Lehrinhalte
The module ``Foundations of Wireless Communications'' consists of 4 courses of 3 Pts each, for a total of 12 Pts (ECTS). Two of these courses are required:
1) Foundations of Digital and Wireless Communications;
2) Information Theory;
Other two can be chosen within a list of elective courses.
Foundations of Digital and Wireless Communications provides the basics of digital and wireless
communications. In particular, the material covered by the course includes basic principles
of communication over time-varying wireless channels, performance measures, stochastic modeling of
wireless channels, the notions of frequency, time and spatial diversity, basic transmit and receive
diversity techniques, the impact of channel state information, basic spread-spectrum techniques,
OFDM principle and basic multiaccess techniques.
Information Theory presents the fundamentals of Information Theory. In particular,
information measures and information sources, and the fundamental limits of data compression,
channel coding and (lossy) source coding. Relations to channel coding theory, communication
theory and signal processing (notably, audio, image and video coding) are evidenced.
In the list of elective courses, there is the possibility of choosing the two lab-oriented courses in a sequence: Wireless Digital Communications Lab I and Wireless Digital Communications Lab II, which provide the students with a hands-on practical training based on Matlab and FPGA programming, on the algorithms studied in theory on the two required courses. Other elective include: Estimation and Decision Theory for Communication Systems (providing the fundamentals of statistical signal processing applied to communication problems), Projection Methods in Signal Processing and Communications (providing a theoretical framework for optimization in vector spaces, essential for signal processing and communication algorithms), Compressed Sensing (also known as sparse signal reconstruction, provides the basics of a new area in signal processing focused on the estimation of inherently redundant signals when only a small number of linear projections are available, which is gaining more and more importance in areas such as
image coding, features identification, machine learning schemes, channel estimation in wireless communications, and computation in big-data sets), Network Information Theory (this presents the extension of classical information theory to network problems, i.e., problems involving more than one source and one destination, which is at the basis of modern and efficient system design in wireless networks),
Modern Channel Coding (a comprehensive overview of ``graph-based'' modern channel codes and their iterative decoding algorithms, such as Turbo Codes, LDPC codes, Spatially coupled LDPC codes),
Cross-Layer Optimization and Resource Allocation in Wireless Networks (methods to formulate and solve optimization problems related to wireless networks, including decentralized solutions suitable to on-line protocol implementation), Wireless Communication Systems (a deep overview of present and future wireless communication standards, their design rationale and their main working principles), Physical-Layer Security (information-theoretic methods to achieve secure communication over a wireless channel), MIMO Systems and Adaptive Transmission (schemes and techniques for multiple-antenna systems, which have become very popular in recent years and have been massively adopted in wireless communication standards such as IEEE 802.11n, 802.11ac, and 3GPP LTE-Advanced).
