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Review ArticleA Survey on Radio Resource Allocation for V2X Communication

Ahlem Masmoudi Kais Mnif and Faouzi Zarai

NTSrsquoCOM Research Unit National School of Electronics and Telecommunications University of Sfax Sfax Tunisia

Correspondence should be addressed to Ahlem Masmoudi ahlemmassmoudigmailcom

Received 1 May 2019 Revised 22 September 2019 Accepted 27 September 2019 Published 24 October 2019

Guest Editor Donghyun Kim

Copyright copy 2019 Ahlem Masmoudi et al is is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

anks to the deployment of new techniques to support high data rate high reliability and QoS provision Long-Term Evolution(LTE) can be applied for diverse applications Vehicle-to-everything (V2X) is one of the evolving applications for LTE technologyto improve trac safety to minimize congestion and to ensure comfortable driving which requires stringent reliability andlatency requirements As mentioned in the 3rd Generation Partnership Project (3GPP) LTE-based Device-to-Device (D2D)communication is an enabler for V2X services to meet these requirements erefore radio resource management (RRM) isimportant to eciently allocate resources to V2X communications In this paper we present the V2X communications theirrequirements and services the V2X-based LTE-D2D communication modes and the existing resource allocation algorithms forV2X communications Moreover we classify the existing resource allocation algorithms proposed in the literature and wecompare them according to selected criteria

1 Introduction

Internet ofings (IoT) include billions of intelligent objectswhich are regarded as a part of the future Internet [1 2] IoTis a growing number of things (ie physical objects) that arewirelessly connected to the Internet via smart sensors IoTenables these things to interact and exchange data in anecient way without human intervention e 3rd Gener-ation Partnership Project (3GPP) Long-Term Evolution(LTE) is one of the main strengths of the IoTwhich seeks tocover all the IoT applications Vehicle-to-Everything (V2X)communication is an important main area of IoT Recently3GPP has made Release 14 for LTE-based V2X communi-cation (cellular V2X) in order to improve the safety theeciency and the comfort of intelligent transportationsystems (ITS) e term V2X refers to the vehicle to vehicle(V2V) vehicle to infrastructure (V2I) vehicle to pedestrian(V2P) and vehicle to Network (V2N) communications [3]which require a high reliability and low latency

On the other hand in Release 16 3GPP is working nearthe growth of New Radio (NR) V2X constructing over 5GNR that was standardized in Release 15 of 3GPP NR V2Xshould support advanced V2X services that necessitate much

more stringent QoS assurances compared to services thatmay be supported by C-V2X [4 5] For both evolutionarythe 5G NR and C-V2X are designed to progress lower end-to-end latency and reliability services and to support servicesthat require high throughput But their design methodol-ogies meaningfully vary 3GPP does not carry out a similarconstraint on NR V2X V-UEs equipped with NR V2X caninterconnect with C-V2X devices Nevertheless this will bereached through a dual-radio access systemmdashone radio forNR V2X and another for C-V2X [6]

e proximity service (ProSe) known as a Device-to-Device (D2D) communication decurrenned in Release 12 refersto a direct communication between two or more devices inproximity to each other rather than travelling through theeNodeB [7] erefore several kinds of advantages can beobrvbarered due to the proximity reuse and hop gain D2Dcommunications were initially proposed to improve net-work performance (ie enhancing spectrum utilizationimproving UEs throughput increasing cellular capacity andextending UEs battery lifetime) in cellular technologies [8]

Since V2X technologies have stringent reliability andlatency requirements [9] it was declared in Release 14 thatthe D2D communication can be applied in vehicular

HindawiWireless Communications and Mobile ComputingVolume 2019 Article ID 2430656 12 pageshttpsdoiorg10115520192430656

technologies to support V2V communications As V2X isbased on the D2D communication resources are allocated inthe V-UEs either in the overlay mode or in the underlaymode For that reason radio resource management (RRM)plays an important role in V2X system performances

In this paper we provide a wide review of availableliterature for resource allocation algorithms in V2X servicesbased on D2D communication Moreover we provide acomprehensive comparison and classification of V2X re-source allocation algorithms in terms of numerous aspectse paper is structured as follows e V2X services aredescribed in Section 2 e V2X communication modes andthe LTE-V-based D2D communication are introduced re-spectively in Section 3 and Section 4 A review and clas-sification of the existing resource allocation algorithms forV2X communication are addressed in Section 5 We discussand conclude this paper in Section 6 and Section 7

2 V2X Requirements and Services

3GPP defines 27 use cases for V2X services in Release 14 thatcan be divided into safety and nonsafety V2X services [10]erefore the transmission of V2X messages should beclassified according to the message type (eg safety vsnonsafety) e safety services-related use cases aim to avoidautomobile accidents and to protect the property and lifewhich require high reliability and short delay (eg vehicleplatooning and automated driving) e nonsafety use casesaim to improve the driving experience to be more com-fortable and efficient (eg mobile high data rate enter-tainment and trafficmanagement)erefore the non-safetyand the safety V2X services have different latency and packetsize requirements [11]

Five categories of service requirements of this use casesare defined as follows [9 10]

(i) Speed the maximum absolute velocity 160 kmhand the maximum relative velocity 280 kmh shallbe supported e maximum relative speed of500 kmh is supported for the possible scenariowithout speed limitation

(ii) Communication range the effective distance islarger than the distance calculated as the ampleresponse time (eg 4 seconds) for the drivers toavoid collision according maximum relativespeed

(iii) Latencyreliability the maximum end-to-end la-tency between two UEs supporting V2VV2PV2Iapplications shall be 100ms e minimum radiolayer reliability should be supported withoutretransmissions of application-layer messages in theeffective distance and the restricted latency

(iv) Message size the variable length of a periodicallymessage between two UEs supporting V2X appli-cations is about 50ndash300 bytes e message size ofevent-triggered messages can be up to 1200 bytes

(v) Message generation period the minimum messagegeneration period can be 100ms

21 Safety-Critical V2X Services e safety-critical V2Xservices aim to reduce the potential accident and the riskto pedestrians and to deteriorate the possibility of lifedead for V-UEs e information shared between pe-destrians Road Side Unit (RSU) and vehicles (ie ve-hicle speed position and distance) is usually shortbroadcast messages which impose stringent requirementson latency packet loss and reliability Two types of safetyV2X transmissions messages have been standardized theperiodic transmission and event-triggered transmissione periodic transmissions among V2V-UEs (eg thecooperative awareness messages (CAMs) are shortbroadcast messages periodically transmitting aware in-formation of position presence speed and directionsamong vehicles and their neighbors e event-triggeredtransmission among V2X-UEs (ie decentralized envi-ronmental notification messages (DENMs)) is shortbroadcast messages to alert road users about road statusBoth periodic transmission and event-triggered trans-mission can be operated over the LTE-Uu and the PC5interfaces [12]

22 Nonsafety V2X Services e nonsafety V2X servicesessentially focus on management application control con-gestion traffic efficiency and entertainment these servicesenable more comfortable and efficient driving experienceNonsafety V2X applications aim to improve traffic co-ordination assistance and vehicle traffic flow In additionthey also provide entertainment video maps and updatedlocal information erefore a large amount of V-UEssensed data sent to neighbors or to infrastructure eseservices have no strict requirements on reliability andlatency

23 V2X Requirements

231 Reliability Requirement e reliability requirementdefined in different works is generally interpreted fromeither the outage probability (OP) or the packet receptionratio (PRR)

e PRR is the ratio of successful reception among thetotal number of the vehicle transmitter neighbors which arecalculated as follows

PRRu(t) 1

Nu(t)1113944

Nu(t)

j11 c

(u)j (t)ge cth1113966 1113967

c(u)j (t) 1113944

NRB

k1

suk(t)Pu(t) Hk

uj(t)11138681113868111386811138681113868

111386811138681113868111386811138682

σ2 + 1113936NL

m1sum(t) Pj(t) Hk

m(t)1113868111386811138681113868

11138681113868111386811138682

(1)

where Nu(t) denotes the number of the vehicles neighborsof the uth vehicle at time t c

(u)j (t) is the receiving signal-

to-interference-plus-noise ratio (SINR) of the jth vehicleamong Nu(t) cth is the SINR threshold Pu(t) is thetransmit power of uth vehicle σ2 is the power of additivewhite Gaussian noise NL is the number of interfering

2 Wireless Communications and Mobile Computing

vehicles suk(t) is the RBs allocation at time t and

suk(t)

1 if kth RB is allocated to user u at time t

0 otherwise1113896

e OP is the most utilized which is the probability thatNu error-free bits cannot be sent by any coding patternwhich is computed as follows

poutu ≜ Pr 1113944

Eallu

i1ρ log 1 + ci( 1113857ltNu

⎧⎪⎨

⎪⎩

⎫⎪⎬

⎪⎭ (2)

where Eallu is the RBs number that are allocated to the uth

V-UE ρ is the number of complex symbols in the RB andci is the SINR of the ith RB

