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IEEE COMMUNICATION SURVEYS & TUTORIALS, VOL. 17, NO. 2, SECOND QUARTER 2015 525

M2M Communications in 3GPP LTE/LTE-ANetworks: Architectures, Service Requirements,

Challenges, and ApplicationsFayezeh Ghavimi, Graduate Student Member, IEEE, and Hsiao-Hwa Chen, Fellow, IEEE

Abstract—Machine-to-machine (M2M) communication is anemerging technology to provide ubiquitous connectivity amongdevices without human intervention. The cellular networks areconsidered a ready-to-use infrastructure to implement M2M com-munications. However, M2M communications over cellular posesignificant challenges to cellular networks due to different datatransactions, diverse applications, and a large number of connec-tions. To support such a large number of devices, M2M systemarchitecture should be extremely power and spectrum efficient.In this paper, we provide a comprehensive survey on M2Mcommunications in the context of the Third-Generation Partner-ship Project (3GPP) Long-Term Evolution (LTE) and Long-TermEvolution-Advanced (LTE-A). More specifically, this paperpresents architectural enhancements for providing M2M servicesin 3GPP LTE/LTE-A networks and reviews the features andrequirements of M2M applications. In addition, the signal over-heads and various quality-of-service (QoS) requirements in M2Mcommunications also deserve our attention. We address M2Mchallenges over 3GPP LTE/LTE-A and also identify the issues ondiverse random access overload control to avoid congestion causedby random channel access of M2M devices. Different applicationscenarios are considered to illustrate futuristic M2M applications.Finally, we present possible enabling technologies and point outthe directions for M2M communications research.

Index Terms—M2M communication, 3GPP, LTE, LTE-Advanced, architecture, random access.

I. INTRODUCTION

MACHINE-TO-MACHINE (M2M) communications re-fer to the ways enabling automated applications that

provide connectivity among machines or devices without anyhuman intervention. The M2M communications may involvea large number of devices in a wide range of application do-mains, thus forming so-called Internet of Things (IoT). Cellularsystems are expected to play a significant role in the successfuldeployment of M2M communications. Indeed, mobile cellularcommunications feature several advantages, such as globalstandard infrastructure, cost-effective connectivity, easy instal-lation and maintenance, especially for a short-term deploymentof M2M applications.

Manuscript received February 14, 2014; revised July 7, 2014; acceptedSeptember 3, 2014. Date of publication October 7, 2014; date of current versionMay 19, 2015. This work was supported in part by Taiwan Ministry of Scienceand Technology under Grant NSC 102-2221-E-006-008-MY3.

The authors are with the Department of Engineering Science, NationalCheng Kung University, Tainan City 70101, Taiwan (e-mail: [email protected]; [email protected]).

Digital Object Identifier 10.1109/COMST.2014.2361626

Several reports appeared in the literature to predict a con-siderable market growth for both M2M devices and M2Mconnectivity segments. For example, over the next a few years,the number of smart-metering devices per cell in a typicalurban environment is estimated to be in an order of tens ofthousands [1]. The M2M applications may include a largenumber of smart meters, health monitoring devices, and intelli-gent transportation terminals that must be efficiently connectedvia communication links [2]. In order to take full advantagesof the opportunities created by a global M2M market overcellular networks, 3GPP and the Institute of Electrical andElectronics Engineering (IEEE) standardization bodies haveinitiated their working groups for facilitating such applicationsthrough various releases of their standards [3], [4].

The 3GPP LTE and LTE-A offer higher capacity and moreflexible radio resource management (RRM) schemes than manyother packet access data technologies. In LTE-A, stations canbe configured as evolved universal terrestrial radio access(E-UTRA) NodeBs (eNBs) in macrocells or picocells, homeeNBs (HeNBs) in femtocells [5]–[7], and relay nodes (RNs)in relay networks to provide comprehensive wireless access inboth outdoor and indoor environments. Via attaching to thosestations, higher-layer connections among all M2M devices canbe provided. However, LTE and LTE-A were designed basicallyfor wideband applications only; while in M2M communica-tions, transactions at each M2M device are usually dominatedby a small amount of data, leading to an inefficient utilizationof LTE and LTE-A technologies. Therefore, to support a largenumber of M2M devices, important issues such as energyefficiency and short latency have to be addressed in M2Mcommunications. Notably, the efforts have been made by 3GPPto overcome the shortcomings of LTE/LTE-A with its provisionto support M2M communications [8], where its initial studieson M2M communications were focused on the functional ar-chitecture, service requirements, and applications [3], [8], [9].

With regard to service requirements, M2M applications arevery much different from human-to-human (H2H) commu-nications (e.g., typical applications of mobile phones), sinceM2M services have their unique characteristics [3], [10], [11].Furthermore, QoS requirements of different types of M2Mservices may vary widely, and these service requirements thenrequire special architectural designs. With an architecture inplace, numerous challenges remain when implementing RRMfor M2M communications in LTE-A cellular networks. Forexample, time and frequency resources are to be shared be-tween H2H users and M2M devices, thus inevitably causing

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526 IEEE COMMUNICATION SURVEYS & TUTORIALS, VOL. 17, NO. 2, SECOND QUARTER 2015

co-channel interference among them [12]. Such co-channelinterference is responsible for degraded performance of anLTE-A cellular network supporting M2M communications. Tooptimally allocate the physical resource blocks (PRBs) to theuser equipment (UE) and/or M2M devices, the schedular shouldexploit channel and traffic dynamics on a fast time scale,ideally per transmission time interval (TTI) [13]. Therefore, it isnecessary to investigate the ways, in which how H2H users andM2M devices can efficiently share available radio resources, tomitigate the co-channel interference and thus improve networkefficiency. In this paper, we intend to present some architecturalenhancements needed to accomplish the M2M service require-ments. In addition, M2M service requirements and features areto be illustrated in detail.

To deploy M2M communications successfully in 3GPPLTE/LTE-A cellular networks, several major challenges need tobe tackled. One of the most important issues in enabling M2Min LTE/LTE-A networks is congestion and system overloadproblem. The LTE/LTE-A networks were designed mainly tohandle H2H communications, where the amount of uplink (UL)traffic is normally lower than the downlink (DL) traffic. Incontrast, M2M applications may produce more traffic data inUL channels than the data over DL channels. Congestion dueto concurrent transmit messages from a large number of M2Mdevices can be overwhelming, thus impacting on the operationsof a whole mobile network. In the context of M2M communi-cations, signaling congestion may occur due to a malfunction inan M2M server (e.g., M2M devices repeatedly try to connect tothe same remote server, which is down) or an application (e.g.,synchronized operation of a particular M2M application). Thecongestion can also occur due to concurrent attempts from alarge number of M2M devices to attach/connect to the network[3]. The investigations in 3GPP in the literature indicated thatboth M2M devices and UE may suffer uninterrupted collisionsat a random access channel (RACH) when a large number ofM2M devices are active. This challenge attracted a significantattention, and various possible solutions have been proposed bythe 3GPP [14].

Several review papers in literature [15]–[18] discuss M2Mcommunications in the context of emerging wireless technolo-gies. In [15], the authors describe the technological scenarioof M2M communications consisting of wireless infrastructureto cloud and related technologies toward practical realization.Moreover, [16] presents a survey on home M2M networks andexamines the typical architectures of home M2M networksalong with discussing the performance tradeoffs in existingdesigns. Furthermore, [17] presents a survey of existing M2Mservice platforms and explores the various research issues andchallenges involved in enabling an M2M service platform.In addition, the authors in [18] describe machine type com-munications in 3GPP networks and provide a summary ofthe solutions agreed within 3GPP for congestion control andnetwork overload avoidance.

Hence to the best of our knowledge, a comprehensive surveyon M2M communications with its focus on LTE/LTE-A sys-tems is not available in the literature. Therefore, the main pur-pose of this paper is to provide a review on the studies appearedin the literature, helping the readers to understanding what

has been investigated (architecture, technologies, requirements,challenges, and proposed solutions) and what still remains tobe addressed. In addition, this paper will reveal an evolutionarypath of the M2M communications for futuristic research.

The remainder of this paper is outlined as follows. InSection II, we discuss architectural enhancement of LTE/LTE-A with regard to the M2M communications. The M2Mcommunication standardization activities, service require-ments, and features are the subject of Section III. In Section IV,the M2M challenges over 3GPP LTE/LTE-A are studied whilethe principal applications of the M2M communications will beaddressed in Section V. Section VI lists the open research issueson M2M communications via discussing relevant topics suchas traffic characterization, routing, heterogeneity, security, etc.,followed by the conclusions given in Section VII.

II. M2M NETWORK ARCHITECTURE

Different from normal mobile network terminals, M2M de-vices carry many unique characteristic features from the per-spective of mobile operators. Therefore, it is necessary to seekoptimized networking solutions in particular for M2M appli-cations over mobile networks. To provide global integrationamong diverse solutions in the M2M applications, it is im-portant to design a standard end-to-end M2M communicationnetwork architecture. This section provides an overview onM2M network architecture and identifies related M2M R&Dactivities reported in the literature.

A. M2M Access Methods

M2M devices can be either stationary (e.g., power meters inhomes, machines in factory, etc.) or mobile (e.g., fleet manage-ment devices in trucks). The access network connects M2M de-vices to the infrastructure using either wired (i.e., cable, xDSL,and optical fiber) or wireless links. Wireless access methodscan be either capillary/short range (i.e., WLAN, ZigBee, andIEEE 802.15.4x, etc.) or cellular (i.e., GSM, GPRS, EDGE, 3G,LTE-A, WiMAX, etc.). Although the wired solutions can pro-vide high reliability, high rate, short delay, and high security,it may not be appropriate for the M2M communication appli-cations due to its cost ineffectiveness, and lack of scalability/mobility support. Alternatively, wireless capillary solutions,mainly used for shared short range links/networks, are rathercheap to roll out, and generally scalable. However, small cov-erage, low rate, weak security, severe interference, and lack ofuniversal infrastructure/coverage pose restriction on its appli-cations to M2M communications. On the other hand, wirelesscellular offers excellent coverage, mobility/roaming support,good security, and ready-to-use infrastructure, making M2Mover cellular a promising solution for M2M communications.Therefore, in this article, our focus is on the M2M communica-tions based on 3GPP LTE/LTE-A mobile networks.

B. 3GPP Network Architecture

In this part, we describe the 3GPP network architecture toprovide a comprehensive survey and more specifically to reveal

GHAVIMI AND CHEN: M2M COMMUNICATIONS IN 3GPP LTE/LTE-A NETWORKS 527

Fig. 1. An overview of EPC for 3GPP accesses.

an evolutionary path from the non-LTE to the LTE/LTE-Atechnologies helping the readers to understanding what is thesimilarity for the element nodes in non-LTE and LTE/LTE-A aswell as a description of the functionality of them. An overviewof the evolved packet core (EPC), the legacy packet and cir-cuit switched elements, 3GPP RANs, and the most significantinterfaces are illustrated in Fig. 1. Furthermore, Fig. 1 showsthe most important EPC nodes in LTE/LTE-A networks andalso, the corresponding UMTS terrestrial radio access network(UTRAN) nodes, namely serving GPRS support node (SGSN),gateway GPRS support node (GGSN), media gateway (MGW),and mobile switching center (MSC) in the non-LTE network.

The SGSN and mobility management entity (MME) receivedevice trigger from MTC-IWF; encapsulates device triggerinformation in non-access stratum (NAS) message sent tothe UE/M2M device; receives device trigger delivery success/failure status to MTC-IWF. Furthermore, SGSN performs secu-rity functions, access control and location tracking. It plays therole of MME and serving gateway (S-GW) in the EPC.

The GGSN or packet data network gateway (P-GW) maysupport the following functionality. Based on access point name(APN) configuration and unavailability of MSISDN and exter-nal identifier(s) in the GGSN/P-GW either queries an MTCaccounting, authorization, and authentication (AAA) serverfor retrieval of external identifier(s) based on IMSI or routesRADIUS/Diameter requests for AAA servers in external packetdata network (PDN). The GGSN function is similar to theP-GW in the EPC.

The MSC server controls circuit-mode services. The MSCis mostly associated with communications switching functions,such as call set-up, release, and routing. It also performs ahost of other duties, including routing SMS messages, con-ference calls, fax, and service billing as well as interfacingwith other networks, such as the public switched telephonenetwork (PSTN).

TABLE ILIST OF FREQUENTLY USED ACRONYMS

The MGW was introduced to bridge among different trans-mission technologies and to add service to end-user connec-tions. The MGW uses open interfaces to connect to differenttypes of node in the core network and external networks.

