M2M Communications in 3GPP LTE/LTE-A Networks - IEEE Xplore

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

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M2M Communications in 3GPP LTE/LTE-A Networks: Architectures, Service Requirements, Challenges, and Applications Fayezeh Ghavimi, Graduate Student Member, IEEE, and Hsiao-Hwa Chen, Fellow, IEEE

Abstract—Machine-to-machine (M2M) communication is an emerging technology to provide ubiquitous connectivity among devices without human intervention. The cellular networks are considered a ready-to-use infrastructure to implement M2M communications. However, M2M communications over cellular pose significant challenges to cellular networks due to different data transactions, diverse applications, and a large number of connections. To support such a large number of devices, M2M system architecture should be extremely power and spectrum efficient. In this paper, we provide a comprehensive survey on M2M communications in the context of the Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) and Long-Term Evolution-Advanced (LTE-A). More specifically, this paper presents architectural enhancements for providing M2M services in 3GPP LTE/LTE-A networks and reviews the features and requirements of M2M applications. In addition, the signal overheads and various quality-of-service (QoS) requirements in M2M communications also deserve our attention. We address M2M challenges over 3GPP LTE/LTE-A and also identify the issues on diverse random access overload control to avoid congestion caused by random channel access of M2M devices. Different application scenarios are considered to illustrate futuristic M2M applications. Finally, we present possible enabling technologies and point out the directions for M2M communications research. Index Terms—M2M communication, 3GPP, LTE, LTEAdvanced, architecture, random access.

I. I NTRODUCTION

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ACHINE-TO-MACHINE (M2M) communications refer to the ways enabling automated applications that provide connectivity among machines or devices without any human intervention. The M2M communications may involve a large number of devices in a wide range of application domains, thus forming so-called Internet of Things (IoT). Cellular systems are expected to play a significant role in the successful deployment of M2M communications. Indeed, mobile cellular communications feature several advantages, such as global standard infrastructure, cost-effective connectivity, easy installation and maintenance, especially for a short-term deployment of M2M applications.

Manuscript received February 14, 2014; revised July 7, 2014; accepted September 3, 2014. Date of publication October 7, 2014; date of current version May 19, 2015. This work was supported in part by Taiwan Ministry of Science and Technology under Grant NSC 102-2221-E-006-008-MY3. The authors are with the Department of Engineering Science, National Cheng Kung University, Tainan City 70101, Taiwan (e-mail: faiezeh.ghavimi@ gmail.com; [email protected]). Digital Object Identifier 10.1109/COMST.2014.2361626

Several reports appeared in the literature to predict a considerable market growth for both M2M devices and M2M connectivity segments. For example, over the next a few years, the number of smart-metering devices per cell in a typical urban environment is estimated to be in an order of tens of thousands [1]. The M2M applications may include a large number of smart meters, health monitoring devices, and intelligent transportation terminals that must be efficiently connected via communication links [2]. In order to take full advantages of the opportunities created by a global M2M market over cellular networks, 3GPP and the Institute of Electrical and Electronics Engineering (IEEE) standardization bodies have initiated their working groups for facilitating such applications through various releases of their standards [3], [4]. The 3GPP LTE and LTE-A offer higher capacity and more flexible radio resource management (RRM) schemes than many other packet access data technologies. In LTE-A, stations can be configured as evolved universal terrestrial radio access (E-UTRA) NodeBs (eNBs) in macrocells or picocells, home eNBs (HeNBs) in femtocells [5]–[7], and relay nodes (RNs) in relay networks to provide comprehensive wireless access in both outdoor and indoor environments. Via attaching to those stations, higher-layer connections among all M2M devices can be provided. However, LTE and LTE-A were designed basically for wideband applications only; while in M2M communications, transactions at each M2M device are usually dominated by a small amount of data, leading to an inefficient utilization of LTE and LTE-A technologies. Therefore, to support a large number of M2M devices, important issues such as energy efficiency and short latency have to be addressed in M2M communications. Notably, the efforts have been made by 3GPP to overcome the shortcomings of LTE/LTE-A with its provision to support M2M communications [8], where its initial studies on M2M communications were focused on the functional architecture, service requirements, and applications [3], [8], [9]. With regard to service requirements, M2M applications are very much different from human-to-human (H2H) communications (e.g., typical applications of mobile phones), since M2M services have their unique characteristics [3], [10], [11]. Furthermore, QoS requirements of different types of M2M services may vary widely, and these service requirements then require special architectural designs. With an architecture in place, numerous challenges remain when implementing RRM for M2M communications in LTE-A cellular networks. For example, time and frequency resources are to be shared between H2H users and M2M devices, thus inevitably causing

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co-channel interference among them [12]. Such co-channel interference is responsible for degraded performance of an LTE-A cellular network supporting M2M communications. To optimally allocate the physical resource blocks (PRBs) to the user equipment (UE) and/or M2M devices, the schedular should exploit channel and traffic dynamics on a fast time scale, ideally per transmission time interval (TTI) [13]. Therefore, it is necessary to investigate the ways, in which how H2H users and M2M devices can efficiently share available radio resources, to mitigate the co-channel interference and thus improve network efficiency. In this paper, we intend to present some architectural enhancements needed to accomplish the M2M service requirements. In addition, M2M service requirements and features are to be illustrated in detail. To deploy M2M communications successfully in 3GPP LTE/LTE-A cellular networks, several major challenges need to be tackled. One of the most important issues in enabling M2M in LTE/LTE-A networks is congestion and system overload problem. The LTE/LTE-A networks were designed mainly to handle H2H communications, where the amount of uplink (UL) traffic is normally lower than the downlink (DL) traffic. In contrast, M2M applications may produce more traffic data in UL channels than the data over DL channels. Congestion due to concurrent transmit messages from a large number of M2M devices can be overwhelming, thus impacting on the operations of a whole mobile network. In the context of M2M communications, signaling congestion may occur due to a malfunction in an M2M server (e.g., M2M devices repeatedly try to connect to the same remote server, which is down) or an application (e.g., synchronized operation of a particular M2M application). The congestion can also occur due to concurrent attempts from a large number of M2M devices to attach/connect to the network [3]. The investigations in 3GPP in the literature indicated that both M2M devices and UE may suffer uninterrupted collisions at a random access channel (RACH) when a large number of M2M devices are active. This challenge attracted a significant attention, and various possible solutions have been proposed by the 3GPP [14]. Several review papers in literature [15]–[18] discuss M2M communications in the context of emerging wireless technologies. In [15], the authors describe the technological scenario of M2M communications consisting of wireless infrastructure to cloud and related technologies toward practical realization. Moreover, [16] presents a survey on home M2M networks and examines the typical architectures of home M2M networks along with discussing the performance tradeoffs in existing designs. Furthermore, [17] presents a survey of existing M2M service platforms and explores the various research issues and challenges involved in enabling an M2M service platform. In addition, the authors in [18] describe machine type communications in 3GPP networks and provide a summary of the solutions agreed within 3GPP for congestion control and network overload avoidance. Hence to the best of our knowledge, a comprehensive survey on M2M communications with its focus on LTE/LTE-A systems is not available in the literature. Therefore, the main purpose of this paper is to provide a review on the studies appeared in the literature, helping the readers to understanding what

has been investigated (architecture, technologies, requirements, challenges, and proposed solutions) and what still remains to be addressed. In addition, this paper will reveal an evolutionary path of the M2M communications for futuristic research. The remainder of this paper is outlined as follows. In Section II, we discuss architectural enhancement of LTE/ LTE-A with regard to the M2M communications. The M2M communication standardization activities, service requirements, and features are the subject of Section III. In Section IV, the M2M challenges over 3GPP LTE/LTE-A are studied while the principal applications of the M2M communications will be addressed in Section V. Section VI lists the open research issues on M2M communications via discussing relevant topics such as traffic characterization, routing, heterogeneity, security, etc., followed by the conclusions given in Section VII. II. M2M N ETWORK A RCHITECTURE Different from normal mobile network terminals, M2M devices carry many unique characteristic features from the perspective of mobile operators. Therefore, it is necessary to seek optimized networking solutions in particular for M2M applications over mobile networks. To provide global integration among diverse solutions in the M2M applications, it is important to design a standard end-to-end M2M communication network architecture. This section provides an overview on M2M network architecture and identifies related M2M R&D activities reported in the literature. A. M2M Access Methods M2M devices can be either stationary (e.g., power meters in homes, machines in factory, etc.) or mobile (e.g., fleet management devices in trucks). The access network connects M2M devices to the infrastructure using either wired (i.e., cable, xDSL, and optical fiber) or wireless links. Wireless access methods can be either capillary/short range (i.e., WLAN, ZigBee, and IEEE 802.15.4x, etc.) or cellular (i.e., GSM, GPRS, EDGE, 3G, LTE-A, WiMAX, etc.). Although the wired solutions can provide high reliability, high rate, short delay, and high security, it may not be appropriate for the M2M communication applications due to its cost ineffectiveness, and lack of scalability/ mobility support. Alternatively, wireless capillary solutions, mainly used for shared short range links/networks, are rather cheap to roll out, and generally scalable. However, small coverage, low rate, weak security, severe interference, and lack of universal infrastructure/coverage pose restriction on its applications to M2M communications. On the other hand, wireless cellular offers excellent coverage, mobility/roaming support, good security, and ready-to-use infrastructure, making M2M over cellular a promising solution for M2M communications. Therefore, in this article, our focus is on the M2M communications based on 3GPP LTE/LTE-A mobile networks. B. 3GPP Network Architecture In this part, we describe the 3GPP network architecture to provide a comprehensive survey and more specifically to reveal

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

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TABLE I L IST OF F REQUENTLY U SED ACRONYMS

Fig. 1.

An overview of EPC for 3GPP accesses.

an evolutionary path from the non-LTE to the LTE/LTE-A technologies helping the readers to understanding what is the similarity for the element nodes in non-LTE and LTE/LTE-A as well as a description of the functionality of them. An overview of the evolved packet core (EPC), the legacy packet and circuit switched elements, 3GPP RANs, and the most significant interfaces are illustrated in Fig. 1. Furthermore, Fig. 1 shows the most important EPC nodes in LTE/LTE-A networks and also, 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) receive device trigger from MTC-IWF; encapsulates device trigger information in non-access stratum (NAS) message sent to the UE/M2M device; receives device trigger delivery success/ failure status to MTC-IWF. Furthermore, SGSN performs security functions, access control and location tracking. It plays the role of MME and serving gateway (S-GW) in the EPC. The GGSN or packet data network gateway (P-GW) may support the following functionality. Based on access point name (APN) configuration and unavailability of MSISDN and external identifier(s) in the GGSN/P-GW either queries an MTC accounting, authorization, and authentication (AAA) server for retrieval of external identifier(s) based on IMSI or routes RADIUS/Diameter requests for AAA servers in external packet data network (PDN). The GGSN function is similar to the P-GW in the EPC. The MSC server controls circuit-mode services. The MSC is mostly associated with communications switching functions, such as call set-up, release, and routing. It also performs a host of other duties, including routing SMS messages, conference calls, fax, and service billing as well as interfacing with other networks, such as the public switched telephone network (PSTN).

