D2D communications can be prone to potential security threats. For example, D2D mobiles need to know who else is located nearby so as to pair up. If the location information is spoofed, the interference caused by wrongly paired D2D users can significantly lower the system performance. Additionally, D2D communications between neighboring D2D nodes provide alternative security approaches (physical-layer security) by using channel statistics. In this chapter, we will study the following two security problems in detail.

1. • Location security: D2D networks need to pair D2D users on the basis of location information so as to use locally available spectrum. This creates a critical loophole for global-positioning-system (GPS)-spoofing attack, where the adversary attacks the GPS signals received by D2D devices, so that D2D devices obtain false available spectrum information with false location information. This security loophole can potentially result in large-scale malfunctioning of mobile D2D networks.

2. • Data transmission security: Security in D2D communications is traditionally implemented using cryptography, as in other wireless communication systems. Alternatively, physical-layer security provides additional security provided by the channel statistics, which fits well the D2D communications scenarios. We will consider physical-layer security in D2D communications as an underlay to cellular networks with an eavesdropper. Benefiting from the underlaid spectrum reuse, D2D users can contribute to the system's secrecy capacity, while D2D users may interfere with cellular users and decrease their secrecy capacity.

Location security

8.1.1 Problem overview

Dynamic-spectrum-access (DSA) technology has received much attention in industry and academic environments due to its promise of better utilization of spectrum resources compared with the current static spectrum-allocation method. Traditionally, spectrum allocation is static, where FCC assigns communities licenses to use specific frequencies, such as AM, FM, short-wave and citizens' bands, and VHF and UHF television channels, as well as hundreds of less familiar bands that serve cellular and cordless telephones, GPS trackers, air-traffic-control radars, security alarms, radio-controlled toys, and the like. While some of these assigned spectrum bands have been overloaded due to the growth of their users, other spectrum bands are scarcely used.

Introduction

Two major requirements for the LTE-A (Long Term Evolution-Advanced) standard for 4G (fourth-generation) cellular wireless networks are the need to improve spectrum efficiency and to enhance network throughput. D2D communications technology is a promising add-on component of LTE-A systems to satisfy those requirements. The concept of D2D communications is to allow direct communications among the user equipments (UEs) by reusing the cellular resources rather than using the uplink or downlink resources of the cellular networks (see Figure 4.1). D2D communications can achieve four types of gain [161], namely proximity gain, hop gain, reuse gain, and pairing gain. In D2D communications, the UEs can operate in one of three traditional modes as follows.

1. • Reuse mode: D2D UEs directly transmit data among themselves by reusing some radio resources used by cellular UEs to enhance the spectrum utilization.

2. • Dedicated mode: D2D UEs directly transmit data among themselves by using a dedicated portion of spectrum to avoid interference with cellular UEs.

3. • Cellular mode: Similarly to cellular UEs, D2D UEs relay their data through the base station.

One key question here is how to select a transmission mode for each D2D link. In the cellular mode, more resources (e.g., the number of time slots) may be required for transmitting data to the receiver than in the reuse mode or dedicated mode; however, it is easier to manage interference with cellular users. The reuse mode can achieve a higher spectrum efficiency but D2D communications in this mode may interfere with cellular users and other D2D users using the cellular mode. By contrast, the dedicated mode can completely avoid interference, since some resources are reserved for the D2D communications; however, the spectrum utilization can be very poor in this mode. A simple method is to choose the mode by considering only the received signal strength over the D2D link or the distance between the terminals. However, the interference conditions and the differences between sharing cellular uplink and downlink also affect the overall network throughput.

This chapter mainly introduces the motivation and requirement for using D2D communications over Long Term Evolution (LTE)/LTE-Advanced (LTE-A). The agreed working scenarios and working assumptions are discussed and also the methods for link-and system-level performance evaluation are provided.