The requirements and major elements of the EPC architec-ture were characterized in 3GPP Release 8, which will playan important role in the implementation of the next generationM2M networks [21]. Along with the 3GPP LTE that appliesmore to the radio access technology, there is also an evolutionof the core network known as system architecture evolution(SAE). These two major parts lead to the characterization ofthe EPC, evolved UTRAN (E-UTRAN), and E-UTRA, eachof which corresponds to the core network (CN), RAN, and airinterface of the whole system, respectively [5].

Some frequently used acronyms in this paper are listedin Table I. In the following, we provide an overview of theE-UTRAN architecture, the main EPC node functionalities, andfunctionalities defined for LTE-A systems, respectively.

1) LTE-A E-UTRAN Overview: The architecture of theE-UTRAN for LTE-A is shown in Fig. 2. As mentioned earlier,an LTE-A network comprises two parts, i.e., the EPC andthe RAN, where the former is known as CN, and the latterconsists of base stations (BSs) that are referred to as evolvednode base stations (eNBs) [5]. The EPC is responsible foroverall control of mobile devices and establishment of InternetProtocol (IP) packet flows. The eNB is responsible for wireless


Fig. 2. LTE-A E-UTRAN architecture.

Fig. 3. User and control plane protocol stacks.

communications and radio access, and provides an air interfacewith user plane and control plane protocol terminations towardthe UE and M2M devices. Each of the eNBs serves one orseveral E-UTRAN cells, and the interface interconnecting theeNBs is called the X2 interface. Besides, the eNB is connectedto the EPC through the S1 interface. In addition, HeNBs that arethe eNBs for indoor coverage improvement can be connectedto the EPC directly or via a gateway that caters for additionalsupport for a large number of HeNBs. Furthermore, the 3GPPLTE-A encompasses relay nodes and sophisticated relayingstrategies for network performance augmentation. The aim ofthis new technology is to offer large coverage, high data rate,and better QoS performance and fairness for different users.

As mentioned earlier, the eNBs provides the E-UTRANwith the user and control plane termination protocols. Fig. 3gives a graphical overview of both protocol stacks. In the userplane, the protocols include packet data convergence protocol(PDCP), radio link control (RLC), medium access control(MAC), and physical layer (PHY) protocols. The control planestack additionally includes the radio resource control (RRC)protocols.

The main functionalities carried out in each layer are sum-marized as follows [5], [22]–[25].

• NAS: The NAS is the highest stratum of the control planebetween UE/M2M and core network at the radio interface.This layer is used to support the continuous connection ofUE/M2M as it moves, and also to manage the establish-ment of communication sessions to maintain IP connec-tivity between the UE/M2M and an P-GW. Furthermore,the NAS is a protocol for messages passed between theUE/M2M and core network. The NAS messages includeupdate or attach messages, authentication messages, ser-vice requests, and so forth. In addition, the NAS controlprotocol performs bearer context activation/deactivation,registration, and location registration management.

• RRC: The RRC protocol layer handles the control planesignaling between the UE/M2M and eNB. The main ser-vices and functions of the RRC sublayer include broadcastof system information related to the NAS and AS. Fur-thermore, establishment, modification, and release of RRCconnections are performed in this protocol layer. Initial se-curity activation (i.e., initial configuration of AS integrityprotection and AS ciphering), RRC connection mobilityincluding intra-frequency and inter-frequency handovers,and specification of RRC context information are theother important tasks of RRC sublayer. Moreover, thissublayer performs QoS control functions, UE/M2M devicemeasurement configuration and reporting. In addition, theRRC transfers dedicated NAS information and non-3GPPdedicated information.

• PDCP: This layer performs IP header compression and de-compression using ROHC protocol (the current version isFFS) at the transmitting and receiving entities, respectively.Furthermore, the PDCP transfers user plane or RRC data,and this function is used for conveying data among users ofPDCP services. Maintenance of PDCP sequence numbersfor radio bearers and in-sequence delivery of upper layerpacket data units (PDUs) at HO are other functions ofPDCP layer. In addition, duplicate detection of lowerlayer session data units (SDUs), ciphering and decipheringof user plane data and control plane data, and integrityprotection of control plane data are performed in this layer.

• RLC: The RLC protocol layer exists in UE/M2M and eNB.It is part of LTE/LTE-A air interface control and userplanes. This layer transfers upper layer PDU and performserror correction through automatic repeat request (ARQ).Moreover, the RLC protocol layer is used for concatena-tion, segmentation, and reassembly of RLC SDUs. In ad-dition, re-segmentation and reordering of RLC data PDUs,RLC re-establishment, and error detection and recoveryare the other functions of this protocol layer.

• MAC: The MAC protocol is responsible for regulatingaccess to the shared medium. Furthermore, the choice ofMAC protocol has a direct bearing on the reliability andefficiency of network transmissions. Responsibilities ofMAC layer include multiplexing/demultiplexing of RLCPDUs, scheduling information reporting, error correctionthrough hybrid ARQ (HARQ), logical channel prioritiza-tion, and transporting format selection.


2) Evolved Packet Core Overview: The EPC is a flat all IP-based core network that can be accessed through 3GPP radioaccess (e.g., WCDMA, HSPA, and LTE/LTE-A) and non-3GPPradio access (e.g., WiMAX and WLAN), to efficiently accessto various services such as the ones provided in IP multimediasubsystem (IMS). The access flexibility to the EPC is attractivefor operators since it enables them to modernize their core datanetworks to support a wide variety of access types using acommon core network. The following text describes the maincomponents of the EPC along with their functionalities.

• Mobility Management Entity (MME): The MME is a keycontrol plane element for the LTE/LTE-A access network.It is responsible for managing security functions (authenti-cation, authorization, and NAS signaling), roaming, hand-over, and handling idle mode user equipment. It is alsoinvolved in choosing the S-GW and packet data networkgateway (P-GW) for an UE/M2M device at an initialattach. The S1-MME interface connects the EPC withthe eNBs.

• Serving Gateway (S-GW): The S-GW resides in the userplane, where it routes and forwards packets to and from theeNBs and packet data network gateway (P-GW). It is alsoa mobility anchor point for both local inter-eNB handoverand inter-3GPP mobility. The S-GW is connected to theeNB through S1-U interface and to the P-GW through S5interface. Each UE/M2M device is associated to a uniqueS-GW, which will be hosting several functions.

• Packet Data Network Gateway (P-GW): The P-GW pro-vides connectivity from the UE/M2M device to an PDNby assigning an IP address from the PDN to the UE/M2Mdevice. Moreover, P-GW provides security connectionbetween UEs/M2M devices by using Internet protocolsecurity (IPSec) tunnels between UEs/M2M devices con-nected from an untrusted non-3GPP access network withthe EPC.

As mentioned earlier, this system is considered as “flat” sincefrom a user-plane point of view there are only the eNBs andthe gateways. This leads to a reduced complexity compared toprevious architectures.

C. M2M Communications Over 3GPP LTE/LTE-A Networks

The 3GPP system provides services for M2M communica-tions,1 including various architectural enhancements (e.g.,control plane device triggering), transport, and subscriber man-agement. Different deployment paradigms foreseen for M2Mcommunications between the M2M applications and the 3GPPLTE/LTE-A networks are discussed in the text followed [26].

The most straightforward deployment paradigm is the directmodel, where the application server (AS) connects directly toan operator network in order to communicate with the M2Mdevices without using the services of any external servicecapability server (SCS), as shown in the left-most stack of Fig. 4(or Fig. 4(a)).

1M2M communication is also known as machine-type communications(MTC) in 3GPP.

Fig. 4. Deployment scenarios for M2M communications over 3GPP LTE/LTE-A operator network. (a) Direct model. (b) Indirect model. (c) Hybrid model.

The second deployment paradigm is the indirect model,in which the AS connects indirectly to an operator networkthrough the services of an SCS in order to utilize additionalvalue added services for M2M (e.g., control plane device trig-gering). The SCS can be either

1) M2M service provider controlled, which is deployed out-side the operator domain. The SCS is an entity that mayinclude value added services for M2M communications,performing user plane and/or control plane communica-tion with the M2M device; or

2) the 3GPP LTE/LTE-A network operator controlled andconsidered as an internal network function. In this case,security and privacy protection for communications be-tween the 3GPP LTE/LTE-A network and the SCS isoptional for being trusted.

Yet another deployment paradigm is the hybrid model, wherethe AS uses the direct model and indirect model simultaneouslyin order to directly connect to an operator network to performdirect user plane communications with the M2M devices whilealso using an SCS. From the 3GPP LTE/LTE-A network per-spective, the direct user plane communications from AS andany value added control plane related communications from theSCS are independent and have no correlation to each other eventhough they may be serving the same M2M applications hostedby the AS.

As shown in Fig. 5, two communication scenarios can beenvisioned. One scenario considers communications betweenthe MTC devices and one or more MTC servers in the M2Mapplication domain. In this scenario, an M2M user (e.g., apower plant in the smart grid, or indoor health monitoring athome, etc.) can manage a massive number of M2M devicesthrough M2M server(s). The M2M servers are catered by anoperator, who offers an application program interface (API)for M2M users to access the M2M servers. The M2M serversand the 3GPP LTE/LTE-A infrastructure can be under the sameoperator domain (i.e., the operator domains A and B in Fig. 5can be the same).


Fig. 5. Communication scenarios with MTC devices communicating with theMTC server.

To provide communications between M2M devices andM2M server(s), the public land mobile network (PLMN) en-ables transactions between an M2M device and an M2M server.Furthermore, the PLMN should provide authentication andauthorization for an M2M device before the M2M device cancommunicate with the M2M server [3].

An alternative scenario is depicted in Fig. 6, in which thereis a peer-to-peer model, and M2M devices are communicatingdirectly among themselves without M2M server(s). Communi-cations among M2M devices can be provided within the sameoperator domain or among different ones. Inter-M2M devicecommunications can be either via the mobile network or inad-hoc mode.

D. Service Capability Server (SCS)

As mentioned earlier, the SCS connects to the 3GPP LTE/LTE-A network via MTC-IWF in HPLMN to communicatewith M2M devices used for M2M communications. The SCSprovides an API to allow different ASs to use the capabilities ofSCS. An SCS may be controlled by the operator of HPLMN orby an MTC service provider.

The SCS uses subscription database to authorize connectionson Tsp reference point,2 and to locate the SCS serving node sothat control and data could be routed towards the SCS [27].The SCS subscription identifier may be permanent subscriberdata and can be used for the following purposes: authenticationand charging on the Tsp reference point, charging for the SMSmessages that may be sent towards the SCS, or charging for thedata that may be sent to SMS-SC.

2Tsp is a 3GPP standardized interface to facilitate value-added servicesmotivated by M2M communications (e.g., control plane device triggering) andprovided by an SCS.

The format of the SCS subscription ID can be an interna-tional mobile subscriber identity (IMSI). Temporary subscrip-tion identifiers may be established for security purposes in amanner similar to establishing a temporary IMSI (T-IMSI) fora 3GPP LTE/LTE-A UE.

The MTC devices use SCS public identifier to send SMSmessages and/or IP packets towards the SCS. The SCS publicidentifier may be permanent subscriber data and can be usedfor the following purposes: identification on the Tsp referencepoint, charging on the Tsp reference point, charging for SMSmessages that may be sent towards the SCS (e.g., instead of theSCS subscription ID), or charging for data that may be sent tothe SMS-SC.

The SCS public identifier can be used as a field in triggermessage interactions on the Tsp reference point. The SCS pub-lic identifier may be an MSISDN. In this case, a special rangeof the MSISDN is allocated for the SCS so that core networknode can identify when traffic is destined for an M2M deviceor an SCS. The format of the SCS public identifier may bethe format of a fully qualified domain name (FQDN), a mobilestation integrated services directory (MSISD), an IP address,or an alpha-numeric format. The SCS can have multiple publicidentifiers.

An SCS connects to the SCS serving node for control planecommunications (e.g., including short message exchange). Theother core network nodes use this information to determinethe next hop destination of the control messages in order toreach a particular SCS. The SCS serving node may be a corenetwork node. Furthermore, the SCS serving node can be anMTC-IWF, an MSG, an MME, an SGSN, or an S-GW. An SCSserving node identifier may be temporary subscriber data. Inaddition, the serving node can be the primary node used forrouting control information towards an SCS. Also, it can be anIP address or an ISDN address.

The SCS trigger quota can be permanent subscriber data,indicating the number of triggers that an SCS is allowed torequest per time period. Furthermore, the SCS trigger quotadefines the number of successful triggers that an SCS initiatesper unit of time.

E. 3GPP LTE/LTE-A Architecture Reference Model for M2M

Fig. 7 depicts a typical architecture for M2M devices usedfor M2M connecting to the 3GPP LTE/LTE-A radio accessnetworks.

