Advanced Digital Communications (P01825)

? Credit Points : 20 ? SCQF Level : 11 ? Acronym : EEL-P-PGADC

This module will cover the current topics of interest in Advanced Digital Communications. In particular information theory fundamentals related to source and channel coding, modulation of signals and channel capacity are studied. Rate-distortion theory and quantisation for uncorrelated and correlated signals are of particular interest.
Syllabus:
Scalar quantisation, asymptotic quantisation theory, vector quantisation, rate-distortion theory, linear prediction and model-based source coding, multimedia source codecs (overview); the separation principle of information theory, digital modulation, channel coding, convolutional codes, Viterbi and soft-in/soft-out decoding, Turbo codes, codes for error detection.

? Keywords : source coding, quantisation, rate-distortion theory, channel coding, channel capacity, turbo codes, digital modulation

Entry Requirements

? Pre-requisites : Prior attendance of Discrete-Time Signal Analysis, Statistical Signal Processing and Digital Communication Fundamentals is recommended.

Subject Areas

Home subject area

Postgraduate (School of Engineering and Electronics), (School of Engineering and Electronics, Schedule M)

Delivery Information

? Normal year taken : Postgraduate

? Delivery Period : Semester 2 (Blocks 3-4)

? Contact Teaching Time : 5 hour(s) per week for 11 weeks

First Class Information

Date	Start	End	Room	Area	Additional Information
07/01/2008	10:00	13:00			Sanderson Drawing Office

All of the following classes

Type	Day	Start	End	Area
Lecture	Monday	10:00	12:00	KB
Tutorial	Monday	12:10	13:00	KB
Lecture	Friday	11:10	13:00	KB

Summary of Intended Learning Outcomes

The students will understand fundamentals as well as advanced concepts in digital communications. They will be able to quantify the bit rate that is theoretically needed to perform source coding of continuous-valued signals with some given maximum distortion. They will be able to explain the complexity-quality tradeoffs in practical systems and they will be able to quantify how close practical quantisation and channel-coding algorithms can get to the theoretical limits given by information theory. They will be able to design scalar and vector quantisers and linear predictive coding schemes for practical signals and they will be able to understand and apply modern channel coding concepts and digital modulation schemes in a given practical problem setting.