Hex Values

14) Click Export and select

15) Now, open the ReadDPROF.xlsx workbook and select the RawDataFile Tab (at the bottom):

16) Select Data: Import Text, set file type to ALL, select the *RTF file (this is the rich text conversion file from the HxD program)

17) Select Delimited and Next

18) Deselect Tab, select Space , and Finish

19) Select Cell A1 for import and press OK

20) Now, the formatted data will be transferred to the Excel Sheet

21) Click on the Calculations tab to see the reformatted data

The raw data format (*ROF) returns the record period, number of record steps, the Voltage, and Current of all channels.
The calculations tab of the Excel sheet is designed for use with the three channel DP800s and is only formatted for the first four data points. You can the final row of cells to cover all of the data points for your application as well as re-label the channels.

Each data point in the *ROF file is 4 bytes long. To calculate the actual decimal value, the sheet:
– Reorders the bytes (AA BB CC DD to DD CC BB AA) using the Excel MID function
– Concatenates the bytes using the CONCATENATE Excel function – Converts hex to decimal using the Excel HEX2DEC function
– Divides the decimal conversion by 10,000.

Products Mentioned In This Article:

• DP800 Series please see HERE

Active loads and the RIGOL DP800 and DP1000 Series 1.

1. Introduction
The RIGOL DP800 series and DP1000 series are programmable linear DC power supplies. They can only provide power for a pure load that does not have the ability to output a current.
Active loads, such as those that can provide power (batteries, solar cells, etc..), should not be used with the DP800 series or DP1000 series power supply. Active loads can lead to instability in the power supply control loop and may damage the powered device.
Connecting the power supply to active loads is not recommended.

Figure 1 Improper use of DP800 and DP1000 Series Power Supply

2. Detailed Technical Description
The RIGOL DP800 series and DP1000 series programmable linear DC power supply can only work in the first quadrant (source positive voltage and a positive current) or the third quadrant (source negative voltage and a negative current).
They cannot work in the second quadrant (negative voltage, positive current.. an adjustable load of negative power) or the fourth quadrant (positive voltage, negative current.. as used for a battery discharge test).
When the load itself is a source and the power supply is required to work in the second quadrant as an adjustable load, the control loop may lose control and the power supply will output an uncontrolled voltage. This could damage or destroy the load.

When the power supply works in the fourth quadrant (e.g., used in a battery discharge test), the control loop is also unstable and will quickly drain the battery. This can result in dangerous conditions, including damage to the battery, power supply, and a very high risk of fire and explosion.

2.1.Power Quadrants in more detail
The Cartesian coordinate system is a common representation of power supply output capabilities. The horizontal axis represents voltage, and the vertical axis represents current. The distributions of the four quadrants of the power supply as shown in Figure 2.
The first quadrant: the power supply provides a positive voltage and a positive current (the direction of the current flows from the power supply to the load).
The second quadrant: the power supply provides a negative voltage and a positive current (the direction of the current flows from the power supply to the load).
The third quadrant: the power supply provides a negative voltage and negative current (the direction of the current flows from the load to the power supply).
The fourth quadrant: the power supply provides a positive voltage and a negative current (the direction of the current flows from the load to the power supply).

Figure 2 Distributions of Power Quadrants

2.2.Principle of DP800 and DP1000
Here is a block diagram of DP800 and DP1000 series:

Figure 3 Block Diagram of DP800 and DP1000

If a current is forced into the supply (I.E. sinking the current), it will directly affect the working status of the MOS transistor and result in instability within the control loop of the power supply as shown in Figure 4.

Figure 4 Current Anti-irrigation Diagram

In addition, the DP800 and DP1000 series power supply outputs do not have an output relay. When a specific output channel is disabled (power off) the output voltage is set to 0V and is regulated by the control loop.

For charging batteries with the DP800 and DP1000 series power supplies, we recommend using constant current mode and implement the circuit shown in Figure 5. The external diode can prevent the flow of current into the supply and prevent damage.

Figure 5 Application Program of Battery Charge Test

Products Mentioned In This Article:

• DP800 Series please see HERE

Power and Function
The relationship between power and function in an Internet of Things (IoT) project is perhaps the most fundamental trade-off a design team needs to address; therefore, it must be made with definitive, testable goals from the customer’s perspective. Expert product development always begins with the an IoT development where the final product is a wrapper around the ‘big idea’, but it is all the more important because of it. It can be tempting to design a product around a battery the engineering team has used before or a display they know how to integrate. This design approach focuses on solutions the engineering team can visualise and not what would satisfy or delight the customer. Instead, viewed through a user’s lens, the product may need to work for a week while recharging only once overnight. It may be important to be on instantly when needed or it may work just as well to push a button to wake the device for use. A battery warning may be required or a sleep mode may be acceptable. The best way to truly understand the options is to start with a definition of as many customer use models as reasonable. Ultimately, there is a trade-off between size/weight and use time/energy but there are many choices for optimization and a testing framework can assist in these determinations.
Estimating Power Usage in Development
An important first step is always to estimate the power required to collect data, make decisions, and take responding action within the requirements of your device. Estimating this usage over time in a theoretical model from specifications of components is useful, but ultimately rigorous, iterative use case testing is important to really understanding your power needs. In a modern IoT platform this measurement may not be straight forward.
A low power System on Chip (SoC) for IoT development may specify a power draw for the low energy Bluetooth (BLE) radio of 5-10 mA but that isn’t transmitting constantly. Depending on the power modes available a device could use tens of milliamps in operating mode while consuming less than several microamps in a global system sleep mode. Additionally, with a lot of chip development focused in this area the state of the art is always changing.
Power Test Methodologies
Traditional electronics battery power consumption could be measured simply with a digital multimeter (DMM) monitoring the current draw over time. Today’s IoT platforms may be more complicated. Often, a pulsed draw that is too quick for a typical DMM to measure is utilized. This requires a faster measurement system to verify. The IoT platform may provide a current measurement test point. An oscilloscope typically uses this to measure the voltage around a small sense resistor in the battery circuit. Depending on the accuracy and resolution you need this may be an effective technique. For instance, if a 10 Ohm resistor is used then every mA results in 10 mV. With a typical oscilloscope noise floor near 1-2 mV this may be noisy. Another option would be to use a current probe to capture the signal. The noise performance may not be as good but the connections are significantly easier if no current measurement test point is provided.
After establishing the best measurement technique for your system, I prefer to begin with a static measurement to establish baseline performance. Typically, I would use a standard example program. In this case, we will view the current draw from a simple program that toggles several LEDs. In this mode, we measure a baseline of about 5 mA. As shown in figure 1, activating each LED also requires 10-12 mA of current on this baseline.
Second, establish a start-up or bootup power requirement for the system. Here, we conducted a test from a hard boot. In addition to power we are also monitoring the energy usage using the integration of voltage * current over time as an approximation. Refer to Figure 2. Understanding the start-up power requirements from different boot states is critical to optimizing the design for sleep or shutdown power mode usage.