To support indirect and hybrid models of M2M communi-cations, one or more instances of an MTC-IWF reside in thehome public land mobile network (HPLMN). The MTC-IWFis a functional entity that hides the internal PLMN networktopology and relays or translates signaling protocols used overTsp to invoke specific functionality in the PLMN. An MTC-IWF may be a standalone entity or a functional entity of anothernetwork element [28].

The SCS connects to the 3GPP LTE/LTE-A network viathe MTC-IWF in the HPLMN to communicate with M2Mdevices used for M2M communications. The SCS offers ca-pabilities for use by one or multiple M2M applications. AnM2M device can host one or multiple M2M applications. The


Fig. 6. Communication scenarios of MTC devices communicating with each other without intermediate MTC server.

Fig. 7. 3GPP LTE/LTE-A architecture reference model for M2M communications.

corresponding M2M applications in the external networks arehosted on one or multiple ASs. The interface between SCSand AS is not standardized by 3GPP, but other standardsdevelopment organizations (SDOs), such as the ETSI TC M2M,are expected to standardize the API. It is important to noticethat the development of M2M API should be drawn up forall devices of the identified application areas. Furthermore, auniform protocol view compatible with the current IP suite,will provide protocols at different levels and will be the basisof device interoperability. The development of interfaces willallow all devices, generally developed with a precise service inmind, to embrace a greater variety of applications and to enable

proactive communications of devices which are transparent tothe users.

Tsms is a non-standardized interface that encompasses vari-ous proprietary short message service-service center (SMS-SC)to short message entity (SME) interfaces [29]. Tsms can be usedto send a trigger to an M2M device encapsulated in a mobileterminated-SMS (MT-SMS) as an over-the-top application byany network entity (e.g., SCS) acting as an SME.

As further development of the M2M architecture takes place,further reference points are added. In Fig. 7, blue colored arrowreference points are the new reference points added to facilitateM2M communications over 3GPP LTE/LTE-A systems.


The T4 interface is used by the MTC-IWF to route a devicetrigger as an MT-SMS to the SMS-SC in the HPLMN. T5a/b/cinterfaces provide optimized paths for device trigger deliveryand small data service to the M2M devices. The MTC-IWFuses S6m interface to interrogate the home subscriber server(HSS)/home location register (HLR) for mapping an externalidentifier or a mobile station integrated services digital net-work (MSISDN) to the international mobile subscriber identity(IMSI), authorizing a device trigger to a particular M2M device,and retrieving serving node information. The MTC AAA usesan S6n interface to interrogate HSS/HLR for mapping IMSI toexternal identifier(s) and vice versa.

III. SERVICE REQUIREMENTS AND FEATURES OF M2MCOMMUNICATIONS OVER 3GPP LTE/LTE-A

All kinds of applications can be involved in M2M communi-cations and it becomes massive in terms of diversity across theapplications. However, not all M2M applications have the samecharacteristics [3]. This implies that every system optimizationmay not be suitable for every M2M application with regardto the variety of requirements. In order to cope with thisheterogeneity of requirements, the 3GPP has defined a numberof features [3] (i.e., particular characteristic features associatedwith certain applications), for which the network needs tobe optimized. In this section, first some information relatedto the standardization activities are provided. Then, we giveinformation pertaining to the service requirements. Finally, thecategories of features for M2M communications are specifiedin the last part of this section.

A. Standardization Activities for M2M Communications

Recently, 3GPP, European Telecommunications StandardsInstitute (ETSI), Open Mobile Alliance (OMA), China Com-munications Standards Association (CCSA), and the Alliancefor Telecommunications Industry Solution (ATIS) have startedstandardization processes on the M2M communications. Theactivities of 3GPP is concentrated on the M2M communicationsthat can be supported by mobile cellular networks. In contrast,ETSI addresses the issues on M2M service architecture, itscomponents, and the interactions between three domains, i.e.,M2M device domain, communication network domain, andM2M application domain.

• 3GPP standardization group: In order to take potential ad-vantages of M2M communications over cellular networks,3GPP system architecture working group 2 (SA2) aims touse 3GPP network and system progress that support M2Min evolved packet system (EPS) [8]. In [19], the first studyon M2M was initiated without specifying system charac-teristics. The 3GPP SA2 defined 3GPP network systemimprovements in Release 10 to enable M2M communica-tions in UMTS and LTE-A core networks. The objectiveis to optimize the system design that can mitigate M2Msignaling congestion and network overload problems. ForRelease 10 and beyond, the focus is mainly on studyingthe impacts of standardized system network improvementson the architecture. The purpose of these studies is to

provide essential network enablers for M2M services andto distinguish 3GPP network enhancements required tosupport a large number of M2M devices in the 3GPPnetwork domain.

• ETSI standardization group: The ETSI technical com-mittee (TC) M2M standardization intends to provide anend-to-end overview of M2M standardization, which con-centrates on the service middleware layer that is indepen-dent of the underlying access network and transmissiontechnologies. The goal of the ETSI TC M2M is to supporta wide range of M2M applications and needed functions(e.g., functional architecture and interface standardization)to be shared by different M2M applications.

• OneM2M: The aim of oneM2M is to meet the criti-cal needs for designing a common M2M service layer,which can be easily embedded within different hardwareand software to connect a large number of devices withM2M application servers. Furthermore, oneM2M will de-velop globally agreed-upon M2M end-to-end specifica-tions and architecture principles across multiple M2Mapplications [20].

B. M2M Service Requirements

In this part we identify the service requirements for M2Mapplications.

1) General Service Requirements: Here, general require-ments for the M2M systems are provided. However, there isno need for all particular M2M systems or components of thesesystems to implement every requirement. The followings arethe M2M general service requirements [3]:

• Enable the network operator to identify which individ-ual M2M features are subscribed by a particular M2Msubscriber.

• Provide a mechanism to activate or deactivate M2M fea-tures for the M2M subscribers.

• Identify which individual M2M features are activated fora particular M2M subscriber by the network operator.

• Provide a mechanism for the network operator to controlthe addition or removal of individual M2M features andalso restrict activation of M2M features.

• Provide a mechanism to reduce peaks in data and signalingtraffic when a large number of M2M devices simultane-ously attempt data transmissions.

• Provide a mechanism to restrict downlink data traffic andalso limit access towards a specific APN when the networkis overloaded.

• An M2M device may support the extended access barring(EAB) mechanism.

• An M2M device supporting the EAB mechanism shouldbe able to be configured for EAB by the HPLMN.

• The HPLMN should be able to configure EAB on an M2Mdevice that supports it.

• Provide mechanisms to efficiently maintain connectivityfor a large number of M2M devices.

• The system should provide mechanisms to lower powerconsumption of M2M devices.


2) M2M Device Triggering: Device triggering is one ofthe key requirements for a 3GPP LTE/LTE-A network. Moti-vated by the network, triggered devices should perform cer-tain application-related tasks. For devices that do not have IPaddresses (e.g., 2/3G devices), it is obvious that these devicescannot be attached in the packet switch (PS) domain in orderto be reached by the network. Since the majority of M2Mapplications are data applications, it is necessary for an ap-plication server to reach the device in the PS domain. Thisrequires a device to be allocated an IP address. Therefore,device triggering is related to the devices that are not reachableby the AS or the SCS.

To address this requirement, control plane device triggeringis defined as the mechanism [28] to trigger a device to performspecific applications. To this end, the AS first determines theMTC-IWF that serves the M2M device. Then, AS queries theMTC-IWF for the IP address assigned to the M2M deviceby sending a trigger request message. The MTC-IWF initiatesprocedures for triggering the M2M device. Then, MTC-IWFpasses the device trigger request to the PSDN, which commu-nicates with the RAN. The device trigger request message con-tains information that allows the network to route the messageto an appropriate device and also allows the device to routethe message to an appropriate application [26]. The informationdestined to the application, along with the information to routeit, is referred to as the trigger payload. An M2M device needsto be able to distinguish a mobile terminated (MT) messagecarrying device triggering information from any other type ofmessages.

Device triggering is subscription-based. The informationprovided by the subscription determines whether an M2M de-vice is allowed to be triggered by a specific SCS. Tsp providesconnectivity for the MTC-IWF to connect to one or more SCSsand receive the device trigger request from the SCS.

3) M2M Identifier: A large number of M2M services arecurrently deployed over circuit-switched (CS) GSM architec-ture and therefore use E.164 MSISDNs, although such servicesdo not require dialable numbers. On the other hand, thereis a concern over the numbering requirements and shortageof E.164 MSISDNs for new M2M services. Therefore, 3GPParchitecture has been enhanced to allow delivering communi-cation services using an alternate identifier, which is called anexternal identifier. More information about identifiers relevantfor the 3GPP network are specified in [30].

M2M identifiers can be categorized into:

1) Internal identifiers, which is the identity that the entitieswithin the 3GPP system use for addressing an M2Mdevice.

2) External identifiers, which is the identity used from out-side the 3GPP system, by which an M2M device is knownto the M2M server.

The IMSI is used as an internal identifier within the 3GPPsystems. For the external identifier, a subscription used forM2M communications has one IMSI and may have one orseveral external identifier(s) that are stored in the HSS. Theexternal identifier is globally unique and has two components:the domain identifier used to identify where services provided

Fig. 8. The structure of the IMSI.

Fig. 9. The structure of the MSISDN.

by the network can be accessed (e.g., MTC-IWF providedservices); and the local identifier that is used to derive or obtainthe IMSI. The local identifier should be unique within theapplication domain.

4) Addressing: In M2M communications, each terminal isconsidered as a mobile subscriber and must have a unique IMSI.The current structure of the IMSI allows a network operatorto theoretically support up to 1 billion subscribers, assuming9 digits Mobile Subscriber Identification Number (MSIN). Thisnumber, however, includes both H2H UEs and M2M terminals.The structure of the IMSI is shown in Fig. 8 [31].

In addition, each mobile station in a cellular network musthave at least one assigned MSISDN. The structure of theMSISDN is depicted in Fig. 9 [31]. The current structure ofthe MSISDN, assuming a 9 digit subscriber number (SN), cantheoretically support up to 1 billion subscribers. This number,again, includes both H2H UEs and M2M terminals.

On the other hand, the growth in M2M communications isprojected to reach over 50 billion devices connected to theInternet by 2020 [32]. Therefore, the development of M2Mapplications will have an impact on national numbering planssince devices need to be uniquely addressed in order to com-municate with them, or rather to enable them to communicatewith each other. Thus, the 3GPP studied the problems in [33]and concluded that IMSI is the limiting factor of addressing andmay not be suitable for M2M applications, which may need tomake use of IP addresses. Therefore, 3GPP networks shouldcontain mechanisms to connect with IP-based devices.

The IPv4 protocol identifies each node through a 4-byteaddress. Due to the large number of devices in M2M com-munications, it is well known that the number of availableIPv4 addresses is decreasing rapidly and will soon reach zero.Therefore, other addressing policies should be utilized. To solvethis problem, IPv6 addressing [34] has been proposed. The IPv6address is a 128-bit identifier which should be enough to iden-tify any device in M2M communications in 3GPP LTE/LTE-Anetworks. In fact, its nearly infinite address space enables afuture with ever more ubiquitous computation. Issues suchas connectivity, interoperability, and compatibility with M2Mcommunication networks must be provided. In this context,IETF IPv6 provides a set of protocols over low-power wirelesspersonal area networks (6LoWPAN) [35] that can be utilized to


integrate resource-limited devices into IPv6 networks by sim-plifying IPv6 including compressing addresses, removing op-tions considered rarely used, simplifying packet processing, etc.

C. Features of M2M Communications

To facilitate system optimization, the 3GPP defines 14 fea-tures [3] in M2M communications. These features are listed asfollows.

1) Low Mobility: The low mobility feature is suitable forM2M devices that do not move, move infrequently, or moveonly within a certain area [3], [36]. This feature enables the net-work operator to be able to simplify and reduce the frequencyof mobility management procedures [36].

2) Time Controlled: This feature is suitable for those M2Mapplications that can tolerate to transmit and receive data duringdefined time intervals and can therefore avoid unnecessarysignaling outside these time intervals. The network operatormay allow such applications to send/receive data and signalingoutside these defined time intervals but charge differently forsuch traffic. To make use of time controlled M2M feature,the network operator should reject access requests per M2Mdevice during a defined forbidden time interval. Furthermore,the local network should be able to alter the access grant timeinterval based on local criteria (e.g., daily traffic load, timezones, etc.). The forbidden time interval should not be altered.It is assumed that an access grant time interval will not overlapwith a forbidden time interval.

3) Time Tolerant: The time tolerant feature is suitable forM2M devices that can delay their data transfer. The purposeof this functionality is to allow the network operator to preventM2M devices that are time tolerant from accessing the network(e.g., in case of radio access network overload).

