A Novel Hybrid OFDM Technique for 5G
Onur Dursun Tören, Emre Ayduslu, Yücel AydÕn and Ali Özen
Nuh Naci Yazgan University - HARGEM
Department of Electrical and Electronics Engineering, 38010 Kayseri, Turkey.
Email: toren_onur@hotmail.com, emreayduslu@gmail.com, yucelaydin50@hotmail.com, aozen@nny.edu.tr
interference (ISI) affected multipath channels. These channels
often experience strong frequency selective fading. OFDM has
been chosen for current communication systems like LTE [5],
Wireless LAN IEEE 802.11a [6] or DAB, DVB-T [7]. The
high data rate payload is multiplexed over a set of sub-carriers
that are orthogonal to one another. In OFDM, the symbol
period is significantly increased and with the use of suitable
cyclic extension, the received data sequence (in the frequency
domain) is not affected by the time dispersive nature (ISI) of
the channel. However, it is known that OFDM, which is used
in existing LTE systems for asynchronous network and
wireless systems expected to become widespread in the future,
is not appropriate. Taken place in standards related to many
different Wired and wireless systems and widely used with
broadband systems OFDM method cannot meet the needs of
the next generation systems in every situation; the search for
alternative waveform methods has gained speed. For this
reason, it is considered that the OFDM technique will not be
sufficient for 5G and later for the waveform, which is effective
in selecting several subcomponents of communication systems
[8]. In previous 5G studies, the drawbacks of the OFDM
method for new designs have been taken as a basis, but a
waveform, which can be regarded as the best in terms of
overall performance criteria with clear and superiority over the
OFDM method, has not been yet developed.
Each of the existing waveform techniques has various
positive and negative aspects, and therefore the search for the
new waveform method is ongoing. One of the design modifiers
may need to be traded-off during the healing of one of the other
modifiers. Efforts are being made to optimize the most
appropriate design in this during trade-off. The current
waveforms proposed for 5G are generally compared with the
OFDM technique [9].
The new waveforms designed for the upcoming 5G can
now be classified as Zero-Tail OFDM (ZT OFDM) [10], ZT
Discrete Fourier Transform (DFT) spread OFDM (ZT DFT-s
OFDM) [11], Unique Word OFDM (UW OFDM) method [12],
Filter Bank Multi Carrier (FBMC) method [13], Universal
Filtered Multi Carrier (UFMC) method [14], Filtered OFDM
(F-OFDM) [15] method and Generalized Frequency Division
Multiplexing (GFDM) [16] method. In this study, a new hybrid
OFDM (H-OFDM) method is proposed to improve the
performance of the conventional OFDM method and unique
word OFDM (UW OFDM) technique from 5G candidate
waveforms. In order to compare the proposed H-OFDM with
the conventional OFDM system, computer simulations are
Abstract—A novel hybrid orthogonal frequency division
multiplexing (H-OFDM) technique, for 5G candidate waveforms,
has been proposed to improve the performance of conventional
OFDM systems in this paper. In H-OFDM system instead of
conventional cyclic prefixes (CPs) it is used hybrid CP as a guard
interval. The hybrid CP consists of zero tail (ZT), unique word
(UW) and CP. Computer simulations have been performed to
show the performance of the proposed system in stationary and
non-stationary frequency selective Rayleigh fading channels. The
obtained simulation results using IEEE 802.16 physical layer
specifications have demonstrated that the proposed H-OFDM
method has considerably better performance and Doppler shift
tracking than conventional OFDM.
Keywords—Hybrid
Waveform Design.
CP;
ZT-OFDM;
UW-OFDM;
5G;
I. INTRODUCTION
Communication technologies have become an integral part of
our society, having an extreme socio-economic impact, and
enriching our daily lives with an excess of services from media
entertainment (e.g. video) to more sensitive and safety-critical
applications (e.g. e-commerce, e-Health, first responder
services, etc.). If analysts’ predictions are correct, just about
every physical object we see (e.g. clothes, cars, trains, buses,
etc.) will also be connected to the networks by the end of the
decade, called Internet of Things (IoT) [1].
