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RESEARCH Open Access
Device discovery for D2D communicationin in-band cellular
networks using spheredecoder like (SDL) algorithmO. Hayat1,2* , R.
Ngah2 and Yasser Zahedi3
Abstract
In the fifth generation (5G), it is anticipated that
device-to-device (D2D) operation will be locally incorporated as
apart without any bounds. In D2D network, multiple devices
coexisting is a challenging subject of device discovery.The device
discovery is performed under a visually impaired situation such as
channel information, location, andthe number of devices. In this
paper, centralized device discovery is chosen due to power
consumption and signalingoverhead of the distributed system. A
distinctive approach for device discovery in an in-band cellular
network, basedon the device’s power, is suggested with an efficient
technique which enhances the implementation of D2Dcommunication and
improves the accomplishment by alleviating the discovery issues.
The group of devicesforms a lattice structure, and it is positioned
in the coverage area. The hypersphere is constructed based onthe
power knowledge of a discoverer device which helps for accurate and
fast device discovery in a latticestructure. Besides, sphere
decoder like (SDL) algorithm is applied for quick and precise
discovery in the latticestructure. Simulation results present the
performance of the proposed QR factorized lattice structure
schemeregarding device power, enhanced in the number of discovered
devices and controlled signaling overhead.
Keywords: Device-to-device (D2D) communication, Sphere decoder
like (SDL) algorithm, Device discovery,Cellular network, End users
(EU)
1 IntroductionDevice-to-device (D2D) communication alludes to
directtransmission between two devices without passingthrough the
base station. It has been broadly anticipatedto be an essential
cornerstone to enhance systemperformance and bolster new amenities
beyond 2020 infuture fifth generation (5G) systems [1]. In 5G
networks,it is anticipated that controlled D2D communication
of-fers the open door for short-distance communicationand local
management and permits the isolation of localactivity from the
global activity, for example, local dataoffloading. D2D
communication evacuates the data traf-fic heap load on the backhaul
and center systems anddecreases the vital exertion for managing
data traffic atthe center system. Due to proximity services,
D2D
communication is viewed as a promising remedy for en-hancing
communication accomplishment and systemcapacity of long-term
evolution-advanced (LTE-A) net-work. The potential enhancements in
proximity servicesthat can be given by D2D are not entirely
exploited yet.In the 5G network, such confinement does not exist
anylonger, and it is anticipated that D2D operation in thein-band
cellular network will be locally incorporated as acomponent without
any bounds in the 5G network [2].The in-band cellular network is
considered in this re-search because interference and resource
allocation iscontrolled by the base station or center system [3].An
important technique in deploying D2D communi-
cation is device discovery. Device discovery is character-ized
into two categories which are distributed discoveryand centralized
discovery. In the distributed discoverydesign, optimal resources
and legitimate transmissionpower are apportioned with the consent
of base station.However, this strategy involves complex signaling
over-head and multifaceted nature of multiple transmitters to
* Correspondence: [email protected] of Engineering,
National University of Modern Language(NUML), H-9, Islamabad,
Pakistan2Wireless Communication Centre (WCC), Faculty of Electrical
Engineering,Universiti Teknologi Malaysia, 81310 Johor Bahru,
MalaysiaFull list of author information is available at the end of
the article
© The Author(s). 2018 Open Access This article is distributed
under the terms of the Creative Commons Attribution
4.0International License
(http://creativecommons.org/licenses/by/4.0/), which permits
unrestricted use, distribution, andreproduction in any medium,
provided you give appropriate credit to the original author(s) and
the source, provide a link tothe Creative Commons license, and
indicate if changes were made.
Hayat et al. EURASIP Journal on Wireless Communications and
Networking (2018) 2018:74
https://doi.org/10.1186/s13638-018-1083-8
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be composed [4]. In contrast, centralized device discov-ery
design is adequately controlled by the base stationand resources
are managed by center system. Besides,the proximity services, for
example, commercial an-nouncement, public transport and
municipality informa-tion, local programs, and impulsive social and
corporatecontacts infer decreased energy consumption and la-tency.
Therefore, in D2D-enabled centralized networks,multiple devices
coexisting is a challenging subject ofdevice discovery for D2D
communication to initiate theproximity services. However, latest
reviews have concen-trated on the D2D communication issues
accepting thatdevice discovery issue [5–7] is the vital problem
andneeds solution.Discovery signal is designed in [8], minimizes
colli-
sions, and tries to improve the discovery process. Aslight
portion of resources used for device discovery anddiscovery signal
which can be broadcasted with a mini-mum delay is proposed in [9,
10]. Distinguishing be-tween different discovery signals is
difficult which leadsto an increment in power consumption.