Not all of the peripherals utilize power in a DC fashion like LEDs. Test other peripherals you are using to see how they pull power from the battery. A simple test of the SPI bus demonstrates power being drawn in a pulsed fashion. Analysing the amplitude, width, and repetition rate of these current pulses (shown in Figure 3) enables us to understand the power usage.
We can use a similar method to test the actual output power of the Bluetooth radio as well as the battery power used during the transmission. This is important once the complete RF antenna layout is completed since power shortages here could result from reflections or mismatch in the RF path. In the test, we leave the Bluetooth Low Energy radio in a constant power transmit to easily monitor the power consumption. In a real use case, the transmit function is never constant, but the power values here are a guide to optimization in on time and power for the radio use cases. In the results below, a transmit power of 0 dBm resulted in 83 mA of power usage while a transmit power of -40 dBm resulted in 67 mA of current. Even in an off state, the radio example uses significant power to prep the radio and peripherals. These baseline values help us to determine the radio power and transmit cycles that may fit into our customer use cases. RF and DC power are shown for these 2 cases in Figure 4.

Once we have determined typical power levels by state and peripheral usage, the next step is to verify that there are no other effects contributing to power usage when in a more dynamic mode of switching operational states. We can test our code examples using a function to both measure instantaneous power and energy over time. With this approach, we can now determine the energy usage of an approach over time and see how different sleep algorithms generally affect battery life. With this level of information, code optimization in response to customer needs becomes much simpler.
In order to complete the IoT design and get a product to market quickly and cost effectively, our information on power usage in different setups and modes is an invaluable tool. The completed tests have enabled us to gather information about static state power usage for our platform and our required peripherals. We also have details on sleep states and boot power from which we can make informed decisions about trade-offs between battery size and use times in our customer use models. With a basic understanding of how power is consumed in our system we can use this as a guideline for incremental improvements throughout our design cycle. For instance, we better understand the advantage of waiting to service the peripherals vs. putting the whole system into sleep mode for a short period. These decisions can then be validated and refined as your application and use cases become clear.
Conclusions and Key Learnings
When working in the fast-changing atmosphere of IoT design and development, reliable test methodologies become increasingly important. As engineers integrate the newest sensors and platforms on the fly to reach highly competitive markets as fast as possible, understanding core customer requirements and trade-offs and how those can be evaluated and compared throughout the development is an important step toward improving the strategic design process.
Whether the challenges of an application are more form or function, issues related to battery life and power usage are fundamental elements of design in the IoT ecosystem that play a significant role in market success. Establishing these principles early in the process and testing them iteratively is one of the best ways to limit budget and schedule risks in the latter stages of the design. Modern, easy to use test equipment that is more affordable than ever can be utilized to develop the limits and baselines that will guide an engineering team through a successful product development.

Products Mentioned In This Article:

• Digital Multimeters please see HERE

Introduction to Waveform Generator Technology
Traditional function and arbitrary waveform generators have for many years been built on one common technology – DDS or Direct Digital Synthesis. DDS allows an instrument to create waveforms by tracking the phase of a reference clock and outputting the closest sample to the desired signal at each output sample time. DDS has enabled quality performance at a reasonable price for generations of function generators.
Today, new technologies are emerging that enable instruments to utilise both the advantages of DDS while improving signal fidelity and usability in more applications than ever before. Technologies like Keysight’s improving signal fidelity in waveform generators. SiFi technology was created for Rigol’s latest arbitrary waveform generator family, the DG1000Z series. These instruments combine the true point to point waveform generation of arbitrary signals and redesigned output hardware to create arbitrary waveforms with flexibility and accuracy not available a few years ago. Combine this with the available deep memory and SiFi technology enables emulation of precise arbitrary signals over longer periods without losing fidelity.

Understanding DDS or Direct Digital Synthesis
The DDS method uses phase to determine the correct output over time. Let’s look at an example. Assume we have an 8192 point arb that we want to play back at 6.25 kHz. We load an arbitrary waveform made up of 400 cycles of a Sine wave. Therefore, we should have a fundamental frequency of 2.5MHz. The DDS generator assigns a phase value to each point in the wave. The first point is 0 degrees. Each point after that add an increment of 360 degrees/8192 allowing for all the points to be played in a period and the first point to be up again when it returns to 0 degrees. That increment is approximately 0.044 degrees. Driven by the clock source (often a PLL) the instrument essentially measures its phase from start every 5 ns (the instrument has a 200 MSa/sec update rate – or once every 5 nsec) and chooses the closest phase value to select from the arb table. In this example, each 5 ns represents 360 degrees/ (160 us / 5 ns) = 0.01125 degrees. Therefore, the arbitrary waveform looks like figure 1 in the UltraStation software and then the actual output values that are selected over MHz fundamental frequencies are shown in figure 2.
What is worth noting about the output is that even though we are able to output samples much faster than is required we have created some distortion. Namely, some of the points in the arb, which are all evenly spaced, are repeated for 10 ns and some will be repeated for 15 ns. The lack of smooth, continuous changes created by the file’s quantisation of the sine wave causes this distortion. The distortion is increased significantly when the playback period is adjusted slightly because the DDS algorithm is forced to make tougher decisions about which point to output since the ideal output is now further from the available points which were chosen for the initial playback period. This is critical because it is the careful sampling to generate the correct, high fidelity arbitrary signal which is the time consuming and difficult task. Using DDS, engineers who want high fidelity signals must go back and resample, recreate, and reload an arbitrary waveform whenever they want to tweak the playback period. DDS forces engineers to choose between convenient and efficient signal generation or high fidelity and accuracy during playback.

Figure 1: 400 cycles of Sine wave in an arbitrary waveform shown in Rigol UltraStation Software

Figure 2: Arbitrary wave data table showing DDS algorithm for playback

SiFi technology overcomes this basic effect on signal integrity with a new architectural approach. Let’s take the same signal and example and test it in SiFi mode. Here we load the same arbitrary wave. We simply set the output sample rate to be 8192 points * 6.125 kHz = 51.2 MSa/sec. Now, after changing that one setting we investigate the output of the signal with a spectrum analyser. The data is overlaid with the DDS mode data in Figure 3. To create this spectrum we used Max Hold on each trace while we changed the playback frequency for DDS and the output sample rate for SiFi to create fundamental frequencies between 1 and 2.5MHz. As we adjust the playback parameters in real time, DDS mode creates signal distortion at various frequencies across the 2-10 MHz band shown in yellow. Using the same exact arbitrary waveform a simple switch to SiFi mode creates much more even waveforms with significantly higher signal fidelity shown in purple.
This is a simple example of the difference between the 2 architectures, but even advanced users may be unaware of the trade-offs they are making with a traditional signal generator. Most users would assume that a 30 or 60 MHz arbitrary generator is capable of a nearly perfect 1 MHz sine wave. It all depends on the importance of signal fidelity to the application at hand. After all, many engineers look at output sample rate as a key specification but it doesn’t tell the whole story. In the example we just did, the DDS wave was being output at 200 MSa/sec while the SiFi wave was being output at about 50 MSa/sec. Still, the SiFi wave produced a much cleaner signal. The more complex the arbitrary waveform the more difficult it becomes to understand the impact of the sampling technology. Artefacts from this resampling can have profound impact on the frequency content of a true arbitrary wave and there is no way to easily separate the real wave from the sampling artefacts. This also means that buying a DDS waveform generator with a higher output sample rate invariably alters the frequency components of the signal even when playing the same arbitrary file. With SiFi technology this is not case.
Signal fidelity is critical to design engineers using waveform generators in their testing. Using a generator with SiFi technology improves the accuracy of waveforms you reproduce by allowing the engineer maximum flexibility in setting the output rate of their arbitrary waveform.

