OFDM Simulation Using GNURadio

on Dynamic Channels

Nyaris Pambudiyatno1(B) , B. B. Harianto1 , and A. Mauludiyanto2

1 Aviation Polytechnic of Surabaya, Surabaya, Indonesia
n.pambudi@gmail.com
2 Institute Teknoplogi Sepuluh Nopember, Surabaya, Indonesia

Abstract. OFDM system can be implemented on GNU Radio, one type of SDR
(software-defined radio). SDR is a transmitter and receiver system that uses digital
signal processing to code, decode, and modulate data. GNU Radio is used as
a transmitter and receiver model for quality measurements for the working of
the OFDM system under various conditions. This measurement will compare
real-time data transmission performance results through AWGN channels and
dynamic channel models, namely Rayleigh Distributed (NLOS) and Rician (LOS).
The specification of the OFDM system used in this study is to use GNU Radio
software with BPSK modulation (Binary Phase Shift Keying). The simulation
model’s output in the GRC during real-time data transmission via AWGN and
Rayleigh distributed (NLOS) and Rician Distributed (LOS) model channels with
GNU Radio is the performance of OFDM signals with the noise of 25mV, 50mV,
100 mV, and 200mV. The results of the research simulation obtained SNR values
on AWGN, NLOS, and LOS channels directly proportional to noise. The SNR
value is down significantly to four times the initial value.

Keywords: GNURadio · Digital Communications · OFDM · Dynamic Channels

1 Introduction

With the development of communication technology, the demand for more exten-
sive/faster data rates services such as multimedia, voice, and data via cable and wireless
is also increasing [1, 2]. To achieve a more significant data rate, of course, requires band-
width in a single carrier transmission because the minimum bandwidth needed is equal
to Rs/2 (Hz), where Rs is the symbol rate. When the signal bandwidth becomes more
significant than the coherent bandwidth on a wireless channel, it is subject to multipath
fading resulting in Inter-Symbol Interference (ISI) [3]. In general, adaptive equalizers
are developed to address ISI due to multipath fading channels [4]. But the more data
rates increase, the more difficult the compensation is designed to be complicated to
implement.
To solve this problem, the right solution for high data rates is to use multicarrier
transmission. Because on multicarrier transmissions, the total bandwidth available in
the spectrum is divided into subbands for multicarrier transmissions in parallel form.

© The Author(s) 2023

B. Bagus Harianto et al. (Eds.): ICATEAS 2022, AER 217, pp. 100–110, 2023.
https://doi.org/10.2991/978-94-6463-092-3_9
 OFDM Simulation Using GNURadio on Dynamic Channels 101

(a) Single Carrier Frequency

(b) FDM Frequency

Savings
Bandwidth

(c) OFDM Frequency

Fig. 1. Comparison of Single Carrier, FDM, and OFDM

The bandwidth for each sub-band is relatively smaller compared to coherent bandwidth.
For example, multicarrier transmission is OFDM, wherein this OFDM allows the carriers
to have a narrow distance even to overlapping each other so that it is more bandwidth-
efficient when compared to other multicarrier such as Frequency Division Multiplexing
(FDM) [3, 5]. OFDM itself has been applied to various telecommunication system stan-
dards in both wireless and wireline technology as an example of IEEE802.1z1g for
wireless LANs (Wifi) standards. Here is a comparison image of signals on a single
carrier, FDM, and OFDM (Fig. 1).
In this paper, the process of implementing and evaluating the performance of OFDM
on dynamic channels uses SISO (Single Input Single-Output) communication [2] so that
it only uses simulations from software. Such communication can be implemented on an
SDR (Software Defined Radio), namely GNU Radio. GNU Radio is a type of wire-
less open-source communication system software that will be implemented for OFDM
techniques with various measurement conditions.

2 Theoretical Foundation
2.1 AWGN Channel
Additive White Gaussian Noise (AWGN) is an additive channel due to the increase in
noise to send signals and cannot be doubled. The noise in this channel will be randomly
significant under normal circumstances. Therefore, it cannot determine the amount of
noise. Otherwise, rejecting the exact amount of noise will get the receiver without any
sound, meaning white, because each frequency’s power is equal [6]. Therefore, at each
frequency, the noise level and frequency domain are fixed. On channel A, Gaussian noise
is allowed in the current cause. Noise is defined through the front. It has a spectral inten-
sity of energy. The channel AWGN is the perfect pattern for satellite communication. It
is not ideal for links obtained due to overlapping, plentiful, relief cover, etc. Considering
bandlimited Gaussian channels that operate in additional Gaussian noise, the Shannon-
Hartley Theorem can be used, which states that channel capacity was formulated with
[7, 8].
 