The MGW was introduced to bridge among different transmission technologies and to add service to end-user connections. The MGW uses open interfaces to connect to different types of node in the core network and external networks. The requirements and major elements of the EPC architecture were characterized in 3GPP Release 8, which will play an important role in the implementation of the next generation M2M networks [21]. Along with the 3GPP LTE that applies more to the radio access technology, there is also an evolution of the core network known as system architecture evolution (SAE). These two major parts lead to the characterization of the EPC, evolved UTRAN (E-UTRAN), and E-UTRA, each of which corresponds to the core network (CN), RAN, and air interface of the whole system, respectively [5]. Some frequently used acronyms in this paper are listed in Table I. In the following, we provide an overview of the E-UTRAN architecture, the main EPC node functionalities, and functionalities defined for LTE-A systems, respectively. 1) LTE-A E-UTRAN Overview: The architecture of the E-UTRAN for LTE-A is shown in Fig. 2. As mentioned earlier, an LTE-A network comprises two parts, i.e., the EPC and the RAN, where the former is known as CN, and the latter consists of base stations (BSs) that are referred to as evolved node base stations (eNBs) [5]. The EPC is responsible for overall control of mobile devices and establishment of Internet Protocol (IP) packet flows. The eNB is responsible for wireless

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

Fig. 3. User and control plane protocol stacks.

communications and radio access, and provides an air interface with user plane and control plane protocol terminations toward the UE and M2M devices. Each of the eNBs serves one or several E-UTRAN cells, and the interface interconnecting the eNBs is called the X2 interface. Besides, the eNB is connected to the EPC through the S1 interface. In addition, HeNBs that are the eNBs for indoor coverage improvement can be connected to the EPC directly or via a gateway that caters for additional support for a large number of HeNBs. Furthermore, the 3GPP LTE-A encompasses relay nodes and sophisticated relaying strategies for network performance augmentation. The aim of this 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-UTRAN with the user and control plane termination protocols. Fig. 3 gives a graphical overview of both protocol stacks. In the user plane, the protocols include packet data convergence protocol (PDCP), radio link control (RLC), medium access control (MAC), and physical layer (PHY) protocols. The control plane stack additionally includes the radio resource control (RRC) protocols.

The main functionalities carried out in each layer are summarized as follows [5], [22]–[25]. • NAS: The NAS is the highest stratum of the control plane between UE/M2M and core network at the radio interface. This layer is used to support the continuous connection of UE/M2M as it moves, and also to manage the establishment of communication sessions to maintain IP connectivity between the UE/M2M and an P-GW. Furthermore, the NAS is a protocol for messages passed between the UE/M2M and core network. The NAS messages include update or attach messages, authentication messages, service requests, and so forth. In addition, the NAS control protocol performs bearer context activation/deactivation, registration, and location registration management. • RRC: The RRC protocol layer handles the control plane signaling between the UE/M2M and eNB. The main services and functions of the RRC sublayer include broadcast of system information related to the NAS and AS. Furthermore, establishment, modification, and release of RRC connections are performed in this protocol layer. Initial security activation (i.e., initial configuration of AS integrity protection and AS ciphering), RRC connection mobility including intra-frequency and inter-frequency handovers, and specification of RRC context information are the other important tasks of RRC sublayer. Moreover, this sublayer performs QoS control functions, UE/M2M device measurement configuration and reporting. In addition, the RRC transfers dedicated NAS information and non-3GPP dedicated information. • PDCP: This layer performs IP header compression and decompression using ROHC protocol (the current version is FFS) 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 of PDCP services. Maintenance of PDCP sequence numbers for radio bearers and in-sequence delivery of upper layer packet data units (PDUs) at HO are other functions of PDCP layer. In addition, duplicate detection of lower layer session data units (SDUs), ciphering and deciphering of user plane data and control plane data, and integrity protection 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 user planes. This layer transfers upper layer PDU and performs error correction through automatic repeat request (ARQ). Moreover, the RLC protocol layer is used for concatenation, segmentation, and reassembly of RLC SDUs. In addition, re-segmentation and reordering of RLC data PDUs, RLC re-establishment, and error detection and recovery are the other functions of this protocol layer. • MAC: The MAC protocol is responsible for regulating access to the shared medium. Furthermore, the choice of MAC protocol has a direct bearing on the reliability and efficiency of network transmissions. Responsibilities of MAC layer include multiplexing/demultiplexing of RLC PDUs, scheduling information reporting, error correction through hybrid ARQ (HARQ), logical channel prioritization, and transporting format selection.


2) Evolved Packet Core Overview: The EPC is a flat all IPbased core network that can be accessed through 3GPP radio access (e.g., WCDMA, HSPA, and LTE/LTE-A) and non-3GPP radio access (e.g., WiMAX and WLAN), to efficiently access to various services such as the ones provided in IP multimedia subsystem (IMS). The access flexibility to the EPC is attractive for operators since it enables them to modernize their core data networks to support a wide variety of access types using a common core network. The following text describes the main components of the EPC along with their functionalities. • Mobility Management Entity (MME): The MME is a key control plane element for the LTE/LTE-A access network. It is responsible for managing security functions (authentication, authorization, and NAS signaling), roaming, handover, and handling idle mode user equipment. It is also involved in choosing the S-GW and packet data network gateway (P-GW) for an UE/M2M device at an initial attach. The S1-MME interface connects the EPC with the eNBs. • Serving Gateway (S-GW): The S-GW resides in the user plane, where it routes and forwards packets to and from the eNBs and packet data network gateway (P-GW). It is also a mobility anchor point for both local inter-eNB handover and inter-3GPP mobility. The S-GW is connected to the eNB through S1-U interface and to the P-GW through S5 interface. Each UE/M2M device is associated to a unique S-GW, which will be hosting several functions. • Packet Data Network Gateway (P-GW): The P-GW provides connectivity from the UE/M2M device to an PDN by assigning an IP address from the PDN to the UE/M2M device. Moreover, P-GW provides security connection between UEs/M2M devices by using Internet protocol security (IPSec) tunnels between UEs/M2M devices connected from an untrusted non-3GPP access network with the EPC. As mentioned earlier, this system is considered as “flat” since from a user-plane point of view there are only the eNBs and the gateways. This leads to a reduced complexity compared to previous architectures. C. M2M Communications Over 3GPP LTE/LTE-A Networks The 3GPP system provides services for M2M communications,1 including various architectural enhancements (e.g., control plane device triggering), transport, and subscriber management. Different deployment paradigms foreseen for M2M communications between the M2M applications and the 3GPP LTE/LTE-A networks are discussed in the text followed [26]. The most straightforward deployment paradigm is the direct model, where the application server (AS) connects directly to an operator network in order to communicate with the M2M devices without using the services of any external service capability server (SCS), as shown in the left-most stack of Fig. 4 (or Fig. 4(a)). 1 M2M communication is also known as machine-type communications (MTC) in 3GPP.

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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 network through the services of an SCS in order to utilize additional value added services for M2M (e.g., control plane device triggering). The SCS can be either 1) M2M service provider controlled, which is deployed outside the operator domain. The SCS is an entity that may include value added services for M2M communications, performing user plane and/or control plane communication with the M2M device; or 2) the 3GPP LTE/LTE-A network operator controlled and considered as an internal network function. In this case, security and privacy protection for communications between the 3GPP LTE/LTE-A network and the SCS is optional for being trusted. Yet another deployment paradigm is the hybrid model, where the AS uses the direct model and indirect model simultaneously in order to directly connect to an operator network to perform direct user plane communications with the M2M devices while also using an SCS. From the 3GPP LTE/LTE-A network perspective, the direct user plane communications from AS and any value added control plane related communications from the SCS are independent and have no correlation to each other even though they may be serving the same M2M applications hosted by the AS. As shown in Fig. 5, two communication scenarios can be envisioned. One scenario considers communications between the MTC devices and one or more MTC servers in the M2M application domain. In this scenario, an M2M user (e.g., a power plant in the smart grid, or indoor health monitoring at home, etc.) can manage a massive number of M2M devices through M2M server(s). The M2M servers are catered by an operator, who offers an application program interface (API) for M2M users to access the M2M servers. The M2M servers and the 3GPP LTE/LTE-A infrastructure can be under the same operator domain (i.e., the operator domains A and B in Fig. 5 can be the same).

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

To provide communications between M2M devices and M2M server(s), the public land mobile network (PLMN) enables transactions between an M2M device and an M2M server. Furthermore, the PLMN should provide authentication and authorization for an M2M device before the M2M device can communicate with the M2M server [3]. An alternative scenario is depicted in Fig. 6, in which there is a peer-to-peer model, and M2M devices are communicating directly among themselves without M2M server(s). Communications among M2M devices can be provided within the same operator domain or among different ones. Inter-M2M device communications can be either via the mobile network or in ad-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 communicate with M2M devices used for M2M communications. The SCS provides an API to allow different ASs to use the capabilities of SCS. An SCS may be controlled by the operator of HPLMN or by an MTC service provider. The SCS uses subscription database to authorize connections on Tsp reference point,2 and to locate the SCS serving node so that control and data could be routed towards the SCS [27]. The SCS subscription identifier may be permanent subscriber data and can be used for the following purposes: authentication and charging on the Tsp reference point, charging for the SMS messages that may be sent towards the SCS, or charging for the data that may be sent to SMS-SC. 2 Tsp is a 3GPP standardized interface to facilitate value-added services motivated by M2M communications (e.g., control plane device triggering) and provided by an SCS.

The format of the SCS subscription ID can be an international mobile subscriber identity (IMSI). Temporary subscription identifiers may be established for security purposes in a manner similar to establishing a temporary IMSI (T-IMSI) for a 3GPP LTE/LTE-A UE. The MTC devices use SCS public identifier to send SMS messages and/or IP packets towards the SCS. The SCS public identifier may be permanent subscriber data and can be used for the following purposes: identification on the Tsp reference point, charging on the Tsp reference point, charging for SMS messages that may be sent towards the SCS (e.g., instead of the SCS subscription ID), or charging for data that may be sent to the SMS-SC. The SCS public identifier can be used as a field in trigger message interactions on the Tsp reference point. The SCS public identifier may be an MSISDN. In this case, a special range of the MSISDN is allocated for the SCS so that core network node can identify when traffic is destined for an M2M device or an SCS. The format of the SCS public identifier may be the format of a fully qualified domain name (FQDN), a mobile station integrated services directory (MSISD), an IP address, or an alpha-numeric format. The SCS can have multiple public identifiers. An SCS connects to the SCS serving node for control plane communications (e.g., including short message exchange). The other core network nodes use this information to determine the next hop destination of the control messages in order to reach a particular SCS. The SCS serving node may be a core network node. Furthermore, the SCS serving node can be an MTC-IWF, an MSG, an MME, an SGSN, or an S-GW. An SCS serving node identifier may be temporary subscriber data. In addition, the serving node can be the primary node used for routing control information towards an SCS. Also, it can be an IP address or an ISDN address. The SCS trigger quota can be permanent subscriber data, indicating the number of triggers that an SCS is allowed to request per time period. Furthermore, the SCS trigger quota defines the number of successful triggers that an SCS initiates per unit of time. E. 3GPP LTE/LTE-A Architecture Reference Model for M2M Fig. 7 depicts a typical architecture for M2M devices used for M2M connecting to the 3GPP LTE/LTE-A radio access networks. To support indirect and hybrid models of M2M communications, one or more instances of an MTC-IWF reside in the home public land mobile network (HPLMN). The MTC-IWF is a functional entity that hides the internal PLMN network topology and relays or translates signaling protocols used over Tsp to invoke specific functionality in the PLMN. An MTCIWF may be a standalone entity or a functional entity of another network element [28]. The SCS connects to the 3GPP LTE/LTE-A network via the MTC-IWF in the HPLMN to communicate with M2M devices used for M2M communications. The SCS offers capabilities for use by one or multiple M2M applications. An M2M 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 are hosted on one or multiple ASs. The interface between SCS and AS is not standardized by 3GPP, but other standards development organizations (SDOs), such as the ETSI TC M2M, are expected to standardize the API. It is important to notice that the development of M2M API should be drawn up for all devices of the identified application areas. Furthermore, a uniform protocol view compatible with the current IP suite, will provide protocols at different levels and will be the basis of device interoperability. The development of interfaces will allow all devices, generally developed with a precise service in mind, to embrace a greater variety of applications and to enable

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proactive communications of devices which are transparent to the users. Tsms is a non-standardized interface that encompasses various proprietary short message service-service center (SMS-SC) to short message entity (SME) interfaces [29]. Tsms can be used to send a trigger to an M2M device encapsulated in a mobile terminated-SMS (MT-SMS) as an over-the-top application by any 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 arrow reference points are the new reference points added to facilitate M2M communications over 3GPP LTE/LTE-A systems.

