Lab 1 – Introduction to Software-Defined Radio
ECE531 – Software Defined Radio
1 Overview 2
2 Required Software 2
2.1 GNU Radio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
2.2 MATLAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.3 Git . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
3 Introduction 4
3.1 Getting Started with the GNU Radio Companion . . . . . . . . . . . . . . . . . . . . . . . 5
3.2 Sampling Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
3.3 Complex Sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3.4 Frequency Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
3.5 I/Q Imbalance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.6 Adding Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.7 Interpolation and Decimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
4 Questions 10
5 Lab Report Preparation & Submission Instructions 11
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1 Overview
This laboratory will introduce basic software-defined radio (SDR) concepts through GNU Radio
simulations.
2 Required Software
This course will require a number of different software tools. Many of these tools are compatible
with Windows, Linux, and OSX operating systems. While the goal of the labs will be to remain
platform agnostic, there are many SDR software tools which are available solely for the Linux
operating system.
Students are encouraged to take the time to setup a Ubuntu Linux installation for use in this class
and the final project [1]. This can be accomplished in a variety of methods; including a dual-boot,
“Live USB” environment [2], or through visualization software like VMware or VirtualBox. An
Instant GNU Radio [3] OVA VM image has been posted to D2L and can be used for this lab. The
VM is reconfigured with PlutoSDR support.
2.1 GNU Radio
GNU Radio is a free & open-source software development toolkit that provides signal processing
blocks to implement software radios [4]. It can be used with readily-available low-cost external RF
hardware to create software-defined radios, or without hardware in a simulation-like environment.
It is widely used in research, industry, academia, government, and hobbyist environments to support
both wireless communications research and real-world radio systems.
GNU Radio is a highly modular, “flowgraph”-oriented framework that comes with a comprehensive library of processing blocks that can be readily combined to make complex signal processing
applications. It has been used for a huge array of real-world radio applications, including audio
processing, mobile communications, tracking satellites, radar systems, GSM networks, Digital
Radio, and much more – all in computer software.
It has filters, channel codes, synchronisation elements, equalizers, demodulators, vocoders,
decoders, and many other types of blocks which are typically found in signal processing systems.
More importantly, it includes a method of connecting these blocks and then manages how data is
passed from one block to another.
Extending GNU Radio is also quite easy; if you find a specific block that is missing, you can
quickly create and add it. The GNU Radio community has releases am always-expanding library of
3rd party GNU Radio applications. The Comprehensive GNU Radio Archive Network (CGRAN) is
a free open source repository for Out-Of-Tree (OOT) Modules that are not officially supported by
the GNU Radio project [5]. “gr_modtool” is also available to assist in custom GNU Radio module
and signal processing block creation [6].
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2.1.1 Install GNU Radio
Obtain and install a copy of GNU Radio to simulate software-defined radio baseband signal
processing. A prebuilt GNU Radio windows binary installer was distributed by Analog Devices Inc.
(ADI) and may now be considered outdated. This installer includes native “IIO” support needed to
interface with the Pluto hardware. This installer is also archived on the class D2L web site.
VirtualBox VM: Preconfigured Linux Virtual Machine image available here.
radioconda: Conda-based Python Distribution available here.
Windows Installer: Windows installer is available here. (version 3.7)
Linux Installer: Linux install instructions are here.
2.2 MATLAB
MATLAB also provides support needed to prototype and test software-defined radio (SDR) systems
using Analog Devices ADALM-PLUTO with MATLAB and Simulink. An academic license for
MATLAB and toolboxes is available at no cost to UA students at: https://softwarelicense.
arizona.edu/mathworks-matlab.
2.2.1 Install MATLAB with Toolboxes
Students may choose to install all toolboxes with their MATLAB installation. This may grant some
added capability for final projects. At a minimum, The Mathworks suggests the following toolboxes
to support the PlutoSDR hardware:
Required Toolboxes:
• MATLAB
• Communications Toolbox
• DSP System Toolbox
• Signal Processing Toolbox
Recommended Toolboxes:
• Simulink
• LTE Toolbox
• WLAN Toolbox
MATLAB installation can be interfaced with hardware such as the PlutoSDR through Hardware
Support Packages [7]. We will install the Hardware Support Package and begin working with the
PlutoSDR hardware in Lab 2.
