In this chapter, we study the intersymbol interference channel. Intersymbol interference (ISI) is a self-noise introduced by a dispersive channel. Since the ISI channel can significantly degrade the performance of communication systems, we need to mitigate the ISI. One of the methods that can achieve this is channel equalization.

There are two different structures for channel equalization. Linear equalization is based on a linear filtering approach. Since an ISI channel can be seen as a linear filter, a linear equalizer at the receiver equalizes the frequency response of the ISI channel to mitigate the ISI. The other approach is called decision feedback equalization, in which linear filtering and cancelation are used to alleviate the ISI. In addition to these approaches, which are based on the structure of the equalizer, the performance criterion is important in the optimization of an equalizer. Two of the most popular criteria will be introduced in this chapter.

We also study adaptive equalizers with fundamental properties of adaptive algorithms. For a given ISI channel, an adaptive equalizer can adjust itself to achieve the optimum performance. Therefore, adaptive equalizers are important practically.

In this chapter, we assume that the reader is familiar with the fundamental concepts of signal processing, including convolution, linear filtering, and the sampling theorem. In addition, a working knowledge of probability and random processes is required.

ISI channels and the equalization problem

We will derive a model for the ISI channel in the discrete-time domain since most receiver operations are generally carried out with digital circuits or digital signal processors after sampling.

Orthogonal frequency division multiplexing (OFDM)was proposed in the 1960s (see Chang and Gibbey (1968)) and has been actively investigated since then. It can be used for both wired and wireless communications, providing several attractive features. One important feature of OFDM is that it is ISI-free. In OFDM, data symbols are transmitted by multiple orthogonal subcarriers. Each signal transmitted by a subcarrier has a narrow bandwidth and experiences flat fading without interfering with the other subcarriers' signals. From this, a simple one-tap equalizer can be used in the frequency domain to compensate for fading, while a complicated equalizer is required in a single-carrier system to overcome ISI.

It is generally known that OFDM will not outperform single-carrier systems (in terms of the average BER) when a single modulation scheme is used for all subcarriers. However, OFDM can offer a better performance if adaptive bit loading is employed. Since each subcarrier may experience different fading, the SNR varies among the subcarriers. A different number of bits per symbol can be transmitted using a different modulation scheme across subcarriers depending on the SNR for each subcarrier. For example, subcarriers with low SNR may transmit no signal or may use a lower-order modulation to stay below a certain BER ceiling, while more bits per symbol can be transmitted through subcarriers with high SNR. This approach of adaptive bit loading is used for wired communication systems (Bingham, 1990). Indeed, adaptive bit loading allows OFDM to outperform single-carrier systems. However, in some wireless communication systems, including digital terrestrial TV broadcasting, adaptive bit loading becomes impractical to implement in compensating for different fading across subcarriers.

This chapter's main objective is to discuss and to some extent dispel some common myths and misconceptions associated with interference mitigation solutions. Our goal is to shed some light on the lessons learned while researching and developing solutions.

A common path taken in the development of interference mitigation techniques often begins by identifying solutions developed for different purposes and applying to the problem at hand. In general, this path constitutes an extremely powerful approach, and examples given in Chapter 7, including time and spectral multiplexing, clearly demonstrate the effectiveness of the resulting solutions. However, applying solutions out of the original context for which they were developed is no simple task, since it requires a careful examination of all the parameters and the assumptions that come into play. It is often when this step is overlooked that myths are constructed.

Contrary to common belief, we show that some techniques often associated with interference mitigation do not constitute solutions. These techniques may in fact aggrevate the interference problem or have a negative impact on the overall system performance. They constitute what we call pitfalls that should be avoided if possible.

We find two recurring myths in most pitfalls studied, although this list is far from exhaustive.

1. Dealing with interference is similar to dealing with random noise and other wireless channel propagation properties and impairments.

2. A set of system parameters such as transmitted power, offered load, packet size, error correction scheme, and modulation techniques can be optimized in order to mitigate interference.

Our objectives in this chapter are to describe the basic building blocks in performance evaluation as we focus on identifying and understanding the effects of interference in wireless communications and its impact on system performance.