D2D communications in LTE-A networks

Now that more and more new multimedia-rich services are becoming available to mobile users, there is an ever-increasing demand for higher-data-rate wireless access. As a consequence, new wireless technologies such as LTE have been introduced. These technologies are capable of providing high-speed, large-capacity, and mobile services with guaranteed quality of service (QoS) [183]. With the technological evolution of cellular networks, new techniques, such as small cells, which are able to improve network capacity by reducing cell size and effectively controlling interference, have been developed. However, most attempts still rely on the centralized network topology which requires mobile devices to communicate with an evolved Node B (eNB). Such a centralized network topology can easily suffer from congestion with a large number of communicating devices. Additionally, the eNB might not have complete information about transmission parameters among devices, which is required in order to achieve optimal network performance. Consequently, the concept of D2D communications has been introduced to allow local peer-to-peer transmission among mobile devices by bypassing the eNB and AP [1].

Many technical groups such as the 3GPP and the IEEE are currently addressing the standardization of D2D communications in the licensed band. A major breakthrough was achieved in due course when the 3GPP agreed on starting a study item for D2D technology. The objective of this study item is to investigate the operator-controlled communications between user equipments (UEs) that are in proximity, under continuous network control, and in 3GPP network coverage. Specifically, besides cellular operation, where the UEs can be served by the network via the eNB in the LTE system, some UEs may communicate with each other directly over direct links for proximity services [381].

Introduction

Traditional D2D communications take place among any mobile units to transfer “data.” However, current and emerging mobile applications pose the new challenges of “information” transfer. Typically, information is related to social relations of people. Therefore, social information and social networks have been integrated with wireless and mobile communication to serve the new demand of users for information transfer. When the social information is used or the social network is operated on wireless systems, we can refer to it as a mobile social network [321, 322]. The mobile social network can be integrated or used in D2D communications with the following approaches.

1. • D2D communications to support mobile social network: In this approach, typical social-network applications and mobile social networks will utilize D2D communications to transfer data and information. Instead of using a fixed wireless infrastructure (e.g., a base station of a cellular network) to transfer social-network information, the information can be conveyed through D2D networks. The typical advantages of D2D communications are inherited in this case for the mobile social network, including reducing radio-resource usage, alleviating network overload, and improving the data-and information-dissemination and -delivery performance.

2. • Social-based D2D communications: In this approach, D2D communications supporting other applications can utilize social information of users to improve the efficiency and effectiveness of data and information transfer. For example, packet routing of D2D LAN can be enhanced by taking social ties among devices and users into account to determine an optimal route. Such an optimal route may not only minimize a network cost, but also maximize the social impact, improving the satisfaction of D2D communications and networking.

In this chapter, we focus on the mobile social network and its role in D2D communications. Firstly, Section 10.2 presents an overview of mobile social networks. Their architecture, applications, issues, and approaches are reviewed. Section 10.4 presents some seminal works in the field of social-aware data routing and dissemination. Section 10.5 introduces a detailed formulation for cooperative content delivery in mobile social networks.

Introduction

Wireless connectivity is rapidly expanding beyond traditional mobile devices used by humans. In the near future, many wireless devices (e.g., sensors and actuators) will be connected in the framework of the Internet-of-Things (IoT) [363]. In cellular networks, hundreds or thousands of devices can exist in one cell. Therefore, the concept of machine-to-machine (M2M) communications has been introduced to handle the transmission of a number of devices in the network. M2M communication, also known as machine-type communications (MTC), refers to mobile nodes communicating over a network without (or with minimal) human intervention. M2M communication enables ubiquitous connectivity among autonomous devices and/or Internet connectivity of MTC devices (i.e., communications between an MTC device and an M2M server or between two MTC devices). M2M communication is different from human-to-human (H2H) communication, which mainly involves voice calls, messaging, and web browsing. The goal of M2M communications is to increase the level of system automation by allowing the devices and systems to exchange and share data. Therefore, the protocol and data format are the major issues in M2M communications owing to the need to ensure seamless data and control flows.

D2D communication can be considered as a type of M2M communication when the D2D user equipments UEs are in close proximity and have small amounts of data to transmit among themselves (e.g., in application scenarios relating to the control of appliances in the home). In this chapter, we provide an overview of M2M communications in Section 11.2. Specifically, we focus on MTC in Long Term Evolution (LTE) and LTE-Advanced (LTE-A). Section 11.3 presents the mechanisms to support MTC, i.e., a random-access (RA) procedure and random-access-channel (RACH)-overload control mechanisms. Section 11.4 introduces a performance-modeling technique based on queueing theory to analyze the performance of the RA mechanism for M2M communications. Finally, Section 11.5 gives a summary of the chapter and lists some important research directions.