232 Latency Requirement e latency requirement insome studies is interpreted by the latency constraint thatallows V-UEs to allocate their required RBs before themaximum tolerable latency according to scheduling timeunit number Most of the studies designate that C-V2X cansupport safety services reliably that required an end-to-endlatency of nearby 100milliseconds (msec)

3 V2X Communication Modes

To support both safetynonsafety V2X applications the3GPP standard provides two radio interfaces for LTE-Ve-hicle (LTE-V) [13 14] the Uu cellular interface that sup-ports V2I communications (eg enhanced MultimediaBroadcast Multicast Service (eMBMS) and the PC5 interface(direct LTE sidelink) that supports V2V communications asshown in Figure 1

31 LTE-Cellular Communication Mode Using Uu InterfaceLTE-Cellular communication refers to the communicationmode between V-UEs and the eNB which is suitable fornondelay tolerant use cases (eg mobility services andsituational awareness) using the LTE technologies e eNBreceives unicast messages from V-UEs and rebroadcaststhem for all V-UEs receivers in the pertinent area usingeMBMS Based on coordination between multiple cellsMBMS aims to reduce the latency and to improve theperformance of the cell edge

32 LTE-D2D Communication Mode Using PC5 InterfaceLTE-D2D communication refers to the communicationmode between two V-UEs in proximity to each otherbypassing the eNB is mode is appropriate for V2V safetyservices that require low latency delay (eg advanced driver-assistance systems (ADAS) is communication mode isbased on Release 12 proximity services (ProSe) which exploitdirect communication between neighboring devices Twotransmission modes are introduced in Release 12 (mode 1and mode 2) for LTE sidelink (or D2D communication)public safety ese modes are designed in order to prolongthe devicesrsquo battery lifetime at the cost of increasing thelatency erefore mode 1 and mode 2 are not convenientfor V2X applications since connected vehicles require low

latent and highly reliable V2X communications Recentlytwo new sidelink communication modes are introduced inRelease 14 which are typically intended for V2V commu-nications the mode 3 and the mode 4 In mode 3 the radioresources used by the direct V2V communications and theinterference management are managed and assisted by thecellular infrastructure (eg eNB) However vehicles au-tonomously select and assign the radio resources in mode 4for their direct V2V communications without infrastructureassistance (ie this mode can be operated out of cellularcoverage)

In this paper we investigate the radio resource allocationin mode 3 for the V2X services based on D2D communi-cation in LTE cellular network

4 LTE-V-Based D2D Communication

Since there is a similarity between the localized nature ofV2V and D2D communications it is mentioned in Release14 that the D2D communication can be useful in vehicularnetworks e V2VD2D communication can allocate thecellular resources in orthogonal or nonorthogonal way

41 V2V-Based D2D Communication Modes ere are twoV2V communication modes the overlay mode (which is theorthogonal resource allocation) and the underlay mode(which is the nonorthogonal one) as shown in Figure 2

In the overlay mode specific radio resources from cel-lular resources are dedicated to the D2DV2V communi-cation us the C-UEs cannot achieve the full capacity ofthe eNB consequently this mode decreases the spectrumutilization e advantage of the overlay mode is that theinterference between C-UEs and V2V-UEs does not need tobe managed

In the underlay mode the eNB allows V2V-UEs andC-UEs to share the same radio resources which can achievea greatest spectrum efficiency However the eNB needs tomanage the strong interference among V2V-UEs commu-nications and the C-UEs communications

Backhaul

LTE-C linkLTE-D link

eNB

C-UE

V-UE

V-UE

V-UE PC5

Uu

Uu

Figure 1 Radio interfaces for V2X communications

Wireless Communications and Mobile Computing 3

Both of the overlay and the underlay modes can utilizeeither the Downlink (DL) or the Uplink (UL) subframe eset of resources that will be allocated to V2V communicationare chosen from the UL subframe owing to their minorpeak-to-average power ratio (PAPR) and because it is lessutilized than the DL subframe

42 Nonorthogonality among V-UEs Orthogonal multipleaccess (OMA) techniques are established by all of the currentcellular mobile networks (ie LTE LTE-A) such as or-thogonal frequency division multiple access (OFDMA) andtime-division multiple access (TDMA) where a single usercan be served in each orthogonal resource block (RB) inOFDMA subcarriers Nevertheless these techniques cannotmeet the great demands of the future radio access networks[15] erefore the nonorthogonal multiple access (NOMA)is suggested as a candidate for 5G cellular mobile systemswhich becomes a significant principle for the 5G radio accesstechniques [16] NOMA can be deployed in the future andthe existing mobile systems due to its compatibility withother technologies Unlike OMA and without needing anymodifications to the LTE RBs NOMA can serve multipleusers on the same RB (in the same frequency and timedomain) as shown in Figure 3erefore the NOMA systemthroughput can be expressively greater than that of theOMA e NOMA technique is also applied to cellularvehicular network in order to achieve low latency and highreliability and to reduce resource collision [17]

5 RRM for V2X Services over LTE

RRM in LTE includes a diversity of techniques and pro-cedures such as radio resource allocation and packetscheduling Nowadays resource allocation in LTE-V is oneof the most discussed topics e V-UEs can communicateusing either direct link or cellular link ey can also operateeither in the underlay or in the overlay modes e majorityof existing related works suggest using the cellular spectrumfor both V-UEs and C-UEs Since in the overlay mode a setof RBs are dedicated to V-UEs using the direct link theCUEs cannot achieve the full spectrum capacity ereforestudies based on the overlay mode aim to avoid the waste ofresources On the other hand C-UEs and V-UEs share thesame RBs in the underlay mode which reach a best spectrumefficiency but the huge interference could occur amongC-UEs and V-UEs Several V2X resource allocation algo-rithms have been investigated in the literature e majority

of these algorithms underlaying C-UEs need to deal in-terferences among C-UEs and V-UEs In this section wedemonstrate an overview classification on V2X resourceallocation algorithm existing in the literature as shown inFigure 4

en we provide a comprehensive classification andcomparison of the V2X resource allocation algorithmsexisting in the literature in terms of numerous aspects (egcommunication mode and allocation process) Moreoverwe study the existing effort in LTE-V2X resource allocationalgorithms in-band communication over the underlay modeand the overlay mode where the allocation of RBs is done bythe eNB (mode 3)

51 Underlaying Resource Allocation in V2X ServicesEarly-proposed V2X radio resource allocation algorithmsin LTE-V environments suggest reusing cellular spectrumfor V2X communications Nowadays the majority ofexisting resource allocation work is dedicated to theunderlaying V2X communications in cellular networksese works typically study the interference problemsbetween V-UEs and C-UEs due to RBs shared betweenthem e existing resources allocation algorithmsdesigned in the underlay mode can be categorizedaccording to several criteria We classify these algorithmsaccording to RBs sharing process the RBs sharing basedon user pairing user clusteringgrouping and user geo-graphic location

511 RBs Sharing-Based User Pairing Most of the un-derlaying resource allocation algorithms allow UEs to sharethe same RBs based on user pairing where the eNB finds theoptimal combination between at least two UEs to share thesame RB e main objective is to allow at least one V-UEusing direct link to share the same RB with only one C-UE orwith only one V-UE using cellular link e comparison ofthese algorithms is summarized in Table 1

In [18] Zhang et al proposed a novel resource sharingof the underlaying communication mode for vehicularnetworks which aims to increase throughput of the ve-hicular network through efficient interference manage-ment protocols Different V2I and V2V communicationlinks are allowed to access the same resources for theirdata transmission e resource-sharing problem wasformulated as a resource allocation optimization problem

Cellular spectrum Cellular spectrum

D2DV2V

Cellular Cellular

V2V V2V

Underlay Overlay

Figure 2 Underlay vs overlay modes

NOMA

OFDMA

UE1 UE2

f

f

Figure 3 Difference between OMA and NOMA


Resource allocation inV2X services-based D2D

Underlayingcellular user

Overlayingcellular user

RBs sharing-based userpairing

RBs sharing-based userclusteringgrouping

RBs sharing-based usergeographic location

Figure 4 Resources allocation in V2X services classification

Table 1 Comparison of the existing underlaying RBs sharing-based user pairing V2X services