Figure 3: Comparison of 1-2.5 MHz Sinusoidal arbitrary waves. Yellow is DDS generated. Purple is SiFi technology.

Enabling more functions and waveform types
Improved signal fidelity is great, but signal quality alone doesn’t make a great technology or a great instrument. Alongside Rigol’s SiFi technology is the capability to create more unique waveform types without having to build custom arbitrary waves. This includes the unique ability to build harmonic waves on the instrument front panel where the engineer describes the phase and amplitude of each harmonic element of the starting frequency. Figure 4 shows how an engineer can define a harmonic wave from the instrument’s front panel. Harmonic waves let the engineer set amplitude and phase values for the fundamental frequency up through the 8th harmonic. Traditionally, engineers who need signals which are more easily defined in RF space would have to define each frequency, amplitude, and phase and sum them together into an arbitrary wave. To create the wave in RF space the user would then have to resample the output in time domain with the correct sample spacing. This is a cumbersome way to generate and work with arbitrary waves. Harmonic waves are much easier to create. Simply define the power and phase at each frequency at a multiple of the fundamental and the instrument automatically combines them and plays them back. Figure 5 shows the matching spectrum to the signal defined in figure 4. Figure 6 is the same wave captured on a scope. This is the time domain arbitrary data a user would have to create, load, and configure on a traditional generator to get the same signal they can now quickly build from the front panel. With these new capabilities empowered by SiFi technology, the Rigol DG1000Z series waveform generators add significant power and flexibility to the engineer’s bench.

Figure 5: Harmonic Wave Spectrum Analyzer measurement

Figure 6: Harmonic Wave Oscilloscope measurement

Developing Powerful and Flexible Deep Memory Arbitrary Waveforms
The key technological advance of SiFi is the ability to deliver true point to point arbitrary waves. Without this capability arbitrary waves become notoriously difficult to generate accurately and require additional behind the scenes work by engineers slightly adjusting sampling and points to improve the overall signal fidelity. This task becomes considerably more difficult when using deep memory arbs that contain millions of points. With SiFi technology, engineers can create longer, more precise arbitrary waveforms. In the adjustable sample rate mode users can define a signal that will be output at up to 60 MSa/sec. With up to 16 Million points of memory depth, it is then possible to create completely custom point to point waveforms up to 250 milliseconds in length while still maintaining the full output sample rate. The traditional difficulty with working with such long waveforms is they are a challenge to edit. For instance, Microsoft Excel 2013 only allows just over 1 million rows of data. Using a DDS generator, to make a slight change to the playback period you need to either resample the wave or deal with artefacts created by the DDS phase based sample selections. With SiFi technology, you can leave the precise waveform as sampled and simply adjust the output sample rate. This saves the considerable time and effort of editing and reloading long waveforms to the instrument.
While SiFi makes arbitrary waves easier to manipulate and more flexible once they are created, users still need a reliable method of generating, editing, and loading long waveforms to their instrument the first time. SiFi enabled generators come with free UltraStation software for waveform editing. This tool enables importing, combining, and freehand editing of deep memory waves. Waveforms can then be loaded directly to the instrument over LXI or USB. In addition to the time domain, the editing software has a spectrum view to see the power and phase of the signal you created as shown in Figure 7. The combination of deep memory, SiFi technology, and enabling editing software empowers engineers to reproduce more flexible, more precise waveforms than traditional DDS technology alone.

Figure 7: Arbitrary waveform spectrum view in UltraStation software

Unprecedented Value
Rigol’s SiFi technology and the DG1000Z series waveform generators allow engineers to cover more signal reproduction applications than ever before with improved signal fidelity, flexibility, and ease of use. The deep memory capabilities and hardware design of the instruments work together with SiFi sampling technology to make these improvements possible and deliver unprecedented value to the engineer’s bench.

Products Mentioned In This Article:

• DG1000Z Series please see HERE

Unique waveform reproduction technology
RIGOL’s newest arbitrary waveform generators, the DG800 and DG900 Series, combine high resolution output and advanced filtering techniques in point-to-point waveform generation expanding the value of arbitrary waveform generators in test platforms. The DG800 and DG900 (shown in Figure 1) each have our new 16 bit output capability which improves the accuracy of each step in a waveform. Customisable filtering gives you more options to define how these points go together. Without recreating the waveform points change the bandwidth of a signal by precisely defining the high frequency edges. This is the essence of SIFI II technology and it makes RIGOL’s new generators some of the most customisable generators available today.

Figure 1: Rigol DG900 Series Waveform Generator

High Resolution with 16 bits
Output resolution is an important characteristic of any signal generator. On modern, digital instruments resolution is measured in bits. Let’s look at a common example. Assume your signal generator has a 10 Vpp output. If the voltage level within that 10 volt swing is represented by a 14 bit number, that means that there are 2^14 or 16,384 possible output values. These are then distributed evenly so 10 volts divided by 16,384 means that each level is 610 microvolts from its neighbour. If the desired voltage level at a point in time is really between two of these levels then one level is selected as the closest option. This creates a small error in relation to the desired signal. Over time this error can make a substantial difference to the signal fidelity and ultimately to the response of the device under test.
With a 16 bit generator the same 10 volt swing is split into 2^16 or 65,536 sections. Since each of the additional bits has 2 states (0 or 1) there are 4 times as many states in a 16 bit number. With 4 times as many voltage settings available the error introduced is significantly reduced. But that isn’t the only effect. Since there are more voltage options the instrument is more often able to adjust the output taking advantage of its output rate.
Let’s take a look at how these two signals compare with an oscilloscope. Figure 2 shows the averaged waveforms from the 14 and 16 bit output. Figure 3 shows an arbitrary wave that we have created for this test. It is a standard 8192 point arbitrary wave that includes a slow ramp in voltage followed by a pulse to -5 V and then to 5 V.

The purpose of the pulse activity is to make certain the generators we test are setting their output range correctly for 10 Vpp. We loaded this same arbitrary wave into two instruments. One is a 14 bit generator and one is the new DG900 Series 16 bit generator. We synchronised the outputs and set each instrument to output 1 MSample per second to make the minimum step time 1 microsecond. We then captured the outputs of both generators on the oscilloscope using heavy averaging. This reduced the noise and enabled us to view the output steps of each instrument. The oscilloscope screen is the comparison shown in Figure 2.
The purple trace is the 14 bit generator. As you can see the output changes every 6 microseconds. Even though the output is set to change every microsecond the slow ramp in the arbitrary wave only moves enough in voltage every 6 steps to trigger an actual level change in the output.
The 16 bit channel in yellow is using the same arbitrary wave file. Because the output has a smaller voltage step size it makes smaller steps and also makes them more frequently since the voltage change requested in the waveform file is 4 times as likely to trigger a change. Under these test conditions the 16 bit generator updates the output about 4 times as often and each step has 4 times the resolution.
To analyse this data further we can request it from the scope and chart it in Excel (shown in Figure 4). Here we show the data extracted from the oscilloscope for the two channels as well as the ideal ramp line we were trying to emulate, all overlaid. As shown in the inset, the RMS error of each waveform is calculated in comparison to the ideal line. The 16 bit generator reduces the RMS error of the signal by a factor greater than 2 meaning that is contains less than half the RMS error.
In cases where accuracy and signal fidelity are important, the RIGOL 16 bit generators provide significantly more capability than traditional 14 bit generators.

