Logo

Communication Theory

Code: 102696
Credits: 9
2026/2027
Degree programme Type Course
Telecommunication Systems Engineering OB 3

Contact lecturer

Name :
Gonzalo Seco Granados
Email :
gonzalo.seco@uab.cat

Teaching staff

Rafael Terris Gallego

Group languages

You can consult this information at the end of the document.

Prerequisites

This subject can be considered as the continuation of the 102714 Communication Foundations, therefore, it is recommended to have passed and passed 102714 Foundations of Communications.

It is also recommended to have a good knowledge of 102690 Foundations of Signals and Systems, and 102712 Signals and Discrete Systems.

Objectives

A communications system in general consists of the following blocks: source, source encoder, channel encoder, modulator, channel, demodulator, channel decoder, source decoder and recipient. During the Foundations of Communications course, the emphasis was placed on the study of the modulator, channel and demodulator. In this course, first of all, they will be remembered and some new aspects of modulation and demodulation will be seen, but above all the other blocks of the system will be studied in depth, paying special attention to the characterization of the sources at the level of Information theory, compression using source codes and correction of errors introduced by the channel through channel encoding.

The specific objectives are to:

  • Consolidate the knowledge about modulations and demodulations, and describe some more advanced techniques than the previous courses.
  • Dimension communication systems from the point of view of probability of error (coding).
  • Analyze the flow of information throughout the communications system using the concepts of information theory.
  • Understand the fundamental limits given by the theory of information.
  • Encode fonts to reduce redundancy.
  • Become knowledgeable of the main methods of channel coding and its operating principles.

Learning outcomes

  1. Use the concepts of systems of data source code compression and secure digital message transmission in single-user and multiuser systems.
  2. Differentiate the blocks and functionalities of a complete data transmission system.
  3. Identify the minimum requirements for the communication of reliable and secure digital data.
  4. Autonomously associate new knowledge and techniques that are adequate for conceiving, developing or exploiting telecommunication systems and services, with special emphasis on data transmission.
  5. Distinguish the fundamental parameters of a complete data transmission oriented communications system.
  6. Classify the advantages and disadvantages of different technological alternatives for deploying or implementing communication systems in terms of digital source compression, channel coding and security mechanisms.
  7. Describe, develop, analyse and optimise the different blocks of a data transmission system.
  8. Combine different technological alternatives to propose data transmission systems that are optimised for features of the application scenario.
  9. Use communication and computer applications (office automation, databases, advanced calculation, project management, display, etc.) to support the design of data transmission systems and facilitate posterior technological transfer.
  10. Plan the design process as part of a digital communication systems team with emphasis on source compression, data coding and secure message transmission.
  11. Judge and criticise, both orally and in writing, different reliable and secure concepts, methods and techniques for digital data transmission.
  12. Be able to analyse, encode, process and transmit multimedia information employing analogue and digital signal processing techniques.
  13. Interpret the fundamental limits of information theory.
  14. Differentiate and classify the main source coding and compression algorithms.
  15. Understand and illustrate the main methods of channel coding and its operative principles.
  16. Recognise different multiuser access techniques and choose the best solutions in accordance with the communication scenario.
  17. Discuss and apply cryptography systems designed to improve the security of a communication system.
  18. Develop critical thinking and reasoning.
  19. Develop the capacity for analysis and synthesis.
  20. Develop scientific thinking.
  21. Work autonomously.
  22. Develop independent learning strategies.
  23. Manage available time and resources.
  24. Prevent and solve problems.
  25. Critically evaluate the work done.
  26. Work in an organised manner.
  27. Work cooperatively.
  28. Communicate efficiently, orally and in writing, knowledge, results and skills, both professionally and to non-expert audiences.
  29. Efficiently use ICT for the communication and transmission of ideas and results.
  30. Develop curiosity and creativity.

Contents

1. Definitions and basic properties of information theory


  • Introduction to data transmission systems.
  • Error detection and need for source and channel coding.
  • Logical channel.
  • Entropy, relative entropy, mutual information.
  • Data processing inequality. Fano's inequality.
  • Asymptotic equipartition property.


2. Source coding and data compression


  • Types of source codes and properties.
  • Source coding theorem (Shannon's first theorem).
  • Huffman coding.
  • Shannon-Fano-Elias coding.
  • Lempel-Ziv coding.


3. Channel capacity


  • Types and characterization of channels. Channel capacity.
  • Channel coding theorem (Shannon's second theorem).
  • Differential entropy.
  • Gaussian channel capacity.