S
C = Blog 2 + 1 + (1)
N
102 N. Pambudiyatno et al.

where C is the capacity in bits per second, B is the channel’s bandwidth in Hertz, and S
= N is the Signal to Noise Ratio.

2.2 Rayleigh Fading Channel Model (NLOS)

In regular vehicle traffic, buildings, and other objects, signals come at receivers and
senders in different lanes. When there are different signal paths between receivers and
transmitters, Rayleigh limits the motion entirely to the receiver and can change the
probability of the intensity of the Rayleigh Fading channel function [9] and can be
expressed in the equation [10, 11].
 
r r2
p(r) = 2 exp − 2 forr ≥ 0 (2)
σ 2σ

where σ 2 = the difference from random variable r = amplitude of the signal receiver


N
h(t) = an ej(2π fn t+ϕn ) (3)
n=1

where N is the number of multipath and an is the amplitude of the nth .fn path, ϕn is
representing the shift in Doppler frequency and phase of each path. nth The Doppler
frequency of the shift expres fn = (v/c)fc cosθn as, where is the v speed of motion of the
user. c It is the speed of light, fc is the carrier of frequency and is the angle between the
θn User’s movement direction and the angle of the radio wave coming.

2.3 Rician (LOS)

The receiver signal is a mixture of multipath fading and the visible trajectory between
the receiver and sender. The LOS line (line of sight) is a signal path that exits directly
from the sender to the receiver. The action of rayleigh fading on the sending signal will
be more than Rician Fading. The probability intensity of a fading rician channel function
can be expressed in the equation [10, 12].
 
(
− r 2 +s2 )  rs 
r 2σ 2
p(r) = 2 exp I0 forr ≥ 0, s ≥ 0 (4)
σ σ2
LOS (line of sight) is an assumed condition for propagation of a trajectory with a
positive free distance or no obstruction whatsoever. The distribution of LOS. It mainly
depends on the location of the base station antenna and the line of sight area open around
the site [13]. LOS identified three similar cases:

• With a circular area available around the base station,

• Half the LOS open space when the base station antenna is mounted on the roof at the
edge of the building block.
• The LA/NLOS status distribution is homogeneous throughout the base station
coverage area without a LOS area close to the base station.
 OFDM Simulation Using GNURadio on Dynamic Channels 103

In the case of the Rician distribution, the transmitted signal experiences non-fading
dominance due to the presence of a Line of Sight (LOS) line between the transceiver,
so it is assumed there is no obstruction. In this context, many weaker random multipath
signals arriving at different angles are generated by reflection, diffraction, or scattering
effects superimposed on the dominant signal. This ratio between deterministic signal
strength and variance of the multipath is known as Rician.
The study measured the value of Signal Noise to Ratio (SNR) using GNU Radio on
Modulation of Orthogonal Frequency Division Multiplexing (OFDM). The signal-to-
noise ratio was defined as the ratio between the desired power and noise power signal and
is comprehensive to be used as a standard measure of signal quality for communication
systems. An information signal as a communication medium will experience a lot of
interference by noise to damage the information signal. Signals that share this disruption
experience a decrease in quality. The quality of this signal can be determined from the
Signal value to the Noise Ratio (SNR) measured in decibels (dB) [14]. Signal to noise
ratio calculations can be done through a reduction between noise value and frequency
strength [15].

3 Design
The block diagram as a whole is shown in Fig. 2. The explanation is as follows: Ran-
dom bits are generated, then modulated BPSK (Binary Phase Shift Keying). In BPSK
modulation, two possible phase outputs will come out and carry information (Binary,
i.e., 2). One output (0°) represents a logic one and the other (i.e., 180°) logic 0. By the
changing state of the digital input signal, the phase at the carrier’s output shifts between
two angles that are both 180° (out of phase) apart. Figure 2 shows the configuration of
the design and measurement of the channel. On a single SDR or GNU Radio worksheet,
transceiver blocks are assembled as digital signal processing. These transceiver blocks
are created to be able to transmit signals multicarrier. The signal is not emitted with a
GNU Radio simulation, so it does not require an antenna and RTL. The signal will be
sent and directly received by the receiver block, and the PC processes the information
signal as the sending and receiving system. The data received will be taken from FFT
output, phase, and magnitude for SNR measurements.
Then the serial signal is converted to a parallel signal form. Then each similar signal
goes into the IFFT block. Multicarrier is signal coming out from the IFFT block. The