Due to too much data traffic request the International
Telecommunication Union (ITU) has described the conditions
for international mobile communication in 2020 and beyond
[2]. These are aimed at data rates of 20 Gbps, user data rates of
100 Mbps to 1 Gbps, and a minimum latency of less than 1 ms.
Current radio access technologies such as Long Term
Evolution (LTE) and advanced long-term evolution (LTEAdvanced) have problems such as incompatibility constraints
and internal constraints to meet ITU requirements [2]. The
industry and academia are exploring new methods for 5th
Generation (5G) radio access technology that will remove
previous generation radio access technologies [3].
Additionally, the number of terminals will increase
exponentially due to new technologies such as Machine to
Machine (M2M), Vehicular to Vehicular (V2V) and Device to
Device (D2D) that will come with 5G and later technologies
[4]. Communication technologies are being developed to
achieve ever high date rates over power and band limited radio
channels. Orthogonal frequency division multiplexing (OFDM)
has appeared as a strong contender for use with inter symbol
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195
TSP 2017
executed on stationary and non-stationary frequency selective
Rayleigh fading channels. From the obtained results, it is seen
that the proposed H-OFDM system has better performance than
the conventional OFDM system in both stationary and nonstationary channels.
The rest of the paper is organized as follows: the Unique
Word OFDM system model used in simulations is summarized
in Chapter 2. The proposed H-OFDM-FDE structure is
described in detail in Chapter 3. The performed computer
simulations have been introduced in the fourth section. The
obtained results by taking into account computer simulation
results are given in the last section.
improving the performance of conventional OFDM system.
The hybrid CP (H-CP) consists of zero tail, unique word and
conventional CP as shown in Figure 2.
II. UNIQUE WORD OFDM
In the proposed H-CP, conventional CP length is of channel
impulse response length, UW length is of half-length of CP and
the rest of the CP is assigned ZT, filled with zero. CAZAC
sequence, given in IEEE 802.16 standard, has been used as a
unique word in this proposed technique. Since the UW is
deterministic sequence, it can be optimally designed for
particular needs like synchronization and/or channel estimation
purposes at the receiver side. Additionally, in UW-OFDM the
guard interval is part of the FFT interval, whereas this is not the
case for CP-OFDM which improves the bit error ratio (BER)
performance [17]. However, Zero Tail (ZT) OFDM has the
superior spectral density of the generated waveform than CPOFDM [10]. Therefore, in this study, due to the conveniences
of ZT and the advantages of UW, a new H-CP is designed to
improve the performance of the conventional OFDM method
and UW-OFDM technique from 5G candidate waveforms.
The block diagram of the transmitter and the receiver
structure of the proposed H-OFDM system using the frequency
domain channel equalizer (FDE) is given in Figure 3.
OFDM Symbol
H-CP
Data 1
CP1
UW
Data 1
UW
CP2
Data 2
Data 2
H-CP
Unique Word
Data 2
CP2
Serial
UW
FEC
Input Coding
Fig. 1. Transmit symbol structures for CP-OFDM and UW-OFDM.
CP
I-Q
Mapping
IFFT
H-CP
Adding
ISI
Channel
Some key differences between a UW and a CP based
OFDM system can be pointed out:
1. The UW lies inside the Fast Fourier Transform (FFT)
window, while the CP lies outside the FFT interval.
2. The CP is based on the transmitted data. Since the OFDM
data symbol varies from symbol to symbol the CP is observed
to be random.
3. The UW is deterministic and therefore the same for all
OFDM symbols.
Key characteristic of a Unique Word are that it has good
periodic correlation properties, and its symbols have constant
amplitude. Ideally, the sequence is constant amplitude zero
auto-correlation (CAZAC) sequence. Unique Words could be
used for channel; timing and carrier offset estimation for
OFDM system [18].
H-CP
Fig. 2. The proposed H-OFDM system symbol structure.
OFDM Symbol
CP1
H-CP
Zero Tail
Instead of CP, which is a random sequence in the CP-OFDM
technique, a non-random sequence, unique-word (UW), is used
in the UW OFDM method [17]. Since UW is known
sequences, it can be used for time-frequency alignment and
channel estimation. Compared to the CP-OFDM technique,
out-of-band propagation is less in the UW-OFDM scheme.
