[email protected]

Software Defined Radio Applications for Mini
GSM BTS and Spectrum Analyzer with BladeRF
Ihan Martoyo
Department of Electrical Engineering
Universitas Pelita Harapan
Tangerang, Indonesia
ihan.martoy[email protected]u
Herman Y. Kanalebe
Department of Electrical Engineering
Universitas Pelita Harapan
Tangerang, Indonesia
herman.kanale[email protected]du
Andi Coandi
Department of Electrical Engineering
Universitas Pelita Harapan
Tangerang, Indonesia
Henri P. Uranus
Department of Electrical Engineering
Universitas Pelita Harapan
Tangerang, Indonesia
[e-mail]
Dave Pratignyo
Department of Electrical Engineering
Universitas Pelita Harapan
Tangerang, Indonesia
Marincan Pardede
Department of Electrical Engineering
Universitas Pelita Harapan
Tangerang, Indonesia
[e-mail]
Abstract—Software Defined Radio (SDR) technology
enables the flexibility of a programmable hardware platform
for radio applications. A wideband SDR can be programmed
to function with various radio systems: FM radio, GSM (2G),
3G or WiFi systems. In this paper, the BladeRF SDR with the
frequency range of 300 MHz – 3.8 GHz and full-duplex
transmission capability will be set up as a GSM BTS (base
transceiver station). The BladeRF is working with the YateBTS
software for the BTS operation. Raspberry Pi is utilized as the
processor to provide further portability. A GSM repeater that
is connected to the BladeRF was used to amplify the signal up
to 41 dB, and can increase the coverage range to about 70 m.
Although the reliability of voice and SMS communication is
only about 50% and 85% respectively, the BladeRF can still
provide an ad-hoc alternative communication system in time of
emergency or in remote areas.
Keywords—
SDR, BladeRF, Radio Characterization, GSM
BTS
I. I NTRODUCTION
The term software radio was coined by Joseph Mitola, at
first for military radio communication systems [1]-[2]. Since
software radio is based on software, the flexibility for a
multimode, multisystem, multiband radio communication
should come as easy as downloading and installing the
appropriate software – if needed – by over-the-air
download [3]. Even if a military troop is deployed in an
unknown area with unknown availability of communication
systems, the Software Radio should be able to be
reprogrammed for the need of that situation.
That was the initial dream. Soon, however, many realized
the technological limit of the concept. An analog-to-digital
converter (ADC) must be put right after the antenna so that
all incoming signals can be converted to digital, fitting for
further digital processing with software. However, such an
ADC that can convert a signal with a very high bandwidth to
cover various radio systems is prohibitively very expensive.
Then Software Defined Radio (SDR) came as a
compromised version for the pure Software Radio. An SDR
is hardware, thus not very flexible; but the FPGA-based
hardware can be controlled or reprogrammed by software,
therefore providing a certain amount of flexibility [4]. If the
SDR were to cover the frequency band from 800 MHz to 5.5
GHz, an ADC of 12 bit and 11GS/s would be needed [5].
That would be impossible today and for the foreseeable
future. The key for the front-end is not to receive the whole
available bandwidth, but to tune electronically to a certain
bandwidth of interest for a particular system [5].
Several kinds of SDR are already available: USRP,
HackRF One and BladeRF. Table I displays the basic
parameters of these SDR systems. USRP, the most expensive
of the three, can have a bandwidth up to 61.44 MHz
(depending on the specific model), has the highest sample
rate of up to 128 Msps, and is operating in full-duplex. The
HackRF One, which provides a cheaper alternative, is
operating only in half-duplex, and has a bandwidth of 20
MHz (frequency up to 6 GHz). For the work in this paper,
the BladeRF is chosen because it can already function in full-
duplex, thus can be operated as a GSM BTS, but not as
expensive as the USRP.
This paper reports the setting up and characterization of a
GSM BTS using the BladeRF SDR. The next section will
describe the system, followed by measurement results and
discussions in Section III. Section IV closes with some
conclusions.
II. SDR
WITH B LADE RF S YSTEM
A. BladeRF Transmit/Receive with MATLAB
BladeRF can be connected to MATLAB installed in a
Laptop for transmit/receive testing as shown in Fig. 1.
