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The Impact of Adaptive Guards
for 5G and Beyond
Ali Fatih Demir∗,Student Member, IEEE, Hüseyin Arslan∗†, Fellow, IEEE
∗Department of Electrical Engineering, University of South Florida, Tampa, FL, 33620
†School of Engineering and Natural Sciences, Istanbul Medipol University, Istanbul, TURKEY, 34810
e-mail: afdemir@mail.usf.edu, arslan@usf.edu
Abstract—The next generation communication systems
are evolving towards an increased flexibility in different
aspects. Enhanced flexibility is the key in order to address
diverse requirements. This paper presents the signifi-
cance of adaptive guards considering a windowed-OFDM
system which supports a variety of services operating
asynchronously under the same network. The windowing
approach requires a guard duration to suppress the out-of-
band emissions (OOBE), and the guard band is required to
handle the adjacent channel interference (ACI) along with
the windowing. The guards in both time and frequency
domains are optimized with respect to the use case and
power offset between the users. To fully exploit and further
increase the potential of adaptive guards, an interference-
based scheduling algorithm is proposed as well. The results
show that the precise design that facilitates such flexibility
reduce the guards significantly and boost the spectral
efficiency.
Index Terms—5G, ACI, OFDM, OOBE, scheduling,
windowing.
I. INTRODUCTION
The next generation communication systems including
5G are expected to support high flexibility and a diverse
range of services, unlike the previous standards. The
IMT-2020 vision defines the use cases into three main
categories as enhanced mobile broadband (eMBB), mas-
sive machine type communications (mMTC), and ultra-
reliable low-latency communications (URLLC) featuring
20 Gb/s peak data rate, 106/km2device density, and
less than 1 ms latency, respectively [1]. The appli-
cations which require larger bandwidth and spectral
efficiency fall into eMBB category, whereas the ones
that have a tight requirement for device battery life
falls into mMTC. Usually, the industrial smart sensors
or medical implants [2] need to operate several years
without maintenance, and hence low device complexity
and high energy efficiency are crucial for these mMTC
services. Furthermore, the mission-critical applications
such as remote surgery [3] or self-driving vehicles are
represented in URLLC. Therefore, a flexible air interface
is required to meet these different requirements.
Orthogonal frequency-division multiplexing (OFDM)
is the most popular multi-carrier modulation scheme
which is currently being deployed in many standards
such as 4G LTE and the IEEE 802.11 family [4]. A major
disadvantage of OFDM systems is their high out-of-band
emissions (OOBE). The OFDM signal is well localized
in the time domain with a rectangular pulse shape,
which corresponds to a sinc shape in the frequency
domain. The sidelobes of the sincs cause significant
OOBE and should be reduced to avoid adjacent channel
interference (ACI). Especially, the frequency localiza-
tion is important to allow asynchronous transmission
across adjacent sub-bands and coexistence with other
waveforms/numerologies in the network [5]. However, a
signal cannot be limited in both domains simultaneously
due to the Heisenberg’s uncertainty principle [6]. Hence,
a better spectrum confinement is realized with the cost
of expansion in the time domain. Typically, OOBE is
reduced by various windowing/filtering approaches, and
numerous waveforms are proposed for the upcoming
5G standard to provide better time-frequency concen-
tration [1], [5], [7]–[10]. These filtering and windowing
operations require additional period which extends the
guard duration between the consecutive OFDM symbols.
Also, extra guard bands are needed in between adjacent
channels to control the ACI along with the window-
ing/filtering that handles the OOBE. The forthcoming
generations must optimize the guards in both time and
frequency domains to boost the spectral efficiency.
This paper presents the significance of adaptive guards
considering an OFDM-based system which supports a
variety of services operating asynchronously under the
same network. The OOBE is reduced with a transmitter
windowing operation that smooths the inherent rect-
angular pulse shape of OFDM. This technique retains
the main design of the OFDM receivers and provides
backward compatibility for the existing systems. The
guard band and the window parameters that control the
guard duration are jointly optimized regarding the use
case and the power offset between the users. Although
various windowing approaches are proposed towards
better spectral concentration [11]–[14], this study also
reduces the need for guards by grouping the users with
similar power levels and SIR requirements. Hence, the
potential of adaptive guards is further increased and ex-
ploited with an interference-based scheduling algorithm.
978-1-5386-3531-5/17/$31.00 c
2017 IEEE
2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)
8–13 October 2017, Montreal, QC, Canada
The rest of the paper is organized as follows. Section
II describes the system model and explains the methodol-
ogy in detail. Section III presents optimization of guards
regarding the user requirements. Section IV proposes
the interference-based scheduling strategy along with
the utilization of adaptive guards. Finally, Section V
summarizes the contributions and concludes the paper.