Compressivesensing method has been suggested in [11], in whichuser
detection decreases the collision for device discov-ery. However,
when many devices are involved, activecongestion will occur, and
actual discovery will also beproblematic. Device beaconing system
is offered in [12];it makes a discovery in the background of
cellular traffic.If the devices are moving, then beaconing design
forhigh-speed moving devices is much complicated. Neigh-bour
discovery in LTE network, where the distributedorthogonal frequency
multiple access (OFDMA) radioresources are used as user identities,
is projected in [13],in which device discovery in high dense areas
is notconsidered. Recommended technique in [14] uses thebase
station for discovery in which signaling flowfrom the base station
can be used for discovery. Inthe large number of devices, the
signaling overheadand discovery interference become problematic.
Bio-inspired and Firefly algorithm used for direct devicediscovery
are advised in [15]. Due to the computa-tional complexity,
probability of misdetection is high.A device discovery scheme based
on clustering hasbeen introduced in [16] for a heterogeneous
network,but the deficiency in the work is the sluggish discov-ery,
and needs some techniques to decide clustering.All the previous
discussions are guided to design anovel algorithm for device
discovery which performwell in all aspects.Therefore, in this
article, the device’s power-based
sphere decipherer discovery scheme is proposed inwhich the
device’s power is incorporated for device dis-covery procedure.
Power efficient, minimum collision,and low signaling overhead
characterized discovery areachieved based on the utilization of a
sphere decoder
like (SDL) algorithm. The primary commitments of thisarticle are
encapsulated as follows:
� We propose a device’s power-based device discoveryto enhance
the power efficiency and minimize thesignaling overhead of typical
D2D discovery.
� We propose disseminated collision fortitude algorithmand
scheme which can take care of the D2Dimpairment like device power
issue happeningduring the discovery phase.
� We evaluate the performance of the proposedalgorithm by fusing
the suppositions in recent LTE-Aspecialized reports [6].
The rest of the paper is organized as follows: Section 2provides
the overview of discovery resources which areused in discovery
procedure, while Section 3 consists ofthe D2D discovery system
model. In Section 4, powerscheme for device discovery is
elaborated, and Section 5contains the results’ analysis. In the
end, the paper isconcluded in Section 6.
2 Resources for device discoveryIn general, devices in D2D
communication may misuseboth downlink and uplink resources for
cellular commu-nication [2]. In this work, we expect that device
discov-ery uses uplink resources based on reusing the
uplinktransmission chain [17] Therefore, to ensure the excel-lent
performance of device discovery, shared radio re-sources are
suggested alternately with dedicated radioresources. Accordingly,
D2D devices, taking an interestin discovery, will choose one radio
resource blocks(RRB) among the intermittent discovery radio
resources.A case of discovery period and RRB is exhibited inFig. 1.
The D2D devices can transmit own discoverysignal on their chosen
RRB one time and tune for re-ception of discovery signals from
other D2D devices.During the discovery period, each D2D device
takesan interest in the discovery procedure only, and othersorts of
communications are not permitted.Each device surveys all RRB’s
received power level and
selects the RRB which has the most reduced power level[18].
Appropriately, numerous devices situated far awaymay pick a similar
resource. On the other hand, everydevice randomly chooses RRB
resources for discoverysignal transmission. We concentrate on a
random choicedue to the human mobility pattern [19]. There are
twoscenarios for device discovery that depend on mobility,haphazard
walk scenarios, and velocity scenarios inwhich discovery is
computed. Haphazard walk modeldoes not much depend on environment
changes, whilemobility depends on context and velocity, which
mightbe unknown or partially known or measurable by somemodels
[20]. The sensing-based determination is wasteful
Hayat et al. EURASIP Journal on Wireless Communications and
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when the sensing outcomes are obsolete rapidly, for ex-ample,
under high-mobility situation. When two or moredevices reuse
similar discovery resources in the vicinity, acollision may happen
because of the asynchronous trans-mission [21]. Accordingly, these
neighboring D2D devicescan neither distinguish each other nor be
recognized be-cause of the mutual interference.
