Robert W. Heath Jr. - Introduction to Wireless Digital Communication: A Signal Processing Perspective

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A Signal Processing Perspective

Robert W. Heath, Jr.

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ISBN-13: 978-0-13-443179-6
ISBN-10: 0-13-443179-0

To my family

RWH

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 Nyquists 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 , 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 , 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 . 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.