II. SYSTEM MODEL
Consider a multiuser OFDM-based system where
asynchronous numerologies operate in the network. The
users which have different use cases (i.e., requirements)
and power levels perform transmitter windowing to
control their OOBE levels and reduce interference to
the users serving in adjacent bands. The guard duration
that is designated for the multi-path channel is fixed
and sufficient to handle the inter-symbol interference
(ISI). An additional guard duration is required to perform
windowing. Several windowing functions have been
evaluated in detail [15] with different tradeoffs between
the width of the main lobe and suppression of the side
lobes. The optimal windowing function is beyond the
scope of this study, and the raised-cosine (RC) window is
adopted due to its computational simplicity and common
use in the literature [11]–[13]. The RC window function
[11] is expressed as follows:
g[n]=
⎧
⎪
⎪
⎪
⎪
⎨
⎪
⎪
⎪
⎪
⎩
1
2+1
2cos π+πn
αNT0≤n≤αNT
1αNT≤n≤NT
1
2+1
2cos π−πn
αNTNT≤n≤(α+1)NT
where α is the roll-off factor (0 ≤ α ≤ 1) and NT is the
symbol length of the RC function. The roll-off factor
(α) controls the taper duration of the window. As α
increases, the OOBE decreases at the price of increased
guard duration to perform windowing. The transmitter
windowing operation is illustrated in Fig. 1. First, the
cyclic prefix (CP) that is allocated to deal with the multi-
path channel is further extended on both edges, and then
the extended part from the beginning of the OFDM
symbol is appended to the end. The transitions parts
(i.e., ramp-ups and ramp-downs) of adjacent symbols
are overlapped to decrease the additional time-domain
overhead resulting from the windowing operation.
TOFDM
TCP
CP for channel;dWͲŚͿ
CP for windowing;dWͲtŝŶͿ
Postfix for windowing
Overlap with ƚŚĞnext symbol
Fig. 1. Transmitter windowing operation and the guard durations.
The windowing operation is not sufficient to handle
the OOBE, and non-negligible guard bands are still
needed. However, the amount of guard band (GB) or
the length of guard duration (GD) to perform windowing
depends on the power offset and the required signal to
interference ratio (SIR) level of the users in adjacent
bands. As an example, the leaked energy from the near
user can be more powerful than the in-band energy of the
far user in its adjacent band (i.e., the well-known near-far
problem). The power control mechanism is a solution for
this power offset problem. Nonetheless, it prevents near
users to deploy higher order modulation schemes. Thus,
the power control needs to be relaxed with an adaptive
design to improve the spectral efficiency.
The required guards in both time and frequency
domains are tightly related to the use case as well.
For example, the guard units and other extra overheads
decrease the spectral efficiency, which is especially crit-
ical for the eMBB type of communications. Hence, the
guards are reduced with an expense of interference on
the adjacent bands. On the other hand, the reliability
and latency are extremely important for mission critical
communications where errors and retransmissions are
less tolerable. Thus, a strict OOBE suppression is more
feasible for URLLC applications. In addition, mMTC
operates at the low power level to preserve energy and
might suffer from the ACI seriously in an asynchronous
heterogeneous network.
As a result of these discussions, the threshold for
allowed interference level (θ) on adjacent bands should
be adaptive considering the power offset (PO) and the
use case. Fig. 2 presents how GB is inserted regarding θ
to achieve the desired SIR level when there is a PO
between the users in adjacent bands. Throughout the
numerical evaluations in the paper, TCP−Win (i.e., GD)
and GB are adaptive, and these guards are optimized
in Section III. The rest of the parameters belong to
the windowed-OFDM (W-OFDM) system are fixed and
summarized in Table I.
Power O ffset
Required SIR
User A User B
GB
OBW
Allowed
Interference
ɽ
Fig. 2. Guard band allocation considering the interference threshold
(θ) in the adjacent band. (OBW stands for occupied bandwidth and θ
is represented in dB w.r.t. the power of “user A” throughout the paper)
(1)
TABLE I
SIMULATION PARAMETERS
Parameter Val ue
FFT Size 1024
CPchannel Size 256
Subcarrier Spacing (ȴf) 15 kHz
Occupied Bandwidth (OBW) 15.36 MHz
TOFDM 66.7 μs
TCP-channel 16.68 μs
# OFDM Symbols 300
Window Type Raised Cosine
III. OPTIMIZATION OF THE ADAPTIVE GUARDS
The ACI is handled by windowing and allocating
guard band between adjacent users as described in Sec-
tion II. Since windowing operation suppresses the OOBE
with a penalty of additional guard duration, the proce-
dure converges to the utilization of guard duration (GD)
and guard band (GB) to achieve desired interference
threshold (θ). Fig.3 presents the required GB and GD
for selected θ. Each αvalue in the figure corresponds
to a GD to perform windowing, and a GB to deal with
the remaining interference power for a given θ.