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The T4 interface is used by the MTC-IWF to route a device trigger as an MT-SMS to the SMS-SC in the HPLMN. T5a/b/c interfaces provide optimized paths for device trigger delivery and small data service to the M2M devices. The MTC-IWF uses S6m interface to interrogate the home subscriber server (HSS)/home location register (HLR) for mapping an external identifier or a mobile station integrated services digital network (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 uses an S6n interface to interrogate HSS/HLR for mapping IMSI to external identifier(s) and vice versa. III. S ERVICE R EQUIREMENTS AND F EATURES OF M2M C OMMUNICATIONS OVER 3GPP LTE/LTE-A All kinds of applications can be involved in M2M communications and it becomes massive in terms of diversity across the applications. However, not all M2M applications have the same characteristics [3]. This implies that every system optimization may not be suitable for every M2M application with regard to the variety of requirements. In order to cope with this heterogeneity of requirements, the 3GPP has defined a number of features [3] (i.e., particular characteristic features associated with certain applications), for which the network needs to be optimized. In this section, first some information related to the standardization activities are provided. Then, we give information pertaining to the service requirements. Finally, the categories of features for M2M communications are specified in the last part of this section. A. Standardization Activities for M2M Communications Recently, 3GPP, European Telecommunications Standards Institute (ETSI), Open Mobile Alliance (OMA), China Communications Standards Association (CCSA), and the Alliance for Telecommunications Industry Solution (ATIS) have started standardization processes on the M2M communications. The activities of 3GPP is concentrated on the M2M communications that can be supported by mobile cellular networks. In contrast, ETSI addresses the issues on M2M service architecture, its components, and the interactions between three domains, i.e., M2M device domain, communication network domain, and M2M application domain. • 3GPP standardization group: In order to take potential advantages of M2M communications over cellular networks, 3GPP system architecture working group 2 (SA2) aims to use 3GPP network and system progress that support M2M in evolved packet system (EPS) [8]. In [19], the first study on M2M was initiated without specifying system characteristics. The 3GPP SA2 defined 3GPP network system improvements in Release 10 to enable M2M communications in UMTS and LTE-A core networks. The objective is to optimize the system design that can mitigate M2M signaling congestion and network overload problems. For Release 10 and beyond, the focus is mainly on studying the impacts of standardized system network improvements on the architecture. The purpose of these studies is to

provide essential network enablers for M2M services and to distinguish 3GPP network enhancements required to support a large number of M2M devices in the 3GPP network domain. • ETSI standardization group: The ETSI technical committee (TC) M2M standardization intends to provide an end-to-end overview of M2M standardization, which concentrates on the service middleware layer that is independent of the underlying access network and transmission technologies. The goal of the ETSI TC M2M is to support a 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 critical needs for designing a common M2M service layer, which can be easily embedded within different hardware and software to connect a large number of devices with M2M application servers. Furthermore, oneM2M will develop globally agreed-upon M2M end-to-end specifications and architecture principles across multiple M2M applications [20].

B. M2M Service Requirements In this part we identify the service requirements for M2M applications. 1) General Service Requirements: Here, general requirements for the M2M systems are provided. However, there is no need for all particular M2M systems or components of these systems to implement every requirement. The followings are the M2M general service requirements [3]: • Enable the network operator to identify which individual M2M features are subscribed by a particular M2M subscriber. • Provide a mechanism to activate or deactivate M2M features for the M2M subscribers. • Identify which individual M2M features are activated for a particular M2M subscriber by the network operator. • Provide a mechanism for the network operator to control the addition or removal of individual M2M features and also restrict activation of M2M features. • Provide a mechanism to reduce peaks in data and signaling traffic when a large number of M2M devices simultaneously attempt data transmissions. • Provide a mechanism to restrict downlink data traffic and also limit access towards a specific APN when the network is overloaded. • An M2M device may support the extended access barring (EAB) mechanism. • An M2M device supporting the EAB mechanism should be able to be configured for EAB by the HPLMN. • The HPLMN should be able to configure EAB on an M2M device that supports it. • Provide mechanisms to efficiently maintain connectivity for a large number of M2M devices. • The system should provide mechanisms to lower power consumption of M2M devices.


2) M2M Device Triggering: Device triggering is one of the key requirements for a 3GPP LTE/LTE-A network. Motivated by the network, triggered devices should perform certain application-related tasks. For devices that do not have IP addresses (e.g., 2/3G devices), it is obvious that these devices cannot be attached in the packet switch (PS) domain in order to be reached by the network. Since the majority of M2M applications are data applications, it is necessary for an application server to reach the device in the PS domain. This requires a device to be allocated an IP address. Therefore, device triggering is related to the devices that are not reachable by the AS or the SCS. To address this requirement, control plane device triggering is defined as the mechanism [28] to trigger a device to perform specific applications. To this end, the AS first determines the MTC-IWF that serves the M2M device. Then, AS queries the MTC-IWF for the IP address assigned to the M2M device by sending a trigger request message. The MTC-IWF initiates procedures for triggering the M2M device. Then, MTC-IWF passes the device trigger request to the PSDN, which communicates with the RAN. The device trigger request message contains information that allows the network to route the message to an appropriate device and also allows the device to route the message to an appropriate application [26]. The information destined to the application, along with the information to route it, is referred to as the trigger payload. An M2M device needs to be able to distinguish a mobile terminated (MT) message carrying device triggering information from any other type of messages. Device triggering is subscription-based. The information provided by the subscription determines whether an M2M device is allowed to be triggered by a specific SCS. Tsp provides connectivity for the MTC-IWF to connect to one or more SCSs and receive the device trigger request from the SCS. 3) M2M Identifier: A large number of M2M services are currently deployed over circuit-switched (CS) GSM architecture and therefore use E.164 MSISDNs, although such services do not require dialable numbers. On the other hand, there is a concern over the numbering requirements and shortage of E.164 MSISDNs for new M2M services. Therefore, 3GPP architecture has been enhanced to allow delivering communication services using an alternate identifier, which is called an external identifier. More information about identifiers relevant for the 3GPP network are specified in [30]. M2M identifiers can be categorized into: 1) Internal identifiers, which is the identity that the entities within the 3GPP system use for addressing an M2M device. 2) External identifiers, which is the identity used from outside the 3GPP system, by which an M2M device is known to the M2M server. The IMSI is used as an internal identifier within the 3GPP systems. For the external identifier, a subscription used for M2M communications has one IMSI and may have one or several external identifier(s) that are stored in the HSS. The external identifier is globally unique and has two components: the domain identifier used to identify where services provided

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Fig. 8. The structure of the IMSI.

Fig. 9. The structure of the MSISDN.

by the network can be accessed (e.g., MTC-IWF provided services); and the local identifier that is used to derive or obtain the IMSI. The local identifier should be unique within the application domain. 4) Addressing: In M2M communications, each terminal is considered as a mobile subscriber and must have a unique IMSI. The current structure of the IMSI allows a network operator to theoretically support up to 1 billion subscribers, assuming 9 digits Mobile Subscriber Identification Number (MSIN). This number, 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 must have at least one assigned MSISDN. The structure of the MSISDN is depicted in Fig. 9 [31]. The current structure of the MSISDN, assuming a 9 digit subscriber number (SN), can theoretically 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 is projected to reach over 50 billion devices connected to the Internet by 2020 [32]. Therefore, the development of M2M applications will have an impact on national numbering plans since devices need to be uniquely addressed in order to communicate with them, or rather to enable them to communicate with each other. Thus, the 3GPP studied the problems in [33] and concluded that IMSI is the limiting factor of addressing and may not be suitable for M2M applications, which may need to make use of IP addresses. Therefore, 3GPP networks should contain mechanisms to connect with IP-based devices. The IPv4 protocol identifies each node through a 4-byte address. Due to the large number of devices in M2M communications, it is well known that the number of available IPv4 addresses is decreasing rapidly and will soon reach zero. Therefore, other addressing policies should be utilized. To solve this problem, IPv6 addressing [34] has been proposed. The IPv6 address is a 128-bit identifier which should be enough to identify any device in M2M communications in 3GPP LTE/LTE-A networks. In fact, its nearly infinite address space enables a future with ever more ubiquitous computation. Issues such as connectivity, interoperability, and compatibility with M2M communication networks must be provided. In this context, IETF IPv6 provides a set of protocols over low-power wireless personal area networks (6LoWPAN) [35] that can be utilized to

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integrate resource-limited devices into IPv6 networks by simplifying IPv6 including compressing addresses, removing options considered rarely used, simplifying packet processing, etc. C. Features of M2M Communications To facilitate system optimization, the 3GPP defines 14 features [3] in M2M communications. These features are listed as follows. 1) Low Mobility: The low mobility feature is suitable for M2M devices that do not move, move infrequently, or move only within a certain area [3], [36]. This feature enables the network operator to be able to simplify and reduce the frequency of mobility management procedures [36]. 2) Time Controlled: This feature is suitable for those M2M applications that can tolerate to transmit and receive data during defined time intervals and can therefore avoid unnecessary signaling outside these time intervals. The network operator may allow such applications to send/receive data and signaling outside these defined time intervals but charge differently for such traffic. To make use of time controlled M2M feature, the network operator should reject access requests per M2M device during a defined forbidden time interval. Furthermore, the local network should be able to alter the access grant time interval based on local criteria (e.g., daily traffic load, time zones, etc.). The forbidden time interval should not be altered. It is assumed that an access grant time interval will not overlap with a forbidden time interval. 3) Time Tolerant: The time tolerant feature is suitable for M2M devices that can delay their data transfer. The purpose of this functionality is to allow the network operator to prevent M2M 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 feature is packet switched only, which is intended to provide PS-only subscriptions with or without assigning an MSISDN [3]. Remote M2M device triggering will be supported with or without assigning an MSISDN. Remote M2M device configuration will still be supported for subscription without an MSISDN. 5) Mobile Originated Only: This feature is suitable for use together with M2M devices that only utilize mobile originated communications. This is intended for applications where it is possible to reduce the frequency of mobility management procedures per M2M device; the network should be able to provide a mechanism for the network operator to dynamically configure the M2M devices to perform mobility management procedures only at the time of mobile originated communications. 6) Small Data Transmission: This feature is suitable for use with M2M devices that transmit small amounts of data and can thus 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 that mainly utilize mobile originated communications and thus the network operator is able to reduce the frequency of mobility control information per M2M device. 8) M2M Monitoring: This is suitable for monitoring the state of the M2M devices and possible events that occur in

