Preface

I wrote this book to make the principles of wireless communication more accessible. Wireless communication is the dominant means of Internet access for most people, and it has become the means by which our devices connect to the Internet and to each other. Despite the ubiquity of wireless, the principles of wireless communication have remained out of reach for many engineers. The main reason seems to be that the technical concepts of wireless communication are built on the foundations of digital communication. Unfortunately, digital communication is normally studied at the end of an undergraduate program in electrical engineering, leaving no room for a course on wireless communication. In addition, this puts wireless communication out of reach for students in related areas like computer science or aerospace engineering, where digital communication may not be offered. This book provides a means to learn wireless communication together with the fundamentals of digital communication.

The premise of this book is that wireless communication can be learned with only a background in digital signal processing (DSP). The utility of a DSP approach stems from the following fact: wireless communication signals (at least ideally) are bandlimited. Thanks to Nyquist’s theorem, it is possible to represent bandlimited continuous-time signals from their samples in discrete time. As a result, discrete time can be used to represent the continuous-time transmitted and received signals in a wireless system. With this connection, channel impairments like multipath fading and noise can be written in terms of their discrete-time equivalents, creating a model for the received signal that is entirely in discrete time. In this way, a digital communication system can be viewed as a discrete-time system.

Many classical signal processing functions have a role to play in this discrete-time equivalent of the digital communication system. Linear time-invariant systems, which are characterized by convolution with an impulse response, model multipath wireless channels. Deconvolution is used to equalize the effects of the channel. Upsampling, downsampling, and multirate identities find application in the efficient implementation of pulse shaping at the transmitter and matched filtering at the receiver. Fast Fourier transforms are the foundation of two important modulation/demodulation techniques: orthogonal frequency-division multiplexing and single-carrier frequency-domain equalization. Linear estimation and least squares become the basis of algorithms for channel estimation (estimating an unknown filter response) and equalization (finding a deconvolution filter). Algorithms for estimating the parameters of an unknown sinusoid in noise find application in carrier frequency offset estimation. In short, signal processing has always been a part of communication; leveraging this fact, digital communication can be learned based on connections to signal processing.

I begin this book with an introduction to wireless communication and signal processing in Chapter 1, providing some historical context. A highlight of the chapter is the discussion of different applications of wireless communication, including broadcast radio and television, cellular communication, local area networking, personal area networks, satellite systems, ad hoc networks, sensor networks, and even underwater communications. The review of applications gives context for subsequent examples and homework problems in the book, which often draw on developments in wireless local area networks, personal area networks, or cellular communication systems.

In the next two chapters, I establish a fundamental background in digital communication and signal processing. I start with an overview of the typical block diagram of digital communication systems in Chapter 2, with an explanation of each block at the transmitter and the receiver. Important functions are described, including source coding, encryption, channel coding, and modulation, along with a discussion of the wireless channel. The remainder of the chapter focuses on a subset of these functions: modulation, demodulation, and the channel. To provide a proper mathematical background, I provide an extensive overview of important concepts from signal processing in Chapter 3, including deterministic and stochastic signals, passband and multirate signal processing, and linear estimation. This chapter gives tools that are used to describe the operations of the digital communication transmitter and receiver from a signal processing perspective.

With the fundamentals at hand, I continue with a more thorough treatment of modulation and demodulation in Chapter 4. Instead of considering all possible modulation formats as would be done in a deep-dive treatment, I focus on strategies described by complex pulse-amplitude modulation. This is general enough to describe most waveforms used in commercial wireless systems. The demodulation procedure is derived assuming an additive white Gaussian noise channel, including pulse shaping, maximum likelihood detection, and the probability of symbol error. The key parts of the transmitter and the receiver are described using multirate signal processing concepts. This chapter forms the basis of a classical introduction to digital communication but with a signal processing flair.

The full specialization of the receiver algorithms to the wireless environment comes in Chapter 5. Specific impairments are described, including symbol timing offset, frame timing offset, carrier frequency offset, and frequency-selective channels. Several methods for mitigation are also described, including algorithms for estimating unknown parameters based on least squares estimation and equalization strategies that leverage alternatively the time or frequency domain. I focus on algorithms for dealing with impairments in the simplest ways possible, to set the stage for more advanced algorithms that might be encountered in the future. The chapter concludes with a description of large- and small-scale channel models, and a discussion about how to characterize the time and frequency selectivity of a channel. The knowledge in this chapter is essential for the design and implementation of any wireless system.

The final chapter, Chapter 6, provides a generalization of the concepts from Chapters 4 and 5 to systems that use multiple transmit and/or multiple receive antennas, generally referred to as MIMO communication. In this chapter, I define different MIMO modes of operation and explore them in further detail, including receiver diversity, transmitter diversity, and spatial multiplexing. In essence, most of the descriptions in prior channels generalize to the MIMO case with suitable vector and matrix notation, and additional complexity in the receiver algorithms. While most of the chapter focuses on the flat-fading channel model, some generalizations to frequency-selective channels are provided at the end. This chapter provides important connections between wireless fundamentals and the types of communication systems now widely used in commercial wireless systems.

I developed this book as part of a course at The University of Texas at Austin (UT Austin) called the Wireless Communications Lab, which served both senior undergraduates and new graduate students. The lecture portion of the course materials was based on drafts of this book. The lab portion uses my laboratory manual Digital Wireless Communication: Physical Layer Exploration Lab Using the NI USRP, published by the National Technology and Science Press in 2012. This laboratory manual is bundled with a USRP hardware package available from National Instruments. In the lab, students implement quadrature amplitude modulation and demodulation. They must deal with a succession of more sophisticated impairments, including noise, multipath channels, symbol timing offset, frame timing offset, and carrier frequency offset. The lab provides a way to see the concepts in this book in action on real wireless signals. For self-study or courses without a laboratory component, I have included several computer problems that involve simulating key pieces of the communication link. To see the concepts in action, you can implement the described algorithms over an audio channel using a microphone and speaker. I have used this approach in the past to prototype a High Frequency Near Vertical Incidence Skywave wireless communication link, operating in amateur radio bands.

This book may be used in several different ways, with or without a laboratory component. In a junior-level undergraduate course, I would cover Chapters 1 through 5 and spend some extra time at the beginning on the mathematical fundamentals. For a senior-level undergraduate course, I would cover the material from the entire book. For a graduate course, I would cover the entire book with an additional implementation or research project. At UT Austin, the course I teach for both undergraduates and graduates covers the entire book and the first several laboratory experiments in the aforementioned lab manual. The graduate students also perform a project. It is an intense but rewarding course.

The textbook is highly recommended as independent study, as a comprehensive review of the fundamentals is provided in Chapters 2 and 3. I encourage careful review of the mathematical fundamentals before proceeding to the main content in Chapters 4 through 6. To digest the material, I suggest working out all of the example problems with pen and paper, to help visualize the key ideas. Attempting select homework problems is also recommended. I believe that this book will provide a good foundation for further studies in wireless communications.

As wireless communication continues to integrate into our lives, there continues to be a constant evolution of wireless technologies. My hope is that this book offers a fresh perspective on wireless and acts as a launching point for further developments to come.