NETWORK INFORMATION THEORY
cod. 1009281

Academic year 2023/24
1° year of course - Second semester
Professor
NOT ASSIGNED
Academic discipline
Telecomunicazioni (ING-INF/03)
Field
A scelta dello studente
Type of training activity
Student's choice
0 hours
of face-to-face activities
6 credits
hub: PARMA
course unit
in ENGLISH

Learning objectives

The objective of this course consists of building on the basic information theory background built in the course 1005249 - INFORMATION THEORY, to develop advanced concepts in network (multi-terminal) information theory.
Students taking this course will master the information-theoretic concepts at the basis of uplink (multiaccess) and downlink (broadcast) channels in wireless communications, interference management, and link scheduling in ad-hoc device-to-device networks. They will be able to apply such concepts of actual problems arising in state of the art wireless communication systems, with special emphasis to 5G wireless networks.

Prerequisites

1005249 - INFORMATION THEORY

Course unit content

The course provides a deep knowledge of basic results in network information theory, including the most fundamental network topologies building blocks such as the multiple access channel, the broadcast channel, the interference channel, and the relay channel. Then, the course provides also several contemporary advanced topics and applications, such as multiuser MIMO (with applications to 5G massive MIMO schemes), the relation between the information theoretic multiple access channel and successive/iterative multiuser detection/decoding in modern CDMA schemes and the regime of TIN (treating interference as noise) optimality, with relations on link selection and scheduling in Device-to-Device (D2D) networks. Relations with the current trends of actual wireless standards and in particular with 5G systems will be pointed out.

Full programme

- Review of advanced concepts in typical sequences: packing lemma, covering lemma, conditional typicality, Markov lemma.
- Lossy source coding and rate-distortion theory for memoryless sources.
- Lossy compression of correlated Gaussian sources, bit-allocation and reserve waterfilling
- The capacity region of discrete memoryless and Gaussian multiple access channels.
- The capacity region of discrete memoryless and Gaussian degraded broadcast channels.
- Binning schemes: Slepian-Wolf separated encoding of correlated sources.
- Binning schemes: Wyner-Ziv lossy source coding with side information at the decoder.
- Binning schemes: Gelfand-Pinsker coding for channels with state known at the transmitter.
- Multiuser MIMO schemes: Vector Gaussian MAC and BC, linear precoding, massive MIMO.
- The 2-user Gaussian interference channel: approximate capacity and generalized degrees of freedom.
- Optimality of treating interference as noise (TIN), in Gaussian interference channels.

Bibliography

El Gamal, A. and Kim, Y.H., 2011. Network information theory. Cambridge University Press.

The course is based on a number of very recent results which are not yet collected in textbooks, therefore a collection of relevant papers (mainly from IEEE Transactions on Information Theory, IEEE Transactions on Communications, IEEE Transactions on Wireless Communications) will be provided as reading material for the course.

Teaching methods

The course is divided into theoretical lessons and exercise sessions. The lectures are organised in video lectures. The slides of the course will be provided on the Elly platform.
Additional teaching material used during the lessons is uploaded to the Elly web site. The registration to the course is necessary to download the slides.

Assessment methods and criteria

Written test (basic theory questions and small problem solving).
Seminar/Project oral presentation (with slides), with additional oral examination (discussion/theory questions).

Other information

Related information and material will be published on a properly prepared course webpage.

2030 agenda goals for sustainable development

Contacts

Toll-free number

800 904 084

Student registry office

E. segreteria.ingarc@unipr.it

Quality assurance office

Education manager:
Elena Roncai
T. +39 0521 903663
Office E. dia.didattica@unipr.it
Manager E. elena.roncai@unipr.it

President of the degree course

Paolo Serena
E. paolo.serena@unipr.it

Faculty advisor

Alberto Bononi
E. alberto.bononi@unipr.it

Career guidance delegate

Guido Matrella
E. guido.matrella@unipr.it

Tutor professor

Alberto Bononi
E. alberto.bononi@unipr.it
Giulio Colavolpe
E. giulio.colavolpe@unipr.it
Riccardo Raheli
E. riccardo.raheli@unipr.it

Erasmus delegates

Walter Belardi
E. walter.belardi@unipr.it

Quality assurance manager

Paolo Serena
E. paolo.serena@unipr.it

Internships

not defined

Tutor students

not defined