RYERSON UNIVERSITY
Graduate Programs in Computer Networks
CN8811– Multimedia Processing and Digital Communications - Fall 2009
Course Information 

The course covers the basic concepts in digital communication techniques. It subsequently introduces various aspects of multimedia processing. Topics include: sampling, quantization, PCM, DPCM, delta modulation, line coding, information theory on entropy, Huffman coding, Lempel Ziv coding, information theory on channel capacity, linear block codes, cyclic codes, convolutional codes, baseband transmission, multimedia data compression standards, and multimedia information retrieval. Theoretical concepts will be re-enforced through some experiments in the laboratory using Matlab.

INSTRUCTOR

 

Name

Office

Tel

Email

Webpage

Lian Zhao

ENG 451

6101

lzhao@ee.ryerson.ca

www.ee.ryerson.ca/~lzhao

 

Teaching Assistant

Name

Office

Email

Office Hours (including tutorial)

Khalid Abdel Hafeez

EPH 406

kabdelha@ryerson.ca

Thursdays 3-5 pm

Maria Gracias

EPH 406

maria.gracias@ryerson.ca

Tuesdays 3-5 pm

 

COURSE EVALUATION

Laboratory

4 x 5% = 20 %

Midterm

35 %

Final exam

45%

NOTES:

·         Assignments: There will be some assignments problems for each chapter. The assignment will not be collected. However, students are expected to solve all assignment problems.

·         Lab report: There will be 4 matlab experiments. Doing the lab helps you understand the course contents. Lab assignment will normally be posted after Thursday’s lecture during the week of 2nd-5th week. You are expected to finish the lab assignment in one week.

·         Midterm: TBD

·         Final Exam: 3-hour closed-book exam.

 

MAJOR TOPICS

  • Introductions: C1 and Appendix A - Introduction to communication systems and digital information, review of Fourier analysis, Fourier series and Fourier transform, linear time invariance system. Reading Sections: 1.1-1.3, 1.6-1.7, Appendix A: A.1-A.4, A.6.
  • Sampling theory in digital communication: C2:  sampling, Nyquist rate, quantization, signal to quantization noise ratio, PCM, PAM.  Reading Sections: 2.1-2.6
  • Source coding and channel coding: C13, C6-7:  Information theory on entropy, Huffman coding, lempel-ziv coding. Cyclic codes, convolutional codes, transfer functions. Reading sections for source coding: 13.1, 13.2.1, 13.2.2, 13.7; Reading sections for channel coding: 6.2, 6.3.2, 6.4, 6.5, 6.7, 7.1, 7.2.
  • Probability, optimal detection of binary signals, Modulation and multiplexing C3/1/4/11: Review probability, autocorrelation function and power spectrum density, WSS processes, optimal detection of binary signals in AWGN channel, optimal transceiver, bit error rate analysis. Reading sections: 3.1, 3.2, 1.5, 1.6, 4.1, 4.2, 4.3, 4.4,  11.1
  • Multimedia data compression and information retrieval, C13: Introduction to multimedia data compression standard (ADPCM, MPEG, JPEG); fundamental of voice compression, audio and image processing techniques. Reading sections: 13.8,

 

TEXTBOOK

 

  • Bernard Sklar, Digital Communications: Fundamentals and applications, Prentice Hall, 2000.
  • Course notes, Ryerson bookstore, 2008.

 

OTHER REFERENCES:

  • Simon Haykin, An Introduction to Analog and Digital Communications, Wiley, 1989.
  • Simon Haykin, Communications Systems, 3rd edition, Wiley, 1994.
  • B.P. Lathi, Modern Digital and Analog Communication System, Oxford Press, 1998.

 

 

Course Schedule (tentative)

 

 

Tuesday

Thursday

September

1                 Introduction

Into to matlab

Lab0

3         Introduction

Sampling Theorem

8          Sampling Theorem

 

Assignment 1

10      Source coding

 

 

15             Source coding

Lab 1 due

Assignment 2

17     Channel coding

 

Midterm

22          Channel coding

Lab 2 due

Assignment 3

 

24     Channel coding

 

October

29             Optimal detection

Lab 3 due

Assignment 4

1      Optimal detection

 

 

6         Multimedia processing

Lab 4 due

8      Finish course

and Review

 

 

 

 Lab Schedules

 

Laboratory: Everyone must read the lab materials and do the preparation before each lab. In order to obtain a passing grade in this course, all students must attend the lab and hand in the lab report. Late submission will not be accepted.

  • Lab0: Familiar with matlab, no report (lab0.pdf  audio file pcm.wav download from CN course website)  .
  • Lab1: Sampling Theorem, Quantization and PCM (lab1.pdf);
  • Lab2: Source Coding Techniques (lab2.pdf);
  • Lab3: Channel coding Techniques (lab3.pdf);
  • Lab4: Binary Transmission in the Presence of AWGN, Bit Error Rate Analysis (lab4.pdf)

 

Assignment

 

Matlab Resources