However, computational complexity is greater in UW-OFDM
[9].
Figure 1 illustrates the differences between the
conventional CP-OFDM and the UW-OFDM transmitted
symbol structures.
OFDM Symbol
Data 1
OFDM Symbol
AWGN
Serial FEC DeOutput Coding
I-Q
De Mapping
FDE
FFT
H-CP
Removing
Fig. 3. Block diagram of the proposed H-OFDM system
transmitter and receiver structure.
Figure 3 shows the proposed technique block diagram’s
basic components for the receiver and the transmitter in multi
carrier communications, where it is used Reed Solomon and
convolutional coding for forward error correction (FEC)
coding, and soft output Viterbi decoding for the FEC decoding.
After the data coming as serially from the source are coded by
the (255, 239, GF 28) Reed-Solomon coding for the outer code
[19], block interleaved [19] and then coded by the binary
convolution code (CC) with the rate of 1/2 as an inner code
[19]. The output of the FEC encoder is divided into groups by
III. THE PROPOSED H-OFDM SYSTEM
The proposed method, inspired by [18], considers the hybrid
cyclic prefix instead of conventional CP as a guard interval,
196
Conventional OFDM-FDE
LMS Channel Estimation
1E-2
Proposed H-OFDM-FDE
LMS Channel Estimation
1E-3
OFDM-FDE
RLS Ch. Est.
1E-4
Reference [18]
Channel Known
1E-5
1E-6
0
5
10
OFDM-FDE
Ch. Known
Proposed M.
RLS Ch. Est.
Proposed
H-OFDM-FDE
Channel Known
AWGN
Channel
15
20
25
30
35
40
Proposed M.
Ch. Known
Proposed M.
RLS Ch. Est.
Proposed M.
LMS Ch. Est.
OFDM-Coded
Ch. Konown
OFDM-Coded
RLS Ch. Est.
OFDM-Coded
LMS Ch. Est
Ref. [18]
Ch. Known
OFDM-Uncoded
AWGN
45
SNR (dB)
Fig. 4. Comparison of the coded BER-SNR performances of conventional
OFDM, Reference [18] and proposed H-OFDM systems
using 4-QAM modulation.
It can be seen from the Figure 4 the coded BER
performance obtained using the LMS channel estimation in
conventional OFDM-FDE converges to lower 1E-2 BER value
but the obtained result is not of significance. It is observed that
the proposed H-OFDM-FDE, with LMS channel estimation,
performs better than the conventional OFDM-FDE and it also
converges to lower 5E-4 BER floor. The BER performance of
the proposed H-OFDM-FDE, with RLS channel estimation,
gets better than the performance of the conventional OFDMFDE, Reference [18] and converges to the performance of the
case of channel known. Additionally, while the performance
of the conventional OFDM-FDE, with RLS channel
estimation, converges to error floor, the performance of the
proposed method removes the error floor.
The un-coded BER versus SNR performances of the
conventional OFDM-FDE, Reference [18] and the proposed
H-OFDM-FDE equalizers are given in Figure 5 for 4-QAM
modulation.
IV. COMPUTER SIMULATION RESULTS
The computer simulation works have composed of two phases.
In the first phase works are performed using the simulated
stationary communication channel. In the second phase works
are executed employing non-stationary communication
channel. Bit error rate (BER) performances are obtained at the
output of error correcting decoder for both the simulated
stationary communication channel and the non-stationary
communication channel with frequency domain channel
equalizer (FDE).
A. Simulation Results of Stationary Channel
{0.227, 0.46, 0.688, 0.46, 0.227}
Simulated Proakis Channel Profile, 4-QAM, FDE, Un-Coded
1E-1
Conventional OFDM-FDE
LMS Channel Estimation
1E-2
BER
In this first phase, simulation results are exhibited to verify
the performance of the proposed H-OFDM method in
simulated stationary frequency selective Rayleigh fading
channels. The proposed technique is compared with
conventional OFDM and Reference [18].