4) Packet Switched (PS) Only: The another M2M featureis packet switched only, which is intended to provide PS-onlysubscriptions with or without assigning an MSISDN [3]. Re-mote M2M device triggering will be supported with or withoutassigning an MSISDN. Remote M2M device configuration willstill be supported for subscription without an MSISDN.

5) Mobile Originated Only: This feature is suitable for usetogether with M2M devices that only utilize mobile originatedcommunications. This is intended for applications where it ispossible to reduce the frequency of mobility management pro-cedures per M2M device; the network should be able to providea mechanism for the network operator to dynamically configurethe M2M devices to perform mobility management proceduresonly at the time of mobile originated communications.

6) Small Data Transmission: This feature is suitable for usewith M2M devices that transmit small amounts of data and canthus ensure minimal network impact (e.g., signaling overhead,network resources).

7) Infrequent Mobile Terminated: This M2M feature, i.e.,infrequent mobile terminated, is suitable for M2M devices thatmainly utilize mobile originated communications and thus thenetwork operator is able to reduce the frequency of mobilitycontrol information per M2M device.

8) M2M Monitoring: This is suitable for monitoring thestate of the M2M devices and possible events that occur in

the network. This is a feature vital to all M2M applications toguarantee that the deployed devices are operational.

9) Priority Alarm Message (PAM): The priority alarm mes-sage M2M feature is suitable for use with M2M devices thatissue a priority alarm in the event of theft, vandalism, or otherneeds for immediate attention. In addition, this feature is used inapplications, which require attention but are not too critical. Anexample is the detection of a leak, which requires some valvesor switches to be closed. In addition, the M2M devices mayissue a priority alarm even when it cannot use normal servicesfor some reasons (e.g., access time not allowed, roaming notallowed).

10) Secure Connection: The secure connection M2M fea-ture is suitable for M2M devices that require a secure connec-tion between the M2M devices and M2M server(s). This featureapplies even when some of the devices are roaming.

11) Location Specific Trigger: This feature is intended forapplications where the M2M devices are known to be in aparticular area and thus the M2M device triggering is performedby using the location information.

12) Network-Provided Destination for Uplink: This featureis suitable for use with M2M applications that require all datafrom an M2M device to be directed to a network provideddestination IP address. For uplink M2M communications, thenetwork should use a destination IP address.

13) Infrequent Transmission: This feature is intended forM2M devices with long periods between two subsequent datatransmissions. The network should provide resource only whena transmission occurs.

14) Group-Based Policing and Addressing: This feature issuitable for applications with an M2M group where devicesshould be optimized to handle in groups for tasks. The networkoperator may use group-based policing feature to perform acombined QoS policing. Group-based addressing M2M featureis suitable for applications with an M2M group, in which thenetwork operator should optimize the message volume whenM2M devices need to receive the same message.

IV. CHALLENGES OF M2M COMMUNICATIONS

OVER 3GPP LTE/LTE-A NETWORKS

In M2M communications, the necessity for supporting a largenumber of M2M devices is a challenging issue. To provide ubiq-uitous wireless connections for M2M devices, 3GPP LTE-Aintroduces a heterogeneous network (HetNet) as a special net-work architecture for this purpose [5], [37], [38]. The HetNetcomprises four parts: conventional macrocells formed by eNBsof E-UTRA, picocells formed by small transmission powereNBs deployed underlay macrocells to share traffic loads ofmacrocells, femtocells formed by HeNBs to enhance signalstrength in indoor environment, and RNs deployed in coverageedges of macrocells (see Fig. 5).

Higher layer connections among all above stations can beprovided by 3GPP LTE/LTE-A infrastructure. On the otherhand, in the HetNet, interference arises between macrocellsand small cells, leading to the degradation of network en-hancement. However, by applying recent solutions [39] forpicocells, [39]–[41] for femtocells, and [42], [43] for RNs,


interference problems can be effectively mitigated. Conse-quently, ubiquitous connections among all M2M devices canbe provided by attaching to these stations. However, it does notensure a successful implementation of M2M communicationsin the 3GPP LTE/LTE-A and therefore some challenges arestill there.

One major challenge lies in the air interface. In order tomeet requirements defined by International Mobile Telecom-munications Advanced (IMT-Advanced), the air interferencein LTE/LTE-A has been designed for broadband applications,while most M2M applications transmit and receive smallamounts of data, leading to an unreasonably low ratio betweenpayload and required control information due to the use of non-optimized transmission protocols. In addition, the other impor-tant aspects, such as the need for low-energy and low-latencydevices, have to be considered for M2M communications.Therefore, efforts have been made by 3GPP under the umbrellaof MTC study and work items to begin the standardizationprocess for the air interface of M2M communications [8], [44].Besides, in order to support a large number of M2M devices,the efforts were also made to address the issues, such as vast di-versity of M2M service characteristics, the need for enhancingenergy efficiency, and coexistence with current communicationsystems. Some solutions have been proposed by using cooper-ative techniques among stations [45]–[49], and a group basedoperation of M2M devices, to be discussed in the text followed,has been regarded as a promising solution [3], [50]–[52] tosupport device-to-device (D2D) communications in the future.

A. Group-Based Operations of M2M Devices

The primary goal of grouping a number of M2M devicesis to alleviate the signaling congestion on the air interface byreducing communication loads between an M2M device and3GPP E-UTRA and EPC. Moreover, one of the most importantrequirements in cellular M2M communications is to reducepower consumption [53]. This requirement can be met by em-ploying group based operation, where a group header collectsrequests, uplink data packets, and status information from M2Mdevices in the group, and then forwards such traffic to a stationof 3GPP LTE/LTE-A. Furthermore, downlink data packets andcontrol messages can be relayed by the group header from astation of 3GPP LTE/LTE-A to M2M devices in the group. ForM2M communications, devices can be grouped logically basedon service requirements or based on physical locations of M2Mdevices.

One of the major applications of M2M communications isto gather measurement data from M2M devices. To logicallygroup M2M devices, it should be mentioned that the traffic ofsuch application typically has the characteristics of periodicalpacket arrivals, small data transmissions, and some given jitterconstraints. Therefore, to develop practical scheduling schemesthat support a large number of M2M devices with small datato meet the corresponding jitter constraints is a challengingissue. To tackle this challenge, M2M devices with similarcharacteristics can be merged into a group logically. Hence, theresources for these M2M devices can be scheduled on the basisof groups [52].

To support physically grouped M2M devices, leveraging onthe presence of more capable nodes to help others in reliably de-livering their data is a good approach in a heterogeneous M2Mcommunications in 3GPP LTE/LTE-A networks. However, thechallenging task is how to place a number of such nodes in anenvironment so as to improve the overall network performance.It is foreseen that M2M communications will add some featuresto current cellular systems, such as WiMAX 1.0 system basedon IEEE 802.16-2009 [6] or WiMAX 2.0 system based on IEEE802.16m [54].

B. Device-to-Device Communications

In a cellular network, direct communications between mobiledevices are not permitted. Traffic should be routed via a corenetwork even if a source and a destination are very close toeach other. However, by allowing two physically close usersto communicate directly, instead of being relayed by a corenetwork, Device-to-Device (D2D) communication may achievelower power consumption, less transmission delay, and lessload distribution of data servers for locally processable M2Mtraffic. To enable direct communications among M2M devices,a new communication scheme (e.g., a new air interface standardwith a new radio frame structure) will be defined in 3GPPRelease 12, to establish communications between end devices[55]–[57]. The D2D communications can improve the effi-ciency [58]–[62] by exploiting the high channel quality of shortrange D2D links. Furthermore, by reducing transmission power,the battery life of M2M devices can be significantly prolonged[63]–[65]. The other advantages of D2D communications overcellular networks include more efficient resource (e.g., spec-trum) utilization because of direct routing of D2D traffic [63]–[68], and improved content delivery performance by usinginter-recipient transmissions [69]–[72]. Therefore, the 3GPPintends to provide the interfaces and protocols for direct packetsexchanges among M2M devices to enable communications forM2M devices in LTE/LTE-A networks.

C. Cognitive M2M Communications

It is expected that a large number of M2M devices willbe deployed to support various applications. Even though thesignaling congestion can be potentially alleviated by the groupbased M2M devices, if the number of M2M devices growsrapidly, this problem may not be easy to solve. In this situation,it may be needed to deploy more E-UTRA stations to dilute traf-fic of UEs and M2M devices. To tackle signaling congestion,E-UTRA stations for UEs and E-UTRA stations for M2Mdevices may need to work together. However, under this cir-cumstance, interference between conventional H2H communi-cations and M2M communications turns out to be a challengingissue. A centralized coordination may help to reduce the inter-ference. However, due to the fact that centralized coordinationcreates significant signaling overhead and management burden,this scheme was not widely adopted. Therefore, for interferencemitigation between H2H and M2M communications, an appro-priate method is to employ a distributed resource management,and a promising solution known as cognitive M2M communi-cations [74], [75] is particularly useful.


To support wireless transmissions for a large number of de-vices, the M2M communications can work based on a randomaccess channel (RACH). The advantage of using the RACH isthat the devices can compete and access an available channel forwireless transmission independently without coordination andcentralized control. Furthermore, the RACH mechanism haslow communication and signaling overheads. This mechanismis found suitable for M2M communications as the data to betransmitted from M2M devices is usually small in amount.However, the RACH mechanism was designed to operate onthe shared channels and the number of available shared chan-nels is limited, and they also have to be shared with H2Hcommunications. Therefore, an appropriate method to utilizethe spectrum for M2M communications is required to supportvarious wireless applications.

Cognitive radio (CR) has been introduced to improve thespectrum utilization and transmission efficiency. In cognitiveradio, unlicensed users (i.e., secondary users) are allowed toaccess the spectrum allocated to the licensed users (i.e., primaryusers) [73], as long as the transmissions of the licensed usersare not interfered. Therefore, cognitive radio is a promisingtechnique for M2M communications by allowing the devicesto opportunistically access the channel, when such a channelcurrently is not used by the primary users. It is expected thatcognitive radios can be an effective solution for the practicalimplementation of M2M networks [74].

D. Resource Allocation With QoS Provisioning

Quality of service (QoS) provisioning is one of the mostimportant requirements and challenging issues in M2M com-munications. M2M communications feature no or little humanintervention, low power, high reliability, and low complexity.The lack of power supply is always a challenge that limits theperformance of wireless communication devices, for both UEsand M2M devices. In H2H communications, battery can easilybe changed in a handset. However, in M2M communications,saving energy for devices is more important than increasingthe data throughput since M2M devices may be deployed indangerous or non-reachable places. Consequently, the batteryin an M2M device should be used for a relatively long time.Furthermore, a typical M2M communication network may con-sist of a large number of devices. To allocate radio resourcesefficiently while ensuring QoS requirement for reliable com-munications is an essential and challenging issue [76], [77]. Inaddition to energy consumption and reliability, complexity isanother consideration in the design of M2M communications.Sophisticated algorithms should be avoided in M2M commu-nication devices that should be simple and yet effective, whichmay not be the same as those in H2H communications.

For M2M devices, some applications (e.g., traffic control,robotic networks, and e-health) need mobility support [78].Some other applications (e.g., data traffic from meters in smartgrid or navigation systems) require strict timing constraints,and catastrophes may occur if timing constraints are violated[52]. Therefore, in M2M communications, providing diverseand strict QoS guarantees is one of the most important and chal-lenging issues [76]. Such diverse QoS requirements particularly

Fig. 10. Illustration of transmission links in 3GPP LTE/LTE-A networks withM2M communications.

need for appropriate resource allocation that can be applied toM2M communications in LTE and LTE-A cellular networks.In [51], joint massive access control and resource allocationschemes was proposed which perform machine node grouping,coordinator selection, and coordinator resource allocation, andalso determine the proper number of groups under a 2-hoptransmission protocol, to minimize total energy consumptionin both flat and frequency-selective fading channel.

Two major methods can be considered for radio resourceallocation between M2M and H2H communications [79]. M2Mand H2H communications can access the same radio resourcesvia orthogonal channels. Although this scheme is simple, itleads to a low spectral efficiency. Another method is to use ashared resource allocation scheme. In this way, M2M devicescan reuse the radio resources allocated to H2H communicationsto achieve a higher spectral efficiency. However, this mayincrease the interference level in comparison with orthogonalchannel allocation.

The minimum resource unit for downlink and uplink trans-missions is referred to as a resource block (RB). One RBnormally consists of 12 subcarriers (180 kHz) in the frequencydomain and one subframe (1 ms) in the time domain [5].When an M2M device has packets to transmit, it performsrandom access (RA) using the physical random access channel(PRACH) during an allowable time slot, called an access granttime interval (AGTI) or RA opportunity (i.e., RA-slots). InM2M communications, generally small amounts of data needto be transmitted. Although the data size is small, when a largenumber of M2M devices try to communicate over the samechannel, the devices should contend to access the shared radiochannels, causing the network overload problem.

