EE224A Fall 2009

Digital Communications

University of California at Berkeley
Department of Electrical Engineering and Computer Sciences

[ Announcements | Administrative Info | Course Info | Handouts | Homework | Miscellany ]


Administrative Info

Instructor: Professor Kannan Ramchandran, 269 Cory Hall,
Lectures:   TuTh 9:30-11:00 am, 3107 Etcheverry
Office hours: Tuesday, 11:00 - 12:00 pm, 212 Cory Hall
Teaching Assistant: None
Point of Contact: Hao Zhang,
Course Administrative Assistant: Lea Barker, 253 Cory Hall, (510) 642-2384,

Course Info


The modern field of digital communication was pioneered by C. E. Shannon in 1948. Digital communication systems have now become the basic workhorses behind the information age. Examples include wireless and wireline telephone transmission systems, storage systems, telephone modems, cable modems, digital subscriber loop technology, etc. This course is an introduction to the fundamental principles underlying the design and analysis of digital communications systems.


The basic prerequisites for this course are EE120 (Signals and Systems), EE123 (Digital Signal Processing), and EE126 (Probability and Random Processes) or equivalent. While EE226A is not a prerequisite, maturity in probability and random processes is required. In particular, familiarity with the following concepts are expected,

If you are not sure about your background, please come and talk to the instructor.


There will be bi-weekly problem sets (15% of course grade) and two exams: Midterm 1 (40%) and Midterm 2 (45%).

Midterm 1: Oct 27th, 7 pm - 9 pm, in Cory 293

Midterm 2: Dec 4th, 7 pm - 9 pm, room TBA


Reference books

Course Overview

1. Overview of digital communications.

Source-channel separation as a layering technique.

2. Source coding, quantization and compression.

Source entropy, Huffman codes, transform coding and quantization. Architecture of current digital image and video compression systems.

3. Signal space concepts with application to modulation. Complex discrete-time baseband representation.

4. Communication over Gaussian channels.

Gaussian noise model. Optimal maximum likelihood detection under Gaussian noise. Error probability performance analysis. Modulation schemes: PAM, QAM, PSK, PPM. Signal space framework.

5. Communication over bandlimited channels.

Baseband pulse amplitude modulation (PAM). Nyquist criterion. Pulse design for bandlimited channels. Power and bandwidth as fundamental resources for communication. Channel capacity. Linear block and convolutional codes. Soft and hard decision decoding. Inter-symbol interference. Equalization: Linear and maximum likelihood sequence detection. Viterbi algorithm. Orthogonal frequency division multiplexing (OFDM).

6. Codes for communication and storage.

MDS codes, Reed Solomon codes, codes on graphs, digital fountain codes, Low Density Parity Check codes.

7. Wireless communications.

Complex baseband representation of passband channels. Modeling of multipath wireless channels. Key parameters: delay spread, coherence bandwidth, coherence time, Doppler spread. Channel fading. Non-coherent and coherent detection in flat fading channels.


Handout1.pdf (MIT course notes of Professor Gallager on introduction to digital communications.)

Homework (Solutions will be posted on bSpace)

The detailed homework submission policy can be downloaded or printed here [link]. Familiarize yourself with the homework submission and grading policy.

Homework1.pdf (Due: Tue Sept 08th in class before lecture)

Homework2.pdf (Due: Tue Sept 22nd in class before lecture)

Homework3.pdf (Due: Tue Sept 29th in class before lecture)

Homework4.pdf (Due: Tue Oct 13th in class before lecture)

Homework5.pdf (Due: Thu Oct 22nd in class before lecture)

Homework6.pdf (Due: Thu Nov 12nd in class before lecture)

Homework7.pdf (Due: Thu Nov 19nd in class before lecture)

Homework8.pdf (Due: Tue Dec 1st in class before lecture)