An excessive amount of resources is needed to solve
the problem only with GB or GD. As a result, the
spectral efficiency, which is defined as the information
rate that can be transmitted over a given bandwidth,
decreases significantly. Therefore, GB and GD must be
jointly optimized to boost the efficiency of the commu-
nication system. This hyper-parameter optimization has
been performed by a grid search algorithm through a
manually specified subset of the hyper-parameter space
[16]. The spectral efficiency (η) is proportional to the
multiplication of efficiencies in the time and frequency
domains which are expressed as follows:
ηtime =TOF DM
TOFDM +TCP−Ch +TCP−Win
(2)
0.05 0.1 0.15 0.2 0.25 0.3
Roll-off Factor (α)
0
100
200
300
400
500
Guard Band (GB) [kHz]
0
10
20
30
40
50
Guard Duration (GD) [μs]
GB for θ = 20 dB
GB for θ = 25 dB
GB for θ = 30 dB
GB for θ = 35 dB
GB for θ = 40 dB
GB for θ = 45 dB
GD for all θ
Fig. 3. Required GB and GD to achieve selected θlevels.
0.01 0.02 0.03 0.04 0.05
Roll-off Factor (α)
60
65
70
75
80
Spectral Efficiency (η) [%]
θ = 20 dB
θ = 25 dB
θ = 30 dB
θ = 35 dB
θ = 40 dB
θ = 45 dB
Fig. 4. Spectral efficiency (η) of the GB and GD pairs that achieves
selected θ. (Please note that each αcorresponds to a GB-GD pair as
shown in Fig. 3)
ηfreq =OBW
OBW +(GB ×2)(3)
Since TOFDM ,TCP−Ch, and OBW are fixed parameters,
the degrees of freedom that can be selected indepen-
dently becomes only TCP−Win (i.e., GB) and GD. The
problem that seeks for the optimal GB and GD pair can
be formulated as follows:
(GB,GD)=arg max
GB,GD
(ηtime ×ηfreq),(4)
subject to: PO +SIR ≤θ. (5)
The spectral efficiency of the W-OFDM system for
selected θvalues is presented in Fig. 4. Each αvalue in
the graph corresponds to a GB-GD pair for a given θand
the peak value of each curve provide the optimal pair.
These optimal pairs are listed in Table II along with the
associated parameters. The results show that the need
for windowing decreases as θdecreases, and hence the
desired ACI level can be achieved only with a few guard
carriers. In addition, the spectral efficiency increases
with the decrease in θ. The variation in required guards
clearly affirms that the adaptive design improves the
spectral efficiency significantly instead of designing the
system considering the worst case (e.g., ηθ=45 dB = 74.11
% whereas ηθ=20 dB = 79.33 %).
TABLE II
THE OPTIMAL GUARDS FOR SELECTED θ
/ŶƚĞƌĨĞƌĞŶĐĞ
dŚƌĞƐŚŽůĚ;ɽͿ
Ě
Max. Spectral
Efficiency (ɻ)
[%]
Roll-of f
Factor (ɲ)
Required
Guard Duration
[ʅs]
Required
Guard Band
[kHz]
Required
Guard Carriers
20 79.33 0.0000 0.00 64.48 5
25 77.92 0.0067 0.55 153.06 11
30 76.43 0.0167 1.40 226.07 16
35 75.30 0.0300 2.57 235.51 16
40 74.65 0.0300 2.57 303.95 21
45 74.11 0.0333 2.86 333.96 23
IV. INTERFERENCE-BASED SCHEDULING
The optimization results in Section III reveal that
the spectral efficiency (η) decreases as the interference
threshold (θ) increases. Since θdepends on the users
operating in the adjacent bands, the potential of adaptive
guards can be increased further along with the utilization
of an interference-based scheduling algorithm. Assum-
ing that the base station or the user equipment has all
necessary information, θis determined as follows:
θi=max(SIRi−1+POi−1,SIRi+1+POi+1),∀i(6)
where iis the indicator of the available consecutive
bands. If the users with similar power levels and SIR
requirements are grouped together, the average θin the
network decreases. As a result, the need for guards is
reduced, and the spectral efficiency increases.
