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Software Defined Radios for Small Satellites
Mamatha R. Maheshwarappa Christopher P. Bridges
Surrey Space Centre, Faculty of Electronic Engineering Surrey Space Centre, Faculty of Electronic Engineering
University of Surrey University of Surrey
Guildford, Surrey, United Kingdom – GU2 7XH Guildford, Surrey, United Kingdom – GU2 7XH
m.maheshwarappa@surrey.ac.u
k
c.p.bridges@surrey.ac.uk
Abstract - Clusters, constellations, formations, or ‘swarms’ of
small satellites are fast becoming a way to perform scientific and
technological missions more affordably. As objectives of these
missions become more ambitious, there are still problems in
increasing the number of communication windows, supporting
multiple signals, and increasing data rates over reliable
intersatellite and ground links to Earth. Also, there is a shortage
of available frequencies in the 2 m and 70 cm bands due to rapid
increase in the number of CubeSats orbiting the Earth – leading
to further regulatory issues. Existing communication systems and
radio signal processing Intellectual Property (IP) cores cannot
fully address these challenges. One of the possible strategies to
solve these issues is by equipping satellites with a Software
Defined Radio (SDR). SDR is a key area to realise various
software implementations which enable an adaptive and
reconfigurable communication system without changing any
hardware device or feature. This paper proposes a new SDR
architecture which utilises a combination of Field Programmable
Gate Array (FPGA) and field programmable Radio Frequency
(RF) transceiver to solve back-end and front- end challenges and
thereby enabling reception of multiple signals or satellites using
single user equipment.
Keywords - Software defined radio; front/back end challenges;
GNURadio
I.
I
NTRODUCTION
Small satellites are attractive due to reduced build time,
more frequent launch opportunities, larger variety of missions,
more rapid expansion of the technical and/or scientific
knowledge base, greater involvement of small industries and
universities [1, 2]. A recent example is the launch of Minotaur-
1 [3] and Dnepr-19 [4] with 63 small satellites added to Lower
Earth Orbit (LEO). This has created strain for licensing and
coordinating organizations, such as the Federal
Communications Commission (FCC) and the International
Amateur Radio Union (IARU) [5]. As mentioned at several
recent workshops [6, 7], the FCC and International
Telecommunication Union (ITU) are in process of clamping
down on licensing for small satellites – particularly in the VHF
band. It is, therefore, important to develop an efficient way of
utilizing this limited bandwidth resource. This expected
shortage of bandwidth has prompted the researchers to explore
new ways of efficiently using limited bandwidth [8, 9]. The
existing small satellite communication systems cannot fully
support these challenges.
One of the possible strategies to solve the above issues is
by equipping satellites with a Software Defined Radio (SDR) -
"Radio in which some or all of the physical layer functions are
software defined" [10]. SDRs offer functionalities otherwise
hard to achieve such as in-flight re-configurability, adaptability
and autonomy which enables limited subsystem re-design and
can develop towards a generic satellite communication
solution. These benefits offered by SDRs and the continuous
advances in commercial digital electronics have triggered the
interest of small satellites in advanced communication systems
[11]. This increase in subsystem performance can potentially
offer satellite communications to looser constraints on
modulation parameters based on link conditions, frequency
bands, Doppler uncertainties and data rates at minimum cost,
thereby making dynamic multiband access and sharing
possible. This flexibility and adaptability comes however with
the expense of power consumption and complexity.
Since its conception in 1995 [10], the growth of terrestrial
SDRs is exponential as seen in Fig. 1. They have evolved not
only in technology from receivers to transceivers but also in
size, mass and power requirements. Though the growth of
space SDRs is slower compared to terrestrial SDRs, the range
of options is continually increasing and a few of these have
found mainstream acceptance in various forms such as payload
on bigger satellites (STS-107 and Mars Reconnaissance
Orbiter (MRO)) [12] and as a test bed on International Space
Station (ISS) [13] which have flown in NASA/ESA missions.
Cadet was developed for DICE as a half-duplex UHF radio
system to provide the high data rate communications system
for a CubeSat [48]. A wide-band receiver (SWIFT-WRX) by
tethers unlimited is aimed at future small satellite missions
[49]. With the above evolution of radios, the future aim is to
have an integrated system of wide-band transceiver along with
sufficient on-board processing, high-speed interfaces and high
data rate communications, as these still remain as major
challenges for small satellites.
