The objective of this book is to allow the reader to predict the received signal power produced by a particular radio transmitter. The first two chapters examine propagation in free space for point-to-point and point-to-area transmission, respectively. This is combined with a discussion regarding the characteristics of antennas for various purposes. In chapter 3, the effect of obstacles, whether buildings or mountains, is discussed and analytical methods, whereby the strength of a signal is the shadow of an obstacle can be predicted, are presented. The following chapter investigates the nature of reflections and the effect that reflections have on the nature of a received signal. Chapter 5 shows how the level of a received signal can be predicted considering all propagation mechanisms. The many effects on a radio wave that are caused by precipitation and the structure of the atmosphere are explained in chapter 6. Chapter 7 demonstrates how knowledge gained can be used to design point-to-point radio links, broadcast systems, Earth–space systems and in-building systems. In chapter 8, the value of software tools in the planning of various radio networks is explained.

A radio wave can often travel from a transmitter to a particular point by a number of routes: directly, by diffraction, by reflection, by penetration. At any point, the power received by a receiving antenna will be a combination of all these propagation mechanisms. Because the combined signal is a phasor sum of all the individual contributions an accurate prediction of the electric field strength is very difficult to obtain: it would need knowledge of the distance travelled for each propagation mechanism to within about a tenth of a wavelength plus details of the electrical properties of any materials involved in the paths involving reflection or penetration. Usually, all that is practical is to estimate the strength of the signal that would be achieved by each propagation path in isolation. The total received power is then estimated as the sum of these individual contributions. This gives an estimate of what is called the ‘local-mean’ level. That means that the actual power received would vary about this level by an amount that depends upon the relative strengths and directions of the individual contributions. If the angular separation of the individual contributions, when viewed from the receiver, is small then the signal will not vary very quickly with distance. Further, if one of the contributions is dominant and provides the majority of the signal power on its own then the variation will not be as great as if all the different propagation paths contributed nearly equal amounts of power.

The test of the usefulness of the knowledge gained can best be determined by undertaking some practical exercises that give an insight into problems encountered by radio system designers in the ‘real world’. Firstly, the value of propagation studies in helping to identify the most appropriate frequency for various services is discussed. The system design of microwave links at 10 GHz (at which multipath fading will dominate) and at 23 GHz (at which rain fading will dominate) is explained in some detail. The fact that many thousands of microwave links will be required in an industrialised country leads to a need for interference management, so this topic is introduced. Next, attention is turned to the design of broadcasting systems with a view to obtaining maximum coverage whilst investigating methods of limiting interference at great distances. Additionally, an example of designing a link to a geostationary satellite is presented. Finally, special methods needed for providing and predicting the signal strength for in-building systems are presented.

Determining the most appropriate frequencies for specific services

We have seen that the frequency of operation affects the way in which a radio wave is affected both by obstacles and by the atmosphere and rain. At first sight, it seems that the lower the frequency, the better. Obstacles cause lower levels of diffraction loss at longer wavelengths. Also, the effect of rain and atmospheric absorption is almost negligible below about 5 GHz. Further, the penetration of materials such as concrete is better at lower frequencies.

This chapter introduces the basic concepts of radio signals travelling from one antenna to another. The aperture antenna is used initially to illustrate this, being the easiest concept to understand. The vital equations that underpin the day-to-day lives of propagation engineers are introduced. Although this chapter is introductory in nature, practical examples are covered. The approach adopted is to deliver the material, together with the most significant equations, in a simplified manner in the first two subsections before providing more detail. Following this, the focus is on developing methods of predicting the received signal power on point-to-point links given vital information such as path length, frequency, antenna sizes and transmit power.

