Course Description
This is a graduatelevel course in Digital Communication theory. This course reviews basic concepts from random variables, random processes, and filtering of linear processes, and then spends a majority of the class analyzing different digital communication schemes. These topics include line coding, baseband communication, binary communication, Mary signaling, signal space concepts, maximum likelihood and minimax decision theory, symbol error and bit error performance analysis, matched filter derivation, coherent carrier modulation, noncoherent modulation, and intersymbol interference.
The textbook used for the course is, "Introduction to Digital Communications", by M. Pursley.
The video lectures listed below provide a full outline of the course, but only portions of the lectures have been recorded so far. I try to add a few more recorded lectures each time I teach the course.
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Video Lectures

Random Variable Review: (6 videos, ~56 minutes)

Topics include: Random variable definition, density and distribution functions, mean, variance, moments, correlated/uncorrelated random variables, independent random variables, Gaussian random variables


Random Process Review: (7 videos, ~75 minutes)

Topics include: Random process definition, density and distribution functions, mean function, autocorrelation function, stationary random processes, widesense stationary (WSS) random processes, crosscorrelation and crosscovariance functions, Gaussian random process, white noise random process.


Random Processes in Linear Systems Review

Part 1 (5 videos, ~55 minutes): Linear systems review, random processes in stable systems, random process output example, mean function example and mean function output derivation

Part 2 (7 videos, ~54 minutes): Autocorrelation function output derivation, random process output power, discretetime input/output relationship summary, Gaussian random process input/output relationship derivation


Frequency Domain Analysis of Random Processes (7 videos, ~52 minutes)

Topics Include: Power spectral density definition, properties, examples, White noise, PSD input/output relationship, PSD of amplitude modulated signals and random processes, bandpass frequency functions.


Baseband Binary Communication

Part 1 (10 videos, ~117 minutes): Signal sets, transmitting binary data, linear receivers/filters, filter output, decision statics, and error probabilities

Part 2 (16 videos, ~163 minutes): Minimax decisions, Bayes decisions, matched filter derivation, matched filter properties, matched filter frequencydomain representation and correlation receiver representation, signal space and signal distance.


Coherent Communication

Part 1: Introduction, BPSK, and ASK

Part 2: Mary Decision Rules

Part 3: 2D Modulation

Part 4: Orthogonal Modulation and Offset Modulation


Noncoherent Communication (12 videos, ~96 minutes)

Intersymbol Interference

Introduction to Information Theory and Error Control Coding