Despite the high costs associated with space, the cost of
building satellites has been reduced through two significant
trends: namely, the use of Commercial off-the-shelf (COTS)
parts and miniaturisation. This paper proposes one such COTS
solution to address the future problems of ever increasing band
utilisation and an increasing small satellite community
targeting distributed satellite missions. The combination of
COTS Radio Frequency (RF) front-end and back-end
technologies for space applications is promising to solve these
issues, referring to the evolution of transceivers and current
state-of-the-art systems. It also highlights the need for an
adaptable software platform to enable multiple-signal
reception, re-assign frequencies, occupied bandwidth, and
various wireless standards. Further to this, the final aim is to
optimise in terms of power consumption and cost which are
typical major satellite design constraints.
978-1-4799-5356-1/14/$31.00 ©2014 IEEE
172
2014 NASA/ESA Conference on Adaptive Hardware and S
y
stems (AHS)
II.
B
ACKGROUND
I
NFORMATION
This section gives an overview of the evolution of wireless
radios which have passed through several generations from
traditional heterodyne radios to software defined radios and
the review is based on [14] and [15].
A. Traditional Radios
Compared to super heterodyne architecture, zero-IF
(Intermediate Frequency) architecture has a clear reduction in
the number of analog components and also allows the use of a
filter having much less stringent specifications than that of the
image-reject filter used in super heterodyne architectures. As a
result, this architecture can make use of a high level
integration, making it a common architecture for multiband
receivers. A configuration similar to the zero-IF receiver is the
low-IF architecture [16] in which the RF signals are mixed
down to a non-zero low to moderate IF instead of going
directly to Direct Current (DC). The signal is converted to the
digital domain with an Analogue-to-Digital Converter (ADC)
of relatively robust performance, which allows the use of Field
Programmable Gate Arrays (FPGAs) for digital filtering for
channel-selection and also mitigate in-phase quadrature (I/Q)
imbalances. However, in low-IF architecture, the image
frequency problem is reintroduced and the ADC power
consumption is increased because now a higher conversion
rate is required. This was followed by band-pass sampling
receiver as seen in [17] and [18], which was a realizable
version of software radio and is called ‘Software Defined
Radio’.
B. Software Defined Radio (SDR)
A SDR is a form of transceiver in which ideally all aspects
of its operation are determined using versatile, general-purpose
hardware whose configuration is under software control. This
solution allows inexpensive, and efficient interoperability
between the available standards and frequency bands. The
concept of SDR first appeared with the work of Mitola [10] in
1995 as shown in Fig. 2. SDRs should be able to adapt to the
air interface by optimising the carrier frequency, modulation,
and choice of radio standard to minimise interference and
maintain communication in a given scenario.
Fig. 2. Architecture of ideal software defined radio [20]
A signal incident on the antenna port is routed to a Low
Noise Amplifier (LNA) through a circulator and is then
digitized. Demodulation and decoding are accomplished in
various modulation formats and access schemes using Digital
Signal Processing (DSP)/FPGA.
At the transmitter stage, the
baseband signals are generated and up-converted into
analogue waveforms, amplified, and band-pass filtered before
passing through the circulator and antenna. The comparison
between the traditional and the software defined radios is
given in Table 1:
TABLE I. T
RADITIONAL RADIOS V
/
S
S
OFTWARE
D
EFINED
R
ADIOS
Traditional radios
Software defined radios
Pros:
• Limited processing and thus
selection of processor/
controller/ADC is less
critical
• Cheap and readily available
Pros:
• Flexible design: Multi-band/
multi-mode
• Software based
reconfigurable platform
• Upgradable during mission
lifetime
Cons:
• Fixed design: Single-band/
single-mode
• Complexity in hardware
• More analogue components
• Cross talk between the
narrow bands due to aging
Cons:
• Complexity in software
• Vulnerable to software
threats
• Faster FPGAs and DSPs and
larger bandwidth ADCs are
required
• Power Consumption
Fig.1. Evolution of terrestrial and space software defined radios
173
C. Generic Problems for Space
SDRs for Distributed Satellite Systems (DSS) will provide
flexibility that will allow deployed satellite communication
transceivers to be software upgraded according to advances in
algorithms and communication standards. However, SDRs for
space applications pose many challenges as mentioned below,
some of them causing SDR to evolve slower than anticipated:
1) Mission constellation scenario: As discussed in [21],
spacecraft crosslink communications are affected by orbital
dynamics, which impose a number of difficulties and
restrictions such as variable inter-satellite ranges and speeds,
variable ISL access for distributed operations. The specific
data rates depend directly on the choice of constellation
design, i.e., the range of the inter-satellite links (ISLs), but a
general description of the performance range expected from
such an S-band system is provided in Fig. 3. ISL range of most
of the targeted missions such as QB50 [22], STRaND-2 [23]
and ARReST [24] is <100 km and thus the data rate that this
research aims at will be <10Mbps.