Serial to Parallel
Random BPSK Add
Parallel IFFT To serial
Source Mod Cp
(S/P) (P/S)

Transmitter
Software Channel

Pararel to Serial
Output BPSK Remove To parallel
Serial FFT
Data Demod CP (S/P)
(P/S)

Receiver
Software

Fig. 2. Design Diagram Block

104 N. Pambudiyatno et al.

multicarrier signal is added CP to reduce ISI. Before it is sent, the parallel OFDM
signal is converted to a serial OFDM signal form. After passing through the channel,
the OFDM signal is converted back to a parallel signal form. The CP will be discarded
on the receiving side, and then the multicarrier signal goes into the FFT block. In FFT
blocks, the multicarrier signal is converted into a parallel subcarrier signal [16, 17].
The information subcarrier signal will go into the P/S block, then modulates to get the
information bits back.
The IFFT (Inverse Fast Fourier Transform) and FFT (Fast Fourier Transform) algo-
rithms serve as modulators and demodulators on OFDM. The image can be explained
binary data mapped in the BPSK mapper will produce a mapper result symbol. The sym-
bol is broken down in serial to parallel form and modulated by a subcarrier signal with a
specific frequency, resulting in interlocking orthogonal signals. Then all the signals are
added so that the OFDM signal is generated.


k−1   
k−1
2π tk 2π t k
s(t) = s(k)sin +j s(k)cos (5)
k k
k=0 k=0

With:
K = Number of IFFT points (total subcarrier).
s(t) = signal value in the time domain.
s(k) = the value of the kth spectrum (frequency domain).
The demodulator OFDM used the Fast Fourier Transform (FFT) algorithm to parse
the SYMBOL OFDM. The symbol is changed from a time domain to a frequency domain
in the FFT algorithm, as shown in the equation.


k−1   
k−1
2π tk 2π t k
s(k) = s(t)sin −j s(t)cos (6)
k k
k=0 k=0

With:
K = Number of FFT points (total subcarriers).
s(t) = Signal value in the time domain.
s(k) = The value of the kth spectrum (frequency domain).
As explained earlier that the orthogonality of the OFDM symbol can be maintained
by applying FFT on the receiver side. This can be achieved if there is no Intersymbol
Interference (ISI) [18] and Intercarrier Interference (ICI) caused by transmission chan-
nels. However, this is very difficult to achieve because wireless transmission channels
can generally cause a plural trajectory on the transmitted signal. This results in the receipt
of the original signal that is delayed on the receiver. This symbol may interfere with the
next symbol or interstitial from the previous symbol.
A way to overcome ISI by multipath channels is to insert guard intervals on each
OFDM symbol. Guard intervals can be CP (cyclic prefix). In the OFDM system, CP plays
an essential role in maintaining the orthogonality of the OFDM subcarrier in frequency-
selective channel situations. CP is a series of bits formed by re-copying some of the bits
of an OFDM signal. With this additional CP, the OFDM signal will not experience ISI
as long as the channel spread delay is shorter than the duration of CP.
 OFDM Simulation Using GNURadio on Dynamic Channels 105

4 GNU Radio Simulation

This simulation uses GNU Radio type 3.7.11.1. This type has many blocks, such as
input/source, sinks, and graphical sinks to misc. Random Source, OFDM Mod, WX
GUI FFT sink, and other are blocks that are used in the simulation. Here are the blocks
and their more complete functions in Table 1 (Figs. 3, 4, and 5).
After understanding the function per block, string together and configure each block
with AWGN, NLOS, and LOS channels. Here is the documentation of the design block
image on each channel (Table 2).
These simulations as a whole using BPSK modulation with the following parameters.
The image below is the result of simulations on each channel on both transmitters
and receivers. The parameter used in this study is sample rate 500K after the parameters
have been configured, then run the program on GNU Radio.