Machine-to-machine (M2M) communications

M2M communication, which is undergoing the process of standardization by the Third Generation Partnership Project (3GPP), can support a wide range of applications (e.g., secured access and surveillance, metering and smart grid, and Internet-of-Things).

Traditional communication systems were built using a layered structure to provide well-defined but limited interfaces among protocols in adjacent layers. The modular design of the layered structure, where the details of each protocol are hidden, promotes the interoperatability of the communication protocols. Although the protocol details (e.g., states and internal functions) are encapsulated in each layer, this structure prevents the protocols sharing, accessing, and controlling the operations of other protocols, which might be required for efficient data transmission. Therefore, the concept of cross-layer design has been introduced to allow tighter integration of different protocols. It is not necessary for these protocols to be in adjacent layers. The benefits of cross-layer design are that it allows one to improve both the flexibility of protocol implementations and network performance. Cross-layer design and optimization have been adopted in various wireless systems. A few surveys on cross-layer design exist in the literature, e.g., [190, 191, 192, 193].

The cross-layer design has been adopted for optimizing D2D communication. In this chapter, we give an overview of the cross-layer design by introducing its definition and different approaches. Then, we present one of the most commonly used cross-layer design models, i.e., the coordination model, which incorporates different functionalities. These functionalities are security, QoS, mobility, and wireless link adaptation. We next present the cross-layer implementation and challenges.

We introduce cross-layer optimization, which is part of the cross-layer design. We provide examples of the cross-layer optimization problems, including opportunistic scheduling, OFDM resource allocation, and congestion control. We then review the cross-layer design framework proposed for D2D communications. They are information correlation routing, routing in sensor networks, and traffic scheduling for a video application. Finally, we outline some research directions of the cross-layer design and D2D communications.

An overview of cross-layer design

In this section, we first introduce the basic concepts including the definition of, and approaches to, cross-layer design. Then, we discuss the coordination model, which incorporates other functionalities (i.e., security, QoS, mobility, and wireless link adaptation) into the protocols.

Introduction

Vehicular networks play an important role in data communications and networking to support intelligent-transportation-system (ITS) applications. The many ITS applications related to vehicles, road traffic, drivers, passengers, and pedestrians have diverse quality-of-service (QoS) requirements, which need to be offered by the vehicular networks [280]. Vehicular networks can be based on vehicle-to-infrastructure (V2I) communications, in which the data transmission happens between a network infrastructure (e.g., a base station or a roadside unit) and vehicular nodes, i.e., on-board units (OBUs) in vehicles. Therefore, V2I communication relies on a centralized network that can be supported efficiently by cellular networks or broadband wireless access. However, V2I communication has limitations in some ITS applications. The transmission latency in V2I communication can be considerable due to relaying through the roadside unit. By contrast, vehicular networks can be based on vehicle-to-vehicle (V2V) communication, in which the data can be transmitted from one vehicular node to another node directly, reducing latency significantly. Therefore, V2V communication is suitable for many real-time ITS applications (e.g., vehicle collision avoidance). V2V communication is inherently D2D communication in which the vehicular node can establish local direct transmission without the help of any network infrastructure (i.e., roadside units). D2D communication in vehicular networks has some unique features, making it different from other typical D2D communication scenarios.

1. • High-speed mobility: In vehicular networks, the network nodes are basically vehicles. Therefore, the mobility of vehicular nodes has a unique feature. Firstly, the nodes generally move relatively fast (e.g., 100 km/h on a highway or 30 km/h in an urban area). Secondly, the nodes move along a road structure (e.g., there is straight-line motion on a highway, but drivers are able to turn at an intersection). As a result, the topology of vehicular networks can change quickly. This makes wireless data transmission and routing challenging due to there being only an intermittent connection.

2. • Energy constraint: A wireless transceiver (i.e., an OBU) of a vehicular node has an abundant energy supply from a gas combustion engine or from a large battery array, in gasoline-powered cars and electric cars, respectively.

D2D communication may cause undesirable interference to primary cellular users due to spectrum sharing. This chapter focuses on interference coordination for D2D communications underlaying cellular networks.