Ref Unicastbroadcast Objectives Scenarios User types Allocation

constraints

Powercontrolallocation

Allocationprocess Methodstheory RB

sharing

[18] Broadcast Increasethroughput Road V2V-UEs

V2I-UEs PF mdashOrthogonal RBsare allocated toeach user type

Graph theory 1 V2V-UE1 V2I-UE

[19] Unicast

Maximize sumrate fairnessminimizelatencyreliability

Urban C-UEsV-UEs

OPSINRLatency

PCOrthogonal RBsare allocated toeach user type

An interior pointmethod

Hungarian algorithm

1 C-UE1 V-UE

[20] Unicast


Urban C-UEsV-UEs

OPSINRLatency

PAOrthogonal RBsare allocated toeach user type

KarushndashKuhnndashTuckertheory

Dual decompositionmethod

Hungarian algorithm

1 C-UE1 V-UE

[21] Unicast


Urban C-UEsV-UEs

OPSINRLatency

PA

Orthogonal RBsare allocated to

C-UEsnonorthogonal

RBs areallocated to V-

UEs

PerronndashFrobeniustheory

Interior point method

1 C-UEN V-UEs

[22] Unicast


Urban C-UEsV-UEs

OPSINRLatency

PA


C-UEsnonorthogonal


UEs

Matching theoryInterior point method

1 C-UEN V-UEs

[23] Broadcast

Maximize thenumber ofconcurrent

V2Vtransmissions

Urbanfreeway V-UEs SINR mdash

NonorthogonalRBs are

allocated to V-UEs

PerronndashFrobeniustheory N V-UEs

[24] Unicast

Maximizethroughputminimizelatency

Urban

C-UEsSafety andnonsafetyV-UEs

SINRLatency mdash

Orthogonal RBsare allocated toeach user type

Hypergraph matchingtheory

1 C-UE1 safetyV-UE1

nonsafetyV-UE

[25] UnicastMaximizethroughputreliability

Multilanefreeway

V2V-UEsV2I-UEs OP PA


Hungarian method 1 V2V-UE1 V2I-UE


taking into account the interference between diversecommunication links e resource-sharing problem hasbeen solved using the graph theory that develops twointerference graph-based resource-sharing schemes theinterference-aware and the interference-classified graph-based resource-sharing scheme

e authors in [19ndash22] proposed a radio resources andpower allocation algorithm for safety-critical vehicularcommunications is algorithm aims to maximize theC-UE sum rate with proportional bandwidth fairness underthe constraint of satisfying the V-UEsrsquo requirements onlatency and reliability First they mathematically formulate

Table 1 Continued


constraints



sharing

[26] Unicast

Reliabilitymaximize the

ergodiccapacity

Multi-lane

freeway




[27] Broadcast

Maximize theC-UEs

informationrate guaranteereliabilitylatency

requirement ofV-UEs

Urban C-UEsV-UEs

LatencyOPSINR


Lagrange dualdecomposition methodBinary search methodSubgradient iteration

method

1 C-UE1 V-UE

[28] Unicast

Maximizethroughput (C-UEsnonsafety

V-UEs)guarantee QoSdemand (W-UEssafety V-

UEs)

Freeway

W-UEsC-UEs

Safety andnonsafetyV-UEs

SINR mdashOrthogonal RBsare allocated toeach user type

KuhnndashMunkresalgorithm

GalendashShapleyalgorithm

1 C-UE1

nonsafetyV-UE

[29] Unicast

Maximize thetotal

throughput forC-UEs and V-

UEs

Freeway

W-UEsC-UEs




KuhnndashMunkresmethod

1 C-UE1

nonsafetyV-UE

[30] Unicast

Maximize V2I-UEs sum rateguaranteeV2V-UEsreliability

requirement

Freeway V2I-UEsV2V-UEs

SINRBuffer sizePacketdelay

mdashOrthogonal RBsare allocated toeach user type

mdash 1 V2I-UE1 V2V-UE

[31] Unicast


requirement





[32] Unicast

Maximize C-UEs sum rateguarantee V-UEs reliabilityrequirement

Freeway

GBR C-UEs

NGBR C-UEs

V-UEs

PDRSINR

Buffer sizePacketdelay


mdash 1 C-UE1 V-UE

[33] Unicast

Maximize sumrate andrespect

constraintdelay of C-

UEs guaranteeV-UEs

reliability andlatency

Freeway

C-UEsSafety V-

UENonsafetyV-UE

PDORSINRDelay


mdash

1 C-UE1 safety V-

UE1

nonsafetyV-UE


the requirement of V2X communication into optimizationconstraints that compute with only slowly varying CSIen they propose a RRM to decide which users can sharethe same RB

In [19] a two-step resources allocation algorithm wasinvestigated Firstly resources are allocated to both C-UEsand V-UEs in an optimal way by allowing equal powerallocation To communicate with the eNB and amongV-UEs orthogonal RBs are used by C-UEs and V-UEsrespectively So both V-UE and C-UE can use the same RBthat will produce intracell interference among each other Bytransforming the problem of RB allocation into a maximumweight matching (MWM) problem for bipartite graphs theinterference will be resolved Secondly the transmit power isoptimally adjusted for each C-UE and V-UE In [20] theC-UEs sum rate maximized as much as possible and theV-UEs transmit power is minimized

In [21] a heuristic radio resources allocation scheme wasdesigned considering the fast fading effects in order tosupport a significantly higher number of V-UEs by allowingnonorthogonality among V-UEs Resource sharing can takeplace not only between vehicles and cellular users but alsoamong different vehicles on condition that the SINR con-straints of V-UEs and the best rate of C-UEs are satisfied Todo this they will first introduce the underlaying mode usingthe PerronndashFrobenius theory to design an RB sharingmetric Second they propose a heuristic RB sharing schemethat associates in a sequential fashion each V-UE with aC-UE Finally the power is allocated based on the RB al-location en they extend in [22] to improve more strictlatency and reliability requirement designed based onmatching theory in order to obtain higher performanceespecially for high load scenario

In [23] a radio resource allocation algorithm based onRBs sharing was proposed in order to maximize the con-current V2V transmissions number unlike other authorswho maximize the sum rate where one RB can be shared bymultiple V-UEs by allowing nonorthogonal access amongthem Firstly the reliability requirement is transformed intoconstraint of spectral radios matrix to limit the interferenceamong V-UEs Secondly they mathematically formulate theRB sharing problem that maximizing the number of V-UEswhich is equivalent to minimize the occupied RBs numberTo better improve the spectrum efficiency they use thespectral radius estimation theory

In [24] Wei et al proposed a 3D-matching-based radioresources allocation algorithm for V2X communicationeobjective is to maximize the total throughput of nonsafetyV-UEs on condition of satisfying the SINR requirements onC-UEs and on safety V-UEs ey proposed three stages toallow these UEs to share the same RB on condition that oneRB cannot be shared by more than one UE in the same typeIn the first stage they obtain the data rate for each nonsafetyV-UE in all possible combinations for each RB In the secondstage they construct the hypergraph model that representsall the combinations of these users to find the set of thelargest sum weight of hyperedge obtained from the firststage en in the third stage the resources allocationmatrix was founded based on k-claw

In [25] the authors proposed a robust radio resource andpower allocation scheme for V2X communication in orderto maximize the sum throughput of all V2I links whileguaranteeing the reliability of each V2V link A low-com-plexity algorithm was designed to find the optimal strategyof spectrum sharing among V2V and V2I links whileadjusting their transmit powers Firstly they mathematicallyformulate the optimized problem to meet the V2V and V2Irequirements where one V2I-UE shares spectrum with oneV2V-UE Secondly a theorem is described in order to obtainthe optimal power allocation that maximizes the capacity forV2I-UEs when it shares RB with V2V-UEs while guaran-teeing the minimum capacity requirement of V2I en theHungarian method is used to find the optimal resourcesreuses

In [26] Liang et al proposed a spectrum sharing re-sources and power allocation algorithm based only onslowly varying large-scale fading information of wirelesschannels over the fast fading e algorithm objective is tomaximize the V2I-UE ergodic capacity while guaranteeingthe reliability requirement for each V2V-UEs is algo-rithm was proposed to support both types of vehicularconnections ie V2I and V2V links where the resourcesharing happens between V2V-UEs and V2I-UEs Firsteach V2V-UE is paired with each corresponding V2I-UEthat satisfies the minimum capacity requirement en theoptimal spectrum sharing is found between the V2V-UEsand V2I-UEs sets by constructing a bipartite graph usingthe Hungarian method

In [27] Mei et al investigated a power and resourceallocation scheme to jointly optimize the V2V communi-cations is scheme aims at maximizing the C-UEs in-formation rate and at guaranteeing the reliability and thelatency requirements of V-UEs e latency packets areconsidered as the most important requirement rather thanthe data rate Firstly they mathematically formulate the end-to-end latency packets and transform it into data rateconstraint To guarantee this requirement a minimumamount of RBs must be assigned to each V-UE en theLagrange dual decomposition method is applied to find theoptimal solution of RBs sharing where at most one V-UE canshare the RB that is assigned to C-UE

In [28] Wei et al proposed a joint resource sharingpower control and resource allocation for V2X communi-cation over unlicensed spectrum aiming at guaranteeing faircoexistence among C-UEs WiFi-UEs and V-UEse latteris classified into nonsafety and safety V-UEs e safetyV-UEs require high reliable services in terms of latency andrate so they are allowed to use the licensed spectrum In caseof licensed spectrum shortage they can use the unlicensedspectrum whereas the nonsafety V-UEs can select to useunlicensed spectrum over Content-Free Period (CFP) LTE-U or CP-based WiFi modes erefore a low complexityscheme is designed in order to maximize the totalthroughput for nonsafety V-UEs and C-UEs

