The goal of the course is to provide a description of the fundamental features and technologies of digital communication systems.
In particular, the following blocks will be analysed: source encoder/decoder, channel encoder/decoder, digital modulator/demodulator, equalizer, detector. A complete description of OFDM follows. Frequency, time and code division multiplexing techniques are compared. Block and convolutional codes are described and analyzed in terms of implementation and performance.

• Knowledge of information theory
• Ability to perform data compression using the Huffman code (source coding)
• Knowledge of the fundamental blocks inside a digital transmitter and a digital receiver
• Ability to analyze the system performance for linear modulations over the additive white Gaussian noise channel
• Ability to design an equalizer
• Ability to dimension multiplexing systems using time, frequency and code division techniques
• Knowledge of OFDM systems
• Knowledge of basic block and convolutional code properties (channel coding)

The ability to apply the gained abilities will be verified through class exercises, as well as during the oral examination. The oral examination will also help students in improving their communication skills.

Probability theory and random processes (white Gaussian noise in particular), signal theory (Fourier and z transforms, energy, power, scalar product of signals, convolution, autocorrelation functions, spectra), system theory (transfer function, impulse response, stability) in the cases of both continuous and discrete time. Evaluation of the error probability for ideal PAM over an AWGN channel.

Information theory (1.5 credits)

• A measure for information: entropy of discrete random variable, differential entropy (2h)
• Source Coding (4h)
  • Huffman coding and variable length source codes
• Mutual information and Capacity and of channels (9h)
  • Capacity of the AWGN channel
  • Capacity of some discrete channels
    • BEC and BSC
    • Symmetric channels
  • Mutual information with Modulation
  • Channel Coding theorem
  • Data processing theorem

Digital transmission over linear frequency and time selective channels and access techniques (3.5 credits)

• Performance of digital receivers and linear modulations over the Additive White Gaussian Noise Channel (8h)
  • Analytic signal and complex envelope
  • Power spectrum of linearly modulated signals
  • Maximum Likelihood and Minimum distance criteria, structure of a digital receiver, matched filter
  • Gaussian probability density function and cumulative distribution function, P(e) and Pb(e) for the classical constellations (PAM, QAM and PSK), union bound
  • ISI and eye diagrams


• Criteria for the optimization of transmitting and receiving filters for narrowband channels (5h)
  • First Nyquist criterion
  • Square Root Raised Cosine filters
• Equalization techniques (10h)
  • MMSE and zero forcing filters
  • Maximum likelihood sequence estimation based on the Viterbi algorithm
  • Adaptive equalization
• OFDM systems (10h)
  • Signal structure
  • Waterfilling
  • Cyclic prefix
  • Equalization
• Multiple access techniques (2h)
  • TDMA
  • FDMA
  • CDMA

“Conventional” channel codes (3 credits)

• Binary Linear block codes (20h)
  • Generating matrix and parity check matrix
  • Hard and soft decoding, error detection
  • Minimum distance, performance evaluation and coding gain
  • Interleaving for burst channels
  • Practical applications
• Convolutional codes (10h)
  • Encoder, trellis representation
  • Hard and soft decoding: the Viterbi algorithm
  • Minimum distance, performance evaluation and coding gain
  • Puncturing
  • Practical applications

The practice classes are based on numerical analysis of the systems described in the theoretical lectures.

Oral examination with theoretical questions and short exercises.