Consider an exemplary scenario with eight users,
where the users have different power levels and SIR
requirements as shown in Tables III and IV. The power
offset (PO) pairs in the tables are provided regarding the
users in adjacent bands. The users are assigned to the
bands in two different ways. In the first scenario, a ran-
dom scheduling has been realized (Fig. 5), whereas the
ACI based scheduling strategy is utilized in the second
scenario (Fig. 6). To compare and present the impact of
the adaptive guards, a fixed guard assignment strategy is
implemented in the random scheduling scenario as well.
The guards are selected regarding the worst case scenario
(i.e., θ= 45 dB) in the fixed assignment scenario.
The comparison of required guards for the fixed guard
assignment with random scheduling, the adaptive guard
assignment with random scheduling, and the adaptive
guard assignment with interference-based scheduling
scenarios is summarized in Table V. The results show
that the amount of guard duration (GD) and guard band
(GB) decreased by 57% and 19%, respectively when the
fixed guards are replaced with the adaptive guards. In
addition, the amount of GD and GB decreased further by
35% and 16%, respectively when the random schedul-
ing is replaced with the interference-based scheduling
strategy.
Power
Frequency Band
User-1
eMBB
User-2
eMBB
User-3
eMBB
User-4
URLLC
User-5
eMBB
User-6
mMTC
User-7
URLLC
User-8
eMBB
Fig. 5. Random scheduling of eight users which have different
requirements.
TABLE III
THE REQUIREMENTS OF RANDOMLY SCHEDULED USERS
Band 12345 6 78
User 12345 6 78
Req. SIR [dB] 20 20 20 25 20 25 35 20
Rx Power [dBm] 0-10-150 -5 -25 -10 -20
Power Offset [dB]10-10, 5-5, -1515, 5-5, 20-20, -1515, 10-10
/ŶƚĨThr. (ɽ) [dB]3025153545 20 40 25
TABLE IV
THE REQUIREMENTS OF INTERFERECE-BASED SCHEDULED USERS
Band 12345 6 78
User 741523 86
Req. SIR [dB] 35 25 20 20 20 20 20 25
Rx Power [dBm]-10 0 0 -5 -10 -15 -20 -25
Power Offset [dB]-1010, 00, 5-5,5-5, 5-5, 5 -5,5-5
/ŶƚĨThr. (ɽ) [dB]1545252525 25 30 15
TABLE V
THE COMPARISON OF REQUIRED GUARDS FOR DIFFERENT
SCENARIOS
Scenario Required
Guard Duration [μ
s]
Required
Guard Band[ŬHz]
Fixed Guards
Random Scheduling
22.88 23ϯϳ
Adaptive Guards
Random Scheduling
9.95 189ϭ
AdaptiveGuards
/ŶƚĨͲďĂƐĞĚ Scheduling 6.46 15ϳϵ
V. C ONCLUSIONS
This paper presented the importance of adaptive
guards considering a windowed-OFDM system which
supports a variety of services operating asynchronously
under the same network. The guards in both time and
frequency domains are optimized taking the use case
and power offset into account. Furthermore, the need for
guards is reduced with an interference-based scheduling
algorithm. Such a scheduling strategy is especially crit-
ical when the power offset between the users operating
in adjacent bands is high. The results show that the
precise design that facilitates such flexibility considering
the user requirements improve the spectral efficiency
significantly. Although the computational complexity
increases compared to conventional OFDM-based sys-
tems, the computation of the optimal GB and GD is an
Power
Frequency Band
User-7
URLLC
User-4
URLLC
User-1
eMBB
User-5
eMBB
User-2
eMBB
User-3
eMBB
User-8
eMBB
User-6
mMTC
Fig. 6. Interference-based scheduling of eight users which have
different requirements.
offline process that requires a one-time solution. Hence,
a lookup table method can be adopted to reduce the
complexity. This study will be extended by optimiz-
ing the guards and scheduling the users under various
channel conditions and impairments. Also, the proposed
methodology is applicable to the filtered-OFDM sys-
tems. The next generation communications systems are
evolving towards an increased flexibility in different
aspects. Enhanced flexibility is the key especially to
address diverse requirements, and definitely, the guards
should be a part of the flexibility consideration as well.
REFERENCES
[1] X. Zhang, L. Chen, J. Qiu, and J. Abdoli, “On the Waveform
for 5G,” IEEE Communications Magazine, vol. 54, no. 11, pp.