Fig.3. Near Earth S-band communication rates at various transmit powers[25]
2) Frequency uncertainties with Doppler tracking
capabilities: Two Line Elements (TLEs) after the launch are
often different from the ones estimated before the launch and
NORAD typically takes few days to identify any new object in
space and even weeks when the objects are small (CubeSats)
and/or many (30+ satellites in single launch [3, 4]). The true
anomaly () may also differ during the launch/deployment and
as it is critical to establish the communication soon after the
launch, the receiver on-board is usually designed to be turned-
on only above a desired ground station which is common in
CubeSat mission power budgets. Due to aging, temperature
and Doppler effects the frequencies might shift/change few
kHz to MHz depending on the operating band from the
allotted centre frequency.
3) Signal fading: The relative velocity between satellites in
different orbits varies with time. The communication channel
of in-space transmission is mainly characterised by free-space
loss and thermal noise of the electronics, presumed to be
Additive White Gaussian Noise (AWGN) [26] and signal
fading due to mobility, antenna pointing, phase propagation
delay, attenuation caused by electron-neutron collisions and
refraction due to varying plasma density causing multi-path
effects. Also, the signals pass through the ionosphere with
effects such as scintillation, fading and Faraday rotation [27].
Between 300 MHz and 3 GHz, in which UHF, L and S band
lie, severe disruptions are possible during a solar storm [28]
which could affect ISL communications.
4) Reconfigurability time: Satellites in LEO with orbital
period of ~ 98 minutes revolve ~ 14.7 times/day. So, on an
average they visit a particular location on Earth 5-6 times/day
for about 5-15 minutes each, depending on the elevation. It is
therefore crucial to utilise this time efficiently to carry out
different tasks such as downloading beacon/telemetry and
payload data, tele-commanding the satellite and reconfiguring
the software modules when required.
5) Interference with adjacent channels: Fig. 4 shows the
reception of NOAA-18 signals along with the interference by
unknown sources and DC offset. This often makes decoding
difficult as the signal levels interfere with the desired signal.
Fig. 4. Reception of NOAA18 Signals & Interference
The architecture proposed needs to adapt transmission and
receiver parameters to avoid interference and maximize
spectral efficiency. To avoid causing interference, numerous
techniques can be used and combined such as frequency tuning
[29] (adaptive frequency hopping, dynamic frequency
selection and RF band switching), Orthogonal Frequency
Division Multiplexing (OFDM) sub-channelization [30],
channel aggregation [31], time multiplexing [32], power
control [33], modulation and coding for Quality of Signal
(QoS) adaptability [34], beam forming and space-time coding
for Multiple Input Multiple Output (MIMO) [35]. To maintain
link in adverse conditions, wide dynamic range especially for
ADC and high sensitive receiver with rapid adaptation to
changes in interference temperature are required. SDR will be
also based on strong cross layer interactions. For example, the
SDR management involves intelligent use of spectrum based
on anticipating the demand for spectrum by different satellites
and the number of satellites in view at a given point of time.
Desired Signal
DC offset
Interference
174
III.
P
ROPOSED
S
OLUTION
As discussed in the previous section space presents a
unique engineering environment with a new set of problems to
overcome. SDRs have evolved from a conceptual solution for
enabling multiple radio applications to a practical solution as a
product which are commercially available. This section
introduces new concepts with new test-bed options for
improving the flexibility of the SDR in space.
A. Detailed Transceiver
Detailed Zero-IF architecture for a triple-band Very High
Frequency (VHF), Ultra High Frequency (UHF) and S-band
transceiver for multi-mode applications such as Ground-to-
Earth and Inter-Satellite Links (ISLs) is proposed in Fig. 5.
