• 052477 - DIGITAL COMMUNICATION II

• Blended Learning & Flipped Classroom

Lectures and exercise sessions will make students able to

1) Knowledge and understanding. Understand the general principles of data transmission in digital communication systems, analyze and understand the requirements associated to a communication system in terms of signal bandwidth, filtering, modulation, coding.

2)  Applying knowledge and understanding. Identify and define at the block-diagram level a proper filtering, modulation and coding scheme for the most common channel models, compute the performance of  transmission systems in terms of error probability for the most common channel models.

3) Making judgements. Judge if a given filtering,  modulation and coding scheme is appropriate for a practical radio or optical communication system. Recognize the design space and the degrees of freedom that can be exploited to reach given objectives in terms of performance of filtering,  modulation and coding, with specific application to practical radio and optical communication systems.

4) Communication. Communicate to other engineers with presentations and documents about filtering, modulation and coding schemes using the appropriate mathematical tools as Fourier analysis, probability theory, calculus and matrix algebra. Communicate to non-specialists the requirements, the constraints and the features of communication systems using graphical representation (block diagrams) and writings.

Lectures and laboratory sessions will make students able to

1) Knowledge and understanding. Understand the general principles of advanced topics of digital communication. Analyze and understand the requirements associated to a communication system in terms of equalization, predistortion, synchronization.

2) Applying knowledge and understanding. Identify and define at the block-diagram level a proper equalization, predistortion, synchronization scheme for the most common modulation schemes. Encode software by common commercial tools as Matlab and/or Simulink to simulate the chain of transmitter, channel, receiver of data communication systems.

3) Making judgements. Judge if a given equalization, predistortion, synchronization scheme is appropriate for a practical radio or optical communication system. Recognize the design space and the degrees of freedom that can be exploited to reach given objectives in terms of performance of equalization, predistortion, synchronization, with specific application to practical radio and optical communication systems.

4) Communication. Communicate to engineers in technical documents and presentations about the analysis and design of equalization, predistortion, synchronization, MIMO systems using the appropriate mathematical tools as Fourier analysis, probability theory, calculus and matrix algebra. Communicate to non-engineers by block diagrams and writings about the needs and constraints that advanced telecommunication systems are subject to in terms of receiver performance.

Equalization. Wiener’s method. Discrete-time AWGN model, FIR and unconstrained linear equalization, adaptive equalization, decision feedback equalization, channel capacity with decision feedback  equalization. Maximum likelihood sequence detection by the Viterbi algorithm. Maximum a posteriori probability sequence detection by the BCJR algorithm.

Precoding. Tomlinson-Harashima precoding, partial response systems, examples.

Predistortion. AM-AM and AM-PM characteristic of power amplifiers. Adaptive predistortion of memoryless power amplifiers.

Elements of MIMO transmission. The MIMO principle, the MIMO Gaussian channel, detection for the memoryless MIMO channel, detection for the MIMO channel with memory.

Phase-lock loop. Continuous-time PLL, discrete-time PLL, first-order and second-order loop; common phase detectors, design of the loop filter in the presence of phase noise.

Carrier and timing recovery.  Decision-directed phase detector, S-curve, power of M phase detector, differential encoding, feed-forward and feed-back carrier recovery. Square-law timing detector, Gardner detector; digital re-sampling. 

Laboratory activities. Use of Simulink and Matlab for simulation of digital communication systems.

Blended learning and flipped classroom will be adopted for about 1/10 of the course to show the relationship between digital communication and other courses in the field of communication and signal processing.

Knowledge of Signal Theory: Fourier analysis, filtering, basics of digital signal processing. Knowledge of probability theory and random processes. Knowledge of the basics of digital communication.

The exam can be taken in any one of the July, September, February sessions. The exam consists in a written part based on a question about the theory, in an oral part based on the theory and on the written exam. The oral part can include an optional (up to the student) presentation of the laboratory activities.

The student will be asked to answer questions regarding the theory, to draw block diagrams of digital communication systems and to explain them by writings and equations, to compute system performance in terms of error probability and/or mean square error, to explain and comment on the code encoded during the laboratory activity (optional).