the network. This is a feature vital to all M2M applications to guarantee that the deployed devices are operational. 9) Priority Alarm Message (PAM): The priority alarm message M2M feature is suitable for use with M2M devices that issue a priority alarm in the event of theft, vandalism, or other needs for immediate attention. In addition, this feature is used in applications, which require attention but are not too critical. An example is the detection of a leak, which requires some valves or switches to be closed. In addition, the M2M devices may issue a priority alarm even when it cannot use normal services for some reasons (e.g., access time not allowed, roaming not allowed). 10) Secure Connection: The secure connection M2M feature is suitable for M2M devices that require a secure connection between the M2M devices and M2M server(s). This feature applies even when some of the devices are roaming. 11) Location Specific Trigger: This feature is intended for applications where the M2M devices are known to be in a particular area and thus the M2M device triggering is performed by using the location information. 12) Network-Provided Destination for Uplink: This feature is suitable for use with M2M applications that require all data from an M2M device to be directed to a network provided destination IP address. For uplink M2M communications, the network should use a destination IP address. 13) Infrequent Transmission: This feature is intended for M2M devices with long periods between two subsequent data transmissions. The network should provide resource only when a transmission occurs. 14) Group-Based Policing and Addressing: This feature is suitable for applications with an M2M group where devices should be optimized to handle in groups for tasks. The network operator may use group-based policing feature to perform a combined QoS policing. Group-based addressing M2M feature is suitable for applications with an M2M group, in which the network operator should optimize the message volume when M2M devices need to receive the same message. IV. C HALLENGES OF M2M C OMMUNICATIONS OVER 3GPP LTE/LTE-A N ETWORKS In M2M communications, the necessity for supporting a large number of M2M devices is a challenging issue. To provide ubiquitous wireless connections for M2M devices, 3GPP LTE-A introduces a heterogeneous network (HetNet) as a special network architecture for this purpose [5], [37], [38]. The HetNet comprises four parts: conventional macrocells formed by eNBs of E-UTRA, picocells formed by small transmission power eNBs deployed underlay macrocells to share traffic loads of macrocells, femtocells formed by HeNBs to enhance signal strength in indoor environment, and RNs deployed in coverage edges of macrocells (see Fig. 5). Higher layer connections among all above stations can be provided by 3GPP LTE/LTE-A infrastructure. On the other hand, in the HetNet, interference arises between macrocells and small cells, leading to the degradation of network enhancement. However, by applying recent solutions [39] for picocells, [39]–[41] for femtocells, and [42], [43] for RNs,


interference problems can be effectively mitigated. Consequently, ubiquitous connections among all M2M devices can be provided by attaching to these stations. However, it does not ensure a successful implementation of M2M communications in the 3GPP LTE/LTE-A and therefore some challenges are still there. One major challenge lies in the air interface. In order to meet requirements defined by International Mobile Telecommunications Advanced (IMT-Advanced), the air interference in LTE/LTE-A has been designed for broadband applications, while most M2M applications transmit and receive small amounts of data, leading to an unreasonably low ratio between payload and required control information due to the use of nonoptimized transmission protocols. In addition, the other important aspects, such as the need for low-energy and low-latency devices, have to be considered for M2M communications. Therefore, efforts have been made by 3GPP under the umbrella of MTC study and work items to begin the standardization process 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 diversity of M2M service characteristics, the need for enhancing energy efficiency, and coexistence with current communication systems. Some solutions have been proposed by using cooperative techniques among stations [45]–[49], and a group based operation of M2M devices, to be discussed in the text followed, has been regarded as a promising solution [3], [50]–[52] to support device-to-device (D2D) communications in the future. A. Group-Based Operations of M2M Devices The primary goal of grouping a number of M2M devices is to alleviate the signaling congestion on the air interface by reducing communication loads between an M2M device and 3GPP E-UTRA and EPC. Moreover, one of the most important requirements in cellular M2M communications is to reduce power consumption [53]. This requirement can be met by employing group based operation, where a group header collects requests, uplink data packets, and status information from M2M devices in the group, and then forwards such traffic to a station of 3GPP LTE/LTE-A. Furthermore, downlink data packets and control messages can be relayed by the group header from a station of 3GPP LTE/LTE-A to M2M devices in the group. For M2M communications, devices can be grouped logically based on service requirements or based on physical locations of M2M devices. One of the major applications of M2M communications is to gather measurement data from M2M devices. To logically group M2M devices, it should be mentioned that the traffic of such application typically has the characteristics of periodical packet arrivals, small data transmissions, and some given jitter constraints. Therefore, to develop practical scheduling schemes that support a large number of M2M devices with small data to meet the corresponding jitter constraints is a challenging issue. To tackle this challenge, M2M devices with similar characteristics can be merged into a group logically. Hence, the resources for these M2M devices can be scheduled on the basis of groups [52].

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To support physically grouped M2M devices, leveraging on the presence of more capable nodes to help others in reliably delivering their data is a good approach in a heterogeneous M2M communications in 3GPP LTE/LTE-A networks. However, the challenging task is how to place a number of such nodes in an environment so as to improve the overall network performance. It is foreseen that M2M communications will add some features to current cellular systems, such as WiMAX 1.0 system based on IEEE 802.16-2009 [6] or WiMAX 2.0 system based on IEEE 802.16m [54]. B. Device-to-Device Communications In a cellular network, direct communications between mobile devices are not permitted. Traffic should be routed via a core network even if a source and a destination are very close to each other. However, by allowing two physically close users to communicate directly, instead of being relayed by a core network, Device-to-Device (D2D) communication may achieve lower power consumption, less transmission delay, and less load distribution of data servers for locally processable M2M traffic. To enable direct communications among M2M devices, a new communication scheme (e.g., a new air interface standard with a new radio frame structure) will be defined in 3GPP Release 12, to establish communications between end devices [55]–[57]. The D2D communications can improve the efficiency [58]–[62] by exploiting the high channel quality of short range 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 over cellular networks include more efficient resource (e.g., spectrum) utilization because of direct routing of D2D traffic [63]– [68], and improved content delivery performance by using inter-recipient transmissions [69]–[72]. Therefore, the 3GPP intends to provide the interfaces and protocols for direct packets exchanges among M2M devices to enable communications for M2M devices in LTE/LTE-A networks. C. Cognitive M2M Communications It is expected that a large number of M2M devices will be deployed to support various applications. Even though the signaling congestion can be potentially alleviated by the group based M2M devices, if the number of M2M devices grows rapidly, this problem may not be easy to solve. In this situation, it may be needed to deploy more E-UTRA stations to dilute traffic of UEs and M2M devices. To tackle signaling congestion, E-UTRA stations for UEs and E-UTRA stations for M2M devices may need to work together. However, under this circumstance, interference between conventional H2H communications and M2M communications turns out to be a challenging issue. A centralized coordination may help to reduce the interference. However, due to the fact that centralized coordination creates significant signaling overhead and management burden, this scheme was not widely adopted. Therefore, for interference mitigation between H2H and M2M communications, an appropriate method is to employ a distributed resource management, and a promising solution known as cognitive M2M communications [74], [75] is particularly useful.

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To support wireless transmissions for a large number of devices, the M2M communications can work based on a random access channel (RACH). The advantage of using the RACH is that the devices can compete and access an available channel for wireless transmission independently without coordination and centralized control. Furthermore, the RACH mechanism has low communication and signaling overheads. This mechanism is found suitable for M2M communications as the data to be transmitted from M2M devices is usually small in amount. However, the RACH mechanism was designed to operate on the shared channels and the number of available shared channels is limited, and they also have to be shared with H2H communications. Therefore, an appropriate method to utilize the spectrum for M2M communications is required to support various wireless applications. Cognitive radio (CR) has been introduced to improve the spectrum utilization and transmission efficiency. In cognitive radio, unlicensed users (i.e., secondary users) are allowed to access the spectrum allocated to the licensed users (i.e., primary users) [73], as long as the transmissions of the licensed users are not interfered. Therefore, cognitive radio is a promising technique for M2M communications by allowing the devices to opportunistically access the channel, when such a channel currently is not used by the primary users. It is expected that cognitive radios can be an effective solution for the practical implementation of M2M networks [74]. D. Resource Allocation With QoS Provisioning Quality of service (QoS) provisioning is one of the most important requirements and challenging issues in M2M communications. M2M communications feature no or little human intervention, low power, high reliability, and low complexity. The lack of power supply is always a challenge that limits the performance of wireless communication devices, for both UEs and M2M devices. In H2H communications, battery can easily be changed in a handset. However, in M2M communications, saving energy for devices is more important than increasing the data throughput since M2M devices may be deployed in dangerous or non-reachable places. Consequently, the battery in an M2M device should be used for a relatively long time. Furthermore, a typical M2M communication network may consist of a large number of devices. To allocate radio resources efficiently while ensuring QoS requirement for reliable communications is an essential and challenging issue [76], [77]. In addition to energy consumption and reliability, complexity is another consideration in the design of M2M communications. Sophisticated algorithms should be avoided in M2M communication devices that should be simple and yet effective, which may 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 smart grid or navigation systems) require strict timing constraints, and catastrophes may occur if timing constraints are violated [52]. Therefore, in M2M communications, providing diverse and strict QoS guarantees is one of the most important and challenging issues [76]. Such diverse QoS requirements particularly

Fig. 10. Illustration of transmission links in 3GPP LTE/LTE-A networks with M2M communications.

need for appropriate resource allocation that can be applied to M2M communications in LTE and LTE-A cellular networks. In [51], joint massive access control and resource allocation schemes was proposed which perform machine node grouping, coordinator selection, and coordinator resource allocation, and also determine the proper number of groups under a 2-hop transmission protocol, to minimize total energy consumption in both flat and frequency-selective fading channel. Two major methods can be considered for radio resource allocation between M2M and H2H communications [79]. M2M and H2H communications can access the same radio resources via orthogonal channels. Although this scheme is simple, it leads to a low spectral efficiency. Another method is to use a shared resource allocation scheme. In this way, M2M devices can reuse the radio resources allocated to H2H communications to achieve a higher spectral efficiency. However, this may increase the interference level in comparison with orthogonal channel allocation. The minimum resource unit for downlink and uplink transmissions is referred to as a resource block (RB). One RB normally consists of 12 subcarriers (180 kHz) in the frequency domain and one subframe (1 ms) in the time domain [5]. When an M2M device has packets to transmit, it performs random access (RA) using the physical random access channel (PRACH) during an allowable time slot, called an access grant time interval (AGTI) or RA opportunity (i.e., RA-slots). In M2M communications, generally small amounts of data need to be transmitted. Although the data size is small, when a large number of M2M devices try to communicate over the same channel, the devices should contend to access the shared radio channels, causing the network overload problem. On the other hand, in collocated H2H and M2M communications networks (as shown in Fig. 10), various types of links exist 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, interference arises and poses a big challenge. Thus, it is needed to efficiently partition the radio resources in such networks [79]. The purpose of radio resource partition is to apply the restrictions to the radio resource management between H2H and M2M devices. Given the characteristics of links, the restrictions can be either on the transmit power or in the form of restrictions on available radio resources. Such restrictions improve the signal-to-interference-plus-noise ratio (SINR), and consequently 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 does not have uplink radio resources assigned to send user data or control data (e.g., a channel measurement report) to the eNB. Furthermore, random access procedure is used by the M2M device in order to perform handover from one eNB to another eNB, or to acquire the uplink timing synchronization. When the number of UE/M2M devices is an acceptable value, random access provides efficient request delivery. However, the number of M2M devices in a cell is expected to be much larger than the number of UEs. When a large number of M2M devices try to access the network simultaneously, it leads to a low RA success rate, and thus both M2M devices and UEs may suffer continuous collisions at the PRACH [17], [81]. This may cause packet losses, extra energy consumption, waste of radio resources, and unexpected delays. The channel can be further overloaded when the M2M devices repeat their access attempts after collisions. Thus, effective overload control mechanisms are 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 performance in terms of throughput of random access and traffic channels, and random access delay was evaluated. Furthermore, best effort application for random access in wireless multimedia network [83] and distributed random access scheduling exploiting the time-varying nature of fading channels for multimedia traffic in multihop wireless network [84] have been studied. In the next part of this section, we review the existing mechanisms for controlling PRACH overload to support M2M communications in LTE/LTE-A networks. To support M2M communications in LTE/LTE-A, the following solutions have been proposed for controlling PRACH overload [46], [47]. 1) Backoff Scheme: The backoff scheme is used to delay the random access (RA) attempts of H2H and M2M devices separately. In this scheme, the backoff time for the H2H devices is set to a small value (e.g., the maximum backoff duration 20 ms); while the backoff time for the M2M devices is set to a large one (i.e., an upper limit for the retransmission intervals, which can be as long as 960 ms). This scheme is effective in low channel overload, and thus it can alleviate collisions in these situations. However, it cannot solve the congestion problem in heavy overload situations when a massive number of M2M devices initiate RA at the same time. Seo and Leung [85]