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2.3 Git
Git is a distributed version control system (DVCS) used heavily for collaboration of open-source
project such as GNU Radio. A vast majority of SDR software and signal processing algorithms
are hosted on GitHub. Source code for the software, firmware, drivers, and utilities needed for
the PlutoSDR hardware used in this course are publicly available on the Analog Devices github
account [8].
Github is an effective way to collaborate and manage source code for the project. Students
can also receive a free upgraded account and access to a numerous software tools at https:
//education.github.com/students. You will require a free GitHub account. A git software
installer is available at https://git-scm.com/.
3 Introduction
A software defined radio system (SDR) is a radio communication system where components that have
been typically implemented in hardware (e.g., mixers, filters, amplifiers, modulators/demodulators,
detectors) are instead implemented by means of software on a personal computer or embedded
system. Most conventional radios utilize the classic superheterodyne receiver architecture, similar
to what is shown in Figure 1. In a superheterodyne architecture, the RF signal from the antenna is
mixed with a local oscillator to produce an intermediate frequency, or IF. Conversely, SDR uses
direct-conversion architecture, shown in Figure 2. A direct-conversion transceiver, also known as
homodyne, synchrodyne, or zero-IF transceiver, is a radio transceiver design that (de)modulates
the radio signal using a local oscillator (LO) whose frequency is identical to, or very close to, the
carrier frequency of the intended signal. Direct-conversion eliminates the IF by translating the band
of interest directly to baseband (DC).
Figure 1: Multistage superheterodyne receive and transmit signal chains
Comparing Figure 1 and Figure 2, direct conversion is attractive due to simplicity of the signal
path and is an enabling architecture for software-defined radio.
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Figure 2: Direct conversion, or Zero-IF transceiver architecture used for software-defined radio.
3.1 Getting Started with the GNU Radio Companion
GNU Radio Companion (GRC) is a graphical user interface that allows you to build GNU Radio
flowgraphs using predefined DSP blocks. GRC was created to simplify the use of GNU Radio by
allowing us to create python files graphically as opposed to creating them in code alone (we will
discuss this more later). Start the GRC by typing gnuradio-companion in a terminal window in
Linux and you will see an untitled GRC window similar to Figure 3.
Figure 3: The GNU Radio Companion Interface. There are four main parts: Library, Toolbar, Terminal, and Workspace.
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3.2 Sampling Rates
The definition of proper sampling is quite simple. Suppose you sample a continuous signal in some
manner. If you can exactly reconstruct the analog signal from the samples, you must have done the
sampling properly. Even if the sampled data appears confusing or incomplete, the key information
has been captured if you can reverse the process
Given the flowgraph shown in Figure 4, we have a single sinusoidal frequency source with a
frequency of 2 kHz. The sampling rate is able to be changed at runtime using the “QT GUI Range”
block. Each flowgraph block is colored orange to denote a real, Float 32, input/output type. You can
lookup the color for each data type from the GRC help menu.
Figure 4: GRC flowgraph for Lab 1, Section 3.2
Given the flow graph in Figure 4, complete the following:
1. Construct and execute the GRC flowgraph shown in Figure 4.
2. Visualize the sinusoidal signal in time and frequency, provided by the “Time” and “Frequency”
sink tabs.
3. Using the default 10 kHz sample rate: Zoom in on the time domain signal. Does this look as
expected? Determine the location of the frequency peak. Hover over the peaks and measure
the frequency location.
4. While continuing to observe frequency tab, slowly adjust the sampling rate from 10 kHz to
40 kHz. Determine the measured frequency? (Note: you may need to give the frequency sink
a moment to adjust to the new sample rate.)
