Introduction

A successful communication system must establish synchronization, in addition to utilizing the modulation and demodulation techniques discussed so far. Synchronization is required at several levels. At the physical-layer level the receiver needs to know or estimate three parameters: (i) the incoming carrier frequency, fc (hertz); (ii) for coherent demodulation any phase shift or phase drift, θ(t) (radians), introduced during transmission; (iii) the bit (symbol) timing, i.e., where on the time axis do the kTb (or kTs) (seconds) ticks occur. How to obtain estimates of these parameters is the subject of this chapter.

The reader should realize, however, that one needs to establish other levels of synchronization. After detection of the transmitted bit sequence the sequence needs to be segmented or parsed into “words.” The best example of this is perhaps voice where the bit sequence needs to be segmented typically into eight-bit words, each word representing a voice sample. If error coding has been used, the sequence needs to be parsed properly into codewords for error decoding. Another example occurs in time-division multiple access where the communication channel is time shared. In this case the time slots need to be properly segmented to route the information from the different users properly. Such synchronization is typically called frame synchronization.

Introduction

The previous chapter shows that there are benefits to be gained when M-ary (M = 4) signaling methods are used rather than straightforward binary signaling. In general, M-ary communication is used when one needs to design a communication system that is bandwidth efficient. It is based on the observation that as the time duration of a signal, Ts, increases, the bandwidth requirement decreases. See Examples 2.11, 2.16, and Problem 2.38, which illustrate this. Typically, unlike QPSK and its variations in the previous chapter, the gain in bandwidth is accomplished at the expense of error performance. M-ary modulation is also a natural choice when the source is inherently M-ary, for example, the transmission of the English alphabet or when error control coding is used.

However, even when the source is inherently M-ary, the usual scenario is that the M messages are mapped to a sequence of bits, e.g., the ASCII code used for text. Therefore, even in these situations the final source output is binary and from the perspective of the modulator looks like a binary source. The typical application of M-ary modulation is one where a binary source has its bit stream blocked into groups of λ bits. The number of different bit patterns is 2λ, which means M = 2λ, where each bit pattern is mapped (modulated) into a distinct signal.

Introduction

In baseband transmission the transmitted signal power lies at low frequencies, typically around zero. It is desirable in many digital communication systems, for the same reasons as in analog communication systems, for the transmitted signal to lie in a frequency band toward the high end of the spectrum. As an example satellite communication is normally conducted in the 6–8 gigahertz band, while mobile phones systems are implemented in the 800 megahertz–2.0 gigahertz band.

The digital information is encoded as a variation of the parameters of a sinusoidal signal, called the carrier signal. Typically, as for analog modulation systems, the carrier frequency is much higher than the highest frequency of the modulating signals (or messages). Digital passband modulation is based on variation of the amplitude, phase, or frequency of the sinusoidal carrier, or some combination of these parameters.

Amplitude-shift keying (ASK) was probably the first type of digital modulation to be practically applied. In its simplest form it has been used for radio telegraphy transmission in Morse code. Another name for ASK is “on–off keying” (OOK), since a binary “1” corresponds to the sinusoid being transmitted while a binary “0” suppresses the carrier. Phase-shift keying (PSK) is an efficient, in terms of signal power, digital modulation method. It is widely used in modern digital communication systems, such as satellite links, wideband microwave radio relay systems, etc. The digital information is encoded in the phase function of a constant-amplitude carrier signal.

Introduction

Up to now we have assumed that the transmitted signal is only degraded by AWGN. Even when it is subjected to filtering, as in the previous chapter, the filtering characteristics are known precisely by the receiver. This knowledge is exploited in the design of the modulator/ demodulator by employing Nyquist's criterion to avoid intersymbol interference (ISI), or by allowing a certain amount of ISI as in the case of partial response systems, or by using a maximum likelihood sequence detection based on the unavoidable ISI.

In practice, however, there arise communication channels where the received signal is not subjected to a known transformation or filtering. In particular the gain and/or phase of a digitally modulated transmitted signal is not known precisely at the receiver. These parameters can be modeled as either unknown but fixed over the period of transmission or as random. In the former case, one could transmit a known signal briefly at the beginning of transmission to estimate the parameter(s) and then use the estimate(s) for the remainder of the transmission, which would be the message of interest. However, in the more typical application, the parameters do change in time, so though they may remain reasonably constant over a bit interval, or several bit intervals, they do change over the course of the entire message transmission, typically unpredictably.

In the preceding chapter we showed that meshes were good for extending coverage beyond the existing network edge, without requiring additional infrastructure – a sufficient number of user nodes, in the right places, was all that was required. We also implied that this meant that obstacles to propagation such as buildings in the line-of-sight might be less of a problem, given that a mesh could hop around them in a way which cellular systems cannot. We even dropped a small application hint that the structure of a mesh can be quite similar to a grid of downtown city streets. In this chapter we look more closely at linking a number of useful application scenarios with the relevant attributes of a mesh.