Propagation in free space: simplified explanation

Radio waves travel from a source into the surrounding space at the ‘speed of light’ (approximately 3.0 × 108 metres per second) when in ‘free space’. Literally, ‘free space’ should mean a vacuum, but clear air is a good approximation to this. We are interested in the power that can be transmitted from one antenna to another. Because there are lots of different antennas, it is necessary to define a reference with which others can be compared. The isotropic antenna in which the transmitted power is radiated equally in all directions is commonly used as a reference. It is possible to determine the ratio between the power received and that transmitted in linear units, but it is more common to quote it in decibels (dB).

So far, we have focused exclusively on malicious behavior, the traditional area of interest of security. But it is very important to keep in mind that security has been dominated for many years by military considerations, meaning that the “attacker” was indeed an attacker, equipped also with lethal weapons. Consequently, the goal was to defeat it at any cost, and it was pointless to try to quantify its motivation.

Commercial applications are very different from warfare, as we pointed out in Chapter 3. It is our profound belief that focusing exclusively on (malicious) attacks, as frequently done in current practice, captures only one aspect of the problem. Part III will explain how to model the motivation of a given party to depart from its nominal behavior.

The first two chapters of this part take the point of view of a selfish wireless station, considering first the MAC layer and then a fundamental mechanism of the network layer, namely packet forwarding. In both cases, we explain how to model the behavior of the stations by means of game theory. The reader unfamiliar with this discipline is strongly encouraged to first read Appendix B.

In the third chapter, we take the point of view of wireless operators having to cope with each other's presence in the same spectrum. Again, we explain how this problem can be modeled by means of game theory.

Many wireless networking mechanisms, notably routing, require that wireless nodes be aware of their neighborhood. This means that the nodes must know which other nodes they can communicate with directly. The procedure used to acquire this knowledge is called neighbor discovery.

In wired networks, neighbor discovery is a simple issue, because neighbor relationships do not change often, and hence routers can be pre-configured with the list of their wired neighbors. In contrast, in mobile wireless networks, the neighbor relationships change dynamically, which makes neighbor discovery an important mechanism. It is particularly important in the upcoming wireless networks that we described in Chapter 2.

Neighbor discovery can be achieved through simple protocols, where a node that wants to determine who its neighbors are broadcasts a neighbor discovery request, and every node that receives this request responds with a neighbor discovery reply. Receiving a reply means that the requesting node and the responding node can hear each other's transmission. In other words, they can communicate with each other directly, and hence they should consider each other as neighbors. The neighbor discovery protocol is sometimes called “hello protocol,” and the request and the reply are called “hello messages.”

An adversary can try to thwart the successful execution of the neighbor discovery protocol, for instance, by jamming the communication between two nodes. In this way, the adversary achieves that two nodes, which otherwise could communicate directly, cannot establish a neighbor relationship.

Introduction

As we have mentioned in Chapter 3, the way of the future for the proper operation of wireless networks consists in the deployment of appropriate rule enforcement mechanisms. These mechanisms should prevent or discourage malicious and selfish behavior. The design of the latter can tremendously benefit from game theoretic modeling.

Game theory is a discipline aimed at modeling situations in which decision-makers have to choose specific actions that have mutual, possibly conflicting, consequences. It has been used primarily in economics, in order to model competition between companies: for example, should a given company enter a new market, considering that its competitors could make similar (or different) moves? Game theory has also been applied to other areas, including politics and biology.

In wireless networks, the players can be either wireless stations striving to obtain as much possible bandwidth from the (shared) medium; or they can be wireless operators aimed at increasing their market share or their revenue. It is clear that in both cases, the actions of a given player can affect other players, sometimes in a negative way.

In this tutorial, we carefully explain how situations of this kind can be modeled by making use of game theory; for the sake of simplicity, we restrict ourselves in this appendix to the case in which the players are wireless stations (the reader interested in the interactions between operators should refer to Chapter 11).

Before discussing wireless networks, it is necessary to take a broad look at networking in general and to see why malicious and selfish behavior is such a relevant issue. For this purpose, we will consider the Internet.