The simulation studies are executed using the physical
layer specifications of IEEE 802.16 via 1000 independent
Monte Carlo type iterations employing 20 OFDM data blocks
for the 4-QAM modulation. In this paper, a five taps channel
profile with average coefficient amplitudes given by (0.227,
0.46, 0.688, 0.46, 0.227), which is defined by Proakis, is
employed [20]. Simulation studies have been done by taking
the step size parameter of the Least Mean Squares (LMS)
algorithm is 0.045 and the forgetting factor parameter of the
Recursive Least Squares (RLS) algorithm is 0.985 employed
in estimation of the channel coefficients.
The coded BER versus SNR performances of the
conventional OFDM-FDE, Reference [18] and the proposed
H-OFDM-FDE equalizers are given in Figure 4 for 4-QAM
modulation.
{0.227, 0.46, 0.688, 0.46, 0.227}
Simulated Proakis Channel Profile, 4-QAM, FDE, Coded
1E-1
BER
means of I-Q mapping depending on the number of bits to be
sent by a sub-carrier and is modulated with one of the desired
modulation types (BPSK, QPSK, 16-QAM, 64-QAM and 256QAM). After taken the inverse fast Fourier transform of the I-Q
matched data and added the proposed H-CP, OFDM symbols
are generated. The obtained OFDM symbols are transmitted
over a multipath channel and corrupted by additive white
Gaussian noise (AWGN). In the receiver, the H-CP of the
received data is removed and equalized with frequency domain
channel equalizer after the FFT process. The equalized datas
are demodulated by the I-Q de-mapping block. The
demodulated datas are decoded by inner decoder, deinterleaved and decoded again by the outer decoder. ReedSolomon decoder and soft output Viterbi algorithm (SOVA)
are used together in FEC decoding. Finally, output data is
obtained at the output of FEC decoding block and then any
desired performance comparisons are also executed.
Proposed H-OFDM-FDE
LMS Channel Estimation
1E-3
OFDM-FDE
RLS Ch. Est.
1E-4
1E-6
0
5
10
15
20
25
30
35
Proposed M.
LMS Ch. Est.
OFDM-Uncoded
Ch. Known
OFDM-Uncoded
RLS Ch. Est.
Ref. [18] Uncoded
Ch. Known
Reference [18]
Channel Known Proposed M.
RLS Ch. Est.
AWGN
Channel
Proposed M.
RLS Ch. Est.
OFDM-Uncoded
LMS Ch. Est.
Proposed
H-OFDM-FDE
Channel Known
1E-5
Proposed M.
Ch. Known
40
OFDM-Uncoded
AWGN
45
SNR (dB)
Fig. 5. Comparison of the un-coded BER-SNR performances of conventional
OFDM,Reference [18] and proposed H-OFDM systems
using 4-QAM modulation.
When the un-coded BER-SNR performances belong to the
4-QAM modulation is investigated in Figure 5, similar
performances are also obtained in coded BER performances in
197
Figure 4. The performance differences are protected between
the proposed method and conventional OFDM-FDE and
Reference [18]. Because only coding is not used, SNR values
have changed.
In this second phase of the work, simulations are also
obtained for 4-QAM modulated systems employing 20 OFDM
data blocks with IEEE 802.16 physical layer properties in 5.2
GHz carrier frequency over 1000 independent Monte Carlo
loops for non-stationary channels. It is quite common to use an
RMS delay spread of 30-90 ns with Rayleigh channel delay
profile, for this paper we have used a more demanding five tap
channel profile with average coefficient amplitudes given by
(0.227, 0.46, 0.688, 0.46, 0.227), which is defined by Proakis
[20] and corresponds to an RMS delay spread of approximately
50 ns for our system configuration. Simulation studies have
been done by taking the step size parameter of the LMS
algorithm is 0.085 and the forgetting factor parameter of the
RLS algorithm is 0.85 used for estimation of the channel
coefficients in channel tracking. After the channel is estimated,
equalization process is executed again in the frequency domain.
The maximum Doppler frequency values that will occur at
various speeds and carrier frequencies in a receiver moving at a
constant speed are given in Table 1.