In [29] the authors proposed a joint resource sharingand power allocation scheme for heterogeneous vehicularenvironment over LTE-U is scheme aims at maximizingthe total throughput for C-UEs andV-UEs where V-UEs are


categorized into nonsafety and safety V-UEs e safetyV-UEs are allowed to allocate orthogonal RB from the li-censed spectrum without sharing with C-UEs in order toguarantee the safety V-UEs reliability However the non-safety V-UEs can allocate RB into two modes With slowvehicle speed the nonsafety V-UEs compete RBwithW-UEsfrom unlicensed spectrum during the CP interval With highvehicle speed the nonsafety V-UEs use the reserved Con-tent-Free Period (CFP) based on LTE-U

In our previous work [30] radio resource managementwas investigated for V-UEs where both V2V and V2Icommunication exist A resource allocation algorithm isproposed aiming at promising the V2V-UEs reliability re-quirement and at maximizing the V2I-UEs sum rate FirstlyV-UEs are separated into two user types the V2V-UEs andthe V2I-UEs which are sorted in the TD scheduleraccording to its corresponding metric en in the FDscheduler RBs are allocated to V2I-UEs by maximizing theirsum rate and to V2V-UEs by ensuring their SINR constraintin condition that at most one V-UEs from each category canshare the same resources In [31] we add a power controlmechanism tominimize the interference caused by the V2V-UEs when sharing RBs with V2I-UEs erefore not onlythe SINR constraint is considered but also the V2V-UEspower is controlled

In [32] we designed an efficient scheduling and re-sources allocation scheme for both V-UEs and C-UEscommunications in order to improve C-UEs sum rate andrespecting V-UEs latency constraint and C-UEs Packet DropRate (PDR) constraint We classify users into three classesthe V-UEs class the GBR C-UEs class and the NGBR C-UEsclass Firstly all classesrsquo packets are prioritized according totheir QoS requirement Secondly based on the PDR ratioresources are dynamically adjusted for GBR and NGBRC-UEs en resources that already allocated to C-UEs arereused by the V-UEs

In [33] we proposed a mixed resource allocation andtraffic sharing among C-UEs nonsafety V-UEs and safetyV-UEs in order to promise the reliability and latency re-quirements e main goal of our proposed is to regard thesafety V-UEs and the C-UEs delay constraint and the SINRof all users while maximizing the C-UEs sum rate Afterallocating RBs to C-UEs resources are reused by the non-safety and safety V-UEs where at most one RB can be sharedby three users from different classes taking into consider-ation each class requirements

512 RBs Sharing-Based User ClusteringGrouping In thissection we investigate the underlaying resource allocationallowing V-UEs to share the same RBs based on usergroupingclustering e comparison of these algorithms issummarized in Table 2

In [34] a novel proximity-aware resource allocation-based QoS was designed for V2V-UEs in order to reduce thetotal power transmission considering the reliability and thequeuing latency requirements e authors exploited thespatial-temporal aspects of V-UEs based on their physicalproximity and traffic demands First of all clustering

mechanism is demonstrated to gather V-UEs into severalzones based on their physical proximity erefore dedi-cated RBs are allocated to each zone based on their trafficdemands and QoS requirements Secondly within eachzone a power minimization solution based on the leveragingLyapunov optimization techniques is proposed for eachV2V-UE pair

In [35] the authors proposed a graph-based resourceallocation algorithm for broadcast V2V communicationsaiming at maximizing the sum-rate capacity of the systemMany broadcast communication clusters are gatheredWithin any cluster V-UEs should transmit in orthogonalRBs to avoid conflicts but they cannot receive and transmitsimultaneously To prevent conflicts resources should beallocated in different subframes However V-UEs in dif-ferent clusters can share the same RBs erefore they in-troduce a bipartite graph-based solution aiming to assignevery V-UE with a RB that attains the maximum sum rate

In [36] the authors proposed a hybrid-scheduling al-gorithm for geographical zone aiming at maximizing thesum rate of the transmitting V-UEs while taking into ac-count the reliability for all receiving V-UEs ey mathe-matically model their objective function problem to meeteach V-UEs service requirements and to resolve it byadopting the greedy algorithm Firstly a hybrid scheduling isapplied to allocate resource for V-UEs e V-UEs in eachgeographical zone are gathered into groups based on theirgeographical locations Secondly the reuse patterns aredefined where resources are reused in each reuse patternen specific RBs are allocated to V-UEs in each zone andthey will be reused in each reuse pattern

In [37] Liang et al studied and presented a graph-basedresource allocation for V2V-UEs-based direct link and V2I-UEs-based cellular link to improve the sum V2I-UEs and toguarantee theV2V-UEs reliability Firstly they mathemati-cally model the resource and the power allocation problemthat meets the QoS requirements for V2I-UEs and V2V-UEs Secondly a graph partitioning algorithm is exploited toaddress this problemwhich can be converted into a weighted3-dimensional matching problem e main objective is togather V2V-UEs into many clusters based on their mutualinterferences en all V2V-UEs belonging to the samecluster are allowed to share the same RBs with the corre-sponding V2I-UEs whereas V2V-UEs in different clustersare not allowed to share the same RBs

513 RBs Sharing-Based User Geographic Location In thissection we investigate the underlaying resource allocationalgorithms that allow V-UEs to share the same RBs based onuser geographic location e comparison of these algo-rithms is summarized in Table 3

In [38] Yang et al proposed a two-stage resourceallocation in a dense urban in order to satisfy the data rateand the reliability requirements for both nondelay sen-sitive services and delay-sensitive services while mini-mizing the delay-sensitive services latency e delay-sensitive V-UEs utilize LTE-based D2D link whereas thenondelay-sensitive V-UEs can utilize LTE-C link e


intersection is split into four subregions in order to reducethe complexity In the first stage for each subregionresources are allocated based on the Traffic Density In-formation (TDI) where orthogonal resources are allo-cated in different subregions In the second stage based onthe ChannelQueue State Information (CSIQSI) reusableresources are used among subregions

In [39] a dynamic resource allocation in V2V com-munications is proposed with proximity awareness isproposed algorithm aims to minimize the total network costand to maintain successful transmissions while satisfying theQoS requirements for V-UEs e total network cost is

calculated according to traffic load and successful trans-mission First they proposed a dynamic clustering scheme togroup the V-UE pairs with similar characteristics into sets ofzones based on traffic load andmutual interference using theHarendashNiemeyer method to calculate the set of V-UEs in eachzone where V-UEs can reuse resources in each zone whilesimultaneously satisfying their QoS Each zone has a dy-namic size and changes over time according to the trafficload and proximity information en a novel intrazonecoordination mechanism is described based on a matchinggame in order to allocate resources among V-UEs in eachzone

Table 2 Comparison of the existing underlaying RBs sharing based-user clusteringgrouping in V2X services

Ref Unicastbroadcast Objectives Scenarios User

typesAllocationconstraints


Allocation process Methodstheory RBsharing

[34] Unicast

Minimize the totalpower

transmission andlatency reliability

Urban V-UEs Queuelength PA

NonorthogonalRBs are allocatedfor V2V-UEs indifferent clusters


NV2V-UEs

[35] BroadcastMaximizing thesum rate capacityof the system

mdash V-UEs Capacity mdash

NonorthogonalRBs are allocated touser in different

clusters


N V-UEs

[36] Broadcast

Maximize the sumrate of the tr V-UEs reliability for

rx V-UEs

Highway V2V-UEs OP mdash

Orthogonal RBsare allocated in

each zoneNonorthogonal

RBs are allocated indifferent zones

Greedy algorithmN

V2V-UEs

[37] UnicastMaximize the sumV2I reliability of

V2V

Multilanefreeway

V2V-UEsV2I-UEs

OP PA

NonorthogonalRBs are allocated toV2V-UEs in thesame cluster

Orthogonal RB isallocated to V2I-

UEs

Graph theory

1 V2I-UEsN

V2V-UEs

Table 3 Comparison of the existing underlaying resource allocation in V2X services


constraints



sharing

[38] Broadcast

Minimize thedelay andreliabilit

Maximize datarate

Dense urbanIntersection

V-UEs(nondelay-and delay-sensitive)

Avg QueLeng PRR mdash


Traffic flowtheory

1nondelay-sensitive1 delay-sensitive

[39] Unicast Minimizenetwork cost Freewayurban V-UEs SINR mdash


allocated to V-UEs

HarendashNiemeyermethod

Matching theoryN V-UEs

[40] Unicast

Reduce thesignaling

overhead andinterference

Urban C-UEsV-UEs SINR mdash


mdash 1 C-UE1 V-UE

[41] Unicast

Reduce thesignaling


Urban C-UEsV-UEs SINR PC


Graph theory 1 C-UE1 V-UE


In [40] Botsov et al designed a centralized sched-uling mechanism based on the position of the vehicleswithin a single cell ey aim to guarantee continuoustransmission for V2V link while reducing the in-terference and the signaling overhead within the primarynetwork and to satisfy the V2V safety services re-quirements e principle is to divide the cell coverageinto several zones and a set of RBs were assigned to eachzone and is dedicated for D2D communication esesets of RBs are reused by C-UEs while maintaining aminimum distance zone and are chosen according to RBavailability and data rate requirements of the V2V ser-vice en they extended to cover multicellular de-ployments in [41] e zone layout and RB sets are thenfixed and do not change over time