4. Block codes


  • Properties of linear block codes. Systematic codes.
  • Generator and parity-check matrices.
  • Basic block codes: Hamming, repetition, maximum length, BCH, Reed-Solomon.
  • Decoding and error probability.
  • Cyclic codes.
  • Concatenation of codes and advanced coding: LDPC.


5. Convolutional codes


  • Properties of convolutional codes.
  • Representation and description of codes. State diagram and trellis.
  • Types of codes. Systematic codes. Recursive codes.
  • Probability of error and performance. Free distance. BER.
  • Optimal decoding (MLSE). Viterbi algorithm.

Learning activities and methodology

Title Hours ECTS Learning outcomes
Tutoring 6 0.24 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 28
Laboratory sessions 15 0.6 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30
Theory lectures 39 1.56 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20, 22, 30
Problem-solving lectures 15 0.6 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30
Student's individual work 143 5.72 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 30

Classroom activities

  • Theory classes: presentation of the theoretical contents
  • Classes of problems: solving problems related to theory, with the participation of the students themselves.
  • Laboratory sessions: application of the techniques presented to the theory classes to different real systems and implementation with different simulation softwares.
  • Partial and recovery exams.

Autonomous activities

  • Study of the theoretical and practical contents of the subject. Resolution of problems and preparation of deliveries of some sets of problems. Preparation of the exams.
  • Laboratory activities: realization and deepening of laboratory exercises. Preparation of the report of each laboratory session.
Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Assessment

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Practices 20 % 0 0 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30
Partial Exam 2 32 % 2 0.08 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 28, 30
Partial exam 1 48 % 2 0.08 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 28, 30
Recovery Exam 80 % 2 0.08 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 28, 30
Follow-up Activities Up to 10% of AC, if it increases the final grade. 1 0.04 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 23, 24, 25, 26, 28, 29, 30

Principles of assessment

The assessment is structured so that students can choose either a continuous assessment format or a format in which most of the assessment weight is concentrated at the end of the course. This final assessment may also serve as a recovery mechanism for continuous assessment. This allows students to adapt the pace at which they complete the assessment elements to their needs and preferences.

This course does not include the single assessment system.


Assessment elements

The following assessment elements will be used:

  • Follow-up activities
  • Laboratory sessions
  • Partial Exam 1
  • Partial Exam 2
  • Recovery Exam

The follow-up activities (NS) will consist of class participation, solving problems or tests in class and/or submitting problems outside class. The follow-up grade will only be used to increase the continuous assessment grade, up to a maximum of 10%.

The laboratory grade (NP) will be calculated based on the reports that must be submitted at the beginning and/or end of the laboratory sessions, the work carried out and any possible tests completed during or after the sessions, and any additional exercise submissions. It is not necessary to pass each laboratory session individually. Laboratory sessions are non-recoverable activities.

Partial Exam 1 (ExP1) will be held approximately halfway through the course. It does not exempt students from any course material, because the contents of this course are cumulative; that is, students must master the first topics in order to follow the later ones.

Partial Exam 2 (ExP2) will be held approximately during the last week of face-to-face activities, that is, during the theoretical classes.

The Recovery Exam (ExR) will be held once the face-to-face activities have ended, during the period specifically devoted to examinations.

All activities are individual, except for some laboratory activities, which may be carried out in groups.


Academic integrity and authorship verification

Teaching staff reserve the right to request an individual interview or oral verification test when there are indications of copying or lack of authorship in an assessable activity. Failure to satisfactorily prove authorship may affect its grading, in accordance with the applicable academic regulations.


Grade review

After each exam, a time slot will be scheduled on a specific day so that students can review their exam grade, except in the case of exams with automatic grading, such as multiple-choice tests.


Calculation of grades

  • Partial Exams grade [[ExP]]: [[ExP]] = 0.4*[[ExP1]] + 0.6*[[ExP2]]
  • Continuous Assessment grade [[AC]]: [[AC]] = max( [[ExP]], 0,9*[[ExP]] + 0.1*[[NS]] )
  • Overall Exams grade [[NE]]:
  • [[NE]] = [[AC]] if the recovery exam is not performed.
  • [[NE]] = [[ExR]] if the recovery exam is performed.
  • To pass the course, it is necessary to obtain [NE]]>= 4.
  • The Final Grade [[NF]] of the subject is: [[NF]] = 0.8*[[NE]] + 0.2*[[NP]] if [[NE]]>= 4. If [[NE]]<4, [[NF]] = [[NE]].
  • The Final Grade [[NF]] is rounded in accordance with Article 266 "Assessment Results" of the UAB Academic Regulations of 10 July 2025.
  • The course is passed if [[NF]]>=5.