MATLAB works with the BladeRF software for windows
from Nuand [6]. It is important to note the version of the
suitable firmware for the BladeRF. For this work, the
updated firmware version 2.0.0 is used [7]. Some basic
commands available in the m-script bladeRF.m include:
b.rx.frequency and b.tx.frequency to set the frequency
parameter, b.rx.start and b.tx.start to start receiving and
transmitting, and b.rx.stop and b.tx.stop to stop receiving and
transmitting [8].
TABLE I. SDR T YPES AND P ARAMETERS
SDR HackRF One BladeRF USRP
Frequency
30 MHz –
6 GHz
300 MHz –
3.8 GHz
50 MHz –
2.2 GHz / 6 GHz
Bandwidth 20 MHz 28 MHz 16 MHz /
61.44 MHz
Duplex Half Full
Full / 2x2
MIMO
Sample Rate 20 Msps 40 Msps 64 Msps /
128 Msps
2018 International Conference on radar, Antenna, Microwave, Electronics, and Telecommunications
978-1-5386-6519-0/18/$31.00 ©2018 IEEE
108

Fig. 1. BladeRF connected to MATLAB for Tx/Rx testing.
B. BladeRF with Raspberry Pi, GSM Repeater and
YateBTS
To function as a mini GSM BTS, the BladeRF can be
connected to Raspberry Pi 3 as a single board processor,
which runs on Linux Jessie Debian as the operating
system [9]. YateBTS can then be installed on the Raspberry
Pi. The NiPC (Network in a PC) performs the function of a
regular GSM BTS for YateBTS [10]. Fig. 2 and Fig. 3 show
the BladeRF connected to Raspberry Pi and a GSM repeater.
Apache, PHP, and the necessary libraries for USB interface
and GSM libraries should also be installed in the Raspberry
Pi, so that the GSM BTS system can be accessed and
controlled via a web-interface.
Fig. 2. BladeRF (top) connected to Raspberry Pi (middle) and GSM
repeater (bottom).
Fig. 3. GSM mini BTS block diagram with BladeRF.
III. M
EASUREMENT R ESULTS AND SDR A PPLICATIONS
A. BladeRF Transmit/Receive with MATLAB
BladeRF can function as a spectrum analyzer or a signal
generator with Matlab. Fig. 4 and Fig. 5 show a
measurement comparison between BladeRF and a spectrum
analyzer at 375 MHz. We see in the measurement with
BladeRF some visible spurious frequencies, for example,
around 384 MHz (Fig. 4) that cannot be seen with the
spectrum analyzer (Fig. 5).
These spurious frequencies could be an artifact of the
down-mixing strategy of the SDR, e.g., artifact in the
digitizing of the IF signals due to its periodic nature [11].
The SDR also always displays the center frequency of the
measurement (DC Spike). Thus, using the BladeRF as an
affordable spectrum analyzer, we should be aware of the
possible appearance of the spurious frequencies. It is perhaps
good to shift the center frequency and adjust the span while
measuring frequencies with the BladeRF to shake-off any
spurious frequencies that might be visible at certain settings.
Fig. 6 shows another view on the frequencies that include the
signal at 375 MHz. Here, even more spurious frequencies are
visible.
Fig. 7 and Fig. 8 compare two measurements of a signal
at 400 MHz with the BladeRF. In Fig. 7, the reading from
the BladeRF does not show any significant spurious
frequencies; however, Fig. 8 shows the spurious frequency at
384 MHz again (compare with the clean spectrum of Fig. 5
and Fig. 9 with a spectrum analyzer).
Fig. 4. BladeRF measurement of a signal at 375 MHz.
Fig. 5. Spectrum analyzer measurement of a signal at 375 MHz.
109

Fig. 6. Another angle of BladeRF on the signal at 375 MHz.
Fig. 7. BladeRF measurement on a signal at 400 MHz.
Fig. 8. Another angle of BladeRF on the signal at 400 MHz.
B. BladeRF with Raspberry Pi, GSM Repeater and YateBTS
BladeRF is also setup as a GSM BTS on Raspberry Pi 3
as a single board processor running Linux Jessie Debian for
the OS and YateBTS for GSM BTS functionalities. The
addition of a GSM repeater can increase the signal of
bladeRF up to 41 dB (uplink 890-915 MHz; downlink 935-
960 MHz) and increase the coverage of the BTS from about
several meters to about 70m.