3 D2D device discovery system modelIn this section, we present a
short preface for the D2Ddevice discovery system model. A system
model for de-vice discovery where R is the radius of a sphere made
bythe discoverer device is shown in Fig. 2. In our analysis,we
confine our extension of synchronous D2D devicediscovery, for
example, all D2D devices are in timesynchronization and coverage
area reference can be ac-quired from the base station downlink
transmission.This devours significantly less energy and discovery
timecompared with asynchronous. For synchronous devicediscovery,
each D2D device can be dynamic within a
predefined discovery time, which shows up intermit-tently, such
as D2D device occasionally awakes to ac-complish the discovery
process utilizing the D2D RRB.After finishing the periodic
discovery, D2D devices startdozing until subsequent discovery
period starts. Whena D2D device has discovered a fancied target
D2Ddevice by accepting a signal, it can build up a D2Dinterface for
direct communication. In cellular net-work topology, the
transmission of mobile devices isrelied upon base
station.Appropriately, if various cellular devices have a place
with various cells, reuse a common resource in a celledge, a
cellular device signal interferes with the neigh-boring base
station. Then again, in D2D systems, therecoexist numerous D2D
devices which can be both re-ceiver and transmitter. Under this
topology, radiatedsignals from various transmitting D2D devices
will reachproximal D2D device’s receiver. Note that various
re-ceivers are possibly presented to endure high interfer-ence by
numerous D2D links. Accepting the quantity ofk D2D devices in D2D
systems, the greatest number ofD2D links is k(k − 1), which has a
polynomial ratio [18].
4 Power scheme for discoveryIn the LTE-A, D2D users and cellular
users are multi-plexed at the same uplink channel orthogonal
frequencydivision multiplexing (OFDM) physical RRB. The re-ceived
signal from the k cellular devices or D2D devicescan be modelled as
[22]
yk ¼ αk;kHk;kT kxk þX
j≠kαk; jHk; jT jx j þ nk ð1Þ
αk; j
¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiP
jd
−ρk; jχk; j=Nt
qis a scalar depending upon the
total transmitting power Pj for j user, χk, j is shadowing
fading,and dk, j is the distance between k receivers and j
transmitterswith path loss ρ. xk∈ℂNt�1 normalized data vector with
zero
Fig. 1 RRB for discovery Tdis is the total time for discovery
and T is the distributed time for each device. Legend: receiving
time of reference signal andtransmission time of neighboring
devices
Fig. 2 System model for device discovery where R is the radius
of asphere made by the discoverer device. Legend: D2D signal
andcontrol signal
Hayat et al. EURASIP Journal on Wireless Communications and
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mean and uncorrelated Εðxkx†kÞ ¼ INt . Hk, j implies
(Nr×Nt)channel matrix with Nr which receive antennas andNt which
transmit antennas, and Tk refers to kthuser’s diagonal power
matrix. To keep the total powerconstant, Tk must satisfy the
following condition:
trace T kT†k
� � ¼ XNti¼1 T
i; ið Þk
��� ���2 ¼ Nt ∀ k ð2Þnk is additive white Gaussian noise (AWGN)
with zero
mean and covariance is
Rnk ¼ Ε nkn†k� � ¼ σ2n INr ∀ k ð3Þ
Signal model can be written as
yk ¼ αk;kHk;kT kxk þ zk þ nk ð4Þzk ¼
Pj≠kαk; jHk; jT jx j is the interference matrix for
D2D and cellular users with covariance
Rzk ¼ Ε zkz†k� � ¼ X
j≠kα2k; jHk; jT jT
†jH
†k; j ð5Þ
The power of the j device is
P j ¼ PtH t; jγdrP
j≠kHk; j−
σ2nPj≠kH t; j
ð6Þ
Ht, j is the channel response between a base stationand j
device. Hk, j are channel responses between k de-vices and j
devices. γdr is the discovery signal to interfer-ence noise ratio
(SINR) at the receiver device. Successfuldevice discovery is only
achieved when SINR of de-coding signal is greater than the
threshold value ofSINR γthr ; therefore,
Pt ≥γtrX
j≠k
P JHk; jH t; j
þ σ2n
H t; j
� ð7Þ
From (7), P j≥γthr ð 1βPt−σ2nÞ, where β is the ratio ofH t; jHk;
j
δt ¼ 0 γdr < γ
th
1 γdr ≥γth
ð8Þ
where δt ∈ {0, 1}. If δt = 0 no discovery, δt = 1 device has
beendiscovered and γthr ¼ sIþn in which s, I, and n are the
signalpower, interference, and noise power respectively. From
(1)
yk ¼ Hk; jxk þ nk ð9ÞBy taking the QR decomposition of Hk, j
from (9)
R ¼r11 r12⋯ r1 j0 r22⋯ r2 j⋮ ⋱ ⋮0 ⋯ rjj
2664
3775 ð10Þ
QHyk ¼ Rxk þQHnk
y1y2⋮yk
264
375 ¼
r11 r12⋯ r1 j0 r22⋯ r2 j⋮ ⋱ ⋮0 ⋯ rjj
2664
3775
x1x2⋮xk
264
375þQHnk ð11Þ
The SDL algorithm can reduce the complexity bysearching for the
closest device among the possible lat-tice devices that lie within
a hypersphere of radius Raround the discoverer device x.