Figure 2: 14 bit vs 16 bit Oscilloscope comparison

Figure 3: Sample Arbitrary Waveform

Figure 4: Comparison of emulated and ideal signals showing > 2x RMS error improvement with 16 bits

Flexibility in Filtering with SiFi II
While the 16 bit resolution improves signal fidelity, how an instrument moves between points in a waveform has a dramatic effect on both the time domain and RF domain view of a signal’s characteristics. Traditional generators employed DDS (Direct Digital Synthesis) technology which selects the best output point at any time based on phase. RIGOL’s SiFi technology, which was introduced on the DG1000Z series generators employs a true point-to-point output to decrease overall signal noise versus DDS.

The DG800 and DG900 Series generators are the first generators to employ SiFi II technology. These instruments utilise the point-to-point accuracy of SiFi and add filter customisation to the movement between points. This customisable setting provides flexibility for dynamic signal generation. Within the sequence menu users can select between interpolation, step, and smooth filtering. These filtering techniques change the look of the waveform in time and RF domains in ways that aren’t easy to duplicate without starting over with a new waveform on any other generator. Let’s look at a simple 1 kHz square wave. Using the standard square wave function in sequence mode utilises an 8,192 point square wave. In the sequence menu we set 8.192 MSamples per sec so that the wave repeats every 1 millisecond. Now, we can use the same wave amplitude and points in a point by point mode, but alter the output by adjusting the filtering. Figure 5 shows how the different filtering options appear on a spectrum analyser. Using a max hold trace we can see how much wideband noise is generated by each method.
Even though the primary signal is only at 1 kHz the square wave generates harmonics viewable out in MHz. By changing the filtering mode engineers can create a sharper drop-off indicative of a filtered or bandwidth limited signal path or a wide bandwidth footprint can be selected. This capability is very useful for looking at how signal conditioning and system design might affect the interpretation of the generated signal. Figure 6 shows the same 3 signals on an oscilloscope. The step filter creates a near ideal step response with limited overshoot. Consequently, there are fewer high frequency components present. The smoothing filter smooths the transitions but allows for some overshoot creating a different time domain look and a moderate amount of high frequency components. Interpolation mode creates a linear step. This step function has hard edge transitions that add significant high frequency components. The edge time in interpolation mode can be adjusted for further optimisation. We can see this in Figure 7. Here we used infinite persistence on the oscilloscope to show that the edge time can be set from 8 ns to about 90 ns in this configuration. This gives system engineers a tool for fine tuning signal response to verify their design parameters. With all of these filtering options the generated signal can be optimized to closely match whatever signal characteristics are required.

Figure 5: Comparison of SiFi II filter modes in the frequency domain

Figure 6: Comparison of SiFi II filter modes in the time domain

Figure 7: Range of the edge time in interpolation filter mode using SiFi II technology

Unprecedented Value
RIGOL’s SiFi II technology and the DG800 and DG900 series waveform generators allow engineers to more closely reproduce signals of interest with a combination of 16 bit resolution and point to point filtering options. Signals with complex RF footprints or high fidelity requirements can now be emulated more precisely with RIGOL’s SiFi II technology in the DG800 and DG900 series arbitrary waveform generators

Products Mentioned In This Article:

• DG800 Series please see HERE
• DG900 Series please see HERE
• DG1000Z Series please see HERE

Transmitter Functionality – A Perfect Education Training with DSA800 and TX1000 Board
In RF world one of the most interesting techniques is, how to transmit RF data and how does it work? Especially for education market RIGOL Technologies offers a perfect learning tool with spectrum analyser [SA] of DSA800 class1 or using RSA3015N2 [RSA] in combination with a TX1000 demo board. A professor or a teacher will have an easy possibility to demonstrate and show the complex chain of a transmitter or receiver part. A student can follow this lesson and understand transmitter functionality with own hands- on at component level. The overall understanding of RF receivers and transmitters can be learned on a simple way.
This demo board (see figure 1) has the possibility to modulate an RF carrier (500 MHz or 1 GHz) with a base band signal (up to 50 MHz, max bandwidth: +/- 10 MHz). With spectrum analyser DSA815-TG (up to 1.5 GHz) it is possible to stimulate the demo device (via tracking generator) and to analyse it. Alternatively, an external RF Generator with IQ modulation can be used (like RIGOL DSG821A) to test the device with a modulated baseband signal.

1 DSA815-TG: 9 kHz to 1.5 GHz; DSA832E-TG: 9 kHz to 3.2 GHz; DSA875-TG: 9 kHz to 7.5 GHz. All analysers are available with/without tracking generator.
2 RSA3015N contents sweep based and real time spectrum analyser + vector network analyser and EMI pre- compliance measurement tool with frequency range of 9 kHz to 1.5 GHz (or 3 / 4.5 GHz)

The TX1000 demo board incorporates different components:
• 1 GHz local oscillator
• 10 MHz reference
• Mixer
• 1st band pass after mixer
• Amplifier
• 2nd band pass filter after amplifier
Various switches and connection points are integrated on the board. The demo board has the possibility to measure each internal single component or several in different combinations. For example, it is possible to measure the mixed signal after the mixer or to test the amplifier as a stand-alone device. Furthermore, it is possible to omit a component such as a second bandpass filter and use a self- developed one for comparison tests. A block diagram is shown in figure 2.

The spectrum analyser series DSA800 provides a built-in control window for the demo board TX1000. All switches can be opened / closed very easily with the spectrum analyser after connecting the demo board to the analyser via USB without the need for an additional PC with software. If only the demo board is the component of interest or the RSA3000N series Real-time Spectrum Analyser (with VNA) is used together with this board, RIGOL also provides free software for this demo board for control via PC.
The first test scenario is the measurement of a signal after each component of the complete chain of the transmission path with the internal 1 GHz fixed local oscillator signal. For the next 4 measurements, an input signal (baseband) is used at port J1. A baseband signal with a frequency range of 50 MHz +/-10 MHz can be used at this port. In the next measurement examples, a constant wave [CW] of 40 MHz and – 10 dBm was used as the baseband input. If the teacher does not have an RF generator available to generate a baseband signal, the tracking generator of the spectrum analyser can also be used as an input (a fast frequency sweep of a DSG3000 can also be used with a start frequency of 30 MHz and a stop frequency of 70 MHz). Each output of the transmission chain can be measured with a DSA800 or RSA3000N series Spectrum Analyzer [SA]. VBW has been reduced in the SA to a lower value than RBW in order to obtain a less noisy trace and also to see small peaks in the test results.
This signal was measured after the mixer process (Figure 1, J3). The measurement in Figure 3 shows the carrier frequency of 1 GHz (marker 1), the wanted signal at 960 MHz (fc – fcw) and the unwanted mirror frequency of 1.04 GHz (fc + fcw). In addition, some unwanted frequency components (920 MHz, 1.08 GHz) are visible. They can all be measured with the spectrum analyser with advanced marker functions.