Table 1. Block parameters Simulation of AWGN, NLOS, and LOS channel

No Block Value
1 Random Source Randomly generated sample numbers
2 Short to Float The flow short type converter becomes afloat.
3 OFDM Mod Select modulation (BPSK, QPSK, 8PSK to QAM256)
4 Random source max Set sample rates when there is no SDR (hardware)
5 Random source min 1. Media between transmit and receive blocks
2. Set noise voltage, frequency offset, and others
6 WX GUI FFT Sink Monitor signals such as oscilloscope
7 OFDM Demod Modulating carrier signals
8 Float to Short Flow float type converter becomes short
9 File Sink Save information signals with specific directories

Fig. 3. OFDM Transceiver Block on AWGN channel

106 N. Pambudiyatno et al.

Fig. 4. OFDM Transceiver Block on NLOS channel

Fig. 5. OFDM Transceiver block on LOS channel

Table 2. Block parameters Simulation of AWGN, NLOS, and LOS channel

No Block Parameters Value

1 FET Length 512
2 Sample rate 500 k
3 Modulation BPSK
4 Random source max 2
5 Random source min 0
 OFDM Simulation Using GNURadio on Dynamic Channels 107

Fig. 6. Power and Noise Measurements on AWGN channels

Fig. 7. Power and Noise Measurements on NLOS channels

The first simulation is that Fig. 6 is the result of power and noise measurements for
SNR measurements on AWGN channels, Fig. 7 measures on NLOS channels, and Fig. 8
is the result of measures on THE LOS channel. The authors took one sample from each
channel from the three images above on a 100 mV noise test.

5 Analysis and Measurement Results

The results of these measurements aim to analyze the performance of OFDM in various
conditions. The parameters used can be seen in subheading 4. This test is carried out in
several ethics, namely by changing the noise size on AWGN, NLOS, and LOS channels.
In SNR measurements, the parameters measured are by changing the noise voltage,
108 N. Pambudiyatno et al.

Fig. 8. Power and Noise Measurements on LOS channels

which is 25mV, 50 mV, 100 mV, 200 mV, and 500 mV. Here is an image of the signal
output from the tests in this study.
In Table 3 shows the results obtained from the signal picture in FFT 512. It can
conclude that the value of SNR produced is large when the noise is small. It means the
greater the noise, the lower the SNR value, and the signal sent is harder to detect. In the
category index of SNR i.e., 29.0 dB ~ and above: very good, 20.0 dB–28.9 dB: good,
11.0 dB–19.9 dB: enough. The SNR value obtained from research on the transmitter
side is constant at 30 dB, which means very good. While on the AWGN channel receiver
obtained SNR values of 20 dB at noise 25mV and 50 mV, which means good, SNR
10 dB at noise 100 mV and 200 mV, which means less good.
Furthermore, on the NLOS channel, the value of SNR 30 dB with 25 mV noise
is categorized as very good, 20 dB with 50 mV noise is categorizing as good, 15 dB
with 100 mV noise is categorized as sufficient, and 10 dB with 200 mV noise in the
category is not good. Lastly, for the LOS channel on the receiver, obtained SNR value
of 20 dB with the noise of 25 mV and 50 mV categorized as good, 15 dB with the noise
of 100 mV falls into the category of enough and 10 dB with noise 200 mV category is
not good. From the results of SNR measurements in this study, the highest SNR is in
NLOS, which is 30 dB with 25 mV noise which falls into the category of very good, so
it does not have a big effect on the signal. Furthermore, the lowest SNR is 10 dB, with
the most extensive noise of 200 mV on the receiver side on all channels. This 10 dB
SNR dramatically affects the information signal, as high noise power almost reaches the
information signal power itself.
In Table 3 shows the results of SNR values on AWGN, NLOS, and LOS channels.
It shows differences in OFDM modulation phases it’s caused. In the image displayed,
the performance results that deliver on in a while.
 OFDM Simulation Using GNURadio on Dynamic Channels 109

Table 3. SNR Value Measurement Results

No Noise Transmitter Receiver

AWGN NLOS LOS AWGN NLOS LOS
1 25 mV 30 dB 30 dB 30 dB 20 dB 30 dB 20 dB
2 50 mV 30 dB 30 dB 30 dB 20dB 20dB 20 dB
3 100 mV 30 dB 30 dB 30 dB 10 dB 15 dB 15 dB
4 200 mV 30 dB 30 dB 30 dB 10 dB 10 dB 10 dB

6 Conclusion
The results of simulations that we have done on AWGN, NLOS, and LOS channels
concluded that the value of SNR is directly proportional to noise. The higher the noise,
the lower the SNR. The decrease in SNR occurred significantly when the final noise
raised four times the initial noise.

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