Mathematically, the SDLalgorithm solves the problem as:
x̂ ¼ arg y−Hxk k2si∈OM j : y−Hsk k2≤R2
min
ð12Þwhere H∈Rm�n; x∈Rn�1; and ONT show the m-di-mensional
lattice points. O shows the device’s constella-tion. The SDL
algorithm only searches for the maximumlikelihood devices from
among the lattice devices that liewithin a hypersphere of radius R
around the discoveryreceived signal as presented in Fig.
3.Calculating the distance between each lattice device to
the discoverer reduces the exhaustive search. The SDLcan
cleverly find the set of lattice devices within thehypersphere.
This is the simple set of lattice devicesin an interval around the
discoverer. Similarly, if weknow the set of lattice devices in a
k-dimensionalspace that lies within a hypersphere, then the
possiblevalues of the (k + 1)th coordinate for the set of
latticedevices [23]. We can thus recursively find and checkall
lattice devices in the hypersphere. Mathematically,it can be
expressed as:
H ¼ Q�
RN j�N j0 Nk−N jð Þ�N j
�ð13Þ
Fig. 3 Hypersphere of the radius R
Hayat et al. EURASIP Journal on Wireless Communications and
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where the unitary matrix is partitioned as Q = [Q1 Q2]such that
Q1 contains the first NT columns of Q. With alittle manipulation,
it can be shown that the hypersphereconstraint becomes
R2≥ QH1 y|{z}x
−Rx
2
ð14Þ
It also can be written as
R2≥XM j
K¼1 yK−XM j
l¼K rK ;l xl� �2
ð15Þ
where yK, xK, are the kth element of y and x. Also rk, l isthe
(k, l)th element of the upper triangular matrix R. Tosatisfy the
condition in (14), a necessary but not suffi-cient condition is
R2≥ yN j−rN j ;N jxN j
� �2ð16Þ
This implies the following condition on xN j
yN j−R
rN j;N j
& ’≤xN j ≤
yN j þ RrN j;N j
$ %ð17Þ
Likewise, if we define yðMT−1jmT Þ ¼ yMT−1−rMT−1;MT sMT ,we get
the following necessary condition on sMT−1
y N j−1jn jð Þ−RN j−1rN j−1; N j−1
& ’≤xM j ≤
y N j−1jn jð Þ þ RN j−1rN j−1;N j−1
$ %ð18Þ
The SDL algorithm proceeds similarly to obtain thelattice
devices within the hypersphere.
5 Result analysisA simulation setup model [24] is established to
verifythe proposed discovery scheme. A centralized modelwith the
discovery area 500 × 500 m and 50 devices aredeployed randomly
using Poisson point process (PPP) asshown in Fig. 4. Dotted lines
are connected devices,qualified for direct D2D communication and
relay com-munication. RRB selection is performed based on re-ceived
power of discovery resources. These devices senddiscovery signal
through a base station on given RRB todiscover the neighbor
devices. RRBs are not chosen withthe lowest received power which
causes to reduce theprobability of discovery of devices. If the
required de-vice is to be found in its proximal using the
condi-tion (8), then the base station will allow for
D2Dcommunication. Using power conditions, some de-vices may make
D2D LAN via relay devices underthe control link of the base
station.Discovery ratio depends upon the searching power of
each device that lies in the cellular network area as
expressed in (6). Devices in the cell area make
latticestructure, and each device from the lattice has a radiusR.