We now propose that there are, at heart, only two worthwhile motivations for mesh networks. These are

1. coverage improvement,

2. lack of infrastructure.

All successful examples of meshing or multi-hopping known to us embody one or both of these core mesh attributes.

To support this conclusion, we now spend some time considering application scenarios. Overall, from a technology standpoint, we found it hard to envisage any new services which only a mesh could support, although vehicle ad hoc networks and wireless sensor networks are probably the closest – but even here a mesh is the best rather than the only solution. Rather it seems more likely that a mesh would contribute by delivering services in a new way. Six suitable application areas are identified below where mesh adoption is thought to be most likely. In hindsight, it is easy to see that all six applications are based on a mesh network's valuable attributes of coverage and/or reduced reliance on infrastructure.

Continuing in the spirit developed in the previous chapter, rather than looking at meshes by pursuing a linear layer-by-layer exposition of the protocol stack as in Figure 3.1, we will continue to take a more pragmatically integrated view. This chapter and the next chapter therefore look at two key aspects of mesh systems, or indeed of any communications system; these are susceptibility to interference and quality of service. PHY, MAC, routing, transport and application behaviours along with their interactions are all relevant, although this chapter on susceptibility is more related to the lower layers and Chapter 6 on the quality of service is more related to the higher layers.

We begin by looking at interference and how the mesh may react to it. We do this by firstly classifying all the various forms which interference may take.

At the physical layer the effect of interference depends on the modulation and coding in use within the mesh. Of course this is true of any communications system, but we find an important distinction is that a mesh precludes the easy use of some common modulation approaches. The reason for this is the typical lack of any centralised control within a mesh, which precludes approaches demanding synchronisation of modulation across nodes. Examples include many versions of frequency hopping.

At the MAC, the effect of interference depends on the MAC scheme in use. Once again this is true for any communications system, yet again we find an important distinction is that a mesh precludes the easy use of many common MAC approaches. This includes the common slotted schemes of FDMA, TDMA and CDMA.

As we have seen from the previous chapters, there are numerous key considerations to bear in mind when planning to implement a mesh. Some of these key considerations, if not properly addressed, constitute potential pitfalls for the mesh system designer. The aim of this short chapter is to bring all such considerations together for easy reference, so the pitfalls may be avoided. This is particularly appropriate as not all pitfalls have familiar equivalents outside the world of mesh networking.

In summary, potential pitfalls already covered in the body of this book centred around

1. capacity,

2. infrastructure,

3. efficiency,

4. relay exhaustion,

5. initial roll-out,

6. upgradeability,

7. reliance of the system on user behaviour, and

8. ad hoc versus quality of service.

There are also two areas which we have covered implicitly, but now wish to highlight explicitly here:

1. 9. security and trust, and

2. 10. system economics.

Let us deal with these areas in turn.

Capacity

In Chapter 4 we noted that it was often rumoured that meshes self-generate capacity, as if this were a truism. The reasoning behind such a claim was usually along the lines of ‘each new user brings additional capacity to the mesh’, or ‘each new user effectively becomes a base station’. This book critically examined such statements and separated the reality from a something-for-nothing type of mythology. We outlined the difference between network capacity and the user throughput which is actually available, concluding that user throughput cannot grow as fast as the mesh grows. The simple reason is the relay requirement imposed on each node, due to the traffic of other nodes.

Introduction

We are by now well acquainted with the ‘observe, decide, act’ cycle. This chapter is the first of three core chapters that relates to the cycle and focuses on the act part. ‘Taking action’ was introduced in the last chapter as ‘the setting of the various knobs on the radio’. So we have already been introduced to the idea that there are a large number of possible knobs such as frequency, bandwidth, signal duration, modulation technique, power, etc. that can be set, but we have not looked at any details. In this chapter we look at the details and more explicitly at what actions are needed for the kinds of applications described in the opening chapter of this book.

To do this we need first of all to further build our knowledge about what actions are possible. A second important point of this chapter is to develop an understanding of the consequences of the actions taken. While we have stressed in the previous chapter that ‘taking action’ is not just about the physicality of the transmitted signal and can pertain to other aspects of the communication process such as higher-layer performance issues, management of battery lifetime of the node or the processing resources of the node, it is the physical interaction of the transmitted signal with other entities around it that is core to understanding the consequences of the actions that are taken.

Introduction

This book has considered the essential issues associated with cognitive radio. Cognitive radio is a truly interdisciplinary topic. It crosses the fields of information theory, propagation studies, RF design, telecommunications, wireless networking, signal processing, artificial intelligence, cognitive science, software engineering, regulatory policies, security, application design, plus many many more. On the one hand the need for such a breadth of knowledge seems daunting and on the other hand it seems very exciting and opens up the way for new possibilities. In this last chapter an attempt is made to summarise the main points of the book.

A brief summing up

The first main point of the book is that a cognitive radio is not just a radio for dynamic spectrum access. The second is that dynamic spectrum access is a great idea and in looking at dynamic spectrum access many new paradigms for dynamic behaviour of radios come to light. The third point is that there are many potential applications on the horizon for cognitive radio as is hopefully clear from the simple mindmap in Figure 9.1.