Since we set out to evaluate the effects of interference on performance, the first question we ask is what is interference? The term “interference” has been extensively used in the context of communication, in both wired and wireless systems. While an accurate definition may be dependent on the specifics of the context considered, the term generally refers to signal impairments due to factors in the environment such as channel propagation properties, other radiated power, and noise.

The second question is concerned with the performance evaluation of interference, namely, what are the quantitative measures that characterize interference, and consequently how should the resulting level of performance be quantified? One interference metric that has been used extensively includes the so-called signal to interference ratio. However, this measure does not characterize completely the resulting performance since performance is often tied to the quality of service requirements, which vary depending on the application considered. Our objective is to provide a list of performance metrics that can accurately quantify the network performance from an application perspective.

Since not all systems behave in the same way given the same level of interference, an important aspect of performance evaluation is to identify parameters that impact performance.

Wireless networks are rapidly becoming a part of the ubiquitous computing environment, and whether they are enterprise networks or in public hot spots (for example in airports, hotels, homes), often they are deployed in infrastructureless environments. The rapid specification development phase and the tight time to market cycle that follows leave little room for performance enhancements and proper coexistence consideration.

Why did I write this book?

Having gone through a somewhat complete performance analysis and coexistence development cycle for wireless network technologies being developed by the IEEE 802 standard working groups, and having gained some experience on the topic, I feel compelled to share it with other network engineers and researchers that are pursuing similar objectives. In particular, I would like to share the methodologies developed and the lessons learned from this process with others embarking on a similar quest.

The audience for this book includes: (1) researchers interested in performance evaluation and interference mitigation techniques; (2) wireless systems engineers and practitioners designing wireless communication systems; (3) users of wireless networks.

This book is unique because it focuses on a system level view of the problem of interference and its solution space. Generally, interference is dealt with at the physical layer. There are several outstanding books that focus on the accurate characterization of the wireless channel in addition to the development of physical layer techniques for filtering and anti-jamming.

The main themes of this book are to explore evaluation methods for quantifying the mutual effects of interference on the performance of wireless networks and to investigate system-level solutions for their coexistence in the same environment.

The coexistence of wireless communication systems operating in the same environment has become a “hot” topic in recent years as more systems are choosing to use the unlicensed bands and forfeiting the need to purchase spectrum.

There are two specified unlicensed bands for the operation of wireless systems, namely:

1. the industrial scientific and medical (ISM) band that includes the 900 MHz, 2.4 GHz, and 5.8 GHz frequencies;

2. the unlicensed national information infrastructure (UNII) band that includes the 5.2 GHz band. This band was opened in 1997 in the United States in order to expand broadband access opportunities.

Few rules apply in the unlicensed bands such as the ISM band. For example, the rules defined in the Federal Communications Commission Title 47 of the Code for Federal Regulations Part 15 relate to the total radiated power and the use of the spread spectrum and frequency hopping modulations. It is commonly understood that all users of the unlicensed bands can equally affect the quality and the usefulness of this spectrum. Thus, the major downside of the unlicensed band is that frequencies must be shared and potential interference tolerated.

We distinguish between several types of users in these unlicensed bands.

This chapter is designed to give the reader a comprehensive understanding of the fundamentals in wireless protocol design. First, we overview some of the physical layer and the medium access control layer design choices. Then, we give the details of select major protocols as examples of the concepts described.

Physical layer

The physical layer has the main function of transporting the information bits passed by the higher layers over a physical medium and recovering them on the other side of the medium. We can view the physical layer in terms of a digital or analog communication channel and modules that map digital information to an analog signal in case the channel is analog. Figure 2.1 illustrates the main components of the physical layer that are discussed in the following sections. For an in-depth treatment of communication systems, the reader is referred to other texts.

Communication channel

A communication channel consists of a physical medium, such as radio waves, copper wire, optical fiber, and the associated equipment necessary to transmit information over the medium. Communication channels can be used for either digital or analog transmission. Digital transmission consists of transmitting a sequence of pulses corresponding to a sequence of information bits. Analog transmission involves the transmission of waveforms associated with the transmitted signal. The bandwidth of a channel, W, measures the width of the window of frequencies that are passed by the channel.