52 Overlaying Resource Allocation in V2X ServicesDifferent from the underlaying resource allocation algo-rithms studied in the previous section the authors in[42ndash45] proposed to dedicate specific resources for V2Vcommunications ese proposed resources remove theconcerns of interference among V-UEs and C-UEs com-munications and on the other hand decrease the totalachievable resources for cellular communications and ac-cordingly lead in resources starvation e comparison ofthe overlaying V2X resource allocation algorithms is sum-marized in Table 4

In [42] Zhang et al proposed two resource allocationschemes based on V-UEs locations for V2V broadcastservices in order to improve RBs utilization and trans-mission precision in an efficient way and to minimize thetime delay e first scheme is the centralized schedulerwhere RBs are allocated to V-UEs in orthogonal way to avoidthe cofrequency interference ese RBs are reused incondition that the V-UEs distance is less than resource reusedistance e distributed scheduler is the second one wherethe highway is divided into many areas and RBs are gatheredinto groups in order to allow V-UEs to select RBs from aspecific group in each area

In [43] Kim et al proposed a resource allocation schemebased on vehicle direction position speed and density forV2V communication is scheme includes two resourceallocation strategies according to vehicle location thefreeway case and the urban case A specific resources pool isassigned for each geometric area For the urban case highvehicle density occurs in the intersection region so a specialresource was allocated in this region based on traffic densityFor the freeway case resources are allocated based on vehicledirection and position Each zone of the freeway has aspecific resources pool and when a vehicle enters a zone itmust allocate resources of this zone

In [44] 80211p technology andC-V2X communicationwereinvestigated in a hybrid resource allocation aiming to improve thereliability ofV-UEs and tominimize the total latency Either using80211p orC-V2X interface aV-UE can transmit packets thatwillimprove the reliability If the eNB requests aD2D link V-UEs cantransmit using C-V2X interface if not they will use the 80211pinterface In order to improve the latency performance a set ofRBs periodically are assigned for V-UEs based D2D link

In our previous work [45] a swarm intelligence resourceallocation algorithm is proposed in order to improve networksum rate while satisfying the QoS requirements for bothV-UEs and C-UEs Firstly we mathematically express theoutage probability as the requirement of the V-UEs and theuser fairness index as the requirement of the C-UEs Secondlywe adaptively (each TTI) assign a set of RBs to the V-UEs andC-UEs where orthogonal RBs are allocated among themen an ant colony optimization (ACO) mechanism isadopted to the resources allocation algorithm to reduce thecomplexity and to getting a satisfactory performance

6 Discussion

It seems that the V2X resource allocation based-D2Dcommunication algorithms underlaying C-UEs is morepopular than the overlaying one Most of the existing workswere proposed in the underlay mode which are typicallydesigned to avoid the interference problems However

Table 4 Comparison of the existing overlaying resource allocation in V2X services


constraints Allocation process Methodstheory RBsharing

[42] BroadcastImprove resource

utilizationefficiency

Highway V-UEs Reusedistance

Orthogonal resource isallocated to users whoserelative distance is lessthan resource reuse

distance

mdash N V-UEs

[43] mdash mdash Urbanfreeway

Periodictraffic of V-

UEsmdash Orthogonal RB are

allocated for each user mdash 1 V-UEs

[44] Unicast Minimize the totallatency

Multilanehighway V2I-UEs SINR

Orthogonal RBs areallocated to each V-UEs

using D2Dcommunication over C-

V2X or 80211p

Greedy algorithm 1 V2I-UE

[45] Unicast Improve networksum rate Freeway C-UEs

V-UEs

FairnessindexOP

Orthogonal RBs areallocated to C-UEs and V-

UEs

Ant colonyoptimizationmechanism

1 V-UEor 1 C-UE


allocating dedicated RBs to V-UEs is not efficient in terms ofspectral efficiency compared to the RBs sharing (underlaymode) e latter increases the spectral efficiency whereasRBs might be wasted in the overlay mode In terms ofspectrum sharing RBs are shared between one C-UE (orV2I-UEs) and at least one V-UE or between more than twoV-UEs erefore in the existing resources allocation forV2X based-D2D nonorthogonal resources are allocated toV-UEs using direct link (V2V-UEs) whereas orthogonalresources are allocated to C-UEs (or V-UEs using direct link(V2I-UEs))

e focus of the proposed V2X resource allocation al-gorithms aims to maximize the number of V2V-UEs thatshare the same RB with only one C-UE or with only one V2I-UE en allocating nonorthogonal resources to C-UEs (orV2I-UEs) can increase the spectral efficiency ereforeallocating nonorthogonal access to C-UEs (or V2I-UEs) andnonorthogonal access to V2V-UEs to share the same RB willbe more challenging

7 Conclusion

LTE-D2D is a promising candidate for V2X services whichcan meet the V2X requirements in terms of latency andreliability Under LTE-D2D in-band communicationV-UEs can reuse the cellular resources in the underlay modeor in the overlay mode Hence it is essential to design aresource allocation algorithm in a way that V-UEs do notaffect the C-UEs V-UEs can communicate using the directlink and share resources with the C-UEs (or V2I-UEs-basedcellular link) which may affect the cellular network per-formance Consequently the interference should be man-aged by resource allocation and power controlallocationalgorithms In this paper we provide a classification and acomparison of the recent existing resource allocation al-gorithms for V2X communications

Conflicts of Interest

e authors declare that they have no conflicts of interest

References

[1] J Cao M Ma H Li Y Zhang and Z Luo ldquoA survey onsecurity aspects for LTE and LTE-A networksrdquo IEEE Com-munications Surveys amp Tutorials vol 16 no 1 pp 283ndash3022014

[2] K J Ahmed and M J Lee ldquoSecure LTE-based V2X servicerdquoIEEE Internet of 8ings Journal vol 5 no 5 pp 3724ndash37322018

[3] 3GPP TR 22885 v1400 Study on LTE Support for Vehicle toEverything (V2X) Services (Release 14) 3GPP ValbonneFrance 2015

[4] 3GPP TR 38801 V1400 Study on New Radio AccessTechnology Radio Access Architecture and Interfaces 3GPPValbonne France 2017

[5] 3GPP TR 38802 Study on New Radio Access TechnologyPhysical Layer Aspects 3GPP Valbonne France 2017

[6] G Naik B Choudhury and J-M Park ldquoIEEE 80211 Bd amp 5GNR V2X evolution of radio access technologies for V2Xcommunicationsrdquo IEEE Access vol 7 pp 70169ndash70184 2019

[7] A Asadi Q Wang and V Mancuso ldquoA survey on device-to-device communication in cellular networksrdquo IEEE Commu-nications Surveys amp Tutorials vol 16 no 4 pp 1801ndash18192014

[8] P Mach Z Becvar and T Vanek ldquoIn-band device-to-devicecommunication in OFDMA cellular networks a survey andchallengesrdquo IEEE Communications Surveys amp Tutorialsvol 17 no 4 pp 1885ndash1922 2015

[9] S Chen J Hu Y Shi et al ldquoVehicle-to-everything (v2x)services supported by LTE-based systems and 5Grdquo IEEECommunications Standards Magazine vol 1 no 2 pp 70ndash762017

[10] 3GPP TS 22185 v1430 LTE Service Requirements for V2XServices 3GPP Valbonne France 2017

[11] X Wang S Mao and M X Gong ldquoAn overview of 3GPPcellular vehicle-to-everything standardsrdquo GetMobile MobileComputing and Communications vol 21 no 3 pp 19ndash252017

[12] 3GPP TS 33185 V1500 Security Aspect for LTE Support ofVehicle-To-Everything (V2X) Services (Release 15) 3GPPValbonne France 2018

[13] R Molina-Masegosa and J Gozalvez ldquoLTE-V for sidelink 5GV2X vehicular communications a new 5G technology forshort-range vehicle-to-everything communicationsrdquo IEEEVehicular TechnologyMagazine vol 12 no 4 pp 30ndash39 2017

[14] M Gonzalez-Martın M Sepulcre R Molina-Masegosa andJ Gozalvez ldquoAnalytical models of the performance of C-V2xmode 4 vehicular communicationsrdquo IEEE Transactions onVehicular Technology vol 68 no 2 pp 1155ndash1166 2019

[15] B Di L Song Y Li and G Y Li ldquoNon-orthogonal multipleaccess for high-reliable and low-latency V2X communicationsin 5G systemsrdquo IEEE Journal on Selected Areas in Commu-nications vol 35 no 10 pp 2383ndash2397 2017