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studied the uniform backoff in LTE relative to the exponential backoff in IEEE 802.16 WiMAX. Furthermore, these authors investigated a multipacket reception (MPR) slotted ALOHA system using binary exponential backoff (BEB) algorithm with infinite buffers in the mobile terminals [86]. 2) Slotted Access Scheme: In this scheme, each M2M device is allowed to perform RA only in its dedicated access slot. At other times, the M2M devices are in sleep mode. The M2M devices can calculate the allowable access slots through its ID and RA-cycle. The eNB broadcasts the RA-cycle, which is an integer number multiple of a radio frame. The number of unique RA-slots is proportional to the RA-cycle length and the number of RA-slots within a radio frame. PRACH will be overloaded when the number of M2M devices in a cell is greater than the total number of unique RA-slots. In this case, several M2M devices share the same RA-slot and collisions may occur. Increasing the RA-cycle can reduce collision but creates unacceptable delay for an RA request. The impact of the number of transmission attempts on the throughput and delay of the slotted ALOHA based preamble contention in the LTE-A random access system investigated in [87]. 3) Access Class Barring (ACB) Scheme: The ACB-based scheme was originally designed for the access control of devices. In this scheme, an eNB broadcasts an access probability (AP) and access class (AC) barring time. In the ACB, there are 16 ACs. AC 0–9 represents normal device, AC 10 represents an emergency call, and AC 11–15 represents specific high-priority services. When a device initiates RA, the device randomly draws a value between zero and one, and compares this with AP. If the number is less than AP, the device proceeds to the random access procedure. Otherwise, the device is barred for an AC barring duration. The ACB scheme can deal with excessive PRACH overload by setting an extremely small value of AP. However, a small AP leads to unacceptable delay for some devices. From the Release 10 and onwards, the existing ACB scheme has been extended to allow one or more new ACs for M2M devices, and an individual access barring factor can 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 devices belonging to certain ACs (i.e., delay-tolerant devices) are not allowed to perform RA. However, without cooperations among eNBs, devices within dense area suffer severe access delays. To facilitate devices escaping from continuous congestions, [49] proposed the cooperative ACB for global stabilization and access load sharing to eliminate substantial defects in the ordinary ACB, thus, significantly improving access delays. 4) Pull-based Scheme: The pull-based scheme is a centralized control mechanism, in which the M2M server requests the eNB to page the intended M2M devices. Upon receiving a paging signal from the eNB, the M2M device will initiate RA. In this scheme, the eNB can control the number of devices to be paged by taking into account

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the PRACH load and resource availability. However, this scheme requires extra control channel resources to page a huge number of M2M devices. 5) Dynamic PRACH Resource Allocation Scheme: In this scheme, the eNBs can dynamically allocate PRACH resources based on PRACH overload condition and overall traffic load. When a subframe is used for the PRACH, part of that subframe cannot be used for data transmission. Therefore, to meet a given QoS requirement, a certain number of subframes should be used for the PRACH. Although dynamic allocation of PRACH resources can be applied in most cases, the efficiency of this scheme is limited by the availability of additional resources. A selfoptimizing algorithm was proposed in [89], where the eNBs can automatically increase or decrease the number of RA-slots based on channel traffic load. F. Reliable Data Transmission In M2M communications in 3GPP LTE/LTE-A, each transmission of an M2M device may only carry a small amount of data due to the small data transmission feature. Therefore, a high peak data rate transmission scheme may not be necessary for M2M devices. Instead, reliable transmission (i.e., low bit error rate, and low latency) are essential. Network coding has been shown to provide an effective means for efficient reliable data dissemination and to require little coordination among nodes. Furthermore, random data combination is a lightweight, yet effective, mechanism to provide adequate reliability and error control with little overhead. These paradigms have been shown to greatly improve the performance of dissemination in homogeneous networks, but extension of these techniques to heterogeneous scenarios like M2M communications in 3GPP LTE/LTE-A has not yet been addressed. Finally, for densely deployed nodes with limited individual capabilities in such networks it makes sense to look into distributed processing paradigms for decoding. G. Energy Management Energy management ranging from harvesting, conservation, to consumption is a major issue in the M2M communication context in 3GPP LTE/LTE-A networks. Reducing power consumption is one of the major challenges in M2M communications. In the literature, various energy-efficient MAC protocols [16], [90], [91] exist that can be implemented in M2M system to save energy. However, the development of novel solutions that maximize energy efficiency is essential. Network protocols will have to deal with inherent characteristics of M2M communications such as long sleep cycles, energy and processing power constraints, time-varying radio propagation environments, and topologies varying with node mobility. In this regard, current technology is inadequate, and existing processing power are too low to meet future requirements. Therefore, the development of novel, more efficient, and compact energy storage sources such as fuel cells and printed/polymer batteries are paramount. Furthermore, developing new energy generation devices coupling energy trans-

mission methods or energy harvesting using energy conversion, as well as extremely low-power circuitry and energy efficient architectures and protocols will be the key factors for roll out of autonomous and smart M2M communications in 3GPP LTE/LTE-A networks. In order to realize the decoupling of M2M applications and services, novel energy efficient service discovery mechanisms must be designed to minimize human intervention during configuration and management phases [92]. H. Self-Management Capabilities In order to support the expected huge scale of M2M communications in 3GPP LTE/LTE-A, devices will need to selfmanage without external intervention [93]. Due to multi-path fading, path loss, and shadowing phenomena in radio channels, self-management learning is essential when an M2M system encounters with such dynamic and unstable environment. Therefore, when trying to apply M2M communications in 3GPP LTE/LTE-A networks, we have to face the exponential growth in complexity that the connection of large number of devices will bring, which will call for context awareness, selforganization, self-management, self-optimization, self-healing and self-protection capabilities. In a wireless context, the increased topology dynamics due to channel fluctuations and possible device mobility, as well as the loss of signaling and control messages, make these issues all the more challenging task. M2M communications encompass a huge sensor network, with immense amounts of sensor data from various sensors, meters, appliances and electrical vehicles. Data mining and predictive analytics are essential for efficient and optimized operation of such network. A key question is how to analyze and process these data in an efficient and timely manner. Various machine-learning techniques can be used in this regard for data analysis and processing. V. M2M C OMMUNICATIONS A PPLICATIONS The emergence of low-power and low-cost sensors and actuator nodes (such as radio frequency identification, or RFID tags), which are capable of communicating wirelessly using standardized interfaces and protocols, and increased computing capability make it possible to develop a large number of applications for M2M communications in 3GPP LTE/LTE-A. These M2M applications significantly improve the quality of our life at home, at work, in traveling, etc. These M2M applications were proposed based on the possibility for a large number M2M devices to communicate with each other and to convey the information they perceive from the surroundings where a wide range of applications are deployed. These M2M applications can 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


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Fig. 11. M2M applications and relevant scenarios.

others may be futuristic such that we can only imagine at the moment, as the technologies are not available yet and we are not ready for their deployment (see Fig. 11). In the following subsections, we will discuss all of them. A. e-Health Various advantages of the M2M communications can be useful to the healthcare applications, and those M2M applications can include tracking and monitoring of patients and drugs, identification and authentication of patients in hospitals, automatic medical data collection and retrieving [94]. 1) Tracking and Monitoring: Tracking is a function aiming at the identification of a person or object in motion. This includes real-time position tracking, such as the case of tracking a patient or tracking the motion of organ (or a segment of an organ) in a patient. In terms of physical assets, M2M communications can also be used in continuous inventory/stock tracking (e.g., for goods availability maintenance), and substance tracking to prevent left-ins during a surgery. In the case of monitoring [95], the M2M applications in e-health enable remote monitoring of patient health and fitness conditions via M2M sensor nodes, alerting services when elderly people fall, and triggering alarms when critical conditions are detected. The M2M communications can also help in remote medical treatments or operations. 2) Identification and Authentication: Identification and authentication in healthcare are needed in a variety of forms,

including patient identification to reduce the risk of wrong treatments 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 commonly used to grant security access (e.g., to restricted areas and containers). 3) Data Collection: Automatic data collection and transfer is required to reduce patient processing/treatment time and to implement medical treatment automation (including medical data retrieving), medical care service and procedures auditing, and medical inventory management. Depending on the types of M2M applications, data collection may proceed in different ways [9]. For example, important and vital information in e-health should be delivered as soon as detected, whereas the energy consumption data at home may be collected only once a time. The M2M system should support different ways of data delivering/reporting requested by the M2M applications as listed below [9]: • A periodic reporting with the time period being defined by the M2M applications; • An on-demand reporting with two possible modes, one being instantaneous collecting and reporting of data, the other being reporting of data that were pre-recorded at a specific time period; • A scheduled reporting; or • An event-driven reporting.