After the first filter (Figure 1, J5), next to the mixer, the mirror frequency is 45 dB lower than in the previous measurement without filter (Figure 4). The carrier at 1 GHz is about 15 dB lower than before. The wanted signal at 960 MHz is also lower by about 3.6 dB because the filter has a max. insertion loss of 4 dB. Both unwanted components are more suppressed than before.

The next additional component after mixer and filter is an amplifier. This component amplifies the main wanted signal with approx. +20 dB. But also the carrier and the unwanted signal components are amplified (Figure 5), as well as the unwanted mirror frequency due to linearity effects of the amplifier.

The last component in the transmission chain is a second bandpass filter. This filter suppresses the carrier, the mirror frequency and the unwanted signal components (Figure 6). Most of them are no longer visible at this dynamic setting of the device. The carrier is 65 dB lower than the modulated baseband at 960 MHz.

The next step is to analyse each component as an individual component. The first analysis focuses on the mixer. With the integrated mixer, it is possible to measure the 1 dB compression point, conversion loss and isolation.
For the 1-dB compression point, the same CW sine signal of 40 MHz with a starting power of -10 dBm at the IF input (connector J1) is used. This signal can be generated using RIGOL’s DSG800(A) series or DSG3000B series RF generator. The spectrum analyser is connected to the RF output (J3) of the mixer. The input signal is now increased in 1 dB steps. A linear increase of the mixer signal is expected. If the RF output cannot follow the IF input linearity and deviates by 1 dB, a 1-dB compression point is detected. With the DSA800 or RSA3000N series, different waveforms can be used for this test.
The first yellow trace shows a mixed signal at -28 dBm with an IF input of -10 dBm, resulting in a conversion loss of 18 dB. This trace can be frozen in the spectrum analyser. A second pink trace uses the trace type “clear write”. Now the IF input signal can be increased in 1-dB steps until the mixer output linearity deviates by 1 dB, resulting in a conversion loss of 19 dB. (Figure 7). The 1 dB compression point of the TX1000 mixer is visible at an IF input power of +5 dBm.

The last tests focused on the entire transmission chain of the TX1000 using a CW signal as intermediate frequency. The next measurements will use a 2FSK baseband signal instead of a CW signal. The focus is on the measurement point after the mixer process to a carrier.

Figure 8 shows an example with a 2FSK signal at the mixer output. The 2FSK baseband is at the IF input with a carrier of 10 MHz, resulting in a distance of 10 MHz from the 1 GHz carrier. This 2FSK figure can be analysed with the real-time mode of the RSA3000N with density/spectrogram. The characteristics of the 2FSK modulation are visible in the lower (wanted) and upper (unwanted) mirror baseband.

The same signal is tested again in the real-time mode of the RSA3000N (Figure 9) using the “Seamless Signal Capturing” function. With this measurement it is possible to measure the frequency deviation and the distance to the carrier of 2FSK signal(s). In addition, the frequency deviation and amplitude level of the 2FSK signal is measured. Furthermore, a pass/fail test of the amplitude tolerances can be performed with this measurement.

Until now, the internal local oscillator of the TX1000 has been used. However, it is also possible to use a self-generated external LO carrier signal using an RF generator such as DSG821(A) (Figure 1, J12) between 50 MHz and 1000 MHz. The oscillator driver power of the TX1000 is +7 dBm, which can be easily adjusted in the DSG800(A).
Figure 10 shows the same signal as in Figure 9, but with external LO carrier of 900 MHz instead of the internal LO. By using the spectrogram in combination with the normal trace, the acquisition speed can be reduced to 100 µsec. It is now possible to measure the details of different data blocks within the spectrogram using delta and Z markers. The difference in frequency, time and amplitude can be analysed in this way.

In the next measurement, the focus goes back to the internal LO of the TX1000, where the phase noise can be analysed with the spectrum analyser. The phase noise measurement measures the statistical short-time oscillation around the center frequency. Phase noise can have a significant impact on the quality of the transmitted signal by magnifying spectral lines adjacent to the main carrier that may overlay smaller (wanted) baseband components. Larger baseband components have a worse signal-to- noise ratio. To minimise the negative influence with digitally modulated signals, an LO with low phase noise should be used. The short-term stabilisation of the frequency with an LO depends on the oscillator used. For voltage-controlled oscillators [VCO], a PLL circuit is used to improve their stability.
With the RSA3000N and DSA800 series, it is possible to use a noise marker with the reference to 1 Hz bandwidth. This noise marker can be used to qualify the distance to the carrier [dBc] in amplitude with a frequency offset of, for example, 10 kHz. In the measurement (Figure 11) the typical characteristic of PLL stabilization (two elevations next to the carrier) can be seen on the trace. The measurement of the phase noise of the internal local oscillator of the TX1000 is better than -98 dBc/Hz at 10 kHz frequency offset:

The next part of interest in the TX1000 is the amplifier. Following the same principle as for the mixer (measured in Figure 7), the 1 dB compression point can be analysed to qualify the linear operating range of the amplifier. For the transmission of digitally modulated signals, it is important to have a good and wide linear amplifier range, since digital signals have a high peak-to-average ratio (the amplitude deviation can be very small, but also larger). All these signal components must be amplified in a linear range to avoid negative issues in modulation quality during transmission. With the TX1000 it is possible to disconnect the internal amplifier (J5 / J6 open) and to integrate a self-developed external amplifier into the transmission chain of the TX1000. Comparison tests of different amplifiers can be performed, helping students to design and optimise their own amplifiers (Figure 12).

The next measurement will focus on the second bandpass filter. This filter can be measured with the DSA815-TG using the tracking generator at the input. The test cables used can be connected together and normalisation can be performed to avoid their influence on the test result. A 3 dB marker can be used to measure the filter bandwidth at half amplitude of the filter (Figure 13). This S21 characteristic is a scalar measurement, since a spectrum analyser with superposition techniques does not contain phase information.

The RSA3000N has a vector network analyser mode. With this mode, S11, S21 or Distance-to-Fault measurements can be performed, since phase information is available in addition to amplitude information. With these functionalities, additional measurements are possible (such as phase over frequency range or with S11, Smith Chart/Polar Chart and accurate VSWR analysis). With the RSA3000N, the S11 back reflection characteristic was measured with the same filter (Figure 14).

The TX1000 in combination with a spectrum analyser such as the DSA815-TG or the RSA3015N is an ideal tool in educational areas such as universities and technical schools to easily demonstrate the complexity of a transmitter’s functionality. Not only can the analysers be used to create a hands-on lab for students, but due to their extreme flexibility, the instruments can be used for many other engineering applications and further R&D measurements. RIGOL also offers an RX1000 board that can be used with the DSG800(A) series RF generator to perform the measurement procedures in the reverse direction to demonstrate a receiver’s functionality. RIGOL offers one of the best price/performance ratios with outstanding RIGOL quality, which is a result of our more than 20 years of test and measurement experience.

