6.450 Principles of Digital Communications Wednesday, Sept. 4
MIT, Fall 2002 Handout #3
Lecture 1: Introduction to Digital Communication
1 Introduction and Objectives
The digital communication industry is an enormous and rapidly growing industry, roughly
comparable in size to the computer industry. The objective of this course is to study those
aspects of digital communication systems that are unique to these systems. That is, rather
than focusing on hardware and software for these systems, which is much like hardware
and software for many other kinds of systems, we focus on the fundamental system aspects
of modern digital communication.
This is the first subject in the two-term sequence, 6.450 and 6.451. The two subjects are
in the process of being integrated into a coherent year-long sequence, and we hope that
the rough edges do not show too much. Our intention is that 6.450 may be taken on a
stand-alone basis and be accessible to well-prepared undergraduates.
Digital communication is a field in which theoretical ideas have had an unusually pow-
erful impact on actual system design. The basis of the theory was developed 53 years
ago by Claude Shannon, and is called information theory. For the first 25 years or so of
its existence, information theory served as a rich source of academic research problems
and as a tantalizing suggestion that communication systems could be made more efficient
and more reliable by using these approaches. By the mid 1970’s, mainstream systems
using information theoretic ideas began to be widely implemented, for two reasons. First,
by that time there were a sizable number of engineers who understood both information
theory and communication system development. Second, the low cost and increasing pro-
cessing power of digital hardware made it possible to implement increasingly sophisticated
algorithms.
As you learn about digital communication systems and their conceptual basis in infor-
mation theory, you will come to appreciate that these ideas require a fairly deep under-
standing of somewhat abstract concepts. Doing the problem sets is an important part
of developing this understanding, but it is not sufficient. In many undergraduate engi-
neering subjects, the emphasis (reinforced by the grading policy) is on learning to grind
through the solution of a set of types of problems represented by prescribed equations
(“plug and chug”). Here, as is appropriate for a graduate class, the focus is much more
on the connections between engineering and theory.
The relationship between theory, problem sets, and engineering/design is rather complex.
The theory deals with relationships and analysis for models of real systems. A good
theory (and information theory is one of the best) allows for simple analysis of simplified
models. It also provides structural principles that allow insights from these simple models
to be applied to more complex and realistic models. Problem sets provide students with
an opportunity to analyze these highly simplified models, and, with patience, to start to
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