74–80, Nov. 2016.
[2] A. F. Demir, Z. E. Ankarali, Q. H. Abbasi, Y. Liu, K. Qaraqe,
E. Serpedin, H. Arslan, and R. D. Gitlin, “In Vivo Communica-
tions: Steps Toward the Next Generation of Implantable Devices,”
IEEE Vehicular Technology Magazine, vol. 11, no. 2, pp. 32–42,
Jun. 2016.
[3] A. F. Demir, Q. Abbasi, Z. E. Ankarali, A. Alomainy, K. Qaraqe,
E. Serpedin, and H. Arslan, “Anatomical Region-Specific In
Vivo Wireless Communication Channel Characterization,” IEEE
Journal of Biomedical and Health Informatics, vol. PP, no. 99,
pp. 1–1, 2016.
[4] T. Hwang, C. Yang, G. Wu, S. Li, and G. Y. Li, “OFDM
and Its Wireless Applications: A Survey,” IEEE Transactions on
Vehicular Technology, vol. 58, no. 4, pp. 1673–1694, May 2009.
[5] A. F. Demir, M. Elkourdi, M. Ibrahim, and H. Arslan, “Waveform
Design for 5G and Beyond,” accepted for publication in "5G
Networks: Fundamental Requirements, Enabling Technologies,
and Operations Management". John Wiley & Sons, Ltd, 2017.
[6] M. Benedicks, “On Fourier transforms of functions supported
on sets of finite Lebesgue measure,” Journal of Mathematical
Analysis and Applications, vol. 106, no. 1, pp. 180–183, Feb.
1985.
[7] G. Berardinelli, K. I. Pedersen, T. B. Sorensen, and P. Mogensen,
“Generalized DFT-Spread-OFDM as 5G Waveform,” IEEE Com-
munications Magazine, vol. 54, no. 11, pp. 99–105, Nov. 2016.
[8] A. Sahin, R. Yang, E. Bala, M. C. Beluri, and R. L. Olesen,
“Flexible DFT-S-OFDM: Solutions and Challenges,” IEEE Com-
munications Magazine, vol. 54, no. 11, pp. 106–112, Nov. 2016.
[9] Qualcomm Inc., “Waveform Candidates,” 3GPP Standard Con-
tribution (R1-162199), Busan, Korea, Apr. 11-15 2016.
[10] Z. E. Ankarali, B. Pekoz, and H. Arslan, “Flexible Radio Access
Beyond 5G: A Future Projection on Waveform, Numerology
Frame Design Principles,” IEEE Access, vol. PP, no. 99, pp. 1–1,
2017.
[11] T. Weiss, J. Hillenbrand, A. Krohn, and F. K. Jondral, “Mutual
interference in OFDM-based spectrum pooling systems,” in 2004
IEEE 59th Vehicular Technology Conference. VTC 2004-Spring
(IEEE, vol. 4, May 2004, pp. 1873–1877 Vol.4.
[12] E. Bala, J. Li, and R. Yang, “Shaping Spectral Leakage: A Novel
Low-Complexity Transceiver Architecture for Cognitive Radio,”
IEEE Vehicular Tech. Mag., vol. 8, no. 3, pp. 38–46, Sep. 2013.
[13] I. Macaluso, B. Ozgul, T. K. Forde, P. Sutton, and L. Doyle,
“Spectrum and Energy Efficient Block Edge Mask-Compliant
Waveforms for Dynamic Environments,” IEEE Journal on Se-
lected Areas in Communications, vol. 32, no. 2, pp. 307–321,
Feb. 2014.
[14] E. Güvenkaya, A. ¸Sahin, E. Bala, R. Yang, and H. Arslan,
“A Windowing Technique for Optimal Time-Frequency Con-
centration and ACI Rejection in OFDM-Based Systems,” IEEE
Transactions on Communications, vol. 63, no. 12, pp. 4977–
4989, Dec. 2015.
[15] B. Farhang-Boroujeny, “OFDM Versus Filter Bank Multicarrier,”
IEEE Signal Processing Mag., vol. 28, no. 3, pp. 92–112, May
2011.
[16] J. S. Bergstra, R. Bardenet, Y. Bengio, and B. Kégl, “Algorithms
for Hyper-Parameter Optimization,” in Advances in Neural In-
formation Processing Systems 24, J. Shawe-Taylor, R. S. Zemel,
P. L. Bartlett, F. Pereira, and K. Q. Weinberger, Eds. Curran
Associates, Inc., 2011, pp. 2546–2554.