Products Mentioned In This Article:

• TX1000 please see HERE
• RX1000 please see HERE
• DSA800 Series please see HERE
• RSA3000N Series please see HERE
• DSG3000 Series has been discontinued, please see DSG3000B Series HERE
• DSG800 Series please see HERE

RIGOL Technologies extended the RF test system of DSA800 spectrum analyser with additional tests for passive key less entry systems. RIGOL’s test solution is very comfortable to use and much cheaper than other available test systems on the market.
Passive keyless entry [PKE] communication is an electronic lock system mainly used to open cars or buildings without a mechanical key. This lock system works with a passive component (key) which will be activated by a device (e.g. a car) sending a periodical signal to its environment. One most common example is the keyless entry system in a car. The car sends always a constant low frequency [LF] signal around 130 kHz to its environment. If the correct key is closed to the car (~1.5 to 5 meter) then the key recognizes the LF signal and sends back the correct ID with an ASK or FSK modulated RF signal (UHF1). With opening the car door it will be unlocked. With some keys it is also possible to start the car via a button when the key is internally the drivers cab or to open the door of rear trunk. The used frequency of UHF signal depends of location. Mainly ISM2 bandwidth for carrier frequency of 433 MHz will be used in Europe. This application uses also a carrier frequency of 868 MHz in Europe but this frequency range is not part of an ISM bandwidth. USA and Japan use mainly the frequency band of 315 MHz.
Two kinds of procedures are possible3:
1.) Car sends a LF signal with a short wake up signal

1 UHF = Ultra High Frequency (range: 300 MHz to 1000 MHz)
2 ISM = Industrial Scientific and Medical Band are bandwidth which can be used with a defined maximum power in industry, scientific, medical or private applications. ISM defines two types: Type A and Type B. Type B bandwidth can be used without requesting an official license. The most popular ISM band is 2.4 GHz to 2.5 GHz, used for WIFI.
Systems in Modern Cars, Aur´elien Francillon, Boris Danev, Srdjan Capkun Department of Computer Science ETH Zurich 8092 Zurich, Switzerland, §2.2

• In a defined period a car sends a LF signal with short information to its environment (wake up signal).
• If a keyless entry key is closed to the car, the key sends an acknowledgement (UHF) to the car.
• The key and the car starting a data communication with ID check.
• Car sends an ID to the key. If the ID is correct, the key sends the correct key code. If this key code is correct, then car let you open the door.
  2.) Car sends a LF signal with car ID
• In a defined period the car sends a LF signal with the car ID to its environment.
• If a keyless entry key is closed to the car and ID is correct, the key sends the correct key code. If this key code is correct, the car can be opened.
  FSK – Frequency Shift Keying
  Frequency Shift Keying (FSK) is a digital modulation form. The principle of shift keying is to modulate a digital signal to a carrier and the changes are discrete in nature. The basis form is 2FSK. 2FSK is used e.g. in keyless entry systems like a car key or a tire pressure monitoring system. In simplest form of 2FSK modulation two digital state “0” and “1” (2FSK with 1 bit/symbol) will be transmitted with two different frequencies. These two frequencies are modulated to a carrier frequency and both have the same distance to the carrier. The difference to analogue frequency modulation (FM) is that the two transmitted frequency changes in the rhythm of binary data. In FM the frequency changes according to the analogue modulation frequency.
  The distance of both frequencies to carrier is defined as FSK deviation:
• FSK deviation = Δf
• fcarrier ± Δf
  Example:
  2FSK with Δf = 40 kHz and fcarrier = 866 MHz is visible in figure 1

Figure 1: 2FSK Signal with FSK deviation of 40 kHz, fcarrier = 866 MHz, tested with DSA832E

The frequency shift of both frequencies is 80 kHz:

• fmax = fcarrier +Δf = 866 MHz + 40kHz
• fmin = fcarrier – Δf = 866 MHz – 40kHz
• fmax – fmin = 80kHz
  Frequency shift is 2 x FSK deviation:
• Δ(f2-f1) = 2 x Δf
  In constellation diagram of a 2FSK signal is visible in figure 2.
  The tests performed in figure 3 and figure 4 show different kind of important measurement:
• Signal shall not be higher than customer defined pass / fail curve (see figure 3). Test can be performed with a DSA832, DSA832E or DSA875.
• Absolute power values of these two frequencies can be analysed (figure 4, marker 2R and 3D)
• Information of carrier offset can be checked with marker function (figure 4, marker 1D)
• Difference of power values of two frequencies can be measured (figure 4, marker 2R and 2D)
  Another measurement is the analysis of occupied bandwidth (OCP). OCP measures the frequency range which contains 99% of spectral power of signal. The carrier frequency is centered in the middle of this frequency range (see figure 5). OCP can be measured with DSA800 with the option DSA800-AMK.
  Calculation of OCP for 2FSK is defined as follow:
• OCPBW6 = Data rate + 2 x Δf

Figure 2: Constellation diagram of 2 FSK, carrier frequency is in the middle

Figure 3: pass / fail mask for curve analysis

Figure 4: Measurement values of 2FSK signal (see marker table)

Figure 5: Measurement of occupied bandwidth with a 2FSK signal

4 Speed of DSA832, DSA832E and DSA875 (sweep time of 10 msec: processing time is 30-40 msec.): measure speed of ~50 msec. is possible in normal mode.
5 Following tests can be performed with the option DSA800-AMK: Time Power, Adjacent Channel Power, Channel Power, Occupied Bandwidth, Emission Bandwidth, Signal to Noise Ratio, Harmonic Distortion, Third Order Intercept Point
6 With influence of a roll off factor e.g. with 0.35, OCP will be lower than the calculation.

Example: Data rate: 10kSymbols/sec. and frequency deviation: 40 kHz

• OCPBW = 10 kSymbols/sec. + 2 x 40kHz = 90 kHz
  Filtering:
  The target of filtering is, that the digital pulses will get a smoother rounded pulse form (according a gauss clock) to get better spectral results and reduce the bandwidth. In RIGOL’s software ULTRA IQ STATION it is possible to select different filter types. A special Gauss Filter for FSK modulation is available to reduce the bandwidth before transmission. Filtering of FSK modulation with that kind of filter results this modulation form into a GFSK modulation. In this software it is possible to adjust the roll off factor (α = B*T), the impulse length (amount of samples per pulse with duration of one bit) and oversampling (additional sampling to be better compliant of sampling theorem to use a simpler reconstruction filter). A gauss characteristic is visible in figure 6. The length of filter is the product of Impulse length and oversampling values. Roll-off factor α is calculated with:
• the bandwidth (@-3 dB) of gauss characteristic: B
• the duration of one bit: TBit
  2FSK Signal can be generated with Software ULTRA IQ STATION and can be downloaded to an RF signal generator with IQ option (DSG3030-IQ or DSG3060-IQ7).
  The clock frequency in the generator will set the wavetable output clock rate. This clock frequency will be calculated from oversampling value and symbol rate (One symbol contains one bit in this 2FSK modulation example).
  Clock frequency = oversampling value * symbol rate

Figure 6: Gauss characteristic

Software S1220 for 2FSK demodulation

DSG3030-IQ: 9 kHz to 3 GHz; DSG3060-IQ: 9 kHz to 6 GHz; IQ Modulator is an Option and contains also external analogue I and Q in-, and outputs

RIGOL provides (option) a demodulation software solution for ASK / FSK demodulation with software S1220. This software works with spectrum analyser DSA832, DSA832E and DSA8758. ASK demodulation will be described at the end of this document.

