FITech Digital communication

After completing the course, the student

• Can explain the information theoretic foundations of digital communications. They recognise and are able to explain the purpose of source coding, channel coding, and channel capacity for the information transmission task.
• Can recognise and explain the main elements of digital communication systems and the common digital modulation methods in waveform domain. They can also explain the effects of the transmission channel and the electronic modules of the transmission chain on the performance of the communication system.
• Is able to analyse the transmission link level performance of digital communication systems. They recognise the essential analysis methods and is able to apply them for different communication waveforms. They are able to formulate the signal model for a transmission link from a relevant system definition, develop a Matlab model, and simulate its performance.
• Recognises and is able to explain the main functions of digital communications transmitters and receivers. They can explain the principles of detection theory and apply detection theory to the signal processing functions of communications receivers.
• Can explain the significance and principles of error control coding in digital communication systems. They recognise the common error control coding methods and know how the redundancy introduced by the codes can be utilised in the receiver. A student is able to analyse the coding gain at link level.

Information theoretic foundation of electrical communication:

• Information, entropy, and mutual information;
• Maximal mutual information and channel capacity;
• Source coding vs. channel coding;
• Capacity of frequency-selective and fading channels

Baseband and bandpass digital communication:

• Bits, symbols, and waveforms;
• Baseband pulse amplitude modulation (PAM), Nyquist pulse-shaping, line coding;
• Linear I/Q modulation, real and complex symbol alphabets;
• Digital frequency modulation techniques.

Performance of digital communication chains:

• Effects of additive noise, symbol & bit errors and their probability, Gray mapping;
• Spectral efficiency and related concepts, connections to channel capacity theorem.
• Effects of fading on the symbol and bit errors

Detection theory and intersymbol interference (ISI) mitigation:

• Basics of statistical decision making and detection, maximum likelihood (ML) and maximum a posteriori (MAP) principles;
• Signal space concepts and connection to practical waveforms, sufficient statistics;
• Detection of single symbols, matched filtering (MF);
• Detection of symbol sequences;
• Optimal receiver front-end, signal space arguments, intersymbol interference (ISI);
• Zero-forcing (ZF), mean-squared error (MSE) and other optimisation principles;
• ML sequence detection and Viterbi algorithm;
• Channel equalisation, linear vs. nonlinear equalizers, adaptive techniques.

Error control coding in digital communication systems:

• Error detection vs. correction vs. prevention, redundancy;
• Hard and soft decoding, coding gain;
• Block codes and convolutional codes,
• Viterbi decoding;
• Coded modulation and trellis codes;
• Interleaving, puncturing.
• Basic ideas and application of Turbo codes, LDPC codes and Polar codes.

Synchronisation basics:

• Concepts of time, phase and frequency synchronization in digital communications receivers
• Some basic algorithms to acquire synch

Very basics of communications engineering