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4) Sensing: Sensor devices enable many functions related to patients in healthcare, in particular on diagnosing patient conditions, providing real-time information on patients’ biological data [94]. A body area network (BAN) of sensors is typically deployed around a patient to record his/her biological parameters, such as blood pressure, body temperature, heart rate, weight, etc. In order to enable the M2M applications for e-health and to acquire the information on a patient’s health, the BAN of M2M sensors have to be used. For this reason, the patient or monitored person typically wears one or more M2M sensor devices that record health indicators (e.g., body pressure, heart rate, etc.). Due to the strict constraints on form factor and battery consumption of these M2M sensors, it is expected that they require to forward the collected data with some short range technology to a device that can act as an M2M aggregator of the collected information and an M2M gateway. Then, the LTE/LTE-A as an access network connects the M2M gateway to the M2M core network. Through the M2M core network, the M2M gateway is connected to the M2M server that stores and possibly reacts to the collected data and subsequently the M2M application user (i.e., healthcare remote monitoring center). In this scenario, the gateway could be a fixed device such as a PC or a mobile device like a cell phone or a standalone device carried on a keychain or worn around the patient’s wrist or neck. B. Smart Environment With recent advances in wireless communications, intelligent systems, sensor networks, the quality of human life has been improved significantly in every aspect. A futuristic smart city based on M2M communication technologies, first proposed by IBM as one of its most important strategies, may generate an enormous amount of information, and it is capable of collecting, managing, and taking advantage of the information to implement automations in our daily life. Making better decisions based on real-time information leads to significantly reduced living costs, and more efficient utilization of natural resources. To this end, the M2M communications can be used every 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 environment surrounded by various electronic appliances, such as lights, air conditioners, heaters, refrigerators, microwave ovens, and cookers. Sensors and actuators of M2M communications are installed in these devices to make a more efficient utilization of energy and also to make our life more comfortable. Heating and cooling in homes can be adjusted to the weather conditions to maintain a desirable temperature. The lighting in rooms can be adapted to the time of a day and to the number of occupants inside the rooms. Domestic incidents, like fire, a fall of elderly people, or burglary can be detected with appropriate M2M monitoring and alarm systems associated with the M2M devices in place. Energy saving can be improved by automatically switching off the electrical devices when not in use. Consequently, the power consumption costs can be reduced by using electric appliances only when the energy price is cheaper,

a function that can be implemented with the help of smart grid technology [103]. Smart cities, as a new concept in urban planning, have attracted a lot of attention recently. Connected by M2M communication technologies, the people living in the urban areas will 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 the existence of the smart cities in the years to come. Imagine a scenario that people are going shopping in a smart city, where advertisements can be delivered to a customer based on his/her particular taste or hobby, telling him/her about a store around the corner that is selling the items the customer is just looking for with a significant discount available. Once people enter the stores, M2M communication infrastructure can provide unique and innovative communication channels and everything is connected, including beverage coolers and freezers, and people can sense and thus be aware of the drinks they want in the beverage coolers and freezers with their location information displayed in the M2M mobile terminals attached to the glasses or watches. The M2M technology can also optimize inventory, provide automatic updates on maintenance needs, or even handle payment services. This allows retailers to cut down the cost, while ensuring the customers’ satisfaction. 2) Smart Lighting: Another M2M application is to implement smart lighting systems for the homes, offices and streets. Smart lighting can also attribute to a significant improvement on energy saving in the cities around the world. Due to the rapid growth of the urban population, at present about half of the world population live in cities. This trend will continue to escalate with an estimation that by 2050 about 70% of people will live in cities and the number of mega-cities with their populations more than 10 million will increase. This undoubtedly poses a new challenge to the city management, intelligent building, and environment protection, especially in energy management efficiency. Therefore, a highly efficient illumination systems in streets of a city is extremely important to reduce carbon emission, which has be put into the agenda for many big cities in the world. Apart from energy saving through improving lighting systems, smart lighting could contribute to another 40% of electrical energy saving through the implementation of advanced lighting management systems based on M2M technology [105]. More specifically speaking, the power consumption reduction policy in Europe has been extended from cities to the street lighting systems in order to reach the desirable energy efficiency for Europe in 2020, and the low-carbon European economy by 2050 [106]. Therefore, M2M technological innovations, such as remote street light control that allows the M2M user applications such as the city lighting control managers to monitor and control street lights by smart phones, turning them on or off automatically depending on local illumination levels and traffic intensity will soon be widespread. 3) Smart Industrial Plants: Industrial M2M communications will enhance intelligence in control systems to improve the automation in industrial plants by exchanging and gathering information among sensors, actuators, and RFID tags in M2M communications associated with the products. These M2M 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 devices immediately connect to the M2M controller server and transmit this event-related information to the M2M server through the 3GPP LTE/LTE-A core network [96]. If the robots detect an emergency shutdown event, M2M controller server will stop their working immediately. The M2M application user (e.g., plant manager) can also see the status of the Enterprise Resource Planning (ERP) orders, the production progress, the M2M device status, as well as a global view on all factories. It can also predict the consequence of device malfunctions in the production lines based on the information stored in the M2M controller server. 4) Smart Water Supply: Nowadays, demand for water continues to grow rapidly, and worldwide water usage is increasing at a rate twice as fast as the population growth. Many corporations rely on water for their critical functions from management to manufacture. However, most people do not know how much water is wasted. As a matter of fact, a large percentage of world’s water disappears from aging and leaky piping systems, costing a huge amount of money every year. To combat this problem, smart cities must be able to monitor water supply closely to ensure that there is an adequate water supply to residence and business. Smart cities equipped with M2M sensors can accurately monitor water piping systems and discover water leakage at the very first moment. These M2M sensors measure pipe flow data regularly and propagate alerts and transmit an emergency message to the M2M controller server via the 3GPP LTE/LTE-A core network if water usage is beyond an estimated normal range. This M2M communication capability allows a smart city to determine the locations of leaking pipes to prevent a waste of precious water resource. 5) Green Environment: Managing electric devices to maximize energy efficiency is one of the most important issues to establish the green cities. Recently, smart grid has been received a considerable attention as an intelligent solution to manage electric power consumption. The main concept of smart grid is to employ intelligent communication networks to meet the pressing demands for efficiency improvement on power generation, distribution, and consumption sectors with the help of M2M communications. In addition, smart grid works based on an environmentally friendly infrastructure in order to keep its energy wastage as low as possible for minimizing CO2 emission. To realize this goal, it is of great importance to equip smart grid with the abilities to autonomously collect data from various sectors of the grid systems, analyze data on energy usage in real time, and self-configure its operating parameters to achieve the goals. For the aforementioned M2M applications can be considered the following structure. The M2M devices (e.g., a home appliance, smart lighting system, water piping system, etc.) are connected to a smart meter and their information is measured and collected by the smart meter. Due to the resource-constrained sensors associated in the M2M devices, wireless communications technologies based on Zigbee can be established among M2M devices and a smart meter. To collect data packets from smart meters to the M2M gateway short-range communication technologies (e.g., WiFi) could be utilized. The received

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packets are stored in the buffer of the M2M gateway. Different types of data packets with different QoS requirements can be stored in different buffers. The 3GPP LTE/LTE-A transceiver of the M2M gateway receives a head-of-queue packet from the buffer and transmits it to a 3GPP LTE/LTE-A eNB. The 3GPP LTE/LTE-A eNB is in charge of bandwidth allocation for the data transmission of each M2M gateway. After the data packets sent from M2M gateway are received by the eNB, they are then forwarded to the M2M control center. The M2M server is located at the M2M control center for processing and storage of the received data. This data is used to monitor, control, and command for the M2M devices. C. Intelligent Transportation With an increasing number of vehicles on the road, the transportation and logistics services represent another big market for 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 and transported goods use M2M sensors and tags that can also send valuable information to traffic M2M control centers and transportation companies to route the traffic, monitor the status of the transported goods, seamlessly track the physical locations of fleet vehicles, and deliver updated schedule information to customers. More M2M applications in the transportation and logistics services are discussed below. 1) Logistics Services: Goods supply chain can work in a more efficiency way as M2M communications provide possibility to track the status of goods in real-time via the M2M sensors associated with them. The M2M logistics enables total surveillance on the status of goods, raw materials, products, transportation, storage, sale of products, and after-sales services by keeping an eye on temperature, humidity, light, and weight, etc. If the status has some problem, the M2M devices can automatically send an alert to the M2M server via the 3GPP LTE/LTE-A core network. Furthermore, it is also possible to track the inventory in a warehouse so that stockholders and enterprises can respond to the market dynamics and to decide when to refill and when to go on-sale. Therefore, this can significantly reduce the space of warehouse, the waiting time of customers, and the number of the employees to save the operational costs for business entities [97]. 2) M2M Assisted Driving: Intelligent transport systems based on M2M technologies along with the roads equipped with M2M sensors and actuators can help to optimize and control the traffic flows, and vehicle navigation/safety, to reduce the costs and carbon emissions. A sleepy driver can be alerted and warned by the driving behavior M2M monitoring systems to avoid possible traffic accidents. M2M communication systems can also automatically call for help when they detect an accident, and they can alert people if they detect hazardous materials on vehicles. Furthermore, the governmental authorities can overview road traffic patterns for traffic route planning purposes. Moreover, the information about the movement of vehicles transporting goods together with the information about the types and status of the goods can be used to predict the

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delivery time of goods and the time when the traffic peaks will arrive or end. 3) Fleet Management: Today, a large number of container cargo ships are traveling through international waters. These container cargo delivery services may risk theft, physical damage, delivery delays, piracy, and even ship sinking. M2M technology provides solutions that are being used in fleet management to acquire a better control where cargos can be rapidly delivered across different continents. The M2M applications enable the tracking of vehicles and cargo containers to collect the data on locations, fuel consumption, temperature, and humidity, in order to increase fleet safety, reduce the accident rates, and increase the productivity of a fleet company. With more precise information, greater control, better resource management, and higher cost effectiveness, a fleet business can be able to maintain its competitiveness with the help of M2M technology. 4) e-Ticketing and Passenger Services: Ticketing systems of traditional public transport systems are based mainly on manual systems, and in some cases semi-automatic and/or automatic systems are used for fare collection. In most cases, they involve tedious, time-consuming, and stressful labors due to the need of human interventions. As a better choice, the e-ticketing model can be utilized, which comprises of a Near Field Communications (NFC) enabled device as a M2M sensor node for scanning passenger’s identity at the entrance/exit of the stations. Once a mobile phone with NFC capability is scanned in the pay station, the code number of the station is sent to the M2M transportation service provider through the 3GPP LTE/LTE-A core network. Based on the tariff table and distance traveled, the fare is calculated and sent to the mobile M2M service provider, which deducts the money from the passenger’s account. Furthermore, the information about transportation services (e.g., cost, schedule update, number of passengers, and available services) can be saved in an M2M NFC tag. As a matter of fact, the customers can get this information by hovering their mobile phones over the M2M NFC readers. Mobile ticketing can enhance the effectiveness of ticketing, save the costs for transportation service providers, and increase convenience of passenger. 5) Smart Parking: Nowadays the car is the most ubiquitous means of transportation of human beings. Driving a car in urban environments has, however, significantly deteriorated living conditions. This is mainly caused by long searching times which causes frayed nerves, significant pollution, reduced working time, financial loss and much more [98]. M2M application in smart parking is a proven, robust and cost-effective way to ensure that road users know exactly where unoccupied car parking spaces are. Worldsensing [98] provides a cutting edge wireless smart parking technology named Fastprk that is based on a robust package of M2M sensors embedded into the tarmac so that it enables drivers to find parking quickly and efficiently. Fastprk not only can reduce the frustration experienced when trying to locate a parking spot, it will also allow drivers to save time, fuel, and associated costs. In addition, it allows the city council to monitor and manage the parking spaces, and getting real time information. The system relies on embedded M2M sensors in each parking bay in the street. When a car parks

over the M2M sensor, it is detected and M2M sensor relays that information in a wireless way to the 3GPP LTE/LTE-A’s gateway. Then the gateway sends the information to the 3GPP LTE/LTE-A core network. Finally, the core network can send the information via the Internet to the M2M database server in real time. The occupancy is then instantly reported to users via apps and illuminated panels in the street. 6) Smart Car Counting: It is expected that a large number of people will live in the cities in near future, and in the next 20 years the urban population will grow from 3.5 billion to 5 billion people. Therefore, it is undeniable that the private car as a means for transportation will predominate in one form or another for the next decades to come. This undoubtedly poses new challenges in terms of city management, city traffic control, and intelligent transportation. It would be necessary to establish data collection station that provides accurate detection of vehicles for measuring traffic flow. In this regard, Sensefield [99] offers an end-to-end solution for traffic management. Wireless M2M sensors installed on the pavement detect vehicles and measure their speed and length. This information is transmitted to a nearby Data Processing Station (DSP) that rolls as a M2M gateway and provides diverse connectivity and serves as a local hub. Through the 3GPP LTE/LTE-A core network, DSP can be able to transmit collected data to the M2M server. Then, the M2M control center utilizes this data to manage and monitor the infrastructure and analysis the traffic data to ease traffic flow and to smooth transportation in the city region. 7) Journey Time Estimation: Currently available real-time traffic information is practically non-existing and insufficient both for road operators and for travelers. The root of the problem can be found in the data collection systems, which are expensive, inefficient, and inadequate. In addition to the limitations in data collection, most traffic information and management solutions are unable to provide a complete integration in real time of data collection, aggregation, and dissemination. Bitcarrier [100] offers a solution for traffic information and management in any kind of road. This solution consists of three main elements that are as follows. 1) A network of M2M sensors auditing the Bluetooth and WiFi 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 embarked in vehicles, provided that the Bluetooth and WiFi sensors of the mobile devices are active. Furthermore, this solution ensures total privacy protection for travelers. The M2M sensors collect anonymous data which is further encrypted before being sent to the M2M server database. As original data is encrypted and destroyed, 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 residential, as well as commercial and public locations. The concerns over security and safety are attracting a lot of attention.