• This software displays the symbol waveforms of modulation
• Eye diagram can be analysed. This is important to see to analyse jitter effects.
• Specific pattern can be set as reference. Each time the pattern will be transmitted, it will be marked in yellow.
• Carrier Power, Frequency deviation and Carrier frequency offset will be measured.
• Manchester encoding is supported.
• Load and save configuration data

FSK Measurement with DSA815 / DSA705 / DSA710
Software S1220 is usable for
DSA832(E)/DSA875. The measurement speed of
DSA815 / DSA705 and DSA710 is lower than
DSA832(E)/DSA875 and their speed for 2FSK signals are too slow. RIGOL solve this problem with a new option for signal seamless capture (SSC-DSA)9. With the option SSC-DSA 2FSK analysis is also possible to do the FSK measurement with DSA815 / DSA705 and DSA710. With this option the analyser switches into a FFT mode with faster capturing speed. FSK signal measurement (up to three different 2FSK signals) can be performed with that option (see figure 10) in parallel up to 1.5 MHz directly with the device without additional software.
This option has three different main features:

• Real time trace (RT Trace)
• Maximum hold function
• 2FSK signal capture analysis which includes

8 Analyser will be set into a DMA mode (FFT Mode). The analyser can only be controlled with S1220 in DMA mode. 9 This option is only valid for DSA705, DSA710 and
DSA815

o also a maximum hold function parallel to continuous test
o pass/fail measurement according to limit lines to be set
o activation of two mark lines
o measurement of two frequencies from 2FSK signal, amplitude of both frequencies, frequency deviation and carrier offset

Figure 7: 2FSK Signal generation with ULTRA IQ STATION

Figure 8: Software S1220 for ASK / FSK demodulation

Figure 9: FSK configuration in S1220

Figure 10: 2FSK measurement with DSA815 and SSC option

ASK – Amplitude Shift Keying
ASK is also a digital modulation form used in e.g. keyless entry or radio beacon in navigation. In simplest form, the characters one “1” and “0” of digital signal will be multiplied with a carrier frequency (see figure 12 to figure 14). On/Off Keying is used in keyless entry systems using ASK modulation.
On/Off Keying (OOK):

• Carrier will be on with “1”; carrier will be off with “0”.
• ASK modulation is 100% (see figure 14) ASK can also be transmitted with a constant carrier. In this case zero “0” will be transmitted with a lower frequency than one “1”. ASK modulation could be e.g. 10% (e.g. for near field communication [NFC] with a bit rate of 424 kbps).
  ASK modulation index will be calculated as follow:
• m = (A-B)/(A+B) * 100
• If m = 8-14% then ASK modulation is ~10%.
• Modulation depth is B/A

Figure 11: 2FSK measurement with three parallel 2 FSK signals with max hold measurement

Figure 12: Pulse train with “1” and “0” (digital signal)

Figure 13: Carrier of ASK (sine signal))

Figure 14: ASK modulation (digital signal * carrier)

ASK bandwidth is defined with:

• B = 2 x Symbol Rate
  ASK signals can also be generated in RF signal generator DSG3000-IQ (e.g. DSG3060) together with software ULTRA IQ STATION (see figure 16).
  The frequency range is visible in figure 17. ASK Spectrum shows the bandwidth of 2 x sample rate. This spectrum is visible with different signal lines. This makes sense because the expectation of spectrum is not only an on/off cw signal of this modulation form.
• A pulse in time range is a SI (sinx/x) function in frequency range.
• A (constant 0101..) pulse train in time range is a SI function multiplied with a dirac train (like a train of pulses with very small pulse width) in frequency range.
• The multiplication with a carrier results into a shift of this function to the frequency of carrier.

Figure 15: ASK modulation of 10%

Figure 16: ULTRA IQ STATION settings for ASK generation

Figure 17: Spectrum of ASK

Digital Signal is visible in zero span mode (see figure 18). The pulse train in time range can be analysed in this mode.
ASK signal can also be analysed with RIGOL’s S1220 ASK-FSK demodulation software. Settings and analysis form are the same like for 2FSK analysis.

Figure 18: Zero Span analysis of ASK Signal

Figure 19: S1220

Products Mentioned In This Article:

• DSG3000 Series has been discontinued, please see DSG3000B series HERE
• DSA700 Series please see HERE
• DSA800 Series please see HERE

Introduction
The DSG3000 (DSG3000B) Series RF signal source (Figure 1) is designed for RF engineering and signal development and test up to 6 GHz. The instrument is also capable of a number of modulation formats. One of the more advanced capabilities is IQ modulation that is enabled with the DSG3000-IQ option. This option adds both a baseband generator and the ability to externally generate IQ modulation for the carrier. The baseband generator’s I & Q data can also be directly output for additional verification and testing. Rigol’s Ultra IQ Station Software (Figure 2) makes it easy to generate standard IQ signals and load them into the instrument, but many engineers are now working with advanced, custom data or are experimenting with new modulation schemes for IQ data altogether. For these applications, Rigol has developed the following code examples for taking I & Q data in Matlab and delivering it directly to the instrument natively from within Matlab.
This guide will demonstrate how to install and configure the Rigol Matlab code as well as run several examples that load data into the instrument. We will then show the results using our DSA875 Spectrum Analyser (Figure 3) on the modulated carrier and our DS2000A Series oscilloscope on the baseband outputs.

Figure 1: Rigol DSG3060

Figure 2: Ultra IQ Station Software

Figure 3: Rigol DSA875

Installation and Configuration
Required components
There are several requirements for running the example code. We have tested the example code on the current version of Matlab as of this writing which is R2014b. First, download the Rigol custom IQ example here. The example code combines C++ to create the binary data streams with LabVIEW and VISA that handle the instrument communication. That code needs to be accessed from the Matlab command window. To achieve that several items may need to be installed in your system:
1) Microsoft Visual Studio C++ 10.0 and the Windows SDK 7.1
2) LabVIEW runtime engine for 2013 for your OS
3) VISA which installs with Rigol’s UltraSigma
Details:
1) The Microsoft tools are required to access the compiled C++ code that encodes the Rigol IQ data streams. Go here for the Matlab answer for installing these components to work with Matlab. Read the entire answer as there are different installation plans depending on what you currently have installed. Once you have installed the Microsoft tools you can verify the compiler settings from within Matlab by following these steps:
• Open Matlab
• Browse to the Rigol Custom IQ Example folder (Figure 4)
• In the Command Window at the prompt type ‘mex –setup’
• Matlab will respond with its current compiler settings. These responses are acceptable:
• Microsoft Windows SDK 7.1 (Figure 5)
• Microsoft Visual C++ 2010 (Figure 6)

Figure 4: Matlab window with Browse button highlighted and a mex –setup response in the command window