On the other hand, in collocated H2H and M2M communi-cations networks (as shown in Fig. 10), various types of linksexist and they are listed as follows:

• The eNB-to-UE link;• The eNB-to-M2M device link;• The eNB-to-M2M gateway link;• The M2M gateway-to-M2M device link; and• The M2M device-to-M2M device link.


When radio resources are shared among these links, inter-ference arises and poses a big challenge. Thus, it is neededto efficiently partition the radio resources in such networks[79]. The purpose of radio resource partition is to apply therestrictions to the radio resource management between H2Hand M2M devices. Given the characteristics of links, the re-strictions can be either on the transmit power or in the formof restrictions on available radio resources. Such restrictionsimprove the signal-to-interference-plus-noise ratio (SINR), andconsequently to the cell edge performance and coverage.

E. Random Access Channel Congestion

In LTE/LTE-A systems, random access procedure [13], [80]is generally performed when an M2M device turns on and doesnot have uplink radio resources assigned to send user data orcontrol data (e.g., a channel measurement report) to the eNB.Furthermore, random access procedure is used by the M2Mdevice in order to perform handover from one eNB to anothereNB, or to acquire the uplink timing synchronization. Whenthe number of UE/M2M devices is an acceptable value, randomaccess provides efficient request delivery. However, the numberof M2M devices in a cell is expected to be much larger thanthe number of UEs. When a large number of M2M devicestry to access the network simultaneously, it leads to a lowRA success rate, and thus both M2M devices and UEs maysuffer continuous collisions at the PRACH [17], [81]. This maycause packet losses, extra energy consumption, waste of radioresources, and unexpected delays. The channel can be furtheroverloaded when the M2M devices repeat their access attemptsafter collisions. Thus, effective overload control mechanismsare required for RA-based M2M communications. In [82],the feasibility of semi-persistent scheduling for voice over IP(VoIP) by random access was investigated and its performancein terms of throughput of random access and traffic channels,and random access delay was evaluated. Furthermore, besteffort application for random access in wireless multimedia net-work [83] and distributed random access scheduling exploitingthe time-varying nature of fading channels for multimedia traf-fic in multihop wireless network [84] have been studied. In thenext part of this section, we review the existing mechanisms forcontrolling PRACH overload to support M2M communicationsin LTE/LTE-A networks.

To support M2M communications in LTE/LTE-A, the fol-lowing solutions have been proposed for controlling PRACHoverload [46], [47].

1) Backoff Scheme: The backoff scheme is used to delay therandom access (RA) attempts of H2H and M2M devicesseparately. In this scheme, the backoff time for the H2Hdevices is set to a small value (e.g., the maximum backoffduration 20 ms); while the backoff time for the M2Mdevices is set to a large one (i.e., an upper limit for theretransmission intervals, which can be as long as 960 ms).This scheme is effective in low channel overload, andthus it can alleviate collisions in these situations. How-ever, it cannot solve the congestion problem in heavyoverload situations when a massive number of M2Mdevices initiate RA at the same time. Seo and Leung [85]

studied the uniform backoff in LTE relative to the expo-nential backoff in IEEE 802.16 WiMAX. Furthermore,these authors investigated a multipacket reception (MPR)slotted ALOHA system using binary exponential back-off (BEB) algorithm with infinite buffers in the mobileterminals [86].

2) Slotted Access Scheme: In this scheme, each M2M de-vice is allowed to perform RA only in its dedicated accessslot. At other times, the M2M devices are in sleep mode.The M2M devices can calculate the allowable access slotsthrough its ID and RA-cycle. The eNB broadcasts theRA-cycle, which is an integer number multiple of a radioframe. The number of unique RA-slots is proportional tothe RA-cycle length and the number of RA-slots withina radio frame. PRACH will be overloaded when thenumber of M2M devices in a cell is greater than the totalnumber of unique RA-slots. In this case, several M2Mdevices share the same RA-slot and collisions may occur.Increasing the RA-cycle can reduce collision but createsunacceptable delay for an RA request. The impact of thenumber of transmission attempts on the throughput anddelay of the slotted ALOHA based preamble contentionin the LTE-A random access system investigated in [87].

3) Access Class Barring (ACB) Scheme: The ACB-basedscheme was originally designed for the access controlof devices. In this scheme, an eNB broadcasts an accessprobability (AP) and access class (AC) barring time. Inthe ACB, there are 16 ACs. AC 0–9 represents normal de-vice, AC 10 represents an emergency call, and AC 11–15represents specific high-priority services. When a deviceinitiates RA, the device randomly draws a value betweenzero and one, and compares this with AP. If the numberis less than AP, the device proceeds to the random accessprocedure. Otherwise, the device is barred for an AC bar-ring duration. The ACB scheme can deal with excessivePRACH overload by setting an extremely small value ofAP. However, a small AP leads to unacceptable delay forsome devices.

From the Release 10 and onwards, the existing ACBscheme has been extended to allow one or more new ACsfor M2M devices, and an individual access barring factorcan be assigned for each of the classes. Furthermore,3GPP also proposes an extended access barring (EAB)scheme [88], in which when EAB is activated, the devicesbelonging to certain ACs (i.e., delay-tolerant devices)are not allowed to perform RA. However, without coop-erations among eNBs, devices within dense area suffersevere access delays. To facilitate devices escaping fromcontinuous congestions, [49] proposed the cooperativeACB for global stabilization and access load sharing toeliminate substantial defects in the ordinary ACB, thus,significantly improving access delays.

4) Pull-based Scheme: The pull-based scheme is a central-ized control mechanism, in which the M2M server re-quests the eNB to page the intended M2M devices. Uponreceiving a paging signal from the eNB, the M2M devicewill initiate RA. In this scheme, the eNB can control thenumber of devices to be paged by taking into account


the PRACH load and resource availability. However, thisscheme requires extra control channel resources to page ahuge number of M2M devices.

5) Dynamic PRACH Resource Allocation Scheme: In thisscheme, the eNBs can dynamically allocate PRACH re-sources based on PRACH overload condition and overalltraffic load. When a subframe is used for the PRACH, partof that subframe cannot be used for data transmission.Therefore, to meet a given QoS requirement, a certainnumber of subframes should be used for the PRACH.Although dynamic allocation of PRACH resources canbe applied in most cases, the efficiency of this scheme islimited by the availability of additional resources. A self-optimizing algorithm was proposed in [89], where theeNBs can automatically increase or decrease the numberof RA-slots based on channel traffic load.

F. Reliable Data Transmission

In M2M communications in 3GPP LTE/LTE-A, each trans-mission of an M2M device may only carry a small amount ofdata due to the small data transmission feature. Therefore, ahigh peak data rate transmission scheme may not be necessaryfor M2M devices. Instead, reliable transmission (i.e., low biterror rate, and low latency) are essential. Network coding hasbeen shown to provide an effective means for efficient reliabledata dissemination and to require little coordination amongnodes. Furthermore, random data combination is a lightweight,yet effective, mechanism to provide adequate reliability anderror control with little overhead. These paradigms have beenshown to greatly improve the performance of dissemination inhomogeneous networks, but extension of these techniques toheterogeneous scenarios like M2M communications in 3GPPLTE/LTE-A has not yet been addressed. Finally, for denselydeployed nodes with limited individual capabilities in suchnetworks it makes sense to look into distributed processingparadigms for decoding.

G. Energy Management

Energy management ranging from harvesting, conservation,to consumption is a major issue in the M2M communicationcontext in 3GPP LTE/LTE-A networks. Reducing power con-sumption is one of the major challenges in M2M communica-tions. In the literature, various energy-efficient MAC protocols[16], [90], [91] exist that can be implemented in M2M system tosave energy. However, the development of novel solutions thatmaximize energy efficiency is essential. Network protocols willhave to deal with inherent characteristics of M2M communica-tions such as long sleep cycles, energy and processing powerconstraints, time-varying radio propagation environments, andtopologies varying with node mobility.

In this regard, current technology is inadequate, and ex-isting processing power are too low to meet future require-ments. Therefore, the development of novel, more efficient,and compact energy storage sources such as fuel cells andprinted/polymer batteries are paramount. Furthermore, devel-oping new energy generation devices coupling energy trans-

mission methods or energy harvesting using energy conversion,as well as extremely low-power circuitry and energy efficientarchitectures and protocols will be the key factors for rollout of autonomous and smart M2M communications in 3GPPLTE/LTE-A networks. In order to realize the decoupling ofM2M applications and services, novel energy efficient servicediscovery mechanisms must be designed to minimize humanintervention during configuration and management phases [92].

H. Self-Management Capabilities

In order to support the expected huge scale of M2M com-munications in 3GPP LTE/LTE-A, devices will need to self-manage without external intervention [93]. Due to multi-pathfading, path loss, and shadowing phenomena in radio chan-nels, self-management learning is essential when an M2Msystem encounters with such dynamic and unstable environ-ment. Therefore, when trying to apply M2M communicationsin 3GPP LTE/LTE-A networks, we have to face the exponentialgrowth in complexity that the connection of large number ofdevices will bring, which will call for context awareness, self-organization, self-management, self-optimization, self-healingand self-protection capabilities. In a wireless context, the in-creased topology dynamics due to channel fluctuations andpossible device mobility, as well as the loss of signalingand control messages, make these issues all the more challeng-ing task.

M2M communications encompass a huge sensor network,with immense amounts of sensor data from various sensors,meters, appliances and electrical vehicles. Data mining andpredictive analytics are essential for efficient and optimizedoperation of such network. A key question is how to analyzeand process these data in an efficient and timely manner.Various machine-learning techniques can be used in this regardfor data analysis and processing.

V. M2M COMMUNICATIONS APPLICATIONS

The emergence of low-power and low-cost sensors and ac-tuator nodes (such as radio frequency identification, or RFIDtags), which are capable of communicating wirelessly usingstandardized interfaces and protocols, and increased computingcapability make it possible to develop a large number of appli-cations for M2M communications in 3GPP LTE/LTE-A. TheseM2M applications significantly improve the quality of our lifeat home, at work, in traveling, etc. These M2M applicationswere proposed based on the possibility for a large number M2Mdevices to communicate with each other and to convey theinformation they perceive from the surroundings where a widerange of applications are deployed. These M2M applicationscan be classified into the following categories:

• e-Health;• Smart environment (home, office, and plant);• Intelligent transportation;• Security and public safety; and• Other futuristic applications.Some of the applications that we are talking about are rather

straightforward or close to our current living style, and some


Fig. 11. M2M applications and relevant scenarios.

others may be futuristic such that we can only imagine at themoment, as the technologies are not available yet and we arenot ready for their deployment (see Fig. 11). In the followingsubsections, we will discuss all of them.

A. e-Health

Various advantages of the M2M communications can beuseful to the healthcare applications, and those M2M appli-cations can include tracking and monitoring of patients anddrugs, identification and authentication of patients in hospitals,automatic medical data collection and retrieving [94].

1) Tracking and Monitoring: Tracking is a function aimingat the identification of a person or object in motion. Thisincludes real-time position tracking, such as the case of trackinga patient or tracking the motion of organ (or a segment ofan organ) in a patient. In terms of physical assets, M2Mcommunications can also be used in continuous inventory/stocktracking (e.g., for goods availability maintenance), and sub-stance tracking to prevent left-ins during a surgery. In the caseof monitoring [95], the M2M applications in e-health enableremote monitoring of patient health and fitness conditions viaM2M sensor nodes, alerting services when elderly people fall,and triggering alarms when critical conditions are detected.The M2M communications can also help in remote medicaltreatments or operations.

2) Identification and Authentication: Identification and au-thentication in healthcare are needed in a variety of forms,

including patient identification to reduce the risk of wrongtreatments to patients (in terms of drug/dosage/time/procedure),real-time based electronic medical record/data maintenance,and privacy protection against possible medical data intrusion/leakage. Identification and authentication are most commonlyused to grant security access (e.g., to restricted areas andcontainers).

3) Data Collection: Automatic data collection and transferis required to reduce patient processing/treatment time and toimplement medical treatment automation (including medicaldata retrieving), medical care service and procedures auditing,and medical inventory management. Depending on the typesof M2M applications, data collection may proceed in differentways [9]. For example, important and vital information ine-health should be delivered as soon as detected, whereas theenergy consumption data at home may be collected only oncea time. The M2M system should support different ways ofdata delivering/reporting requested by the M2M applications aslisted below [9]:

• A periodic reporting with the time period being defined bythe M2M applications;

• An on-demand reporting with two possible modes, onebeing instantaneous collecting and reporting of data, theother being reporting of data that were pre-recorded at aspecific time period;

• A scheduled reporting; or• An event-driven reporting.