5. What does the time domain signal look like at this new sample rate? Why?
6. Adjust the sampling rate to 3.5 kHz. What is the measured frequency? Did the measured
frequency remain the same or did it change? Why? If so, how much did the frequency change
and why?
7. Save the grc file with a unique filename for use in later sections.
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3.3 Complex Sampling
Direct conversion transceivers, like shown in Figure 2, utilize in-phase (I) and quadrature (Q)
signal paths to sample a complex signal. In-phase refers to the signal that is in the same phase
as the local oscillator (LO), and quadrature refers to the part of the signal whose phase is shifted by 90°.
A bandpass signal can be represented by the sum of its in-phase (I) and quadrature (Q) components:
S(t) = I(t) cos(2π fct) − Q(t)sin (2π fct). (1)
where I(t) is in-phase amplitude, Q(t) is quadrature amplitude and fc is carrier frequency.
Figure 5: GRC flowgraph for Lab 1, Section 3.3
Given the flow graph used previously in Figure 4:
1. Change all block input/output types from “Float 32” to “Complex Float 32”. The port color on
each block should change from orange to blue as shown in Figure 5. (Note: You can quickly
change the input/output type by highlighting the block(s) and pressing the up/down arrows).
2. Visualize the sinusoidal signal in the frequency domain. What has changed? Why?
3. What are the two time domain waveforms shown on the “Time” tab? What is the phase
relationship between them?
4. While observing the time domain tab, slowly adjust the sampling rate from 10 kHz to 40 kHz.
Does the signal amplitude appear as expected for each channel? (Note: You may wish to
zoom in on the time signal).
5. What is the measured frequency peak at 40 kHz sampling rate?
6. While observing the frequency domain tab, slowly decrease the sampling rate to 4 kHz. What
is observed?
7. Continue to slowly decrease to slower sampling rates. What happens? Why?
8. Save the grc file with a unique filename for use in later sections.
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3.4 Frequency Observations
3.4.1 Complex-sampled Flowgraph
Given the complex-sampled flowgraph used previously in Figure 5:
1. Add an adjustable frequency slider using a QT GUI Range block with the following parameters:
Frequency Default value: 2e3, Start: 0, Stop: 15e3, Step: 100
2. Set the signal source frequency to the variable ID used for the QT GUI Range block above.
3. Using a fixed 10 kHz (default) sample rate: Slowly increase the frequency to the maximum
frequency value while observing the frequency sink output.
4. Describe what anomaly is observed when increasing the frequency slider. What is this
anomaly? Why does it occur?
Figure 6: GRC flowgraph for Lab 1, Section 3.4
3.4.2 Real-sampled Flowgraph
Given the flowgraph used previously in Figure 4, or by changing the types to real; Repeat the steps
above, specifically:
1. Add an adjustable frequency slider using a QT GUI Range block with the following parameters:
Frequency Default value: 2e3, Start: 0, Stop: 15e3, Step: 100
2. Set the signal source frequency to the variable ID used for the QT GUI Range block above.
3. Using a fixed 10 kHz (default) sample rate: Slowly increase the frequency to the maximum
frequency value while observing the frequency sink output.
4. What is observed when increasing the frequency? How and why is this different than what
was observed in Section 3.4.1?
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3.5 I/Q Imbalance
Figure 7: GRC flowgraph for Lab 1, Section 3.5
Given the flow graph used previously in Figure 5:
1. Add an IQ Imbalance Generator block to the flowgraph somewhere in the signal path between
the signal source and sink blocks. An example is shown in Figure 7
2. Create two QT GUI Range blocks, one with variable ID “magnitude” and another with ID
“phase”. Set the following parameters respectively:
Magnitude Default value: 0, Start: 0, Stop: 1, Step: 0.1
Phase Default value: 0, Start: 0, Stop: 6.2, Step: 0.1
3. Set the IQ Imbalance Generator values for magnitude and phase to the variable IDs provided
to the GUI Range blocks. (Note: these happen to be the Python variable names. You can use
Python syntax in most block fields).
