communication networksmidas1.e-technik.tu-ilmenau.de/~webkn/webdaten/lehre... · 2019-11-07 ·...

Communication Networks Winter 2019/20

Prof. Jochen Seitz 1

Communication Networks

Chapter 4 – Transmission Technique

Communication Networks: 4. Transmission Technique 133

Overview

1. Basic Model of a Transmission System

2. Signal Classes

3. Physical Medium

4. Coding

5. Multiplexing


133

134




Terminology

• Transmission

▪ Transport of physical signals via a transmission medium between two directly connected devices (source and sink)

• Switching

▪ Provision of a complete transmission path between two end systems over several intermediate devices

• End Systems

▪ Devices used by the end user

❖used for input and output of data

❖ responsible for coding/decoding, multiplexing/demultiplexing, modulating/demodulating

❖ send and receive data with error detection and correction functionality


Source and Sink



SourceSource SinkSinkPhysical Medium

Information

135

136



Physical Medium

Basic Model of a Transmission System



SourceSource SinkSinkSCSC LCLC LDCLDC SDCSDCTransmission ChannelTransmission Channel

TransmissionSystem

TransmissionSystem

ue(t) ua(t)

SC = Source Coding SDC = Source DecodingLC = Line Coding LDC = Line Decoding

Signal Classes


2. Signal Classes

con

tin

uo

us

valu

eco

nti

nu

ou

sva

lue

dis

cret

eva

lue

dis

cret

eva

lue

continuous timecontinuous time discrete timediscrete time

Time t

Value u

Time t

Value u

Time t

Value u

Time t

Value u

analog

digital

Digitalization

137

138



2. Signal Classes

Digitalization of an Analog Signal

1. Sampling

▪ continuous time → discrete time

▪ values are still continuous

▪ Nyquist/Shannon Sampling Theorem:

− determination of minimum sampling frequency

− if fg is the highest frequency of a bandlimited analog signal, the sampling frequency should be at least 2fg to guarantee perfect reconstruction

2. Quantization

▪ continuous values → discrete values

▪ values are mapped onto value intervals → quantization error (noise in D/A conversion)

3. Source Coding

▪ identification of intervals by bit sequence


2. Signal Classes

Example: Digitalization of Human Speech for ISDN

• Theoretically, voice is not a bandlimited signal

• CCITT telephone channel is limited to 300 Hz – 3,400 Hz

• Sampling

▪ at least with 6,800 Hz, but due to the steepness of the signal‘s edge, 8,000 Hz is chosen

• Quantization

▪ 256 quantization intervals

▪ non-linear quantization to improve signal-to-noise ratio SNR (A-law, m-law)

• Coding

▪ 8 bits per sample

• Resulting data rate

𝐷𝑎𝑡𝑎 𝑅𝑎𝑡𝑒𝑣𝑜𝑖𝑐𝑒 =# 𝑆𝑎𝑚𝑝𝑙𝑒𝑠

𝑆𝑒𝑐𝑜𝑛𝑑

𝐵𝑖𝑡𝑠

𝑆𝑎𝑚𝑝𝑙𝑒= 8 000 ∙ 8

𝑏𝑖𝑡

𝑠= 64 000

𝑏𝑖𝑡

𝑠


139

140



Digital Speech Transmission


2. Signal Classes

Network

A/D

Line Decoding

D/A

Line Coding

Source Decoding

Source Coding

File Transfer

Communication Networks: 4. Transmission Technique142

2. Signal Classes

Network

Line Decoding

Digital SignalConversion

Line Coding

Digital SignalConversion

File Transfer

Source Decoding

Source Coding

141

142



Physical Medium


3. Physical Medium

Usage of a physical medium to transfer information

Source Sink

Transmission ChannelTransmission Channel

TransformerTransformer

Medium

Information

x(t) y(t)

x´(t) y´(t)

z´(t)

Primary Signals 𝒙 𝒕 , 𝒚(𝒕): physical parameters related to source/sink

Signals 𝒙′ 𝒕 , 𝒚′ 𝒕 , 𝒛′(𝒕):physical parameters related to channel

Physical Medium:e.g. electrical conductorSource of Interference

TransformerTransformer

≈

𝑦′(𝑡) = 𝐹(𝑥′ 𝑡 , 𝑧′ 𝑡 )

Transmission over PhysicalLayerTaken from F. Halsall (2000)

Repetition from Chapter 2


3. Physical Medium

Transmitted Data

Transmitted Signal

Sampling Instants

Received Data

0 1 1 110 0 0

0 1 0 110 0 0

+V

-V

Bit Error

TypicalReceived Signal

x(t)

x´(t)

y´(t)

y(t)