4) Sensing: Sensor devices enable many functions relatedto patients in healthcare, in particular on diagnosing patientconditions, providing real-time information on patients’ bio-logical data [94]. A body area network (BAN) of sensors istypically deployed around a patient to record his/her biologicalparameters, such as blood pressure, body temperature, heartrate, weight, etc.

In order to enable the M2M applications for e-health andto acquire the information on a patient’s health, the BAN ofM2M sensors have to be used. For this reason, the patient ormonitored person typically wears one or more M2M sensordevices that record health indicators (e.g., body pressure, heartrate, etc.). Due to the strict constraints on form factor andbattery consumption of these M2M sensors, it is expected thatthey require to forward the collected data with some short rangetechnology to a device that can act as an M2M aggregatorof the collected information and an M2M gateway. Then, theLTE/LTE-A as an access network connects the M2M gatewayto the M2M core network. Through the M2M core network, theM2M gateway is connected to the M2M server that stores andpossibly reacts to the collected data and subsequently the M2Mapplication user (i.e., healthcare remote monitoring center). Inthis scenario, the gateway could be a fixed device such asa PC or a mobile device like a cell phone or a standalonedevice carried on a keychain or worn around the patient’s wristor neck.

B. Smart Environment

With recent advances in wireless communications, intelligentsystems, sensor networks, the quality of human life has beenimproved significantly in every aspect. A futuristic smart citybased on M2M communication technologies, first proposed byIBM as one of its most important strategies, may generatean enormous amount of information, and it is capable ofcollecting, managing, and taking advantage of the informationto implement automations in our daily life. Making betterdecisions based on real-time information leads to significantlyreduced living costs, and more efficient utilization of naturalresources. To this end, the M2M communications can be usedevery where around us, at homes, in offices, in industrial plants,and every corner of cities, to realize a smart environment.

1) Smart Homes, Offices, and Shops: We are living in an en-vironment surrounded by various electronic appliances, such aslights, air conditioners, heaters, refrigerators, microwave ovens,and cookers. Sensors and actuators of M2M communicationsare installed in these devices to make a more efficient utilizationof energy and also to make our life more comfortable. Heatingand cooling in homes can be adjusted to the weather conditionsto maintain a desirable temperature. The lighting in roomscan be adapted to the time of a day and to the number ofoccupants inside the rooms. Domestic incidents, like fire, a fallof elderly people, or burglary can be detected with appropriateM2M monitoring and alarm systems associated with the M2Mdevices in place. Energy saving can be improved by automat-ically switching off the electrical devices when not in use.Consequently, the power consumption costs can be reduced byusing electric appliances only when the energy price is cheaper,

a function that can be implemented with the help of smart gridtechnology [103].

Smart cities, as a new concept in urban planning, haveattracted a lot of attention recently. Connected by M2M com-munication technologies, the people living in the urban areaswill be able to enjoy the life style of the smart cities in the future[104]. A lot of new business models will be created due to theexistence of the smart cities in the years to come. Imagine ascenario that people are going shopping in a smart city, whereadvertisements can be delivered to a customer based on his/herparticular taste or hobby, telling him/her about a store aroundthe corner that is selling the items the customer is just lookingfor with a significant discount available.

Once people enter the stores, M2M communication infras-tructure can provide unique and innovative communicationchannels and everything is connected, including beverage cool-ers and freezers, and people can sense and thus be aware of thedrinks they want in the beverage coolers and freezers with theirlocation information displayed in the M2M mobile terminals at-tached to the glasses or watches. The M2M technology can alsooptimize inventory, provide automatic updates on maintenanceneeds, or even handle payment services. This allows retailers tocut down the cost, while ensuring the customers’ satisfaction.

2) Smart Lighting: Another M2M application is to imple-ment smart lighting systems for the homes, offices and streets.Smart lighting can also attribute to a significant improvementon energy saving in the cities around the world. Due to therapid growth of the urban population, at present about half ofthe world population live in cities. This trend will continue toescalate with an estimation that by 2050 about 70% of peoplewill live in cities and the number of mega-cities with theirpopulations more than 10 million will increase. This undoubt-edly poses a new challenge to the city management, intelligentbuilding, and environment protection, especially in energy man-agement efficiency. Therefore, a highly efficient illuminationsystems in streets of a city is extremely important to reducecarbon emission, which has be put into the agenda for many bigcities in the world. Apart from energy saving through improvinglighting systems, smart lighting could contribute to another40% of electrical energy saving through the implementation ofadvanced lighting management systems based on M2M tech-nology [105]. More specifically speaking, the power consump-tion reduction policy in Europe has been extended from cities tothe street lighting systems in order to reach the desirable energyefficiency for Europe in 2020, and the low-carbon Europeaneconomy by 2050 [106]. Therefore, M2M technological inno-vations, such as remote street light control that allows the M2Muser applications such as the city lighting control managers tomonitor and control street lights by smart phones, turning themon or off automatically depending on local illumination levelsand traffic intensity will soon be widespread.

3) Smart Industrial Plants: Industrial M2M communica-tions will enhance intelligence in control systems to improvethe automation in industrial plants by exchanging and gath-ering information among sensors, actuators, and RFID tagsin M2M communications associated with the products. TheseM2M devices can monitor vibration in an industrial machinery,and a warning can be signaled or even the whole production


process can be made stop if it exceeds a specific threshold.Once such an emergency event is triggered, the M2M devicesimmediately connect to the M2M controller server and transmitthis event-related information to the M2M server through the3GPP LTE/LTE-A core network [96]. If the robots detect anemergency shutdown event, M2M controller server will stoptheir working immediately. The M2M application user (e.g.,plant manager) can also see the status of the Enterprise Re-source Planning (ERP) orders, the production progress, theM2M device status, as well as a global view on all factories. Itcan also predict the consequence of device malfunctions in theproduction lines based on the information stored in the M2Mcontroller server.

4) Smart Water Supply: Nowadays, demand for water con-tinues to grow rapidly, and worldwide water usage is increas-ing at a rate twice as fast as the population growth. Manycorporations rely on water for their critical functions frommanagement to manufacture. However, most people do notknow how much water is wasted. As a matter of fact, a largepercentage of world’s water disappears from aging and leakypiping systems, costing a huge amount of money every year.To combat this problem, smart cities must be able to monitorwater supply closely to ensure that there is an adequate watersupply to residence and business. Smart cities equipped withM2M sensors can accurately monitor water piping systems anddiscover water leakage at the very first moment. These M2Msensors measure pipe flow data regularly and propagate alertsand transmit an emergency message to the M2M controllerserver via the 3GPP LTE/LTE-A core network if water usage isbeyond an estimated normal range. This M2M communicationcapability allows a smart city to determine the locations ofleaking pipes to prevent a waste of precious water resource.

5) Green Environment: Managing electric devices to max-imize energy efficiency is one of the most important issuesto establish the green cities. Recently, smart grid has beenreceived a considerable attention as an intelligent solution tomanage electric power consumption. The main concept of smartgrid is to employ intelligent communication networks to meetthe pressing demands for efficiency improvement on powergeneration, distribution, and consumption sectors with the helpof M2M communications. In addition, smart grid works basedon an environmentally friendly infrastructure in order to keepits energy wastage as low as possible for minimizing CO2

emission. To realize this goal, it is of great importance to equipsmart grid with the abilities to autonomously collect data fromvarious sectors of the grid systems, analyze data on energyusage in real time, and self-configure its operating parametersto achieve the goals.

For the aforementioned M2M applications can be consideredthe following structure. The M2M devices (e.g., a home appli-ance, smart lighting system, water piping system, etc.) are con-nected to a smart meter and their information is measured andcollected by the smart meter. Due to the resource-constrainedsensors associated in the M2M devices, wireless communica-tions technologies based on Zigbee can be established amongM2M devices and a smart meter. To collect data packets fromsmart meters to the M2M gateway short-range communica-tion technologies (e.g., WiFi) could be utilized. The received

packets are stored in the buffer of the M2M gateway. Differenttypes of data packets with different QoS requirements can bestored in different buffers. The 3GPP LTE/LTE-A transceiverof the M2M gateway receives a head-of-queue packet from thebuffer and transmits it to a 3GPP LTE/LTE-A eNB. The 3GPPLTE/LTE-A eNB is in charge of bandwidth allocation for thedata transmission of each M2M gateway. After the data packetssent from M2M gateway are received by the eNB, they arethen forwarded to the M2M control center. The M2M serveris located at the M2M control center for processing and storageof the received data. This data is used to monitor, control, andcommand for the M2M devices.

C. Intelligent Transportation

With an increasing number of vehicles on the road, the trans-portation and logistics services represent another big marketfor M2M communication technology. Advanced vehicles (e.g.,cars, trains, trucks, buses, motor-bikes, and container lorries)equipped with M2M sensors, actuators, and processing power,become M2M communication entities. Furthermore, roads andtransported goods use M2M sensors and tags that can also sendvaluable information to traffic M2M control centers and trans-portation companies to route the traffic, monitor the status ofthe transported goods, seamlessly track the physical locationsof fleet vehicles, and deliver updated schedule information tocustomers. More M2M applications in the transportation andlogistics services are discussed below.

1) Logistics Services: Goods supply chain can work in amore efficiency way as M2M communications provide possi-bility to track the status of goods in real-time via the M2Msensors associated with them. The M2M logistics enables totalsurveillance on the status of goods, raw materials, products,transportation, storage, sale of products, and after-sales servicesby keeping an eye on temperature, humidity, light, and weight,etc. If the status has some problem, the M2M devices canautomatically send an alert to the M2M server via the 3GPPLTE/LTE-A core network. Furthermore, it is also possible totrack the inventory in a warehouse so that stockholders andenterprises can respond to the market dynamics and to decidewhen to refill and when to go on-sale. Therefore, this cansignificantly reduce the space of warehouse, the waiting timeof customers, and the number of the employees to save theoperational costs for business entities [97].

2) M2M Assisted Driving: Intelligent transport systemsbased on M2M technologies along with the roads equipped withM2M sensors and actuators can help to optimize and controlthe traffic flows, and vehicle navigation/safety, to reduce thecosts and carbon emissions. A sleepy driver can be alerted andwarned by the driving behavior M2M monitoring systems toavoid possible traffic accidents. M2M communication systemscan also automatically call for help when they detect an acci-dent, and they can alert people if they detect hazardous ma-terials on vehicles. Furthermore, the governmental authoritiescan overview road traffic patterns for traffic route planningpurposes. Moreover, the information about the movement ofvehicles transporting goods together with the information aboutthe types and status of the goods can be used to predict the


delivery time of goods and the time when the traffic peaks willarrive or end.

3) Fleet Management: Today, a large number of containercargo ships are traveling through international waters. Thesecontainer cargo delivery services may risk theft, physical dam-age, delivery delays, piracy, and even ship sinking. M2Mtechnology provides solutions that are being used in fleetmanagement to acquire a better control where cargos can berapidly delivered across different continents. The M2M appli-cations enable the tracking of vehicles and cargo containers tocollect the data on locations, fuel consumption, temperature,and humidity, in order to increase fleet safety, reduce theaccident rates, and increase the productivity of a fleet company.With more precise information, greater control, better resourcemanagement, and higher cost effectiveness, a fleet business canbe able to maintain its competitiveness with the help of M2Mtechnology.

4) e-Ticketing and Passenger Services: Ticketing systemsof traditional public transport systems are based mainly onmanual systems, and in some cases semi-automatic and/orautomatic systems are used for fare collection. In most cases,they involve tedious, time-consuming, and stressful labors dueto the need of human interventions. As a better choice, thee-ticketing model can be utilized, which comprises of a NearField Communications (NFC) enabled device as a M2M sensornode for scanning passenger’s identity at the entrance/exit ofthe stations. Once a mobile phone with NFC capability isscanned in the pay station, the code number of the stationis sent to the M2M transportation service provider throughthe 3GPP LTE/LTE-A core network. Based on the tariff tableand distance traveled, the fare is calculated and sent to themobile M2M service provider, which deducts the money fromthe passenger’s account. Furthermore, the information abouttransportation services (e.g., cost, schedule update, number ofpassengers, and available services) can be saved in an M2MNFC tag. As a matter of fact, the customers can get thisinformation by hovering their mobile phones over the M2MNFC readers. Mobile ticketing can enhance the effectivenessof ticketing, save the costs for transportation service providers,and increase convenience of passenger.