The Internet is probably the most impressive achievement ever in networking: A simple set of brilliant engineering rules has led to the deployment of the most pervasive network that, in spite of its size (or rather, thanks to it), supports a growing number of services and applications. At the core of these rules stands of course the principle of universal connectivity.

Unfortunately, the Internet is plagued by several major problems, fuelled by this very principle. Viruses and spam have become a daily issue for most users around the world, many people fall prey to phishing attacks, and denial-of-service (DoS) attacks are routinely perpetrated against the servers of major corporations. An additional problem is that some network providers tend to establish walled gardens, by which they offer specific capabilities exclusively to their customers. Finally, some providers are tempted to interconnect their network in a way that is beneficial to themselves, but can be detrimental to the rest of the community. The situation is so critical that many prominent specialists, including some of the founding fathers of the Internet, call for a profound revamping of the network. Ambitious research projects, funded notably by the NSF and by the European Commission, have adopted a clean slate approach to respond to this challenge.

In the previous chapter, we have studied selfish behavior at the MAC layer. We will now focus on the network layer. For this purpose, we will consider self-organized wireless ad hoc networks. As we have explained in Chapter 2, in such networks the networking services are provided by the nodes themselves. As a fundamental example, the nodes must make a mutual contribution to packet forwarding in order to ensure an operable network. If the network is under the control of a single authority, as is the case for military networks and rescue operations, the nodes cooperate for the critical purpose of the network. However, if each node is its own authority, cooperation between the nodes cannot be taken for granted; on the contrary, it is reasonable to assume that each node has the goal of maximizing its own benefits by enjoying network services and at the same time minimizing its contribution. This selfish behavior can significantly damage network performance.

In this chapter, we focus on the most resource demanding operation of the network layer, namely packet forwarding. We address the case of self-organized wireless ad hoc networks, in order to derive some fundamental results. In particular, we will see that a network without incentives for cooperation is very likely to collapse. In Chapter 12, we will describe incentive techniques to solve this problem.

In any network, nodes need to be addressable, notably in order for the routing protocol to be able to convey traffic to them. As the node addresses usually have arcane formats, it is common practice to also make use of names, which are easier to manipulate by human beings; there are specific servers (such as the Domain Name System (DNS) in the case of the Internet) that convert names into addresses.

In static networks, it is common practice to relate the address of a node to its location in the network; in this way, routing can typically be organized in a hierarchical fashion. This principle becomes problematic, however, as soon as some nodes start moving.

Naming and addressing strategies have been heavily debated within the Internet community, essentially because of mobility and security, as we have seen in Sub section 2.2.5; it is very difficult to predict how naming and addressing will evolve in the coming years. But this topic is crucial for us, because naming and addressing mechanisms are vulnerable to a number of attacks.

In this chapter, we will first describe an ambitious naming and addressing architecture envisioned for the Internet. We will then focus on the network layer and describe specific attacks related to the mobility and to the intrinsic vulnerability of the nodes. Finally, we will describe the corresponding protection techniques.

In the previous two chapters, we have focused on the behavior of selfish nodes and shown how this can be modeled by means of game theory. In this chapter, we will consider the co-existence of several operators in shared spectrum. We will first discuss multi-domain sensor networks and then address the more involved case of cellular operators.

It is important to stress, as we already did at the beginning of Part III, that the cases presented hereafter must be understood as examples that capture the interactions of operators in shared spectrum, and not as the scenarios on which the manufacturers and operators will focus in the very near future.

Multi-domain sensor networks

An important design criterion for sensor networks is the minimization of the sensors' energy consumption. The sensors are often battery powered and it is impractical (and, in some cases, even impossible) to change or recharge the batteries once the sensors have been deployed. It is known that the energy required to transmit a data packet increases (at least) as the square of the distance of the transmission. In practice, this means that, as far as energy consumption is concerned, it is often more advantageous to transmit a packet in several small hops than to transmit it in a single large hop. Hence, if there are numerous sensors near each other, then they could transmit the packets together and thus increase the lifetime of their batteries radically.