EGR 544 Communication Theory

EGR 544-1 Introduction

Z. Aliyazicioglu Electrical and Computer Engineering Department Cal Poly Pomona

Introduction • • • • •

Office : Building 9-143 Office Hours : M Class Folder: EGR54401 Course Webpage: www.calpolypomona.edu/~zaliyazici/ece544 Grading: Exam 1 Exam 2 Final Homework/Quiz Project

•

Textbook: Digital Communication, 4th Ed. John Proakis, MCGraw Hill 2000 Textbook website www.mhhe.com/engcs/electrical/proakis

•

Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 2

1

Introduction Prerequisites • Probability and Random Processes • Communication Systems Reference: • • • •

[1] Introduction to Digital Communication, by Rodger E. Zeimer and Roger L. Peterson, Second Edition, Prentice Hall, 2001. [2] Digital Communications, by Bernard Sklar, Second Edition, Prentice Hall, 2001 [3] Communication Systems , Simon Haykin, 4th Ed. Wiley, 2001, ISBN 0-471-17869-1 [4] Probability, Random Variables, and Random Processes, A. A. Papoulis, 4th Ed., McGraw-Hill, 2001.

Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 3

Definition Device transfer information from one location (time) to another location (time) Digital: Smoke, Morse Code Telegraph Analog: Commercial Radio, TV Digital: Data, Computer, HDTV

Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 4

2

Types of Communication Systems • Point to Point: Telephone, Fax • Point to Multipoint: Broadcast (Radio, TV) • Simplex: One Way • Duplex: Two Ways

Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 5

Design Consideration Cost/Performance Trade Off Cost Power Bandwidth Complexity

Cal Poly Pomona

Performance Data Rate Bit Error Probability Transmission Range Fault Tolerance Adaptive to Environment Security Anti Jamming Capability Low Probability of Interception

Electrical & Computer Engineering Dept.

EGR 544-1 6

3

Analog Modulation

Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 7

Digital Modulation

Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 8

4

Pulse Modulation

Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 9

Why Study digital communications? • Digital receiver needs only distinguish between two waveforms it is possible to exactly recover digital information • Transmitted bits can be detected and regenerated, so Noise does not propagate additively. • More signal processing techniques are available to improve system performance: source coding, channel (error-correction) coding, equalization, encryption, filtering,… • Better “control” and more flexibility. . . • Digital ICs are inexpensive to manufacture. A single chip can be mass produced at low cost, no mater how complex • Digital communications permits integration of voice, video, and data on a single system (ISDN) • Implementation by software instead of hardware • Security is easier to implement.

Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 10

5

Digital Communication System • The basic elements of a digital communication system Information Source

Source Encoder

Channel Encoder

Digital Modulator Discrete Channel

Source Decoder

Output

Channel Decoder

Information & Coding Theory

Cal Poly Pomona

Noise Channel

Digital Demodulator Modulation & Detection Theory

Electrical & Computer Engineering Dept.

EGR 544-1 11

Digital Communication System • Source are converted into a sequence of binary digits which is called information sequence • Represent the source by an efficient number of binary digits • Efficiently converting the source into a sequence of binary digits is a process, which is called source encoding of data compression • Channel encoder adds some redundancy into binary information sequence that can be used for handle noise and interference effects at the receiver. • Digital modulator maps the binary information sequence into signal waveforms. • Communication channel is used to send the signal from the transmitter to the receiver. Physical channels: the atmosphere, wireless, optical, compact disk,…. Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 12

6

Digital Communication System • Digital demodulator receives transmitted signal contains the information which is corrupted by noise • Cannel decoder attempts the reconstruct the original information sequence from knowledge of the code used by channel encoder. • Source decoder attempts the reconstruct the original signal from the binary information sequence using the knowledge of the source encoding methods. • The difference between the original signal and the reconstructed signal is measured of the distortion introduced by the digital communication system • Estimate what was send, aiming at the minimum possible probability of making mistakes

Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 13

Communication channels and their characteristics •

•

Physical channel media – magnetic-electrical signaled wire channel – modulated light beam optical (fiber) channel – antenna radiated wireless channel – acoustical signaled water channel Virtual channel – magnetic storage media

• Noise characteristic – thermal noise (additive noise) – signal attenuation – phase distortion – multi-path distortion • Limitation of channel usage – transmitter power – receiver sensitivity – channel capacity (such as bandwidth) Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 14

7

Communication channels and their characteristics

Frequency range for guided wire channel

Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 15

Communication channels and their characteristics

Frequency range for wireless electromagnetic channels. [Adapted from Carlson (1975), 2nd edition

Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 16

8

Communication channels and their characteristics • Additive noise channel

s(t )

r (t ) = α s(t ) + n(t )

+ n(t )

r (t ) = α s(t ) + n(t )

• where α is the attenuation factor, s(t) is the transmitted signal, and n(t) is the additive random noise process. • Called Additive Gaussian noise channel if n(t) is a Gaussian noise process.

Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 17

Communication channels and their characteristics • The linear filter channel with additive noise – to ensure the specified bandwidth limitations.

s(t )

Linear filter c(t) Channel

r (t ) = s(t ) ∗ c(t ) + n(t )

+ n(t )

r (t ) = s(t ) ∗ c (t ) + n(t ) ∞

= ∫ c (τ )s(t − τ ) dτ + n(t ) −∞

Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 18

9

Communication channels and their characteristics • The linear time-variant filter channel with additive noise – Time-variant multipath propagation.

s(t )

Linear time-variant Filter c(τ ;t) Channel

r (t ) = s(t ) ∗ c(τ ;t ) + n(t )

+ n(t )

r (t ) = s(t ) ∗ c (τ ;t ) + n(t ) ∞

= ∫ c (τ ;t )s(t − τ ) dτ + n(t ) −∞

where c(τ ;t) is the response of the channel time t due to an impulse applied at time t- τ. Cal Poly Pomona

Electrical & Computer Engineering Dept.

EGR 544-1 19

10