4. Add a “QT GUI Constellation Sink” block to a third tab and connect to the same location as
the other sinks.
5. Your flowgraph should now resemble the one shown in Figure 7.
6. Execute the new flowgraph. The time and frequency domain should match what was observed
previously.
7. While observing the frequency domain tab, slowly increase the phase imbalance from zero.
What happens? Why?
8. Return the phase offset to zero and then slowly increase the amplitude imbalance from zero.
What happens? Why?
9. While observing the constellation sink output, adjust each of the three variables independently.
What happens when each slider is adjusted?
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3.6 Adding Noise
Given the flow graph used previously in Section 3.5:
1. Add gaussian noise to the signal using the “Noise Source” and “Add” blocks.
2. Describe what happened to the signals displayed on each tab; time, frequency, and constellation.
3. Use the “QT GUI Histogram Sink” blocks to verify the pdf of the various noise source types
by connecting directly to the noise source.
3.7 Interpolation and Decimation
The following flowgraph uses the three signal sources with identical parameters; including frequency.
Each source is resampled using a rational resampler block and displayed on three-port sink blocks.
Figure 8: GRC flowgraph for Lab 1, Section 3.7
Given the flow shown in Figure 8:
1. Construct and run the given flowgraph.
2. Observe the time and frequency domain outputs.
3. What do you observe with the three waveforms?
4. The three signal sources have identical properties including frequency. Why do they differ
when the frequency spectrum is visualized?
5. What are the relationships between the waveforms? Which one is interpolated and decimated?
4 Questions
1. What are the benefits of using in-phase and quadrature (I & Q) samples for SDR? Fully
describe at least three benefits of IQ sampling.
2. In GNU Radio What is the Throttle block for? When should it be used? What happens if you
use more than one throttle block? When is a throttle block unnecessary?
3. What are Nyquist zones? How are they useful with software-defined radio?
4. Why is dither noise used on Digital-to-Analog converter (DAC) circuits?
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5 Lab Report Preparation & Submission Instructions
Include all your answers, results, and source code in a laboratory report formatted as follows:
• Cover page: includes course number, laboratory title, name, submission date.
• Suggested: Table of contents, list of tables, list of figures.
• Commentary on designed implementations, responses to laboratory questions, captured
outputs, and explanation of observations.
• Meaningful conclusions to the lab.
• Source code (as an appendix). You may also upload source files with report submission.
Remember to write your laboratory report in a descriptive approach, explaining your experience
and observations in such a way that it provides the reader with some insight as to what you have
accomplished. Furthermore, please include images and outputs wherever possible in your laboratory
report document.
References
[1] Canonical Ltd. (2018) Download ubuntu desktop. [Online]. Available: https:
//www.ubuntu.com/download/desktop
[2] Corgan Labs. (2017) GNU Radio Live SDR Environment. [Online]. Available:
https://wiki.gnuradio.org/index.php/GNU_Radio_Live_SDR_Environment
[3] B. Bloessl, “Github: Instant gnu radio.” [Online]. Available: https://github.com/bastibl/
instant-gnuradio
[4] GNU Radio Foundation, Inc. GNU Radio. [Online]. Available: https://www.gnuradio.org/
[5] The Comprehensive GNU Radio Archive Network. [Online]. Available: http://cgran.org
[6] E. Blossom, “gr_modtool: Swiss Army Knife for editing GNU Radio modules and -components.”
November. [Online]. Available: https://wiki.gnuradio.org/index.php/OutOfTreeModules#gr_
modtool_-_The_swiss_army_knife_of_module_editing
[7] The Mathworks. ADALM-PLUTO Radio Support from Communications Toolbox. [Online].
Available: https://www.mathworks.com/hardware-support/adalm-pluto-radio.html
[8] Analog Devices, “GitHub: Analog Devices Inc.” [Online]. Available: https:
//github.com/analogdevicesinc
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