By the SDL algorithm, the distance of each devicefrom the
discoverer is calculated in lattice devices. QRfactorization helps
to minimize the searching power asexpressed in (18) to find out the
proximal devices. Per-formance of proposed QR factorized lattice
structurebase scheme is shown in Fig. 5, and the results are
com-pared with those of the Gaussian method. In the idealsituation,
minimum discovery cycles discover maximumdevices. In our proposed
model, discovery ratio meetsthe ideal. At five discovery signals,
near about 1000 de-vices have been discovered.Further, we applied
our proposed scheme on central-
ized and distributed system and compared the results.Centralized
and distributed scheme for device discovery
Fig. 4 Randomly deployed devices in a cellular network in500 ×
500 m area
Fig. 5 Performance of proposed QR factorized lattice structure
basescheme. Legend: total result, QR decomposition, and
Gaussianelimination and substitution
Hayat et al. EURASIP Journal on Wireless Communications and
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has been discussed in the Section 1. In the distributedplan, the
main issue is power consumption and signalingoverhead. So, in this
proposed model, these problemshave been overcome as shown in Fig. 6
and 7 respect-ively. Centralized approache is better in-term of
powerconsumption and signaling overhead respectively. In thein-band
cellular network device discovery, a centralizedapproach 0.1 mw
power is consumed on discovery signalwhen 15 devices have been
discovered.When the SDL algorithm with QR factorization is ap-
plied, the signaling overhead significantly decreases asshown in
Fig. 8. Fast device discovery depends upon thenumber of transmitted
discovery signal. If the discoverysignal is significant, then
signaling overhead occurs. Inour proposed method in a centralized
approach, signal-ing overhead decreases. Initially, five devices to
discover
the proximal users need 10 signals, and 10 devices need20
signals; therefore, signaling overhead decrease in acentralized
approach.
6 ConclusionsD2D communication isolates the local cellular
traffic tothe global cellular traffic. Accordingly, device
discoveryis an underlying strategy in D2D communication. In
thisresearch, device’s power-based discovery method isproposed in
the centralized cellular network. This clearapproach for device
discovery enhances the accomplish-ment by alleviating the discovery
issues as fast discovery,minimum signaling overhead, and power
consumption.Our proposed methodology is the QR factorized
latticestructure of devices in a specific area. Discoverer
devicecreates a hypersphere around it and sends a discoverysignal
in the hypersphere using sphere decoder like analgorithm.
Discoverer device visits all the lattice devicesthat lie in the
hypersphere and finds the closest one toinitiate the D2D
communication. Using the hypersphere,the designed discovery scheme
saves the discovery timeand power for searching of unwanted
devices. In future,this plan can be implemented on a distributed
systemand can spare the time by exhaustive search.
AcknowledgementsThe authors would like to express their
gratitude to the Ministry of HigherEducation (MOHE) in Malaysia and
Universiti Teknologi Malaysia (UTM) forproviding the financial
support for this research through the HICOE grant
(R.J130000.7823.4J215). The grant is managed by Research Management
Center(RMC) at UTM.
FundingThe Ministry of Higher Education (MOHE) in Malaysia and
the UniversitiTeknologi Malaysia (UTM) are providing the financial
support for thisresearch through the HICOE grant.
Fig. 6 Power consumption in j devices while power Pj scale is in
nano.Legend: distributed approach and centralized approach
Fig. 7 Signaling overhead for distributed and centralized
approaches.Legend: distributed approach and centralized
approach
Fig. 8 Signaling overhead comparison of different schemes
withproposed scheme. Legend: total result, QR decomposition,
updateand back substitution, and centralized approach
Hayat et al. EURASIP Journal on Wireless Communications and
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Availability of data and materialsMostly, I got the writing
material from different journals as presented in thereferences. A
MATLAB tool has been used to simulate my concept.
Authors’ contributionsOH, an assistant professor at NUML, H-9,
Islamabad, and a student of PhD inWireless Communication Center
(WCC), Faculty of Electrical Engineering,UTM Johor Baharu, Malaysia
under the supervision of associate professor RN,implemented the
idea regarding device discovery. YZ, assistant professor
atDepartment of Information and Communication Engineering, Basrah
Univer-sity College of Science and Technology, Basrah, Iraq, helped
to implementand write this paper. Overall, this paper is built
under the approval andsupervision of RN. All authors read and
approved the final manuscript.
Competing interestsThe authors declare that they have no
competing interests.
Publisher’s NoteSpringer Nature remains neutral with regard to
jurisdictional claims inpublished maps and institutional
affiliations.
Author details1Department of Engineering, National University of
Modern Language(NUML), H-9, Islamabad, Pakistan. 2Wireless
Communication Centre (WCC),Faculty of Electrical Engineering,
Universiti Teknologi Malaysia, 81310 JohorBahru, Malaysia.
3Department of Information and CommunicationEngineering, Basrah
University College of Science and Technology Basrah,Iraq.
Received: 11 September 2017 Accepted: 18 March 2018
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AbstractIntroductionResources for device discoveryD2D device
discovery system modelPower scheme for discoveryResult
analysisConclusionsAcknowledgementsFundingAvailability of data and
materialsAuthors’ contributionsCompeting interestsPublisher’s
NoteAuthor detailsReferences