The voice communication with GSM phones through the
BladeRF BTS was tested with groups of 10 attempts of call
each time. The success of attempts was about 50%. Some
Fig. 9. Spectrum Analyzer measurement on the signal at 400 MHz.
calls were heavily delayed, some calls got connected after
the caller hung up, some calls got connected without any
sound going through, and some calls did not get listed in the
online subscriber list in YateBTS. However, 50% of the calls
went through successfully. It was however difficult to make
a second call while one voice connection was still running
through the BTS. The limitation can come from the rather
small computing capability of the Raspberry Pi, or some
constrains with the YateBTS system.
The SMS (Short Message Service) was tested by sending
groups of 100 messages, each saying “Spinx of black quartz,
judge my vow,” which was chosen because it consists all the
alphabets. If the 100 messages were sent at once, the number
of perfectly arriving messages was around 20% and could be
as low as 7%. If the messages were sent in 2 groups of 50
messages, the success rate could increase to around 40%.
Sending the messages in groups of 20 messages or lower,
increased the success rate to more than 85%.
C. Alternative Applications with BladeRF GSM BTS
The transmit signal of the BladeRF was also tested and
measured. Fig. 10 compares the measurement with cable
connector (top) and through antenna (bottom). The signals
through cable connector were about 20 dB higher than
through the antenna. The frequency response seems to show
that the BladeRF is optimized for the GSM systems in 800-
900 MHz and around 1800 MHz. Thus, the BladeRF system
can be used as a cheap RF signal generator (although an RF
wideband amplifier is needed to operate as a proper and
adjustable signal generator) and spectrum analyzer for
education and research.
Fig. 10. Frequency response of BladeRF transmit signal
110

Although the BladeRF does not seem to support a very
high reliability in voice and SMS communications, the
system could be applied for alternative communication
systems in remote areas or emergency settings. The
availability of cheap GSM handphones and the affordability
of BladeRF are important promising factors.
It is also possible to envision other alternative
applications of the GSM BTS system that do not require high
reliability. An example for such application would be to use
the GSM BTS for free advertisement purposes. Fig. 11
shows some modified SMS welcome messages that can be
used for free SMS advertisement. GSM handphones will be
attracted automatically to a strong nearby BTS signals, so
passing-by handsets might get connected automatically to the
standalone BladeRF BTS. However, care should be taken to
release the handsets again, so that they can regain
communication with the GSM network.
The strength of SDR is its reconfigurability and
multimode operation. Thus, the BladeRF can be reconfigured
rapidly to function and communicate with several
communication systems: Handy Talky systems, GSM, even
detecting car key transmissions. Such capability may open
other potential applications besides the traditional GSM
voice and SMS communications.
IV. C
ONCLUSIONS
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Fig. 11. Modified SMS messages for free advertisement purposes
BladeRF can be set up with Matlab to function as an
affordable spectrum analyzer. Spectrum measurements with
BladeRF might show some spurious frequencies as artifacts
of the internal frequency mixing or sampling. Shifting the
center frequency and span might give more clarity to the
spectrum being measured.
BladeRF has been set-up for a standalone Mini GSM
BTS successfully. To increase portability, a Raspberry Pi
was used as a single board processor to work with the
BladeRF. A GSM repeater was used to increase the signal of
BladeRF to about 41 dB and the coverage of the GSM BTS
to about 70 m. The success rate of voice communication is
around 50% and for SMS can be as high as 85%.
The spectrum measurement capability of BladeRF seems
to be limited by some artifacts of internal mixing and
sampling effects. Despite the shortcomings, the BladeRF can
be used as an affordable spectrum analyzer for education or
even research, considering that a conventional spectrum
analyzer could cost up to ten times the BladeRF. Frequency
response of the transmit signal of BladeRF seems to be
optimized for GSM systems at 800-900 MHz and around
1800 MHz.
Although the reliability of the GSM BTS with BladeRF
is rather low for voice & SMS communication, the system
might be enough for a standalone alternative communication
system in remote areas or emergency settings. Other
alternative application, such as free SMS advertisement
system, can also be explored and applied.
A
CKNOWLEDGMENT
This work is supported by the Indonesian Ministry of
Research and Higher Education no. 021/KM/PNT/2018,
March 6, 2018; Kontrak Penelitian Dasar Unggulan
Perguruan Tinggi no. 149/LPPM-UPH/IV/2018.
R
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