Throughout the book the observe, decide and act cycle was placed at the core of the cognitive radio (Figure 9.2 recaptures the cycle). And secure, build and regulate were seen as the key additional activities of focus. Each of these topics warrants a few words.

The Internet is now firmly part of our everyday life. We perform many common tasks on-line, such as banking, grocery and gift shopping and the purchasing of travel or cinema tickets. Plus we get a growing portion of our entertainment from on-line sources: entertainment and social networking are two of the largest growth areas. We have seen the beginning of basic quality video from, for example, You Tube and the development of social networking sites such as My Space and FaceBook, which have been enormously popular, especially amongst younger generations of consumers. If we are to continue in this trend of doing more on-line, our need for bandwidth will increase. And in future we might expect to generate appreciable content ourselves, for upload onto the Internet, as well as to continue to download content. But that is not all; our need for Internet availability and quality will also increase.

It would be very convenient if such future Internet access were also wireless, with the near ubiquitous service we are used to from cellular phones. However, building a new network to achieve this, or upgrading an existing network to support this, would mean installing or changing a great deal of infrastructure. What then if a method existed which promised improved Internet access with fewer requirements for new infrastructure? This is widely advertised as the domain of the mesh network.

This chapter begins with a top-level introduction to mesh networking, then looks at how meshes may fit into the larger telecommunications infrastructure, before moving on to classify and explain the basic properties of a mesh.

In this chapter we will show that a startling effect in meshes is that quality of service (QoS) is not under the operator's control but depends on mesh node behaviour. In a mobile mesh, this means that your QoS depends on your neighbours' behaviours at any point in time, potentially spanning a range all the way from having no discernable effect up to a complete loss of your service. There is nothing quite like this problem in the networks we commonly use today.

But we begin this chapter by looking at how QoS is defined and what QoS levels are required for the applications of today and into the future. Following this we look at whether there are any useful services which truly only a mesh could support. After considering node mobility and showing how node to node relative speed is the key parameter, we look at an example of how a mesh may break into disconnected pieces. This can occur before the full mesh capacity is approached. Finally we show that mesh quality of service is not entirely within the control of the network operator, but rather depends on user mobility and traffic, before showing how adding infrastructure can help improve the quality of service position. Mitigation techniques for QoS issues induced by normal user activity include the provision of extra network-owned nodes in order to regain some control, but this comes at a cost for the operator.

This book has so far focused on meshes for telecommunications, however another use of multi-hop networking is the wireless sensor network. In fact it is potentially beginning to look like WSNs might outstrip telecommunications as a use for multi-hop and mesh technology. We have kept this chapter separate as WSNs have some unique properties, but we find that many aspects of mesh discussed earlier in the book apply to WSNs in much the same ways. In terms of applications, at the time of writing, smart buildings (advanced control of lighting and HVAC, heating ventilation and air-conditioning) and logistics look like the top two likely WSN applications, in terms of earliest uptake.

Let us begin with an introduction to wireless sensor networks. We take quite a broad overview before concentrating on the networking aspects of WSNs.

The role of a wireless sensor network is essentially that of a monitor. Broadly speaking, what is being monitored can usually be placed within one of three groups:

• area monitoring – i.e. monitoring somewhere; examples include the environment or area alarms (intrusion etc.);

• entity monitoring – i.e. monitoring something; examples include a civil structure (bridge, building etc.) or a human body;

• area–entity interaction monitoring – i.e. monitoring something, somewhere, in context; examples include vehicles on the road, asset tracking or the flow of a manufacturing process.

As to why a sensor network is important, it is most simply understood by realising that, often, individual sensors themselves are limited in their ability to monitor a given situation.

Overview

We listed the characteristics of an ad hoc mesh in Chapter 3, Table 1.1, and we built upon this to create the access mesh concept. But we have not so far attempted to offer any detailed explanation of the key mesh characteristics. The function of this chapter is to examine these fundamentals as a final foundation before Chapter 4, where we begin the detailed testing of the four key hypotheses of mesh performance which we introduced at the end of Chapter 1.

A logical way to address the fundamentals is to consider, in turn, each layer of a generic communications protocol stack as shown in Figure 3.1.

At the bottom of the stack is the physical layer, or PHY. This consists of the parts which directly concern the air interface, for example the antennas and transceiver electronics. By implication this also includes detail design elements, such as the choice of modulation scheme and transmit power.

But it does not include the method by which access to the air interface is determined – this is the job of the medium access control layer, or simply MAC. This, for example, will include schemes to allow multiple users to share the medium in some more or less fair fashion, such as the random collision avoidance approaches used in 802.11 or the structured time and frequency division multiplexing as used in GSM.

To enable nodes to find and communicate with each other, some sort of addressing scheme is required; this is contained in the routing layer. An example is the increasingly ubiquitous Internet protocol.