[16] 3GPP R1-163111 Initial Views and Evaluation Results onNon-orthogonal Multiple Access for NR Uplink 3GPP Val-bonne France 2016

[17] B Di L Song Y Li and Z Han ldquoV2X meets NOMA non-orthogonal multiple access for 5G-enabled vehicular net-worksrdquo IEEE Wireless Communications vol 24 no 6pp 14ndash21 2017

[18] R Zhang X Cheng Q Yao C-X Wang Y Yang and B JiaoldquoInterference graph-based resource-sharing schemes for ve-hicular networksrdquo IEEE Transactions on Vehicular Technol-ogy vol 62 no 8 pp 4028ndash4039 2013

[19] W Sun E G Strom F Brannstrom Y Sui and K C SouldquoD2D-based V2V communications with latency and re-liability constraintsrdquo in Proceedings of the 2014 IEEE Globe-com Workshops (GC Wkshps) pp 1414ndash1419 Austin TXUSA December 2014

[20] W Sun E G Strom F Brannstrom K C Sou and Y SuildquoRadio resource management for D2D-based V2V commu-nicationrdquo IEEE Transactions on Vehicular Technology vol 65no 8 pp 6636ndash6650 2016

[21] W Sun D Yuan E G Strom and F Brannstrom ldquoResourcesharing and power allocation for D2D-based safety-criticalV2X communicationsrdquo in Proceedings of the 2015 IEEE In-ternational Conference on Communication Workshop(ICCW) pp 2399ndash2405 London UK June 2015

[22] W Sun D Yuan E G Strom and F Brannstrom ldquoCluster-based radio resource management for D2D-supported safety-critical V2X communicationsrdquo IEEE Transactions on WirelessCommunications vol 15 no 4 pp 2756ndash2769 2016

[23] S Zhang Y Hou X Xu and X Tao ldquoResource allocation inD2D-based V2V communication for maximizing the number


of concurrent transmissionsrdquo in Proceedings of the 2016 IEEE27th Annual International Symposium on Personal Indoorand Mobile Radio Communications (PIMRC) pp 1ndash6Valencia Spain September 2016

[24] Q Wei W Sun B Bai L Wang E G Strom and M SongldquoResource allocation for V2X communications a local searchbased 3Dmatching approachrdquo in Proceedings of the 2017 IEEEInternational Conference on Communications (ICC) pp 1ndash6Paris France May 2017

[25] L Liang J Kim S C Jha K Sivanesan and G Y LildquoSpectrum and power allocation for vehicular communica-tions with delayed CSI feedbackrdquo IEEE Wireless Communi-cations Letters vol 6 no 4 pp 458ndash461 2017

[26] L Liang G Y Li and W Xu ldquoResource allocation for D2D-enabled vehicular communicationsrdquo IEEE Transactions onCommunications vol 65 no 7 pp 3186ndash3197 2017

[27] J Mei K Zheng L Zhao Y Teng and X Wang ldquoA latencyand reliability guaranteed resource allocation scheme for LTEV2V communication systemsrdquo IEEE Transactions onWirelessCommunications vol 17 no 6 pp 3850ndash3860 2018

[28] Q Wei L Wang Z Feng and Z Ding ldquoWireless resourcemanagement in LTE-U driven heterogeneous V2X commu-nication networksrdquo IEEE Transactions on Vehicular Tech-nology vol 67 no 8 pp 7508ndash7522 2018

[29] Q Wei L Wang Z Feng and Z Ding ldquoCooperative co-existence and resource allocation for V2X communications inLTE-unlicensedrdquo in Proceedings of the 2018 15th IEEE AnnualConsumer Communications amp Networking Conference(CCNC) pp 1ndash6 Las Vegas NV USA January 2018

[30] A Masmoudi S Feki K Mnif and F Zarai ldquoRadio resourceallocation algorithm for device to device based on LTE-V2Xcommunicationsrdquo in Proceedings of the 15th InternationalJoint Conference on e-Business and Telecommunicationspp 265ndash271 Porto Portugal 2018

[31] A Masmoudi S Feki K Mnif and F Zarai ldquoEfficient radioresource management for D2D- based LTE-V2X communi-cationsrdquo in Proceedings of the IEEEACS 15th InternationalConference on Computer Systems and Applications (AICCSA)Aqaba Jordan November 2018

[32] A Masmoudi S Feki K Mnif and F Zarai ldquoEfficientscheduling and resource allocation for D2D-based LTE-V2Xcommunicationsrdquo in Proceedings of the 2019 15th In-ternational Wireless Communications amp Mobile ComputingConference (IWCMC) pp 496ndash501 Tangier Morocco June2019

[33] A Masmoudi S Feki K Mnif and F Zarai A Mixed TrafficSharing and Resource Allocation for V2X CommunicationCCIS 1118 Chapter 11 2019

[34] M I Ashraf C-F Liu M Bennis and W Saad ldquoTowardslow-latency and ultra-reliable vehicle-to-vehicle communi-cationrdquo in Proceedings of the 2017 European Conference onNetworks and Communications (EuCNC) pp 1ndash5 OuluFinland June 2017

[35] L F Abanto-Leon A Koppelaar and S H de Groot ldquoGraph-based resource allocation with conflict avoidance for V2Vbroadcast communicationsrdquo in Proceedings of the 2017 IEEE28th Annual International Symposium on Personal Indoorand Mobile Radio Communications (PIMRC) pp 1ndash7Montreal Canada October 2017

[36] C-Y Wei A C-S Huang C-Y Chen and J-Y Chen ldquoQoS-aware hybrid scheduling for geographical zone-based re-source allocation in cellular vehicle-to-vehicle communica-tionsrdquo IEEE Communications Letters vol 22 no 3pp 610ndash613 2018

[37] L Liang S Xie G Y Li Z Ding and X Yu ldquoGraph-basedradio resource management for vehicular networksrdquo 2018httparxivorgabs180102679

[38] H Yang L Zhao L Lei and K Zheng ldquoA two-stage allo-cation scheme for delay-sensitive services in dense vehicularnetworksrdquo in Proceedings of the 2017 IEEE InternationalConference on Communications Workshops (ICC Workshops)pp 1358ndash1363 Paris France May 2017

[39] M I Ashraf M Bennis C Perfecto and W Saad ldquoDynamicproximity-aware resource allocation in vehicle-to-vehicle(V2V) communicationsrdquo in Proceedings of the 2016 IEEEGlobecomWorkshops (GCWkshps) pp 1ndash6Washington DCUSA December 2016

[40] M Botsov M Klugel W Kellerer and P Fertl ldquoLocationdependent resource allocation for mobile device-to-devicecommunicationsrdquo in Proceedings of the 2014 IEEE WirelessCommunications and Networking Conference (WCNC)pp 1679ndash1684 Istanbul Turkey April 2014

[41] M Botsov M Klugel W Kellerer and P Fertl ldquoLocation-based resource allocation for mobile D2D communications inmulticell deploymentsrdquo in Proceedings of the 2015 IEEE In-ternational Conference on Communication Workshop(ICCW) pp 2444ndash2450 London UK June 2015

[42] X Zhang Y Shang X Li and J Fang ldquoResearch on overlayD2D resource scheduling algorithms for V2V broadcastservicerdquo in Proceedings of the 2016 IEEE 84th VehicularTechnology Conference (VTC-Fall) pp 1ndash5 MontrealCanada September 2016

[43] J Kim J Lee S Moon and I Hwang ldquoA position-basedresource allocation scheme for V2V communicationrdquoWireless Personal Communications vol 98 no 1 pp 1569ndash1586 2018

[44] F Abbas and P Fan ldquoA hybrid low-latency D2D resourceallocation scheme based on cellular V2X networksrdquo in Pro-ceedings of the 2018 IEEE International Conference on Com-munications Workshops (ICC Workshops) pp 1ndash6 KansasCity MO USA May 2018

[45] S Feki A Masmoudi A Belghith F Zarai andM S ObaidatldquoSwarm intelligence-based radio resource management forD2D-based V2V communicationrdquo International Journal ofCommunication Systems p e3817 2018


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technologies to support V2V communications As V2X isbased on the D2D communication resources are allocated inthe V-UEs either in the overlay mode or in the underlaymode For that reason radio resource management (RRM)plays an important role in V2X system performances

In this paper we provide a wide review of availableliterature for resource allocation algorithms in V2X servicesbased on D2D communication Moreover we provide acomprehensive comparison and classification of V2X re-source allocation algorithms in terms of numerous aspectse paper is structured as follows e V2X services aredescribed in Section 2 e V2X communication modes andthe LTE-V-based D2D communication are introduced re-spectively in Section 3 and Section 4 A review and clas-sification of the existing resource allocation algorithms forV2X communication are addressed in Section 5 We discussand conclude this paper in Section 6 and Section 7