TABLE I.
1E-1
1800
2400
8.333
11.111
33.333
44.444
83.333 111.111
166.666 222.222
200.000 266.666
400.000 533.333
500.000 666.666
666.666 888.888
833.333 1111.111
1E-6
Proposed M.
LMS Ch. Tr.
Proposed H-OFDM
Coded RLS Ch. Tracking
0
5
10
15
20
25
30
Proposed H-OFDM
Un-Coded RLS
Ch. Tracking
35
40
45
OFDM-Coded
LMS Ch. Tr.
OFDM-Uncoded
LMS Ch. Tr.
Ref. [18] Coded
RLS Ch. Est.
SNR (dB)
Fig. 6. Comparison of Doppler tracking coded and un-coded BER-SNR
performances of conventional OFDM, Ref. [18] and proposed H-OFDM
systems using 4-QAM modulation in case of a Doppler frequency of 240 Hz.
In case of Doppler frequency is of 240.740 Hz (mobile
vehicle speed is of 50 km/h), when the obtained coded and uncoded BER performances of the conventional OFDM,
Reference [18] and proposed method are examined in Figure
6, the coded and un-coded performances of the proposed HOFDM-FDE, with RLS channel tracking, outperform the
performances of conventional OFDM-FDE and Reference
[18]. Additionally, as can be seen from the Figure 6 coded and
un-coded BER performances of both techniques remove the
error floor. The coded and un-coded performances of the
proposed H-OFDM-FDE, with LMS channel tracking,
outperform the performances of conventional OFDM-FDE.
Moreover, as can be observed from the Figure 6 coded and uncoded BER performances of both techniques, with LMS
channel tracking, converge the error floor.
5200
24.074
96.296
240.740
481.481
577.777
1155.555
1444.444
1925.925
2407.407
In case of the mobile vehicle speed is 50 km/h (Doppler
frequency is 240.740 Hz) in Figure 6, the mobile vehicle speed
is 120 km/h (Doppler frequency is 577.777 Hz) in Figure 7,
and the mobile vehicle speed is 240 km/h (Doppler frequency
1155.555 Hz) in Figure 8, coded and un-coded BER-SNR
performance comparison between the proposed H-OFDMFDE, Reference [18] and the conventional OFDM-FDE system
are given for belong to the channel tracking.
Proposed M.
LMS Ch. Tr.
Conventional OFDM
Coded RLS Ch. Tr.
1E-5
{0.227, 0.46, 0.688, 0.46, 0.227}
Simulated Proakis Channel Profile, 4-QAM, FDE, V. S. = 120 km/h
1E-1
Proposed H-OFDM
LMS Ch. Tracking
Conventional OFDM
LMS Ch. Tracking
Proposed M.
RLS Ch. Tr.
Proposed M.
RLS Ch. Tr.
OFDM-Coded
RLS Ch. Tr.
1E-2
BER
Vehicle Speed [km/h]
4.166
16.666
41.666
83.333
100.000
200.000
250.000
333.333
416.666
Proposed M.
RLS Ch. Tr.
OFDM-Uncoded
RLS Ch. Tr.
1E-3
Reference [18]
Coded RLS Ch. Tracking
Carrier Frequency, MHz
5
20
50
100
120
240
300
400
500
Conventional OFDM
LMS Ch. Tracking
Proposed M.
RLS Ch. Tr.
OFDM-Coded
RLS Ch. Tr.
1E-4
THE MAXIMUM DOPPLER FREQUENCY VALUES IN VARIOUS
CARRIER FREQUENCY AND SPEEDS.
900
Proposed H-OFDM
LMS Ch. Tracking
1E-2
BER
B. Simulation Results of Non-Stationary Channel
{0.227, 0.46, 0.688, 0.46, 0.227}
Simulated Proakis Channel Profile, 4-QAM, FDE, V. S. = 50 km/h
OFDM-Uncoded
RLS Ch. Tr.
1E-3
Proposed M.
LMS Ch. Tr.