5) Smart Parking: Nowadays the car is the most ubiquitousmeans of transportation of human beings. Driving a car inurban environments has, however, significantly deterioratedliving conditions. This is mainly caused by long searchingtimes which causes frayed nerves, significant pollution, reducedworking time, financial loss and much more [98]. M2M applica-tion in smart parking is a proven, robust and cost-effective wayto ensure that road users know exactly where unoccupied carparking spaces are. Worldsensing [98] provides a cutting edgewireless smart parking technology named Fastprk that is basedon a robust package of M2M sensors embedded into the tarmacso that it enables drivers to find parking quickly and efficiently.

Fastprk not only can reduce the frustration experienced whentrying to locate a parking spot, it will also allow drivers to savetime, fuel, and associated costs. In addition, it allows the citycouncil to monitor and manage the parking spaces, and gettingreal time information. The system relies on embedded M2Msensors in each parking bay in the street. When a car parks

over the M2M sensor, it is detected and M2M sensor relaysthat information in a wireless way to the 3GPP LTE/LTE-A’sgateway. Then the gateway sends the information to the 3GPPLTE/LTE-A core network. Finally, the core network can sendthe information via the Internet to the M2M database server inreal time. The occupancy is then instantly reported to users viaapps and illuminated panels in the street.

6) Smart Car Counting: It is expected that a large numberof people will live in the cities in near future, and in the next20 years the urban population will grow from 3.5 billion to5 billion people. Therefore, it is undeniable that the privatecar as a means for transportation will predominate in one formor another for the next decades to come. This undoubtedlyposes new challenges in terms of city management, city trafficcontrol, and intelligent transportation. It would be necessary toestablish data collection station that provides accurate detectionof vehicles for measuring traffic flow.

In this regard, Sensefield [99] offers an end-to-end solutionfor traffic management. Wireless M2M sensors installed on thepavement detect vehicles and measure their speed and length.This information is transmitted to a nearby Data ProcessingStation (DSP) that rolls as a M2M gateway and providesdiverse connectivity and serves as a local hub. Through the3GPP LTE/LTE-A core network, DSP can be able to transmitcollected data to the M2M server. Then, the M2M control centerutilizes this data to manage and monitor the infrastructure andanalysis the traffic data to ease traffic flow and to smoothtransportation in the city region.

7) Journey Time Estimation: Currently available real-timetraffic information is practically non-existing and insufficientboth for road operators and for travelers. The root of theproblem can be found in the data collection systems, whichare expensive, inefficient, and inadequate. In addition to thelimitations in data collection, most traffic information and man-agement solutions are unable to provide a complete integrationin real time of data collection, aggregation, and dissemination.

Bitcarrier [100] offers a solution for traffic information andmanagement in any kind of road. This solution consists of threemain elements that are as follows.

1) A network of M2M sensors auditing the Bluetooth andWiFi public frequencies of mobile devices;

2) A network of M2M servers hosting the databases;3) An online web client displaying all results regarding

speed, travel times and incidents.Bitcarrier M2M sensor is able to audit the signals emitted by

GPS navigators, hands free car kits and cell phones embarkedin vehicles, provided that the Bluetooth and WiFi sensors of themobile devices are active. Furthermore, this solution ensurestotal privacy protection for travelers. The M2M sensors collectanonymous data which is further encrypted before being sentto the M2M server database. As original data is encrypted anddestroyed, it is impossible to link a particular device with a user.

D. Security and Public Safety

Security is one of the most serious concerns for private res-idential, as well as commercial and public locations. The con-cerns over security and safety are attracting a lot of attention.


A great demand for effective security systems makes the M2Mcommunication technology a perfect choice for the simplifica-tion and automation of security and public safety monitoringand management. The M2M technologies provide cost-effective, rapid, and flexible deployment for remote surveil-lance, remote burglar alarms, personal tracking, and publicinfrastructure protection.

1) Remote Surveillance: Remote surveillance is one of thepublic safety applications. Remote surveillance systems can beapplied to monitor any open areas, valuable assets, people oreven pets for appropriate protection, where M2M sensors invideo cameras are used to transmit signals either continuouslyor at a fixed interval. The M2M applications can help todetect possible risky situations, trigger proper actions, alertauthorities, and keep an eye open to all suspicious activities andincidents.

More specifically, the M2M applications can let the userknow if some objects are moved to/from a restricted area (e.g.,home or office), report to an unauthorized entity, and providethe exact locations of the incidental events. In this case, theevent has to be notified immediately to the owner, authorities,and/or to the security companies. The M2M communicationscan simplify the designs of alarm management and quickreporting systems. Connected M2M sensors via 3GPP LTE/LTE-A core network can provide a detailed road map of a thief,and thus increase the security for home residents, personnel,assets, and properties.

2) Personal Tracking: Personal tracking devices integratedwith the M2M technology, allow users to be informed wheretheir relatives/friends are on a real time basis, and they can bewarned in case of troubles/risks or when they request for any as-sistance. In this application [9], persons, assets, and/or animalsare equipped with portable M2M devices, each of which con-tains a M2M communication module, together with an optionalGPS unit, which sends location information automatically oron an on-demand basis to an M2M application server via 3GPPLTE/LTE-A core network, then, the core network can send theinformation via the Internet to the M2M database server in realtime, which can monitor the status while also being able to trackand trace the persons, objects, or animals.

3) Public Infrastructure Protection: Every government hasa wide range of infrastructure, such as roads, bridges, tunnels,buildings, cables, pipes, which should be maintained and moni-tored. The applications of M2M technology enable the govern-ment agencies to enhance their operational efficiencies, and tocut the costs for infrastructure maintenance. The M2M com-munications can be used to efficiently monitor the conditionof public infrastructure equipped with M2M sensors or M2MRFID tags and even simplify daily maintenance by automatingsome routing tasks, including remote parking management,selective activation of street lights, or remote surveillance ofpublic spaces.

E. Information-Ambient Society

The M2M communications play an important role in digitiz-ing “everything”, which means that it interprets the “feeling”or “intuition” in our real life using digital data [107]. The

Fig. 12. Conceptual diagram of the horizontally integrated M2M service.

digitized world is creating a sheer volume of data at a rapidpace, which requires numerous new approaches to delivery thatamount of data effectively. The emerging Big Data technologycan significantly improve the efficiency to process those digitaldata. In fact, the Big Data has a great potential to materialize“everything” in the near future. Furthermore, both M2M andBig Data technologies will be needed, and possibly be mergedas an important platform for the construction of futuristicintelligent societies, such as a smart city or a smart community,etc. In order to enhance our society in terms of its intelligenceand innovation level, it is required to construct a comprehensiveservice platform. Based on the argument made by RobertMetcalf that the value of a network increases exponentially asdevices connect. Therefore, more M2M devices must be linkedto each other and the information from these M2M devices mustbe collected, not individually but all at once. To achieve this,service platform must be shifted from that of a conventionalvertically integrated platform system (or individually optimizedservice) to a horizontally integrated platform system [107].

As depicted in Fig. 12, the horizontally integrated M2Mservice shares the data collected from various M2M devices andutilizes them for various services. Furthermore, the M2M appli-cation users can construct an M2M system with less investmentcost than for those systems that are constructed individuallysince instead of accumulating the required information to con-struct a desired system, employment of a horizontally integratedM2M platform enables the availability of the information forefficient use by various services.

Integrating M2M with Big Data, we create a new infor-mation based society, namely “Information-ambient society”.The “Information-ambient society” will evolve even further andeventually it will provide us with a society, in which machinesdetect various conditions by using their sensors. It will have itscapability to understand what the human being is thinking in anautonomic manner. This is a salient feature of the “Information-ambient society”.

F. Robotic Applications

Robotics are able to improve the quality of our life, to savecosts, and to minimize the resource wastage. In the future,


robots will be highly intelligent, and networked with otherrobots and human beings. They will be used not only to cleanand guard our homes, but also to assist elderly and handicappedpeople, perform surgery, conduct dangerous tasks, such asidentifying and disabling improvised explosive devices (IED),fire-fighting, and hazardous site inspection. These robots aremachines controlled by machines (M2M) with their ability tosense, reason, and communicate in a real time basis. They willcertainly become very powerful tools in our life in the future.

In particular, the M2M based robot controlled cars ordriverless/unmanned vehicles will become more and more pop-ular in the near future. They could help to reduce traffic accidentrisk to human-beings. Furthermore, these robot based driverlessvehicles will be widely used in cargo transportation to reducethe traffic accidents caused by manned vehicles due to thetiredness of the drivers. Some studies carried out by the IEEEreveal that, by 2040, driverless cars will account for up to75 percent of cars on the roads worldwide [108].

G. Environment Monitoring

Environmental monitoring is essential to verify environmen-tal stress, understand ecological patterns, and evaluate the ef-fectiveness of environmental protection policies and programs.Environmental monitoring includes to monitor air, water, soil,animals, and plants. M2M communications provide the solu-tions that can automatically take samples and convey the moni-tored results to the government agencies in charge, and this hasbecome an extremely important part of environmental monitor-ing programs in various countries of the world. Furthermore,the quality of fruits, vegetables, meat, and dairy products isvital to the health of their consumers. Foods from production toconsumers have to go through various stages and be transportedover thousands of kilometers before reaching their consumers.During the transportation processes, the preservation status(e.g., temperature, humidity, and light) need to be monitoredclosely with the help of appropriate M2M sensors. The M2Msensors can precisely measure these variations and send therelated information to the M2M server via 3GPP LTE/LTE-Acore network immediately whenever needed. The advancementof pervasive computing and sensor technologies offers an ef-fective solution for monitoring the environment and in-dangeranimals/plants [101], [102].

VI. OPEN RESEARCH ISSUES

A. Traffic Characteristics

The characteristics of M2M communication traffic are dif-ferent from those of H2H network traffic. M2M traffic encom-passes specific traffic patterns due to its special functions (e.g.,data collection and monitoring) and requirements (e.g., strictlyreal-time based traffic), whereas H2H traffic follows a certaindata volume, session length, and interaction frequency. Trafficcharacterization is an important issue for designing and opti-mization of network infrastructure. It is well known that trafficcharacteristics in wireless sensor networks depend very muchon the application scenarios [109]. It is not a problem as the is-sues of interest are focused on the traffic flow inside the wireless

sensor network itself. Complications arise when sensor nodesbecome part of the overall M2M communication networks. Inthis case, the M2M communications will be traversed by alarge amount of data generated by sensor networks deployed forheterogeneous purposes, thus with extremely different trafficcharacteristics.

M2M applications may generate different traffic patternssuch as streaming, periodic, and event-driven signals [17]. Inaddition, the M2M data could have varying sizes and bandwidthrequirements. In the case of video monitoring devices, data hav-ing a size of megabytes could be normally expected. In the caseof sensor data (e.g., temperature and humidity), the amount ofdata per transmitted packet is usually small, and the measureddata is reported in periodical intervals. Although those intervalsmay range from several minutes to hours [110], the aggregationof multiple M2M devices may form a noticeable dense nodedistribution scenario. Furthermore, allocating a single PRB toan M2M device that transmits only small data could signifi-cantly degrade the spectral efficiency. In cases of emergencyevent-driven traffic like fire and flooding, networks may haveto deal with simultaneous transmissions of emergency data.This can severely impair the overall network performance andmay blockage resources for other regular users. M2M trafficcharacterization is also required to cater for QoS guarantee forvarious M2M applications. The matter of resource allocationfor LTE/LTE-A stations for the support of QoS provisioning forM2M devices is also a challenging problem that is still subjectto further research.

The straightforward employment of the existing LTE/LTE-Aprotocols may not satisfy the requirements of M2M commu-nications due to the large-bandwidth and low-latency linksused in LTE/LTE-A networks. Therefore, a new concept ofthe transport layer is required for M2M communications withregard to the use of LTE/LTE-A networks. Transmission Con-trol Protocol (TCP) utilized at the transport layer is known asinadequate for M2M traffic due to the following reasons:

• Connection setup: most of the communications in M2Mdeal with the exchanges of a small amount of data, andthus the setup phase accounts for a noticeable portion ofthe session time which is unnecessary.

• Congestion control: one of the major goals of TCP is toperform end-to-end congestion control. In M2M commu-nications in 3GPP LTE/LTE-A, this may cause perfor-mance degradation problems since the communicationsare performed by utilizing wireless medium. In addition,if the amount of data to be exchanged is very small, TCPcongestion control would be useless.

• Data buffering: TCP requires data to be stored in a memorybuffer. Management of such a buffer may be not efficientregarding to the resource-constrained M2M devices.

• Real time applications: TCP was not originally designedfor real-time applications and it is not adequate for M2Mwireless communication networks.

Therefore, an enhanced congestion control mechanism isrequired to improve the performance of TCP over LTE/LTE-A before it can be suitable for applications in M2Mcommunications.


