TEACHING: Subjects

 GENERAL INFORMATION

Name:

Digital Communications.

Degree:

Technical Telecommunication Engineering. 3th Year. Mandatory. 6 credits.

Professor(s):

Roberto Sanz Gil.

Timetable:

1st Semester.
Monday (12:30 - 13:30)
Tuesday (12:30 - 13:30)
Wednesday (12:30 - 13:30)
Thursday (12:30 - 13:30)

 OBJECTIVES

Introduction to digital communication systems as well as the most common coding and modulation techniques for baseband and bandpass signals. Performance evaluation of the different techniques based on basic parameters like bandwidth, signal-to-noise ratio (SNR) and error probability.

 SYLLABUS

Digital versus analog communication. Applications of digital communications. System model of a digital communication. Basic nomenclature of digital communication. Design and performance criteria. Location of the digital transmission in the OSI reference model.

Signal classification. Energy and power. Spectral density. Autocorrelation. Random variable. Stocastic processes. Stationarity and ergodicity. Noise characterization in digital communication systems. Log units. Signal transmission through linear systems. Base band and band pass. Signal and system bandwidth.

Data format. Messages, characters and symbols. Sampling, quantification and coding of the analog information. Pulse Code Modulation (PCM). Quantification noise. Non-uniform quantification (-Law and A-Law). Line coding. Classification and properties of line codes. Power spectral density of line codes.

Pulse transmission through a channel. Inter-symbol interference (ISI). Nyquist’s first criterium. Raised cosine filter. Eye diagram. Parcial response system: duobinary coding. Nyquist’s second criterium.

Introduction to decision theory. Minimum probability criterium. Binary channel affected by white gaussian noise. Optimal receiver. Match filter and correlator. Error probability estimation.

Band pass digital modulations. Linear modulations: modulation of a complex base band signal. Receiver for a band pass signal linearly modulated. Geometrical representation of signals and noise in the signal space. Spectral efficiency of the band pass modulations.

Design goals in the design of digital communications. Efficient modulations in bandwidth and power. Band pass signal detection with gaussian noise. Model of the optimal receiver for band pass signals based on a correlators bank. Coherent and non-coherent detection. Error probability in binary systems. Bit and symbol error probability in M-ary systems. Systems comparison.

 EVALUATION CRITERIA

Final exam in February and extraordinary exam in September.

 BIBLIOGRAPHY

B. Sklar: “Digital Communications”; Ed. Prentice-Hall, 2nd Edition, 2001

I. A. Glover, P. M. Grant: “Digital Communications”; Ed. Prentice-Hall, 1998

S. Haykin: “Communications Systems”; Ed. John Wiley & Sons, 4th Edition, 2001

J. G. Proakis: “Digital Communications”; Ed. McGraw Hill, 2nd Edition, 1989

E. Lee, D. Messerschmitt: “Digital Communication”; Kluwer Academic Publishers, 1994

L. Couch: “Digital and Analog Communication Systems”; McMillan Publishing Company, 4th Edition, 1993

P. Z. Peebles Jr: “Digital Communication Systems”; Ed. Prentice-Hall, 1987

P. Z. Peebles Jr: “Probability, Random Variables and Random Signal Principles”; Ed. McGraw Hill, 3rd Edition, 1987

 MATERIALS