Proposed H-OFDM
Un-Coded RLS
Ch. Tracking
1E-4
Reference [18] Coded
RLS Ch. Tracking
Proposed H-OFDM
Coded RLS Ch. Tracking
OFDM-Coded
LMS Ch. Tr.
Conventional OFDM
Coded RLS Ch. Tr.
1E-5
0
5
10
15
20
25
Proposed M.
LMS Ch. Tr.
30
OFDM-Uncoded
LMS Ch. Tr.
35
40
45
Ref. [18]
RLS Ch. Est.
SNR (dB)
Fig. 7. Comparison of Doppler tracking coded and un-coded BER-SNR
performances of conventional OFDM, Ref. [18] and proposed H-OFDM
systems using 4-QAM modulation in case of a Doppler frequency of 577 Hz.
In case of Doppler frequency is of 577.777 Hz (mobile
vehicle speed is of 120 km/h), when the obtained coded and
un-coded BER performances of the conventional OFDM-FDE,
Reference [18] and proposed technique are observed in Figure
7, the coded and un-coded performances of the proposed HOFDM-FDE, with RLS channel tracking, outperform the
198
performances of conventional OFDM-FDE and Reference
[18]. However, the obtained performances of channel tracking
start to be varying since the all methods produce error floor.
{0.227, 0.46, 0.688, 0.46, 0.227}
Simulated Proakis Channel Profile, 4-QAM, FDE, V. S. = 240 km/h
3E-1
Proposed H-OFDM
LMS Ch. Tracking
1E-1
Conventional OFDM
LMS Ch. Tracking
BER
[1]
[2]
Proposed M.
RLS Ch. Tr.
Proposed M.
RLS Ch. Tr.
[3]
OFDM-Coded
RLS Ch. Tr.
3E-2
OFDM-Uncoded
RLS Ch. Tr.
1E-2
Conventional OFDM
Un-Coded RLS Ch. Tr.
Proposed H-OFDM
Un-Coded RLS
Ch. Tracking
3E-3
1E-3
Conventional OFDM
Coded RLS Ch. Tr.
Reference [18]
Coded RLS Ch. Tracking
3E-4
1E-4
REFERENCES
Proposed H-OFDM
Coded RLS Ch. Tracking
0
5
10
15
20
25
30
35
[4]
Proposed M.
LMS Ch. Tr.
Proposed M.
LMS Ch. Tr.
[5]
OFDM-Coded
LMS Ch. Tr.
OFDM-Uncoded
LMS Ch. Tr.
40
45
Ref. [18] Coded
RLS Ch. Est.
[6]
SNR (dB)
Fig. 8. Comparison of Doppler tracking coded and un-coded BER-SNR
performances of conventional OFDM, Ref. [18] and proposed H-OFDM
systems using 4-QAM modulation in case of a Doppler frequency of 1155 Hz.
[7]
In case of Doppler frequency is of 1155.555 Hz (mobile
vehicle speed is of 240 km/h), when the obtained coded and
un-coded BER performances of the conventional OFDM-FDE,
Reference [18] and proposed method are examined in Figure
8, similar performances are also obtained for 4-QAM.
However, the obtained coded and un-coded BER
performances are worse than the performances in the case of
Doppler frequency is of 240 Hz and 577 Hz.
[8]
[9]
[10]
V. CONCLUSION
A new Hybrid OFDM (H-OFDM) system is proposed for
5G, in order to improve the performance of conventional
OFDM system in this study. Hybrid cyclic prefix (H-CP),
consisting of zero tail, unique word and conventional CP, is
employed in the proposed technique. It has been shown that a
combination of conventional OFDM and the proposed H-CP
method provides an effective and robust way for adaptive
channel equalization and channel tracking for 5G. The
proposed technique has been applied to the frequency domain
channel equalization of a multi carrier IEEE 802.16 radio
standard in stationary and non-stationary frequency selective
Rayleigh fading channels. The performance improvement by
the proposed technique is very significant. Thus, the
conventional OFDM has become with a high performance
waveform technique for 5G. The results of this study show that
the proposed H-OFDM based on H-CP is also shown to be
very suitable for high speed channel tracking and offers a very
low complexity alternative for high performance applications
for 5G and beyond.
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