A great demand for effective security systems makes the M2M communication technology a perfect choice for the simplification and automation of security and public safety monitoring and management. The M2M technologies provide costeffective, rapid, and flexible deployment for remote surveillance, remote burglar alarms, personal tracking, and public infrastructure protection. 1) Remote Surveillance: Remote surveillance is one of the public safety applications. Remote surveillance systems can be applied to monitor any open areas, valuable assets, people or even pets for appropriate protection, where M2M sensors in video cameras are used to transmit signals either continuously or at a fixed interval. The M2M applications can help to detect possible risky situations, trigger proper actions, alert authorities, and keep an eye open to all suspicious activities and incidents. More specifically, the M2M applications can let the user know if some objects are moved to/from a restricted area (e.g., home or office), report to an unauthorized entity, and provide the exact locations of the incidental events. In this case, the event has to be notified immediately to the owner, authorities, and/or to the security companies. The M2M communications can simplify the designs of alarm management and quick reporting 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 integrated with the M2M technology, allow users to be informed where their relatives/friends are on a real time basis, and they can be warned in case of troubles/risks or when they request for any assistance. In this application [9], persons, assets, and/or animals are equipped with portable M2M devices, each of which contains a M2M communication module, together with an optional GPS unit, which sends location information automatically or on an on-demand basis to an M2M application server via 3GPP LTE/LTE-A core network, then, the core network can send the information via the Internet to the M2M database server in real time, which can monitor the status while also being able to track and trace the persons, objects, or animals. 3) Public Infrastructure Protection: Every government has a wide range of infrastructure, such as roads, bridges, tunnels, buildings, cables, pipes, which should be maintained and monitored. The applications of M2M technology enable the government agencies to enhance their operational efficiencies, and to cut the costs for infrastructure maintenance. The M2M communications can be used to efficiently monitor the condition of public infrastructure equipped with M2M sensors or M2M RFID tags and even simplify daily maintenance by automating some routing tasks, including remote parking management, selective activation of street lights, or remote surveillance of public spaces.

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

digitized world is creating a sheer volume of data at a rapid pace, which requires numerous new approaches to delivery that amount of data effectively. The emerging Big Data technology can significantly improve the efficiency to process those digital data. In fact, the Big Data has a great potential to materialize “everything” in the near future. Furthermore, both M2M and Big Data technologies will be needed, and possibly be merged as an important platform for the construction of futuristic intelligent societies, such as a smart city or a smart community, etc. In order to enhance our society in terms of its intelligence and innovation level, it is required to construct a comprehensive service platform. Based on the argument made by Robert Metcalf that the value of a network increases exponentially as devices connect. Therefore, more M2M devices must be linked to each other and the information from these M2M devices must be collected, not individually but all at once. To achieve this, service platform must be shifted from that of a conventional vertically integrated platform system (or individually optimized service) to a horizontally integrated platform system [107]. As depicted in Fig. 12, the horizontally integrated M2M service shares the data collected from various M2M devices and utilizes them for various services. Furthermore, the M2M application users can construct an M2M system with less investment cost than for those systems that are constructed individually since instead of accumulating the required information to construct a desired system, employment of a horizontally integrated M2M platform enables the availability of the information for efficient use by various services. Integrating M2M with Big Data, we create a new information based society, namely “Information-ambient society”. The “Information-ambient society” will evolve even further and eventually it will provide us with a society, in which machines detect various conditions by using their sensors. It will have its capability to understand what the human being is thinking in an autonomic manner. This is a salient feature of the “Informationambient society”.

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

F. Robotic Applications Robotics are able to improve the quality of our life, to save costs, and to minimize the resource wastage. In the future,

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robots will be highly intelligent, and networked with other robots and human beings. They will be used not only to clean and guard our homes, but also to assist elderly and handicapped people, perform surgery, conduct dangerous tasks, such as identifying and disabling improvised explosive devices (IED), fire-fighting, and hazardous site inspection. These robots are machines controlled by machines (M2M) with their ability to sense, reason, and communicate in a real time basis. They will certainly become very powerful tools in our life in the future. In particular, the M2M based robot controlled cars or driverless/unmanned vehicles will become more and more popular in the near future. They could help to reduce traffic accident risk to human-beings. Furthermore, these robot based driverless vehicles will be widely used in cargo transportation to reduce the traffic accidents caused by manned vehicles due to the tiredness of the drivers. Some studies carried out by the IEEE reveal that, by 2040, driverless cars will account for up to 75 percent of cars on the roads worldwide [108]. G. Environment Monitoring Environmental monitoring is essential to verify environmental stress, understand ecological patterns, and evaluate the effectiveness of environmental protection policies and programs. Environmental monitoring includes to monitor air, water, soil, animals, and plants. M2M communications provide the solutions that can automatically take samples and convey the monitored results to the government agencies in charge, and this has become an extremely important part of environmental monitoring programs in various countries of the world. Furthermore, the quality of fruits, vegetables, meat, and dairy products is vital to the health of their consumers. Foods from production to consumers have to go through various stages and be transported over thousands of kilometers before reaching their consumers. During the transportation processes, the preservation status (e.g., temperature, humidity, and light) need to be monitored closely with the help of appropriate M2M sensors. The M2M sensors can precisely measure these variations and send the related information to the M2M server via 3GPP LTE/LTE-A core network immediately whenever needed. The advancement of pervasive computing and sensor technologies offers an effective solution for monitoring the environment and in-danger animals/plants [101], [102]. VI. O PEN R ESEARCH I SSUES A. Traffic Characteristics The characteristics of M2M communication traffic are different from those of H2H network traffic. M2M traffic encompasses specific traffic patterns due to its special functions (e.g., data collection and monitoring) and requirements (e.g., strictly real-time based traffic), whereas H2H traffic follows a certain data volume, session length, and interaction frequency. Traffic characterization is an important issue for designing and optimization of network infrastructure. It is well known that traffic characteristics in wireless sensor networks depend very much on the application scenarios [109]. It is not a problem as the issues of interest are focused on the traffic flow inside the wireless

sensor network itself. Complications arise when sensor nodes become part of the overall M2M communication networks. In this case, the M2M communications will be traversed by a large amount of data generated by sensor networks deployed for heterogeneous purposes, thus with extremely different traffic characteristics. M2M applications may generate different traffic patterns such as streaming, periodic, and event-driven signals [17]. In addition, the M2M data could have varying sizes and bandwidth requirements. In the case of video monitoring devices, data having a size of megabytes could be normally expected. In the case of sensor data (e.g., temperature and humidity), the amount of data per transmitted packet is usually small, and the measured data is reported in periodical intervals. Although those intervals may range from several minutes to hours [110], the aggregation of multiple M2M devices may form a noticeable dense node distribution scenario. Furthermore, allocating a single PRB to an M2M device that transmits only small data could significantly degrade the spectral efficiency. In cases of emergency event-driven traffic like fire and flooding, networks may have to deal with simultaneous transmissions of emergency data. This can severely impair the overall network performance and may blockage resources for other regular users. M2M traffic characterization is also required to cater for QoS guarantee for various M2M applications. The matter of resource allocation for LTE/LTE-A stations for the support of QoS provisioning for M2M devices is also a challenging problem that is still subject to further research. The straightforward employment of the existing LTE/LTE-A protocols may not satisfy the requirements of M2M communications due to the large-bandwidth and low-latency links used in LTE/LTE-A networks. Therefore, a new concept of the transport layer is required for M2M communications with regard to the use of LTE/LTE-A networks. Transmission Control Protocol (TCP) utilized at the transport layer is known as inadequate for M2M traffic due to the following reasons: • Connection setup: most of the communications in M2M deal with the exchanges of a small amount of data, and thus the setup phase accounts for a noticeable portion of the session time which is unnecessary. • Congestion control: one of the major goals of TCP is to perform end-to-end congestion control. In M2M communications in 3GPP LTE/LTE-A, this may cause performance degradation problems since the communications are performed by utilizing wireless medium. In addition, if the amount of data to be exchanged is very small, TCP congestion control would be useless. • Data buffering: TCP requires data to be stored in a memory buffer. Management of such a buffer may be not efficient regarding to the resource-constrained M2M devices. • Real time applications: TCP was not originally designed for real-time applications and it is not adequate for M2M wireless communication networks. Therefore, an enhanced congestion control mechanism is required to improve the performance of TCP over LTE/ LTE-A before it can be suitable for applications in M2M communications.


