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Communication Theory

Hírközléselmélet
A tantárgyleírás hatályossága
Hatályosság kezdete:
2026. March 21.
Hatályosság vége:
Subject name (Hungarian, English)
Hírközléselmélet
Communication Theory
Subject code BMEVIHVMA07
Subject type
Training Level
Course types and hours (weekly/semester)
Course type lecture tutorial laboratory
hours (weekly) 3 0 0
type (linked/independent)
Assessment type félévközi érdemjegy
Credits 4
Subject coordinator
DR. Bitó János
position: egyetemi docens
Responsible department
Szélessávú Hírközlés és Villamosságtan Tanszék
Faculty Villamosmérnöki és Informatikai Kar
Subject website http://hvt.bme.hu/index.php?option=com_content&view=article&id=479%3Ahirkoezleselmelet-vihvm107&catid=11%3Amsc-kepzes&Itemid=18%E2%8C%A9%3Dhu&lang=hu
Primary curriculum type
Direct prerequisites – Strong prerequisite none
Direct prerequisites – Weak prerequisite none
Direct prerequisites – Parallel prerequisite none
Direct prerequisites – Milestone prerequisite none
Direct prerequisites – Exclusion none

Objectives

Programme
  1. Introduction: task of telecommunication; sources of information, messages, interferers, noise; main blocks of communication systems, their function; digitl and analog communication. Brief mathematical introduction: stochastic processes
  2. Basics of information theory, definition of basic concepts, presentation via examples.
  3. Source coding: purpose, effectiveness, coding of sources without and with memory. The first coding theorem of Shanon (of source coding)
  4. Methods of source coding: Huffman-code; LZW code; arithmetic codes (szószerint: encoder)
  5. The transmission channel: mutual information; concept of the channel capacity. Typical channels: BSC, DMC, AWGN). Shannon bound. The second coding theorem of Shannon (of channel coding).
  6. Channel coding. Concept of message space, of code space. Classifying of errors. Hamming distance. Laws of code construction Singleton, Hamming bound, MDS, perfect code.
  7. Methods of binary linear channel coding: heuristic coding, code vectors, generator matrix and polynomial, parity check matrix and polynomial. Hamming codes  
  8. Non-binary linear channel coding methods: finite fields; operations over Galois-fields. Non-binary Hamming codes, Reed-Solomon codes, cyclic codes
  9. Basics of decision theory; decision problems in communication. Binary decision, Bayes(minimum risk) decision; likelihood ratio, ML criterion, sufficient statistics, MAP decision.  
  10. Basics of estimation theory: parameter estimation tasks; random parameters, cost functions, MMSE and MAP estimation; deterministic parameters, likelihood function, estimators, biased and unbiased types; Cramer-Rao bound, efficient estimators.
  11. Transmission of digital signals over analog channels. The concept of complex envelope. Signal sets; the signal space. Signal sets of 2D, examples: PSK, QAM; higher dimensionality: orthogonal, regular simplex signal set. Optimum receivers in AWGN channels: correlation, matched filter.
  12. Performance of noisy channels. Band limited channels, choice of signal waveform, Nyquist criterion (SZERINTEM AZ OPT. SIGN. SET ELŐSZÖR AZ AWGN-HEZ TARTOZNA.)
  13. Channel coding and modulation in channels with memory. Convolutional coding, trellis coding. Continous phase modulation. The Viterbi algorithm.
  14. Fading channels; Rayleigh- and Rice-fading. Error probability in fading channels. Principles of spread spectrum transmission, the DS and the FH system.
Widespread concepts of and tasks to be solved by telecommunications can be described by a more or less unified theory. Aim of this subject is to present basics of and applied approaches in this theory. Main topics dealt with are information theory, decision- and estimation theory as well as theory of digital communications. In this framework students get acquainted with important concepts, methods and procedures. Application of these concepts is presented via a detailed discussion of practical examples taken from the techniques of wireless and optical communication. Lectures, exercises as well as tests are put together so to prepare students for being able to understand and apply these concepts. Thus understanding of new or novel systems is relatively easy for them; also they get the basis for following more specialized subjects in later semesters as well as in solving novel tasks during their career.

Learning outcomes

Ez a tantárgy a KKK rendeletben meghatározott, következő kompetenciák fejlesztését szolgálja:

Knowledge

No learning outcomes recorded.

Skills

No learning outcomes recorded.

Attitudes

No learning outcomes recorded.

Autonomy and responsibility

No learning outcomes recorded.

Oktatási módszertan

Six lectures/ fortnight

Tanulástámogató anyagok

Online források
J. G.; Proakis, M. Salehi: Communication Systems Engineering (Prentice Hall, 2002); Th. M.; Cover, J. A. Thomas: Elements of Information Theory (Wiley, 2006); H. L. Van; Trees: Detection, Estimation, and Modulation Theory, Vol I (Wiley)

Recommended preliminary knowledge for completing the subject

Knowledge type competencies
(azon előzetes ismeretek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
Signals and Systems, Infocommunication
Skill type competencies
(azon előzetes képességek és készségek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Recommended (non-compulsory) preliminary competencies
(azon ajánlott (nem kötelező) előzetesen megszerzendő kompetenciák összessége, amelyek jelentősen hozzájárulnak a tantárgy eredményes teljesítéséhez)
Signals and Systems, Infocommunication
General rules
Requirements: During the relevant semester: 4 written exams. Maximum score for each exam is 15 points. Exam result vs. score: 0-4 points: 0; 4.5-7 points: failed (1); 7.5-9 points: pass (2); 9.5-11 points: satisfactory (3); 11.5-13 points: good (4); 13.5-15 points: excellent (5). Exam not written is taken as 0. The mark is failed (1) if there are less than two exams of score pass or better. If there are at least two better-than-failed exams, the mark is the average rounded-to-an-integer of the best two scores. Additional possibilities: -
Assessment methods
In-term assessments

No detailed assessments provided.

Weight of in-term assessments

No weights provided.

Exam-period assessments

No detailed assessments provided.

Weight of exam elements

No weights provided.

Grade calculation

No grade thresholds provided.

Attendance requirements

No attendance requirements provided.

Rules for retake and resubmission

Not provided.

Short description

Not provided.

Detailed description

Not provided.

Recommended courses
-
Workload to complete the subject

No workload breakdown provided.

Validity of subject requirements
Requirements valid from:
Requirements valid until:
Curriculum placement

No curriculum placements recorded for this subject version.