Interference analysis

D2D communication not only provides coverage at the customer's premises, but also radiates toward neighboring mobile users, introducing interference. Owing to this and given that D2D communication typically is performed within the coverage area of existing macro/micro cells, it can cause severe degradation of the cellular network’ sperformance. Furthermore, the occurrence of new D2D networks could also disturb the normal functioning of already-existing D2D communications. Therefore, to reduce the appearance of dead zones within cellular networks and successfully enable a D2D LAN, interference avoidance, randomization, or cancellation techniques must be applied.

In the following, it is assumed that the D2D users are synchronized with the cellular networks as well as with other D2D users. Therefore, considering that the networks define two separate layers (the D2D and cellular layers), interference can be classified as follows.

1. • Cross-layer interference: This refers to situations in which the aggressor (e.g., a D2D user) and the victim (e.g., a cellular user) of interference belong to different network layers.

2. • Co-layer interference: In this case the aggressor (e.g., a D2D user) and the victim (e.g., a neighboring D2D user) belong to the same network layer.

Interference avoidance

To overcome the adverse effects of interference, cancellation techniques have been proposed, but they are often disregarded due to errors in the cancellation process [183]. The use of multiple antenna beamforming at the mobile has also been suggested as a means of reducing interference by decreasing the number of interferers. By contrast, strategies based on interference avoidance also represent efficient alternatives (e.g., power and subchannel management).

Power-control algorithms and radio-resource management are tools that are often used in cellular systems to mitigate interference. If they are not applied, users located far from an eNB will be jammed by users in much closer positions. These techniques are also necessary in D2D communications for the same reasons plus the added problem of cross-layer interference.

Performance evaluation of Wireless Sensor Networks (WSNs), like any communications network system, can be conducted by using simulation analysis, analytic modeling, and measurement/testing techniques. Evaluation of WSN systems is needed at every stage in their life. There is no point in designing and implementing a new system that does not have competitive performance, and does not meet the objectives and performance evaluation and quality of service requirements. Performance evaluation of an existing system is also important since it helps to determine how well it is performing and whether any improvements are needed in order to enhance the performance [1].

After a system has been built and is running, its performance can be assessed by using the measurement technique. In order to evaluate the performance of a component or subsystem that cannot be measured, for example, during the design and development phases, it is necessary to use analytic and/or simulation modeling so as to predict the performance [1–46].

The objective of this chapter is to provide an up-to-date treatment of the techniques that can be used to evaluate the performance of WSN systems.

Background information

Wireless sensor networks (WSNs) are unique in certain aspects that make them different from other wireless networks. These aspects include:

Vehicular networking, the exchange of information in the car and between cars, has been on the mind of researchers since at least the often-cited 1939 New York World's Fair. Here, in its Futurama exhibit, General Motors revealed utopian visions of what highways and cities might look like twenty years later. In fact, many of the visions of intelligent transportation systems (ITSs) showcased there, as well as in the exhibit designer's 1940 book Magic Motorways (Bel Geddes 1940), such as that “car-to-car radio hook-up might be used to advise a driver nearing an intersection of the approach of another car or even to maintain control of speed and spacing of cars in the same traffic lane”, are still being pursued today. Modern vehicles collect huge amounts of information from on-board sensors, and this information is made available to the in-car network and ready for sharing with other cars – not just for the described visions of intersection assistance systems and platooning, i.e., road-train applications, but also for a whole wealth of new applications. Today, with in-car networks merging into networks of cars, these early visions seem closer to reality than ever.

But why did we have to wait this long?

Hugely many research projects have been undertaken since Magic Motorways was written, all of which tried to make visions of ITS a reality (Jurgen 1991). Among the most notable of research initiatives were the Japanese CACS, US ERGS, and European ALI projects for urban route guidance in the late 1960s to late 1970s, the European Prometheus project for autonomous driving (1986–1995), and the US PATH project for cooperative driving (1986–1992). Evidently, the majority of these initiatives led to working prototypes and successful field operational tests; yet, commercial success failed to match the projects' promises.

A possible explanation is given by Chen & Ervin (1990): early approaches were simply too visionary for their time, commonly focusing on infrastructure-less solutions, which could not be supported by current technology. The 1980s then saw a shift of attention from the more long-term goals of complete highway automation to nearer-term goals such as driver-advisory functions.