2 V2X Requirements and Services

3GPP defines 27 use cases for V2X services in Release 14 thatcan be divided into safety and nonsafety V2X services [10]erefore the transmission of V2X messages should beclassified according to the message type (eg safety vsnonsafety) e safety services-related use cases aim to avoidautomobile accidents and to protect the property and lifewhich require high reliability and short delay (eg vehicleplatooning and automated driving) e nonsafety use casesaim to improve the driving experience to be more com-fortable and efficient (eg mobile high data rate enter-tainment and trafficmanagement)erefore the non-safetyand the safety V2X services have different latency and packetsize requirements [11]

Five categories of service requirements of this use casesare defined as follows [9 10]

(i) Speed the maximum absolute velocity 160 kmhand the maximum relative velocity 280 kmh shallbe supported e maximum relative speed of500 kmh is supported for the possible scenariowithout speed limitation

(ii) Communication range the effective distance islarger than the distance calculated as the ampleresponse time (eg 4 seconds) for the drivers toavoid collision according maximum relativespeed

(iii) Latencyreliability the maximum end-to-end la-tency between two UEs supporting V2VV2PV2Iapplications shall be 100ms e minimum radiolayer reliability should be supported withoutretransmissions of application-layer messages in theeffective distance and the restricted latency

(iv) Message size the variable length of a periodicallymessage between two UEs supporting V2X appli-cations is about 50ndash300 bytes e message size ofevent-triggered messages can be up to 1200 bytes

(v) Message generation period the minimum messagegeneration period can be 100ms

21 Safety-Critical V2X Services e safety-critical V2Xservices aim to reduce the potential accident and the riskto pedestrians and to deteriorate the possibility of lifedead for V-UEs e information shared between pe-destrians Road Side Unit (RSU) and vehicles (ie ve-hicle speed position and distance) is usually shortbroadcast messages which impose stringent requirementson latency packet loss and reliability Two types of safetyV2X transmissions messages have been standardized theperiodic transmission and event-triggered transmissione periodic transmissions among V2V-UEs (eg thecooperative awareness messages (CAMs) are shortbroadcast messages periodically transmitting aware in-formation of position presence speed and directionsamong vehicles and their neighbors e event-triggeredtransmission among V2X-UEs (ie decentralized envi-ronmental notification messages (DENMs)) is shortbroadcast messages to alert road users about road statusBoth periodic transmission and event-triggered trans-mission can be operated over the LTE-Uu and the PC5interfaces [12]

22 Nonsafety V2X Services e nonsafety V2X servicesessentially focus on management application control con-gestion traffic efficiency and entertainment these servicesenable more comfortable and efficient driving experienceNonsafety V2X applications aim to improve traffic co-ordination assistance and vehicle traffic flow In additionthey also provide entertainment video maps and updatedlocal information erefore a large amount of V-UEssensed data sent to neighbors or to infrastructure eseservices have no strict requirements on reliability andlatency

23 V2X Requirements

231 Reliability Requirement e reliability requirementdefined in different works is generally interpreted fromeither the outage probability (OP) or the packet receptionratio (PRR)

e PRR is the ratio of successful reception among thetotal number of the vehicle transmitter neighbors which arecalculated as follows

PRRu(t) 1

Nu(t)1113944

Nu(t)

j11 c

(u)j (t)ge cth1113966 1113967

c(u)j (t) 1113944

NRB

k1

suk(t)Pu(t) Hk

uj(t)11138681113868111386811138681113868

111386811138681113868111386811138682

σ2 + 1113936NL

m1sum(t) Pj(t) Hk

m(t)1113868111386811138681113868

11138681113868111386811138682

(1)

where Nu(t) denotes the number of the vehicles neighborsof the uth vehicle at time t c

(u)j (t) is the receiving signal-

to-interference-plus-noise ratio (SINR) of the jth vehicleamong Nu(t) cth is the SINR threshold Pu(t) is thetransmit power of uth vehicle σ2 is the power of additivewhite Gaussian noise NL is the number of interfering



suk(t)


0 otherwise1113896


poutu ≜ Pr 1113944

Eallu


⎧⎪⎨

⎪⎩

⎫⎪⎬

⎪⎭ (2)















Backhaul


eNB

C-UE

V-UE

V-UE

V-UE PC5

Uu

Uu













D2DV2V

Cellular Cellular

V2V V2V

Underlay Overlay


NOMA

OFDMA

UE1 UE2

f

f












constraints



sharing




[19] Unicast


Urban C-UEsV-UEs

OPSINRLatency



Hungarian algorithm

1 C-UE1 V-UE

[20] Unicast


Urban C-UEsV-UEs

OPSINRLatency




Hungarian algorithm

1 C-UE1 V-UE

[21] Unicast


Urban C-UEsV-UEs

OPSINRLatency

PA


C-UEsnonorthogonal


UEs



1 C-UEN V-UEs

[22] Unicast


Urban C-UEsV-UEs

OPSINRLatency

PA


C-UEsnonorthogonal


UEs


1 C-UEN V-UEs

[23] Broadcast


V2Vtransmissions



allocated to V-UEs


[24] Unicast


Urban


SINRLatency mdash



1 C-UE1 safetyV-UE1

nonsafetyV-UE


Multilanefreeway







Table 1 Continued


constraints



sharing

[26] Unicast


ergodiccapacity

Multi-lane

freeway




[27] Broadcast

Maximize theC-UEs


requirement ofV-UEs

Urban C-UEsV-UEs

LatencyOPSINR



method

1 C-UE1 V-UE

[28] Unicast



UEs)

Freeway

W-UEsC-UEs





1 C-UE1

nonsafetyV-UE

[29] Unicast

Maximize thetotal


UEs

Freeway

W-UEsC-UEs





1 C-UE1

nonsafetyV-UE

[30] Unicast


requirement





[31] Unicast


requirement





[32] Unicast


Freeway

GBR C-UEs

NGBR C-UEs

V-UEs

PDRSINR



mdash 1 C-UE1 V-UE

[33] Unicast



UEs guaranteeV-UEs


Freeway

C-UEsSafety V-

UENonsafetyV-UE

PDORSINRDelay


mdash

1 C-UE1 safety V-

UE1

nonsafetyV-UE


































[34] Unicast






NV2V-UEs




clusters


N V-UEs

[36] Broadcast


rx V-UEs





Greedy algorithmN

V2V-UEs


V2V

Multilanefreeway

V2V-UEsV2I-UEs

OP PA



UEs

Graph theory

1 V2I-UEsN

V2V-UEs



constraints



sharing

[38] Broadcast


Maximize datarate





Traffic flowtheory




allocated to V-UEs



[40] Unicast

Reduce thesignaling




mdash 1 C-UE1 V-UE

[41] Unicast

Reduce thesignaling












6 Discussion









distance

mdash N V-UEs









V2X or 80211p



V-UEs

FairnessindexOP


UEs


1 V-UEor 1 C-UE




7 Conclusion




References



















































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



suk(t)


0 otherwise1113896


poutu ≜ Pr 1113944

Eallu


⎧⎪⎨

⎪⎩

⎫⎪⎬

⎪⎭ (2)















Backhaul


eNB

C-UE

V-UE

V-UE

V-UE PC5

Uu

Uu













D2DV2V

Cellular Cellular

V2V V2V

Underlay Overlay


NOMA

OFDMA

UE1 UE2

f

f












constraints



sharing




[19] Unicast


Urban C-UEsV-UEs

OPSINRLatency



Hungarian algorithm

1 C-UE1 V-UE

[20] Unicast


Urban C-UEsV-UEs

OPSINRLatency




Hungarian algorithm

1 C-UE1 V-UE

[21] Unicast


Urban C-UEsV-UEs

OPSINRLatency

PA


C-UEsnonorthogonal


UEs



1 C-UEN V-UEs

[22] Unicast


Urban C-UEsV-UEs

OPSINRLatency

PA


C-UEsnonorthogonal


UEs


1 C-UEN V-UEs

[23] Broadcast


V2Vtransmissions



allocated to V-UEs


[24] Unicast


Urban


SINRLatency mdash



1 C-UE1 safetyV-UE1

nonsafetyV-UE


Multilanefreeway







Table 1 Continued


constraints



sharing

[26] Unicast


ergodiccapacity

Multi-lane

freeway




[27] Broadcast

Maximize theC-UEs


requirement ofV-UEs

Urban C-UEsV-UEs

LatencyOPSINR



method

1 C-UE1 V-UE

[28] Unicast



UEs)