VHF/UHF bands are selected for uplink/downlink for
following reasons:
• There are more ground facilities/ amateur
communities to communicate in these bands across
the world which would help to increase the
communication window.
• It is easier and cheaper to establish VHF/UHF ground
station when compared to other bands.
S-band is selected for Inter-Satellite link as high data rates
can be achieved which would help satellites to exchange data
faster. VHF/UHF and S-band require separate antennas and
thus separate RF Front end. SDR analogue domain comprises
of frequency selection (Band pass filters), frequency
conversion (Low pass and output filters) and the gain control
(Variable Gain Amplifier (VGA)) functionalities whereas the
digital domain includes rest of the functionalities such as
modulation/demodulation, encoding/decoding and
frequency/phase/amplitude offset correction. The focus is to
move the digital domain as close as possible to the antenna
towards achieving an ideal SDR scenario when compared to
traditional radios where even the frequency correction and
modulation are achieved in analogue domain as seen in Fig. 5.
The components in the architecture are grouped to distinguish
between the RF front-end and back-end. The SDR transceiver
blocks can be implemented independently with a combination
of front and backend technologies such as digital TV dongles
and single-board embedded computers or using commercially
available end-to-end options such as Matchstiq [36], Bitshark
[37], or BladeRF [38].
To have a better understanding of the
front-end and back- end blocks before implementing on the
hardware they can also be simulated using tools namely; Eldo
from Mentor Graphics [39] and GNU-radio [40] respectively.
GNU-radio was chosen as it has a large support base and is
open-source.
B. GNU-radio
GNU-radio is used as a simulation tool to understand the
working of the existing/generated filters, channel codes,
synchronisation elements, equalisers, demodulators, decoders
and other processing blocks using pre-recorded or generated
data. This is a GUI that runs on Linux machine. GNU-radio
applications are primarily written using the Python
programming language [41], while the supplied performance-
critical signal-processing path is implemented in C++.To
implement C/C++ code of GNU-radio flow graph on any
embedded system, it needs proper understanding of the
modules such as GNU-radio modules for analogue/digital
modulation/ demodulation, FFTs, designing FIR filters and
plotting data, choosing/defining and configuring blocks, and
connecting blocks. Complete understanding of the above vital
modules along with others as in [42] would help in profiling
GNURadio on the embedded system. Having experimented on
GNURadio, the implementation of appropriate blocks was
carried out on using Surrey Space Centre’s BA and BB
antennas and a FUN-Cube Dongle (FCD) [43].
Fig.5. Transceiver Conceptual Block Diagram
175
Fig.6 shows the flow graph of GNURadio where the
recorded signal from NASA Phonesat [44] is selected,
demodulated and filtered around DC. Muller and Muller based
clock recovery block provides the discrete time error tracking
synchroniser with complex input and complex output. Then the
signal is converted to digital data which is then decoded as
seen in Fig.8. The frequency spectrum of the signal can be
viewed using the Graphical User Interface (GUI) blocks as
seen in Fig. 7 which aids to better understand and debug the
signals.
Fig. 7. NASA PhoneSat Received Frequency Spectrum
Fig. 8. Decoded data from NASA Phonesat
IV.
P
RACTICAL
W
ORK
This section includes a practical investigation of different
platforms and results at the time of writing this paper. The
platforms include SmartFusion2 [45] with FunCube Dongle
(FCD) [43] and Zedboard [46] with Zipper and MyriadRF [47]
boards.
A. Testbed 1
The SF2 [45] was chosen as the initial test-bed. The
architecture includes an ARM Cortex M3 and additional
FPGA fabric on a single device. Initial tests were carried out
on the SF2 such as configuring the Linux kernel, interfacing
the FCD and running utilities such as FCD Control [50] used
to set the frequency and gain as seen in Fig. 9.
Fig. 9. FCD Control on Linux Machine
The practical work demonstrated here has initially looked
into porting and characterising the performance of existing
SDR software chains in an embedded system towards proving
the SDR concept. A hardware test-bed has been formulated
using the SF2 starter kit as a platform to investigate the
existing tools and demonstrating Linux software environment.