143

144



4. Coding

Coding Types (I)

• Source Coding:

▪ Transforming user information so that they can be transferred via the transmission channel as fast as possible and transformed back at the receiver

• Channel Coding:

▪ Transforming information to provide transmission on a bandwidth-limited channel over a long distance with as few errors as possible

• Line Coding:

▪ Transforming digital information into a sequence of physical signals to be transmitted over a physical channel


Coding Types (II)


4. Coding

CodingCoding

Channel CodingChannel CodingSource CodingSource Coding Line CodingLine Coding

Goal:Reduction of redundancy

Goal:Reduction of redundancy

Goal:Detection and correctionof transmission errors

Goal:Detection and correctionof transmission errors

Goal:Adaptation of code symbols to the physicalchannel

Goal:Adaptation of code symbols to the physicalchannel

Example: Manchester encodinghttp://www.althos.com/Tutorial/images/GSM-tutorial-channel-coding.jpg

01100110

145

146

http://www.althos.com/Tutorial/images/GSM-tutorial-channel-coding.jpg



Source Coding

Lossless Compression

• Eliminating statistical redundancy

▪ No information loss

▪ Examples

❖Huffman Encoding

❖Arithmetic Encoding

Lossy Compression

• Removing unnecessary or less important information

▪ Received information is unequal to original information

▪ Examples

❖MP3 for audio files

❖ JPG for photos


4. Coding

Channel Coding

Error Detection

• Adding redundancy

▪ Parity bits

▪ Check sums

• Tests at the receiver to prove integrity of transmitted information

▪ Results to be used together with special protocol functions

❖Acknowledgement

❖Retransmission

Forward Error Correction

• Adding even more redundancy

• Detecting and correcting errors

▪ Hamming Distance: the number of bit positions at which two possible symbols are different

• Receiver reconstructs original information

▪ Block Code

▪ Hamming Code


4. Coding

147

148



4. Coding

Line Coding

• Representing the digital signal to be transported by a waveform that is appropriate for the specific properties of the physical channel

• Requirements:

▪ Eliminate DC component

▪ Facilitate (bit) synchronization

▪ Minimize spectral content

▪ Ease error detection and correction


Line Coding: Non Return to Zero (NRZ)


4. Coding

0 1 0 1 1 0 0 0 1 1

NRZunipolar

NRZ-Inverted(NRZI)

bipolar

149

150



4. Coding

Line Coding: Alternate Mark Inversion (AMI)

• AMI-Code:(modified, as used

for ISDN)

▪ Coding Violation (CV):

▪ When „0“ and „1“ are sent at the same time, the receiver will get a „0“


CV

CV

1 0 0 0 1 1 0 1

Each interval DC-free

„+0” (+750 mV)„1” (0 mV)

„-0” (-750 mV)

1 0 0 0 1 1 0 0 1 0 0 1

Line Coding: Manchester-Code


4. Coding

0 1 0 1 1 0 0 0 1 1

Manchester

Coding: 1 signal transition +A -A in the middle of the bit interval

0 signal transition -A +A in the middle of the bit interval

Eventually, a signal transition at the beginning of the bit interval is required

+A

-A

0

151

152



5. Multiplexing

Multiplexing

• Focus on a physical (analog) channel.

• Information transferred via physical signals that change over time

• These signals occupy capacity/bandwidth of the transmission channel for a given time (connection time, packet duration, …)

• Requested and offered bandwidth usually not corresponding

▪ wasted resources

▪ not adequate communication

Communication Networks - 4. Transmission Technique 153

Requested = Offered Bandwidth


5. Multiplexing

information codedin physical signals

The application utilizes the physical channelin an optimal way

Cbandwidth capacity

of the physical channel

153

154



Requested > Offered Bandwidth


5. Multiplexing


In order to transmit the complete amount of information,several channels have to be bundled

bandwidth capacityof the physical channel


Requested < Offered Bandwidth


5. Multiplexing


Several applications may utilize the physical channelin an optimal way.