The REST architecture is another approach which consists 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 devices in M2M communications. To meet the requirements of resource-constraint M2M devices, Internet Engineering Task Force (IETF) has standardized constrained application protocol (CoAP). The CoAP involves very low Hypertext Transfer Protocol (HTTP) overhead and supports multicast and asynchronous message exchanges over a user datagram protocol (UDP) particularly suitable for M2M applications. However, there are still some concerns regarding to the CoAP applications that require for further considerations. A primary issue is the creation of an intuitive network that directly includes device data without the need for a cross-proxy. Another concern is the ways to support for CoAP’s security. In the past, various solutions have been proposed for the mobility management. However, their validity in the M2M communications should be proven in terms of their scalability and adaptability before being applied to such a heterogeneous network. Another issue regards to the ways in which addresses are obtained. In the M2M communications, the Object Name Service (ONS) associates a reference to a description of an identifier to be translated into a Uniform Resource Locator (URL), identifying where the information about the object resides. In the M2M applications, the ONS should operate in both directions, i.e., it should be able to associate the description of the object specified to a given identifier, and vice versa. Inverting the function is not an easy task and needs an appropriate Object Code Mapping Service (OCMS). Desired features for OCMS were investigated in [111], where a peer-to-peer (P2P) approach was proposed in order to enhance scalability. However, design and evaluation of OCMS in heterogeneous M2M communications are still open issues that require for further considerations. B. Routing Protocols The sensor networks [112] as a primitive form of M2M communications are utilized for sensing and gathering application based on low-rate, low bandwidth, and delay tolerant data collection processes. While current research considers for more sophisticated applications such as scientific, military, healthcare, and environmental monitoring researches, where each M2M device performs various tasks ranging from sensing, decision making, and action executing. Therefore, the communication framework for the sensor nodes in M2M communication encounters various difficulties in satisfying the different technical requirements of these applications. Furthermore, the aforementioned applications have different QoS requirements (e.g., delay, throughput, reliability, bandwidth, and latency) and traffic characteristics. To extract more realistic and precise information of fast changing events in the real world and also to deal with them in a responsive manner, the abilities of sensor nodes in M2M devices should be significantly enhanced. Wireless Multimedia Sensor Networking (WMSN), as a powerful and intelligent class of sensor-based distributed systems, is gaining more popularity since its capability of ubiquitously

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retrieving multimedia information to support a large number of both non-real time and real-time applications [113]. However, routing to satisfy the stringent QoS requirements of multimedia transmission in a resource-constrained M2M communication imposes new challenges. Despite the availability of various routing protocols, the problems still remain and other challenges are emerging with regard to the growing demands for M2M applications [113]– [115]. These challenges include mobility issues of sensors and sinks, multiple sources and sinks, dynamic hole bypassing, cross-layer awareness, multi-channel access, resource constrained QoS guarantee, and secure routing. Available routing protocols proposed for the resource-constrained networks concentrate only on power consumption with the assumption that data traffic has no or loose QoS requirements. Therefore, to provide various QoS requirements for M2M applications and to be power efficient, routing techniques are needed to be significantly improved or re-invented. C. Heterogeneity One of the main requirements for the M2M communications in 3GPP LTE/LTE-A network to be successful is its capability to integrate many types of devices, technologies, and services. At the device domain, this involves vast variety of features in terms of data communication capabilities (e.g., data rates, latency, and reliability), flexibility in handling different technologies, availability of energy, computational and storage power, etc. As to services, the system should be able to support very diverse applications, whose characteristics and requirements may be extremely different, in terms of bandwidth, reliability, latency, etc. These heterogeneity properties of the overall system make the design of communication protocols a very challenging task. There are several other challenges and open research topics to be investigated in future, which are listed as follows. 1) Spectrum Management: In wireless M2M communications, spectrum scarcity is a serious issue for most applications. Heterogeneous LTE/LTE-A network is a new trend in telecommunications, which could significantly enhance spectrum efficiency, power saving, and signal strength and coverage area. However, with the deployment of M2M communications based on the LTE/LTE-A, significant spectrum sharing problems may arise resulting in a low spectrum efficiency. Therefore, the improvement of spectrum efficiency under a spectrum sharing environment for M2M communications should be carefully considered. 2) Opportunity Access: In this way, cognitive radio technique is used to detect spectrum holes and utilize them for dynamic access. It is flexible for supporting various systems including M2M applications in LTE/LTE-A. However, the opportunity access requires complex technologies for detecting the white spectrum space and efficient radio resource management protocols without interfering to the primary users. 3) Connectivity: Another key area of investigation is how to provide communications capabilities to the various devices involved in 3GPP LTE/LTE-A M2M communications. Issues such as communications energy consumption, antenna design, interoperability of different technologies (e.g., via cognitive

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radio capabilities), adaptive techniques for a dynamic environment in the face of possibly heavily constrained resources, etc. will have to be addressed. Furthermore, it should be mentioned that a system that is too connected becomes hard to manage (e.g., due to the excessive interference), thus, it will be important to understand what needs to be connected so as to provide the necessary communications capabilities for M2M devices. Moreover, the 3GPP LTE/LTE-A standards provide ubiquitous wireless access by attaching to eNBs through single-hop links in H2H communications. However, distinct characteristics and a large number of devices in M2M communications may create some other challenges if compared with H2H communications. Therefore, in this scenario, utilizing single-hop may not be an appropriate solution and multi-hop connections may be needed instead, and thus further investigations are required. D. Security Security is an important issue for successful applications of M2M communications. The M2M is vulnerable to attacks for several reasons. First, for most of the time, M2M nodes are normally unattended, and thus it is easy to be physically attacked. Second, due to the limited capabilities of M2M nodes in terms of their energy and computing resources they cannot implement very complex algorithms to support security. Furthermore, very often 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 M2M communications are performed in wireless channels. More specifically, the major problems regarding to the M2M communications security include authentication and data integrity. Authentication is a prerequisite for secure M2M communications, and it requires appropriate authentication infrastructures and servers allowing eNB to confirm the sensory data from the M2M nodes through the exchange of messages with other nodes. However, since the passive sensor nodes cannot exchange too many messages with the authentication servers, and thus such approaches may not be feasible in the M2M applications. Data integrity must guarantee that illegal alteration of the sensory data can be detected. In M2M communications, the data integrity requirement should be satisfied since illegal alteration may cause serious consequences, especially in life-critical M2M applications such as e-healthcare systems. Data can be modified 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 been proposed for wireless sensor networks as well [116]. To protect data against the second type of attack, messages may be protected according to the Keyed-Hash Message Authentication Code (HMAC) [117] that is based on a common secret key shared between the tag and the destination of the message, which is used in combination with a hash function to provide authentication. However, it should be mentioned that, the password length supported by most tag technologies is too short to support strong levels of protections. Furthermore, even if longer

passwords are supported, still their management remains a huge burden and challenging task especially when entities belonging to the heterogeneous M2M networks. The problem of data integrity was extensively investigated in traditional communication systems and some preliminary results (e.g., [118]) are also available for sensor networks. However, new problems arise when sensory nodes are integrated into M2M communications, and thus security in M2M communications remains to be an open issue. In [119], the 3GPP Security Workgroup (SA3) has collected categories of vulnerabilities that are as following: 1) Physical attacks including the insertion of valid authentication tokens into a manipulated device, inserting and/or booting with fraudulent or modified software, and environmental/side-channel attacks, both before and after in-field deployment. These possibilities require trusted ‘validation’ of the integrity of the M2M device’s software and data, including authentication tokens. 2) Compromise of credentials comprising brute force attacks on tokens and (weak) authentication algorithms, as well as malicious cloning of authentication tokens residing 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 compromise of the access control lists. 4) Protocol attacks directed against the device, which included man-in-the-middle attacks3 upon first network access, denial-of-service (DoS) attacks, compromising a device by exploiting weaknesses of active network services, and attacks on over-the-air management (OAM) and its traffic. 5) Attacks on the core network, the main threats to the mobile network operator (MNO), include impersonation of devices; traffic tunneling between impersonated devices; misconfiguration of the firewall in the modem, router, or gateway; DoS attacks against the core network; also changing the device’s authorized physical location in an unauthorized fashion or attacks on the network, using a rogue device. 6) User data and identity privacy attacks include eavesdropping device’s data sent over the E-UTRAN; masquerading as another user/subscriber’s device; revealing user’s network ID or other confidential data to unauthorized parties, etc. Some of the vulnerabilities that are more specifically geared to the subscription aspects of the M2M device are exhaustive and span the network, device, and user [119]. However, for special application, more additional consideration should be involved including the issues of liability identification that restrict user privacy to allow for identification of users whose actions disrupt the operation of nodes or the transportation system. 3 Man-in-the-middle attack considers the cases, in which a node is utilized to identify something or someone and, accordingly, provide access to a certain service or a certain area.


Finally, all the solutions proposed to support security use some cryptographic methodologies. Typical cryptographic algorithms spend large amount of resources in terms of energy at the source and the destination which cannot be applied to the M2M communications in 3GPP LTE/LTE-A, given that M2M devices include elements (like tags and sensor nodes) that are resource-constrained in terms of energy, communications, and computation capabilities. Therefore, new solutions are required able to provide a satisfactory level of security including light symmetric key cryptographic and effective management schemes regarding to the resource-constrained M2M networks. VII. C ONCLUSION With a wide range of potential applications, the M2M communications are emerging as an important networking technology, which will become the infrastructure to implement the IoT. To enable full automation in our daily life, it is needed to provide connections among all M2M devices. To implement those ubiquitous connections, the existing 3GPP LTE/LTE-A networks have considered as a ready-to-use solution to facilitate M2M communications. In this paper, we discussed the architectural enhancements in 3GPP LTE/LTE-A networks for M2M communications. We highlighted key architectural changes as well as the functionalities of 3GPP LTE/LTE-A network elements to support various requirements of M2M communications, such as device triggering, M2M identifier, addressing, etc. Then, the salient characteristic features of M2M communications, and the issues for implementation of M2M communications based on 3GPP LTE/LTE-A networks were identified and discussed. Furthermore, we presented an overview on the major challenges to implement M2M communications over the 3GPP LTE/LTE-A networks. In addition, typical M2M applications that can play a critical role in our future life were illustrated. Finally, the open research issues on M2M communications were pointed out in order to stimulate more research interests in the subjects. R EFERENCES [1] Vodafone, “RACH intensity of time controlled devices,” 3rd Generation Partnership Project (3GPP), Sophia-Antipolis Cedex, France, Tech. Rep. R2-102296, Apr. 2010. [2] EXALTED Deliverable 2-1, 2011, Description of Baseline Reference Systems, Scenarios, Technical Requirements and Evaluation Methodology. [Online]. Available: http://www.ict-exalted.eu [3] 3rd Generation Partnership Project (3GPP), “Service requirements for machine-type communications,” Sophia-Antipolis Cedex, France, 3GPP TS 22.368 V11.5.0, Sep. 2012. [4] DRAFT Amendment to IEEE Standard for WirelessMAN-Advanced Air Interface for Broadband Wireless Access Systems: Enhancements to Support Machine-to-Machine Applications, IEEE Std. P802.16p-11/0033, Oct. 2011. [5] 3rd Generation Partnership Project (3GPP), “Evolved universal terrestrial radio access (E-UTRA) and evolved universal terrestrial radio access network (EUTRAN), Overall Description,” Sophia-Antipolis Cedex, France, 3GPP TS 36.300 V11.2.0, Jun. 2012. [6] IEEE Standard for Local and Metropolitan Area Networks Part 16: Air Interface for Broadband Wireless Access Systems, IEEE Std. 802.162009, May 2009, in revision of IEEE Std. 802.16-2004. [7] V. Chandrasekhar, J. G. Andrews, and A. Gatherer, “Femtocell networks: A survey,” IEEE Commun. Mag., vol. 46, no. 9, pp. 59–67, Sep. 2008. [8] 3rd Generation Partnership Project (3GPP), “System improvements for machine-type communications; (Release 11), v.1.6.0,” Sophia-Antipolis Cedex, France, TR 23.888, 2011-11, 2011.

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Fayezeh Ghavimi (S’13) received the B.Sc. and M.Sc. degrees in electrical engineering from the University of Tabriz, Tabriz, Iran, in 2007 and 2012, respectively. She is currently working toward the Ph.D. degree in the Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan. Her research interests include wireless communications, machine-to-machine communications, QoS provision for supporting next-generation wireless communications, and next-generation CDMA networks. 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) received the B.Sc. and M.Sc. degrees from Zhejiang University, Hangzhou, China, in 1982 and 1985, respectively, and the Ph.D. degree from the University of Oulu, Oulu, Finland, in 1991. He is currently a Distinguished Professor in the Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan. Dr. Chen is the founding Editorin-Chief of Wiley Security and Communication Networks Journal. He is currently serving as the Editor-in-Chief for IEEE W IRELESS C OMMUNICA TIONS . He is a Fellow of IET, and an elected Member at Large of IEEE ComSoc.