FCD is proposed in literature and now practically used to show
that the commercially available front end technologies work
not only with Desktop-PCs but also with the embedded system
such as SF2. However, this implementation of the concept is
missing key SDR features:
Fig. 6 – GNU-radio Flow Graph
176
• A direct interface to the received IQ signal – instead,
the FCD utilises the online ARM Cortex and Linux
software to receive an input stream which could be
piped into applications. This is far from ideal as the
IQ signal must traverse all layers of the Open System
Interconnection (OSI) stack.
• The USB interface is also a potential bottleneck as the
speed is limited to 480 Mbps.
• Transmit functionality – this key function is
completely missing from this test-bed
.
B. Testbed 2
To overcome the above limitations, the new test-bed
includes Zedboard [46] along with Lime Microsystems’ Zipper
and MyriadRF boards [47] as seen in Fig. 10. It has an
advantage of high throughput, direct interface which supports
higher data rates, transmit functionality using the MyriadRF.
Fig. 10. Test-bed 2: Interface of Zedboard and Zipper board
Fig. 11 and 12 shows the transmission of a carrier wave
from the Zynq System-on-Chip (SoC) development board and
the MyriadRF board. As a demonstration, the signal is
reconfigured and centred at 2 GHz and 437 MHz respectively.
Fig. 11. Transmission of Carrier Wave at 2 GHz
Fig. 12. Transmission of Carrier Wave at 437 MHz
Fig. 13 shows the reception of carrier wave on MyriadRF.
The signal was transmitted from a signal generator at 2 GHz
for demonstration. Investigating the data requirements show
the ADC/DAC requirements for the Zynq device is 23 MB/s.
Therefore the internal SRAM of 32 KB would be able to hold
the recorded IQ signals for about approximately 1.4 ms. This
will be implemented as a circular buffer and polled by the
faster ARM Cortex-A9 core running up to 800 MHz for
demodulation and packet handling.
Fig. 14. SDR Architecture
177
Fig. 13. Reception of Carrier Wave on MyriadRF
The Test-bed 2 configuration is planned as seen in Fig. 14
to implement a division of software functions in both the dual-
core ARM processors and associated FPGA fabric. The
distribution of the functions between the FPGA fabric and
dual-processor is based on performance tests of GNURadio
filter blocks on Zedboard. This will be repeated for other
blocks in future to estimate where bottlenecks exist. The
system diagram generated by Xilinx Processing System (XPS)
is shown in Fig. 15. The processing_system (2 x Cortex – A9)
controls the signal and data flow of the blocks over Advanced
eXtensible Interface 4 (AXI4). This is the initial step towards
implementing the software blocks discussed in Fig.14.
Fig. 15. Xilinx XPS System Diagram
V.
S
UMMARY
The review on efficient use of limited bandwidth and
increasing small satellite missions concludes that there is need
for a generic yet configurable communication platform that
can handle multiple signals from multiple satellites, various
modulation techniques, data rates and frequency bands that can
fit in to the requirements of small satellite. SDR is beneficial
for space applications as it provides the flexibility and re-
configurability and this is driven by the fast development
times, new found heritage, cheap, and low mass COTS
interfaces. The implementation of a new combined system-on-
chip (SoC) and SDR communication platform enables a
reduction in cost as well as mass. Also, different parallelisation
techniques for ADC/DAC/FPGA will enable a reduction in
power consumption by improving the computational capacity,
which is an important factor in the design of small satellites.
Current work has looked into various possible approaches
to implement signal processing. To begin with, FCD was
interfaced on the available embedded board with Test-bed 1,
this had many challenges such as setting up servers getting the
details of the detected FCD and building the libraries for the
board. Test-bed 2 overcomes the above problems and this
could be adapted to implement the future SDR technologies.
The novelty here is to combine the state-of-art SDR hardware
and open source software tool towards a new communication
platform on embedded systems aimed at small satellite
missions. Also, this research aims to enable advanced
parallelised SDR back-end technologies in a COTS embedded
system that can support multi-signal processing for multi-
satellite scenarios towards a generic software methodology for
space applications that will remain unaltered despite new
evolutions in hardware.
A
CKNOWLEDGMENT
The authors would like to thank Dr. Brian Yeomans,
Research Fellow, Surrey Space Centre for his valuable time,
discussions and contributions towards the paper and Lime
Microsystems who have gratefully provided Zedboards, Zipper
and MyriadRF boards.
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