Figure 5: Text from a Matlab mex –setup response related to the C++ compiler settings using SDK 7.1

Figure 6: Text from a Matlab mex –setup response related to the C++ compiler settings using Visual C++ 2010

If Matlab is using some other compiler or has yet to select a compiler follow the links and information in the mex –setup response to configure one of these compilers. The example code may or may not work correctly with other compiler settings.
2) Download and install the NI LabVIEW runtime 2013 applicable for your operating system.
This download may require you to register at ni.com and the PC should be rebooted after installation. The example code has been tested on 64 bit and 32 bit systems. All of the required components are available for other OS options as well, but this example was not developed or tested for those environments.
3) Install Rigol UltraSigma. Download it here. It is a 522 MB file that includes the required VISA drivers. It is also helpful for identifying your DSG3000’s VISA address quickly and easily. That download include installation and usage guides for UltraSigma.
Connecting your DSG3000
Plug in and power on the DSG3000 signal source. Push the green PRESET button on the left to reset it to the default conditions. Now connect the USB Device port on the rear panel to the PC running Matlab. The DSG3000 can also connect over Ethernet or GPIB, but we will focus on USB communication.

Then, Run UltraSigma and you will see the DSG3000 appear in the Resource list (Figure 7). The string in parentheses after the model number is the VISA resource string. This is the string we need to edit in our Example.m file. To copy the address right click on the instrument model number and select Operation  Copy Address (Figure 8). Now we will edit the Example.m file in Matlab to have the correct resource address for our connected instrument. In Matlab, right click on Example.m in the Current Folder window and select Open. The file will now open in the editor. In the first line of code InstrVisaAddress is set equal to a string in single quotes. Highlight the string leaving the single quotes and paste the string we copied from UltraSigma. This Matlab view is shown in Figure 9. Once this is complete save the Example.m file. Repeat the paste and save process on Example2.m for later. We are now ready to run the examples. Remember, the DSG3000 must have the DSG3000-IQ option enabled to accept these commands.

Creating Custom IQ data
This example creates the simplest IQ data stream by encoding the I data as sine and Q data as cosine:
InstrVisaAddress =
‘USB0::0x1AB1::0x0992::DSG3A161250003::INSTR’; x = linspace(0,2*pi,1000);
Idata = sin(x); Qdata = cos(x);
status =
RIGOL_PACK_ARB(‘test.arb’,Idata,Qdata,100000); status = RIGOL_DOWN_ARB(InstrVisaAddress,
‘test.arb’,’test.arb’,1,1);
First, we set the VISA resource address. Then, we create arrays of data for I and Q. Next, we pack that information into a binary file and then we finish by sending that data to the instrument.
There are 2 custom commands that call Rigol compiled code:

RIGOL_PACK_ARB
This command converts I & Q data arrays into a local arb file that can be loaded directly to the instrument. The file describes both the data and the desired playback speed. [ status ] =
RIGOL_PACK_ARB(LocalFileName,Idata,Qdata,SampleRate) Definition:
• LocalFileName is the local file to create on the computer. MUST end in .arb

• Idata is the vector of real numbers representing the I data over time. Values should be -1 to 1.
• Qdata is the vector of real numbers representing the Q data over time. Values should be -1 to 1.
• SampleRate is the real number representing the number of samples to put out per second. Default is 100 kSa/sec or a 100 kHz sample rate, so the units is kHz. Value can be set from 1 to 50000. 100000 can also be discreetly set.
Status returns 0 for success and 1 for a failure to pack the file.
RIGOL_DOWN_ARB
This command downloads a local arb file created by RIGOL_PACK_ARB to a connected DSG3000 instrument and optionally enables the output.
[ status ] = RIGOL_DOWN_ARB(InstrVisaAddress, FileNameOnInstr, LocalFileName, OutputEn, KeepLocalFile)
Definition:
• InstrVisaAddress is a string representing the VISA resource name for the DSG3000 you want to load the file to. Typical string would look like
‘USB0::0x1AB1::0x0992::DSG3A1301080006::INSTR’ for a USB resource.
• FileNameOnInstr is the file name to give the wave on the instrument. It MUST end in .arb. This filename is changed to all capital letters in the instrument.
• LocalFileName is the file name created during the PACK procedure. It MUST end in .arb
• OutputEn is the output enable option. Send 1 to automatically load and output the file. 0 does not enable the output. 1 is the default.
• KeepLocalFile determines what to do with the local file on the computer after loading is complete. Send 1 to automatically save the file. 0 deletes the file. 1 is the default.
Status returns 0 for success and 1 for a failure to pack the file.
Tips:
File names do not support paths. Use files directly. Getting active output may require setting of RF, MOD, and or IQ SWITCH to ON. Verify these are active when trying to view output signals.

Custom IQ Test and Verification
Now that we have explained the functions we can run the examples provided. The first example, which we have already discussed, creates a simple sine wave and cosine wave in the I & Q data respectively. We test and verify this with our DS2000A Series oscilloscope. First, connect the Baseband I & Q outputs on the rear panel of the DSG3000 to the channel 1 and channel 2 inputs of the oscilloscope. I out should be connected to channel 1. Q out is connected to channel 2.
Then, run Example.m by right clicking on the name in the current folder window in Matlab. Select Run from the popup. The code will execute and after a few seconds the outputs will appear on the oscilloscope. You can reset the DS2000A oscilloscope to the factory defaults:
• Push Storage
• Select Default
Then, from the factory settings Push AUTO. For our purposes we want to see the relationship in phase between I & Q. While it is a simple comparison because the sine and cosine are 90° out of phase, it is still instructive to view in XY mode. Push the HORIZONTAL MENU button and under TIME BASE select XY. By adjusting the channel scales and offsets you can center that image to get to Figure 10. This view is relevant because it is similar to a basic constellation decoding view used for signals encoded with phase information.
Lastly, we can run Example2.m the same way. This file generates IQ data that traverses a basic 4 x 4 constellation diagram and repeats as shown in Figure 11.
If we connect the DSA875 to the RF output and mix this data onto a 6 GHz carrier by setting the DSG3000 Level to -10 dBm, turning on the RF and MOD lights, and turning the IQ Switch to ON we can view the occupied bandwidth of the signal. The IQ data from Example2 has the spectrum shown in yellow on Figure 12. If we change the SampleRate in the RIGOL_PACK_ARB command from 10 kHz to 1 MHz and run it again the spectrum is now the purple signal in Figure 12.
Therefore, with our DSG3000 RF signal source,
D2072A oscilloscope, our DSA875 spectrum analyser, and our Matlab examples we can create our own custom IQ data, test, and verify the basic IQ constellation patterns as well as compare spectrum usage making a good start on our exploration or advanced RF modulation schemes.

Figure 10: Scope XY mode view of I and Q baseband signals showing phase relationship

Figure 11: Scope XY mode view of Example2.m

Figure 12: DSA875 showing the Example2 modulated signal at 10 kHz and 1 MHz IQ symbol rates

Products Mentioned In This Article

• DSG3000 Series has been discontinued, please see DSG3000B HERE.
• DS2000A Series Oscilloscopes please see HERE.
• DSA875 Spectrum Analyser please see HERE