The REST architecture is another approach which con-sists of clients and servers. The REST uses the GET, PUT,POST, and DELETE protocols to access resources. However,the protocols are not appropriate for resource-constrained de-vices in M2M communications. To meet the requirements ofresource-constraint M2M devices, Internet Engineering TaskForce (IETF) has standardized constrained application proto-col (CoAP). The CoAP involves very low Hypertext TransferProtocol (HTTP) overhead and supports multicast and asyn-chronous message exchanges over a user datagram protocol(UDP) particularly suitable for M2M applications. However,there are still some concerns regarding to the CoAP applicationsthat require for further considerations. A primary issue is thecreation of an intuitive network that directly includes devicedata without the need for a cross-proxy. Another concern is theways to support for CoAP’s security.

In the past, various solutions have been proposed for themobility management. However, their validity in the M2Mcommunications should be proven in terms of their scalabilityand adaptability before being applied to such a heterogeneousnetwork.

Another issue regards to the ways in which addresses are ob-tained. In the M2M communications, the Object Name Service(ONS) associates a reference to a description of an identifier tobe translated into a Uniform Resource Locator (URL), identify-ing where the information about the object resides. In the M2Mapplications, the ONS should operate in both directions, i.e., itshould be able to associate the description of the object speci-fied to a given identifier, and vice versa. Inverting the function isnot an easy task and needs an appropriate Object Code MappingService (OCMS). Desired features for OCMS were investigatedin [111], where a peer-to-peer (P2P) approach was proposed inorder to enhance scalability. However, design and evaluation ofOCMS in heterogeneous M2M communications are still openissues that require for further considerations.

B. Routing Protocols

The sensor networks [112] as a primitive form of M2Mcommunications are utilized for sensing and gathering appli-cation based on low-rate, low bandwidth, and delay tolerantdata collection processes. While current research considersfor more sophisticated applications such as scientific, military,healthcare, and environmental monitoring researches, whereeach M2M device performs various tasks ranging from sensing,decision making, and action executing. Therefore, the commu-nication framework for the sensor nodes in M2M communi-cation encounters various difficulties in satisfying the differenttechnical requirements of these applications. Furthermore, theaforementioned applications have different QoS requirements(e.g., delay, throughput, reliability, bandwidth, and latency)and traffic characteristics. To extract more realistic and preciseinformation of fast changing events in the real world and alsoto deal with them in a responsive manner, the abilities of sensornodes in M2M devices should be significantly enhanced. Wire-less Multimedia Sensor Networking (WMSN), as a powerfuland intelligent class of sensor-based distributed systems, isgaining more popularity since its capability of ubiquitously

retrieving multimedia information to support a large number ofboth non-real time and real-time applications [113]. However,routing to satisfy the stringent QoS requirements of multimediatransmission in a resource-constrained M2M communicationimposes new challenges.

Despite the availability of various routing protocols, theproblems still remain and other challenges are emerging withregard to the growing demands for M2M applications [113]–[115]. These challenges include mobility issues of sensorsand sinks, multiple sources and sinks, dynamic hole bypass-ing, cross-layer awareness, multi-channel access, resource con-strained QoS guarantee, and secure routing. Available routingprotocols proposed for the resource-constrained networks con-centrate only on power consumption with the assumption thatdata traffic has no or loose QoS requirements. Therefore, toprovide various QoS requirements for M2M applications andto be power efficient, routing techniques are needed to besignificantly improved or re-invented.

C. Heterogeneity

One of the main requirements for the M2M communicationsin 3GPP LTE/LTE-A network to be successful is its capabilityto integrate many types of devices, technologies, and services.At the device domain, this involves vast variety of features interms of data communication capabilities (e.g., data rates, la-tency, and reliability), flexibility in handling different technolo-gies, availability of energy, computational and storage power,etc. As to services, the system should be able to support very di-verse applications, whose characteristics and requirements maybe extremely different, in terms of bandwidth, reliability, la-tency, etc. These heterogeneity properties of the overall systemmake the design of communication protocols a very challengingtask. There are several other challenges and open researchtopics to be investigated in future, which are listed as follows.

1) Spectrum Management: In wireless M2M communica-tions, spectrum scarcity is a serious issue for most applications.Heterogeneous LTE/LTE-A network is a new trend in telecom-munications, which could significantly enhance spectrum effi-ciency, power saving, and signal strength and coverage area.However, with the deployment of M2M communications basedon the LTE/LTE-A, significant spectrum sharing problems mayarise resulting in a low spectrum efficiency. Therefore, theimprovement of spectrum efficiency under a spectrum sharingenvironment for M2M communications should be carefullyconsidered.

2) Opportunity Access: In this way, cognitive radio tech-nique is used to detect spectrum holes and utilize them fordynamic access. It is flexible for supporting various systems in-cluding M2M applications in LTE/LTE-A. However, the oppor-tunity access requires complex technologies for detecting thewhite spectrum space and efficient radio resource managementprotocols without interfering to the primary users.

3) Connectivity: Another key area of investigation is howto provide communications capabilities to the various devicesinvolved in 3GPP LTE/LTE-A M2M communications. Issuessuch as communications energy consumption, antenna design,interoperability of different technologies (e.g., via cognitive


radio capabilities), adaptive techniques for a dynamic environ-ment in the face of possibly heavily constrained resources, etc.will have to be addressed. Furthermore, it should be mentionedthat a system that is too connected becomes hard to manage(e.g., due to the excessive interference), thus, it will be impor-tant to understand what needs to be connected so as to providethe necessary communications capabilities for M2M devices.

Moreover, the 3GPP LTE/LTE-A standards provide ubiqui-tous wireless access by attaching to eNBs through single-hoplinks in H2H communications. However, distinct characteristicsand a large number of devices in M2M communications maycreate some other challenges if compared with H2H commu-nications. Therefore, in this scenario, utilizing single-hop maynot be an appropriate solution and multi-hop connections maybe needed instead, and thus further investigations are required.

D. Security

Security is an important issue for successful applications ofM2M communications. The M2M is vulnerable to attacks forseveral reasons. First, for most of the time, M2M nodes are nor-mally unattended, and thus it is easy to be physically attacked.Second, due to the limited capabilities of M2M nodes in termsof their energy and computing resources they cannot implementvery complex algorithms to support security. Furthermore, veryoften a fraction of M2M nodes switch into sleeping mode,which makes the attacks undetectable by system supervisors.Finally, eavesdropping could be relatively easy since the M2Mcommunications are performed in wireless channels.

More specifically, the major problems regarding to theM2M communications security include authentication and dataintegrity. Authentication is a prerequisite for secure M2M com-munications, and it requires appropriate authentication infras-tructures and servers allowing eNB to confirm the sensory datafrom the M2M nodes through the exchange of messages withother nodes. However, since the passive sensor nodes cannotexchange too many messages with the authentication servers,and thus such approaches may not be feasible in the M2Mapplications.

Data integrity must guarantee that illegal alteration of thesensory data can be detected. In M2M communications, thedata integrity requirement should be satisfied since illegal alter-ation may cause serious consequences, especially in life-criticalM2M applications such as e-healthcare systems. Data can bemodified either by

1) adversaries while storing in the M2M node or,2) when it goes through the network.To protect data against the first type of attack, memory is

protected in most tag technologies and solutions have beenproposed for wireless sensor networks as well [116]. To protectdata against the second type of attack, messages may be pro-tected according to the Keyed-Hash Message AuthenticationCode (HMAC) [117] that is based on a common secret keyshared between the tag and the destination of the message,which is used in combination with a hash function to provideauthentication. However, it should be mentioned that, the pass-word length supported by most tag technologies is too short tosupport strong levels of protections. Furthermore, even if longer

passwords are supported, still their management remains a hugeburden and challenging task especially when entities belongingto the heterogeneous M2M networks.

The problem of data integrity was extensively investigatedin traditional communication systems and some preliminaryresults (e.g., [118]) are also available for sensor networks.However, new problems arise when sensory nodes are inte-grated into M2M communications, and thus security in M2Mcommunications remains to be an open issue.

In [119], the 3GPP Security Workgroup (SA3) has collectedcategories of vulnerabilities that are as following:

1) Physical attacks including the insertion of valid au-thentication tokens into a manipulated device, insertingand/or booting with fraudulent or modified software, andenvironmental/side-channel attacks, both before and afterin-field deployment. These possibilities require trusted‘validation’ of the integrity of the M2M device’s softwareand data, including authentication tokens.

2) Compromise of credentials comprising brute force at-tacks on tokens and (weak) authentication algorithms,as well as malicious cloning of authentication tokensresiding on the Machine Communication Identity Module(MCIM).

3) Configuration attacks such as fraudulent software update/configuration changes; misconfiguration by the owner,subscriber, or user; and misconfiguration or compromiseof the access control lists.

4) Protocol attacks directed against the device, which in-cluded man-in-the-middle attacks3 upon first networkaccess, denial-of-service (DoS) attacks, compromisinga device by exploiting weaknesses of active networkservices, and attacks on over-the-air management (OAM)and its traffic.

5) Attacks on the core network, the main threats to the mo-bile network operator (MNO), include impersonation ofdevices; traffic tunneling between impersonated devices;misconfiguration of the firewall in the modem, router,or gateway; DoS attacks against the core network; alsochanging the device’s authorized physical location in anunauthorized fashion or attacks on the network, using arogue device.

6) User data and identity privacy attacks include eavesdrop-ping device’s data sent over the E-UTRAN; masquerad-ing as another user/subscriber’s device; revealing user’snetwork ID or other confidential data to unauthorizedparties, etc.

Some of the vulnerabilities that are more specifically gearedto the subscription aspects of the M2M device are exhaustiveand span the network, device, and user [119]. However, forspecial application, more additional consideration should beinvolved including the issues of liability identification thatrestrict user privacy to allow for identification of users whoseactions disrupt the operation of nodes or the transportationsystem.

3Man-in-the-middle attack considers the cases, in which a node is utilizedto identify something or someone and, accordingly, provide access to a certainservice or a certain area.


Finally, all the solutions proposed to support security usesome cryptographic methodologies. Typical cryptographic al-gorithms spend large amount of resources in terms of energyat the source and the destination which cannot be applied tothe M2M communications in 3GPP LTE/LTE-A, given thatM2M devices include elements (like tags and sensor nodes) thatare resource-constrained in terms of energy, communications,and computation capabilities. Therefore, new solutions are re-quired able to provide a satisfactory level of security includinglight symmetric key cryptographic and effective managementschemes regarding to the resource-constrained M2M networks.

VII. CONCLUSION

With a wide range of potential applications, the M2M com-munications are emerging as an important networking technol-ogy, which will become the infrastructure to implement theIoT. To enable full automation in our daily life, it is neededto provide connections among all M2M devices. To implementthose ubiquitous connections, the existing 3GPP LTE/LTE-Anetworks have considered as a ready-to-use solution to fa-cilitate M2M communications. In this paper, we discussedthe architectural enhancements in 3GPP LTE/LTE-A networksfor M2M communications. We highlighted key architecturalchanges as well as the functionalities of 3GPP LTE/LTE-Anetwork elements to support various requirements of M2Mcommunications, such as device triggering, M2M identifier,addressing, etc. Then, the salient characteristic features ofM2M communications, and the issues for implementation ofM2M communications based on 3GPP LTE/LTE-A networkswere identified and discussed. Furthermore, we presented anoverview on the major challenges to implement M2M com-munications over the 3GPP LTE/LTE-A networks. In addition,typical M2M applications that can play a critical role in ourfuture life were illustrated. Finally, the open research issues onM2M communications were pointed out in order to stimulatemore research interests in the subjects.

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Fayezeh Ghavimi (S’13) received the B.Sc. andM.Sc. degrees in electrical engineering from theUniversity of Tabriz, Tabriz, Iran, in 2007 and 2012,respectively. She is currently working toward thePh.D. degree in the Department of EngineeringScience, National Cheng Kung University, Tainan,Taiwan. Her research interests include wireless com-munications, machine-to-machine communications,QoS provision for supporting next-generation wire-less communications, and next-generation CDMAnetworks. Ms. Ghavimi received the Distinguished

International Student Scholarship from the Department of Engineering Science,National Cheng Kung University, in 2012.

Hsiao-Hwa Chen (S’89–M’91–SM’00–F’10) re-ceived the B.Sc. and M.Sc. degrees from ZhejiangUniversity, Hangzhou, China, in 1982 and 1985, re-spectively, and the Ph.D. degree from the Universityof Oulu, Oulu, Finland, in 1991. He is currently aDistinguished Professor in the Department of Engi-neering Science, National Cheng Kung University,Tainan, Taiwan. Dr. Chen is the founding Editor-in-Chief of Wiley Security and CommunicationNetworks Journal. He is currently serving as theEditor-in-Chief for IEEE WIRELESS COMMUNICA-

TIONS. He is a Fellow of IET, and an elected Member at Large of IEEEComSoc.