Repeating students

Students may keep their laboratory grade (NP) from previous years. This is the default option if they do not repeat the laboratory sessions.


Honors

Granting an honors distinction (MH) is a decision of the teaching staff responsible for the course. Honors will be awarded only to students who have shown a high level of excellence in the course, and not automatically to those with the highest grades. UAB regulations state that honors may only be awarded to students who have obtained a final grade equal to or higher than 9.00. Honors may be awarded to up to 5% of the total number of enrolled students.


Consideration of "Not Evaluable"

The final grade will be “Not Evaluable” only when the student does not take any exam, neither the continuous assessment exams nor the recovery exam.


Consideration in case of copy or plagiarism

Notwithstanding other disciplinary measures that are deemed appropriate, and in accordance with the current academic regulations, the evidence of reports where the student has committed irregularities (eg plagiarism, deception, copying, the fact to leave copy, etc.) that could lead to a variation of the qualification.


Consideration in cases of copying or plagiarism

Without prejudice to any other disciplinary measures deemed appropriate, and in accordance with current academic regulations, any tests or reports in which the student has committed irregularities, such as plagiarism, deception, copying, allowing others to copy, etc., that could lead to a change in the grade will be marked with a zero.


Communication

The Virtual Campus will be the communication platform with the students.


Use of AI

All content submitted by students, such as exams, reports, follow-up activities, etc., must be original and generated solely by them, without the direct involvement of artificial intelligence tools, unless otherwise indicated. This does not prevent students from using AI as a learning or support tool to review content, assist in code creation, or compare results.


Bibliography

Basic

  • Cover, T. M.; Thomas, J. A. Elements of Information Theory. Wiley, 2nd edition, 2006.
  • Proakis, J.; Salehi, M.; Digital Communications. McGraw-Hill, 5th edition, 2008.

Complementary

  • Artés Rodríguez, A.; Pérez González, F.; Cid Suero, J.; López Valcarce, R.; Mosquera Nartallo, C.; Pérez Cruz, F.; Comunicaciones Digitales, http://www.tsc.uc3m.es/~antonio/libro_comunicaciones/El_libro_files/comdig_artes_perez2.pdf
  • Ha, T. T., Theory and Design of Digital Communication Systems. Cambridge University Press, 2011.
  • Glover, I. A.; Grant, P. M., Digital Communications. Prentice Hall, 3rd edition, 2010.

Advanced

  • Proakis, J.; Salehi, M.; Commnications Systems Engineering, Prentice-Hall, 2nd edition, 2001.
  • Du, K.-L.; Swamy, M. N., Wireless Communication Systems. From RF Subsystems to 4G Enabling Technologies. Cambridge University Press, 2010.
  • Madhow, U., Fundamentals of Digital Communication. Cambridge University Press, 2008.
  • Lin, S.; Costello, D. J., Error Control Coding. Prentice-Hall, 2nd Edition, 2004.
  • Gallager, R. G., Principles of Digital Communication. Cambridge University Press, 2008.
  • Moon, T. K., Error Correction Coding: Mathematical Methods and Algorithms. Wiley-Interscience, 2005.
  • Roman, S., Introduction to Coding and Information Theory. Springer, 1996
  • Abramson, N., Information Theory and Coding. McGraw-Hill, 1963.
  • Blahut, R., Algebraic Codes for Data Transmission. Cambridge University Press, 2003.
  • Hamming, R. W., Coding and Information Theory. Prentice-Hall, 1980.
  • Gitlin, R.D.; Hayes, J.F.; Weinstein, S.B. Data communications principles. Plenum Press, 1992.     
  • Adamec, J., Foundations of Coding: Theory and Applications of Error-Correcting Codes with an Introduction to Cryptography and Information Theory. Wiley-Interscience, 1991.
  • Sklar, B.; Digital Communications: Fundamentals and Applications, Prentice Hall, 2nd edition, 2001.
  • Goldsmith, A.; Wireless Communications, Cambridge University Press, 2005.
  • Molisch, A. F.; Wireless Communications, Wiley, 2nd edition, 2011.

Software

During the practical sessions, MATLAB and Simulink will be used.

Likewise, MALTAB and Simulink will also be used as a support for the theoretical and problem classes.

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE

Type of teaching Group Language Semester Shift
(TE) Theory 330 Spanish second semester morning-mixed
(PAUL) Classroom practices 331 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 331 Catalan/Spanish second semester morning-mixed
(PAUL) Classroom practices 332 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 332 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 333 Catalan/Spanish second semester morning-mixed