EECS 378 - Digital Communications
CATALOG DESCRIPTION: Sampling and time-division multiplexing, baseband digital signals and systems. Coded pulse modulation, error control coding, digital modulation systems, information measure and source encoding, and introduction to spread spectrum communications.
- Simon Haykin, Digital Communications , John Wiley & Sons, 1988
- J. G. Proakis, Digital Communications , 4th edition, McGraw Hill, 2001
For Undergraduates: Text 1 is required ; text 2 is optional.
For Graduate Students: Text 1 is optional; text 2 is required .
COURSE COORDINATOR: Chung-Chieh Lee
COURSE GOALS: This is a second course in communications (following C07) that introduces the fundamentals of digital signaling, information theory and coding, digital transmission and reception. The goal is to equip the students with basic knowledge for design, analysis and comparison of digital communication systems and for the physical layer of data communication networks including wireless networks and the internet.
PREREQUISITES: EECS 307
PREREQUISITES BY TOPIC :
- • Probabilities
- • Random processes
- • Fourier series and transforms
- • Filtering, bandwidth, and signal-to-noise ratio
- • Analog modulation techniques (AM/FM/PM) and frequency division multiplexing
- • Envelope detection and synchronous detection
- • Noise and noise effects
DETAILED COURSE TOPICS:
Week 1: Overview of digital communication systems: special characteristics and advantages of digital over analog systems, introduction to information theory and coding: probabilistic information measure and entropy (READINGS Haykin 1.1-1.4, 2.1-2.2)
Week 2: Source coding and source coding theorem, prefix coding and Huffman codes, mutual information and channel capacity concepts (READINGS Haykin 2.3-2.7)
Week 3: Introduction to error control coding, channel coding theorem, linear block codes, error detecting and ARQ versus forward error correcting (READINGS Haykin 8.1-8.3)
Week 4: Syndrome decoding, cyclic codes, channel capacity theorem (READINGS Haykin 8.4, 2.9, 3.1)
Week 5: Basic detection theory: statistical hypothesis testing and probability of error, match filters, detection of signals in additive white Gaussian noise, matched filter receivers (READINGS Haykin 3.5-3.8)
Week 6: Analog-to-digital conversion: sampling and Nyquist sampling theorem, quantization and signal-to quantization noise ratio (READINGS Haykin 4.1-4.5, 5.1, Midterm Exam)
Week 7: Pulse code modulation, bandwidth of digital signals, differential PCM, delta modulation (READINGS Haykin 5.3, 5.5, 5.6)
Week 8: Time-division multiplexing, baseband digital signaling, bandwidth efficiency, intersymbol interference, Nyquist pulse shaping (READINGS Haykin 4.7, 6.1-6.4)
Week 9: Partial response digital signaling, eye pattern, baseband M-ary systems, digital modulation techniques: amplitude shift keying, frequency shift keying, phase shift keying (READINGS Haykin 6.5-6.7, 7.1)
Week 10: Coherent and non-coherent reception of digital modulation signals. Selected topics (if time permits): introduction to spread spectrum communications and code division multiplexing (READINGS Haykin 7.2-7.4)
- Homework 1: Haykin 2.1.3, 2.1.5, 2.1.7, 2.2.2, 2.2.3, 2.1.6
- Homework 2: Haykin 2.3.1, 2.3.3, 2.4.1, 2.5.1, 2.6.2, 2.6.3
- Homework 3: Haykin 2.6.4, 2.7.1, 8.3.1, 8.3.3, 8.3.5
- Homework 4: Haykin 8.3.8, 8.4.2, 8.4.3, 2.9.1, 2.9.3, 2.7.1
- Homework 5: Haykin 3.8.1, 3.8.7, 4.5.1, 4.7.2, 4.7.3
- Homework 6 Haykin 5.3.2, 5.6.1, 5.5.2 (Coding project work starts this week)
- Homework 7: Haykin 6.5.2, 6.4.3, 6.4.4, 6.7.1
- Homework 8: Haykin 7.2.1, 7.2.3, 7.2.6, 7.4.1, 7.7.2
PROJECT: This is a team design project involving software simulation of a digital communication system. Each team must consist of three or four students and must have at least one undergraduate student and one graduate student. The digital communication system consists of a source coder, a channel coder, a WGN channel, a detector, a channel decoder, and a source decoder. The design will involve designing a configurable Huffman code table generator which reads a source symbol probability file (to be given by the instructor to test the design) and is the engine for the Channel Encoder Module and the Channel Decoder Module. The channel coding and decoding modules simulate a (7,4) cyclic code and the associated syndrome decoding. The channel module is basically a Gaussian random variable generator which corrupts each transmitted digit with a “noise.” The detector implements a decision algorithm based on threshold comparison. The design will be tested by an ASCII input file, a source symbol probability file, and a number of selected noise variance values.
- Homework: 15%
- Project: 15%
- Midterm exam: 30%
- Final exam: 40%
COURSE OBJECTIVES: This course will equip the students with basic knowledge for designing, analyzing, comparing, and managing digital communication systems ranging from digital cellular systems to data networking and multimedia services. Specifically, the students will learn from this course how to compress data without sacrificing information by using proper source coding techniques, how to protect transmitted data efficiently by employing a proper channel coding method, how to manage communication system resources including bandwidth and power by selecting a proper signaling and/or digital modulation scheme, how to allocate channel bandwidth to various traffic types (voice, data, video, etc.) using time division multiplexing, and how to assess the performance of a given system design against critical information theoretic limits.
ABET CONTENT CATEGORY: 100% Engineering (Design component).