05-10-2012, 12:36 PM
Digital Communications Lecture Notes Fall 2009
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Class Organization
Textbook Few textbooks cover solely digital communications (without analog) in an introductory communi-
cations course. But graduates today will almost always encounter / be developing solely digital communication
systems. So half of most textbooks are useless; and that the other half is sparse and needs supplemental material.
For example, the past text was the ‘standard’ text in the area for an undergraduate course, Proakis & Salehi,
J.G. Proakis and M. Salehi, Communication Systems Engineering, 2nd edition, Prentice Hall, 2001. Students
didn’t like that I had so many supplemental readings. This year’s text covers primarily digital communications,
and does it in depth. Finally, I find it to be very well-written. And, there are few options in this area. I will
provide additional readings solely to provide another presentation style or fit another learning style. Unless
specified, these are optional.
Introduction
A digital communication system conveys discrete-time, discrete-valued information across a physical channel.
Information sources might include audio, video, text, or data. They might be continuous-time (analog) signals
(audio, images) and even 1-D or 2-D. Or, they may already be digital (discrete-time, discrete-valued). Our
object is to convey the signals or data to another place (or time) with as faithful representation as possible.
Why not Analog?
The previous text used for this course, by Proakis & Salehi, has an extensive analysis and study of analog
communication systems, such as radio and television broadcasting (Chapter 3). In the recent past, this course
would study both analog and digital communication systems. Analog systems still exist and will continue to
exist; however, development of new systems will almost certainly be of digital communication systems. Why?
• Fidelity
• Energy: transmit power, and device power consumption
• Bandwidth efficiency: due to coding gains
• Moore’s Law is decreasing device costs for digital hardware
• Increasing need for digital information
• More powerful information security
Networking Stack
In this course, we study digital communications from bits to bits. That is, we study how to take ones and zeros
from a transmitter, send them through a medium, and then (hopefully) correctly identify the same ones and
zeros at the receiver. There’s a lot more than this to the digital communication systems which you use on a
daily basis (e.g., iPhone, WiFi, Bluetooth, wireless keyboard, wireless car key).
Channels
A channel can typically be modeled as a linear filter with the addition of noise. The noise comes from a variety
of sources, but predominantly:
1. Thermal background noise: Due to the physics of living above 0 Kelvin. Well modeled as Gaussian, and
white; thus it is referred to as additive white Gaussian noise (AWGN).
2. Interference from other transmitted signals. These other transmitters whose signals we cannot completely
cancel, we lump into the ‘interference’ category. These may result in non-Gaussian noise distribution, or
non-white noise spectral density.
The linear filtering of the channel result from the physics and EM of the medium. For example, attenuation in
telephone wires varies by frequency. Narrowband wireless channels experience fading that varies quickly as a
function of frequency. Wideband wireless channels display multipath, due to multiple time-delayed reflections,
diffractions, and scattering of the signal off of the objects in the environment. All of these can be modeled as
linear filters.
The filter may be constant, or time-invariant, if the medium, the TX and RX do not move or change.
However, for mobile radio, the channel may change very quickly over time. Even for stationary TX and RX, in
real wireless channels, movement of cars, people, trees, etc. in the environment may change the channel slowly
over time.