Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

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    Communication Theory

    A tantárgy neve magyarul / Name of the subject in Hungarian: Hírközléselmélet

    Last updated: 2016. január 11.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics

    Villamosmérnöki szak, MSc képzés

    Közös tantárgy
    Course ID Semester Assessment Credit Tantárgyfélév
    VIHVMA07 1, 3 3/0/0/f 4  
    3. Course coordinator and department Dr. Bitó János, Szélessávú Hírközlés és Villamosságtan Tanszék
    Web page of the course 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
    4. Instructors

    Name:

    Position:

    Department

    Dr. János Bitó

    Associate Professor

    Department of Broadband Infocommunications and Electromagnetic Theory

    Dr. István Frigyes

    Professor Emeritus

    Department of Broadband Infocommunications and Electromagnetic Theory

    5. Required knowledge

    Signals and Systems, Infocommunication

    6. Pre-requisites
    Kötelező:
    NEM ( TárgyEredmény( "BMEVIHVM107" , "jegy" , _ ) >= 2
    VAGY
    TárgyEredmény("BMEVIHVM107", "FELVETEL", AktualisFelev()) > 0)

    A fenti forma a Neptun sajátja, ezen technikai okokból nem változtattunk.

    A kötelező előtanulmányi rendek grafikus formában itt láthatók.

    Ajánlott:
    -
    7. Objectives, learning outcomes and obtained knowledge

    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.
    8. Synopsis
    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.
    9. Method of instruction

    Six lectures/ fortnight

    10. Assessment

    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.

    11. Recaps -
    12. Consultations

    By appointment with the lecturer

    13. References, textbooks and resources

    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)

    14. Required learning hours and assignment
    Kontakt óra42
    Félévközi készülés órákra20
    Felkészülés zárthelyire38
    Házi feladat elkészítése 
    Kijelölt írásos tananyag elsajátítása20
    Vizsgafelkészülés 
    Összesen120
    15. Syllabus prepared by

    Name:

     

    Tanszék, Int.:

    Dr. István Frigyes

    Professor Emeritus

    Szélessávú Hírközlés and Villamosságtan Tanszék

    Dr. János Bitó

    Associate Professor

    Szélessávú Hírközlés and Villamosságtan Tanszék

    Dr. Horváth Péter

    Associate Professor

    Szélessávú Hírközlés and Villamosságtan Tanszék