Freeway

W-UEsC-UEs





1 C-UE1

nonsafetyV-UE

[29] Unicast

Maximize thetotal


UEs

Freeway

W-UEsC-UEs





1 C-UE1

nonsafetyV-UE

[30] Unicast


requirement





[31] Unicast


requirement





[32] Unicast


Freeway

GBR C-UEs

NGBR C-UEs

V-UEs

PDRSINR



mdash 1 C-UE1 V-UE

[33] Unicast



UEs guaranteeV-UEs


Freeway

C-UEsSafety V-

UENonsafetyV-UE

PDORSINRDelay


mdash

1 C-UE1 safety V-

UE1

nonsafetyV-UE


































[34] Unicast






NV2V-UEs




clusters


N V-UEs

[36] Broadcast


rx V-UEs





Greedy algorithmN

V2V-UEs


V2V

Multilanefreeway

V2V-UEsV2I-UEs

OP PA



UEs

Graph theory

1 V2I-UEsN

V2V-UEs



constraints



sharing

[38] Broadcast


Maximize datarate





Traffic flowtheory




allocated to V-UEs



[40] Unicast

Reduce thesignaling




mdash 1 C-UE1 V-UE

[41] Unicast

Reduce thesignaling












6 Discussion









distance

mdash N V-UEs









V2X or 80211p



V-UEs

FairnessindexOP


UEs


1 V-UEor 1 C-UE




7 Conclusion




References



















































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia












D2DV2V

Cellular Cellular

V2V V2V

Underlay Overlay


NOMA

OFDMA

UE1 UE2

f

f












constraints



sharing




[19] Unicast


Urban C-UEsV-UEs

OPSINRLatency



Hungarian algorithm

1 C-UE1 V-UE

[20] Unicast


Urban C-UEsV-UEs

OPSINRLatency




Hungarian algorithm

1 C-UE1 V-UE

[21] Unicast


Urban C-UEsV-UEs

OPSINRLatency

PA


C-UEsnonorthogonal


UEs



1 C-UEN V-UEs

[22] Unicast


Urban C-UEsV-UEs

OPSINRLatency

PA


C-UEsnonorthogonal


UEs


1 C-UEN V-UEs

[23] Broadcast


V2Vtransmissions



allocated to V-UEs


[24] Unicast


Urban


SINRLatency mdash



1 C-UE1 safetyV-UE1

nonsafetyV-UE


Multilanefreeway







Table 1 Continued


constraints



sharing

[26] Unicast


ergodiccapacity

Multi-lane

freeway




[27] Broadcast

Maximize theC-UEs


requirement ofV-UEs

Urban C-UEsV-UEs

LatencyOPSINR



method

1 C-UE1 V-UE

[28] Unicast



UEs)

Freeway

W-UEsC-UEs





1 C-UE1

nonsafetyV-UE

[29] Unicast

Maximize thetotal


UEs

Freeway

W-UEsC-UEs





1 C-UE1

nonsafetyV-UE

[30] Unicast


requirement





[31] Unicast


requirement





[32] Unicast


Freeway

GBR C-UEs

NGBR C-UEs

V-UEs

PDRSINR



mdash 1 C-UE1 V-UE

[33] Unicast



UEs guaranteeV-UEs


Freeway

C-UEsSafety V-

UENonsafetyV-UE

PDORSINRDelay


mdash

1 C-UE1 safety V-

UE1

nonsafetyV-UE


































[34] Unicast






NV2V-UEs




clusters


N V-UEs

[36] Broadcast


rx V-UEs





Greedy algorithmN

V2V-UEs


V2V

Multilanefreeway

V2V-UEsV2I-UEs

OP PA



UEs

Graph theory

1 V2I-UEsN

V2V-UEs



constraints



sharing

[38] Broadcast


Maximize datarate





Traffic flowtheory




allocated to V-UEs



[40] Unicast

Reduce thesignaling




mdash 1 C-UE1 V-UE

[41] Unicast

Reduce thesignaling












6 Discussion









distance

mdash N V-UEs









V2X or 80211p



V-UEs

FairnessindexOP


UEs


1 V-UEor 1 C-UE




7 Conclusion




References



















































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia











constraints



sharing




[19] Unicast


Urban C-UEsV-UEs

OPSINRLatency



Hungarian algorithm

1 C-UE1 V-UE

[20] Unicast


Urban C-UEsV-UEs

OPSINRLatency




Hungarian algorithm

1 C-UE1 V-UE

[21] Unicast


Urban C-UEsV-UEs

OPSINRLatency

PA


C-UEsnonorthogonal


UEs



1 C-UEN V-UEs

[22] Unicast


Urban C-UEsV-UEs

OPSINRLatency

PA


C-UEsnonorthogonal


UEs


1 C-UEN V-UEs

[23] Broadcast


V2Vtransmissions



allocated to V-UEs


[24] Unicast


Urban


SINRLatency mdash



1 C-UE1 safetyV-UE1

nonsafetyV-UE


Multilanefreeway







Table 1 Continued


constraints



sharing

[26] Unicast


ergodiccapacity

Multi-lane

freeway




[27] Broadcast

Maximize theC-UEs


requirement ofV-UEs

Urban C-UEsV-UEs

LatencyOPSINR



method

1 C-UE1 V-UE

[28] Unicast



UEs)

Freeway

W-UEsC-UEs





1 C-UE1

nonsafetyV-UE

[29] Unicast

Maximize thetotal


UEs

Freeway

W-UEsC-UEs





1 C-UE1

nonsafetyV-UE

[30] Unicast


requirement





[31] Unicast


requirement





[32] Unicast


Freeway

GBR C-UEs

NGBR C-UEs

V-UEs

PDRSINR



mdash 1 C-UE1 V-UE

[33] Unicast



UEs guaranteeV-UEs


Freeway

C-UEsSafety V-

UENonsafetyV-UE

PDORSINRDelay


mdash

1 C-UE1 safety V-

UE1

nonsafetyV-UE


































[34] Unicast






NV2V-UEs




clusters


N V-UEs

[36] Broadcast


rx V-UEs





Greedy algorithmN

V2V-UEs


V2V

Multilanefreeway

V2V-UEsV2I-UEs

OP PA



UEs

Graph theory

1 V2I-UEsN

V2V-UEs



constraints



sharing

[38] Broadcast


Maximize datarate





Traffic flowtheory




allocated to V-UEs



[40] Unicast

Reduce thesignaling




mdash 1 C-UE1 V-UE

[41] Unicast

Reduce thesignaling












6 Discussion









distance

mdash N V-UEs









V2X or 80211p



V-UEs

FairnessindexOP


UEs


1 V-UEor 1 C-UE




7 Conclusion




References



















































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia




Table 1 Continued


constraints



sharing

[26] Unicast


ergodiccapacity

Multi-lane

freeway




[27] Broadcast

Maximize theC-UEs


requirement ofV-UEs

Urban C-UEsV-UEs

LatencyOPSINR



method

1 C-UE1 V-UE

[28] Unicast



UEs)

Freeway

W-UEsC-UEs





1 C-UE1

nonsafetyV-UE

[29] Unicast

Maximize thetotal


UEs

Freeway

W-UEsC-UEs





1 C-UE1

nonsafetyV-UE

[30] Unicast


requirement





[31] Unicast


requirement





[32] Unicast


Freeway

GBR C-UEs

NGBR C-UEs

V-UEs

PDRSINR



mdash 1 C-UE1 V-UE

[33] Unicast



UEs guaranteeV-UEs


Freeway

C-UEsSafety V-

UENonsafetyV-UE

PDORSINRDelay


mdash

1 C-UE1 safety V-

UE1

nonsafetyV-UE


































[34] Unicast






NV2V-UEs




clusters


N V-UEs

[36] Broadcast


rx V-UEs





Greedy algorithmN

V2V-UEs


V2V

Multilanefreeway

V2V-UEsV2I-UEs

OP PA



UEs

Graph theory

1 V2I-UEsN

V2V-UEs



constraints



sharing

[38] Broadcast


Maximize datarate





Traffic flowtheory




allocated to V-UEs



[40] Unicast

Reduce thesignaling




mdash 1 C-UE1 V-UE

[41] Unicast

Reduce thesignaling












6 Discussion









distance

mdash N V-UEs









V2X or 80211p



V-UEs

FairnessindexOP


UEs


1 V-UEor 1 C-UE




7 Conclusion




References



















































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia


































[34] Unicast






NV2V-UEs




clusters


N V-UEs

[36] Broadcast


rx V-UEs





Greedy algorithmN

V2V-UEs


V2V

Multilanefreeway

V2V-UEsV2I-UEs

OP PA



UEs

Graph theory

1 V2I-UEsN

V2V-UEs



constraints



sharing

[38] Broadcast


Maximize datarate





Traffic flowtheory




allocated to V-UEs



[40] Unicast

Reduce thesignaling




mdash 1 C-UE1 V-UE

[41] Unicast

Reduce thesignaling












6 Discussion









distance

mdash N V-UEs









V2X or 80211p



V-UEs

FairnessindexOP


UEs


1 V-UEor 1 C-UE




7 Conclusion




References



















































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia








6 Discussion









distance

mdash N V-UEs









V2X or 80211p



V-UEs

FairnessindexOP


UEs


1 V-UEor 1 C-UE




7 Conclusion




References



















































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia




7 Conclusion




References



















































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia




























RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia


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