➔Multiplexing


155

156



5. Multiplexing

Conjoined Transmission of Information Streams

• Different streams of information of concurrently active application entities that use the same frequency range interfere with each other

• They cannot be separated at the receiver


Bandwidth(Frequency)

Time

ApplicationEntity1

ApplicationEntity 2

5. Multiplexing

Multiplex Transmission

• Multiplex:

▪ Multiple analog message signals or digital data streams combined into one signal over a shared medium

▪ Sharing an expensive resource

• Different categories of multiplexing:

▪ Space Division Multiplexing

▪ Time Division Multiplexing

▪ Frequency Division Multiplexing

▪ Code Division Multiplexing

▪ Wavelength Division Multiplexing


157

158



5. Multiplexing

Space Division Multiplex

• Space partitioned into different „areas“

• Each user/application is assigned to one area

• No interference possible

• Examples:

▪ analog telephony

▪ radio cells in mobile telephony


5. Multiplexing

Frequency Division Multiplex

• Separate frequency range assigned to each user / application

• Different users / applications might send concurrently

• Receiver can separate the transmissions by tuning to according frequency



Time

ApplicationEntity 1

ApplicationEntity 2

159

160



5. Multiplexing

Time Division Multiplex

• Each user / application has exclusive access to the complete bandwidth of the channel, but only at certain time periods

• Assignment can be done statically or on demand



Time

5. Multiplexing

Code Division Multiplex

• On digital channels, different streams can be separated based on different (mutually orthogonal) codes (chipping sequences)

• The streams occupy the same spectrum

• The receiver can separate the streams



Time

Signal Power

161

162



Multiplex Transmission


5. Multiplexing

Source

+

Modulation Demodulation Sink

Source Modulation Demodulation Sink

Source Modulation Demodulation Sink

Time and Frequency Division Multiplex


5. Multiplexing

1 2 3 4 5 6 7 8 9 10 11 12

60 108 kHz f

Frequency Division Multiplex

frequency range,divided into 12 sub-ranges, 4 kHz each

1 2 3 4 30 31 32

0 125 µs t

Time Division Multiplex

time perioddivided into 32 time slots, approx. 3,9 µs each

29

163

164



Time Multiplexing / Demultiplexing


5. Multiplexing

A B

S1

S2

S3

S4

S1S2

S3 S4

S1

S4

S2

S3

MultiplexFrame

S1

S2

S3

S4

Time Slott4 t3 t2 t1 t4 t3 t2 t1

t4 t3 t2 t1

8 bit Code WordMultiplexing

Transmission PathDemultiplexing

5. Multiplexing

Example of Code Division Multiplex (1)

• Four senders A, B, C, D

• Assigned chipping sequences:

▪ A → (-1 -1 -1 +1 +1 -1+ 1 +1)

▪ B → (-1 -1 +1 -1 +1 +1 +1 -1)

▪ C → (-1 +1 -1 +1 +1 +1 -1 -1)

▪ D → (-1 +1 -1 -1 -1 -1 +1 -1)

• Sender C sends “1”:

• Sender C sends “0”:


See Tanenbaum 2011

165

166



5. Multiplexing


• A sends “1”, B sends “1”, C sends “0”, D sends “1”

▪ A :

▪ B:

▪ C:

▪ D:


5. Multiplexing


• Receiver wants to find out the value sent by C (knowing C‘s chipping sequence):

▪ combined signal RS (-2 -2 0 -2 0 -2 +4 0)

▪ 𝑅𝑆 ∘ 𝐶 =−2 ∗−1 + −2∗+1 + 0∗−1 + −2∗+1 + 0∗+1 + −2∗+1 + +4∗−1 + 0∗−1

8

=2−2+0−2+0.2.4+0

8= −1 =„0“


167

168



5. Multiplexing

Multiplexing - Recapitulation

• Multiplexing allows the transmission of several streams (→ logical channels) over one physical channel

• Multiplexing might support

▪ synchronous communication→ fix data rate and transmission time

▪ asynchronous communication→ variable data rate and transmission time


5. Multiplexing

Multiple Access

• According to the multiplexing techniques, several multiple access procedures can be defined for shared media:

▪ Space Division Multiple Access (SDMA)

▪ Time Division Multiple Access (TDMA)

▪ Frequency Division Multiple Access (FDMA)

▪ Code Division Multiple Access (CDMA)

• Controlled access to the shared medium → avoid collisions


169

170



References

• Comer, Douglas E. (2015): Computer Networks and Internets. Sixth Edition. Boston, Columbus, Indianapolis: Pearson.

• Proakis, John G.; Salehi, Masoud (2015): Fundamentals of Communication Systems. Second Edition. Boston: Pearson.

• Seitz, Jochen; Debes, Maik (2016): Kommunikationsnetze. Eine umfassende Einführung. Anwendungen – Dienste – Protokolle. Ilmenau: Unicopy Campus Edition.

• Stallings, William (2014): Data and Computer Communications. 10th edition. Upper Saddle River, N.J.: Pearson.

• Tanenbaum, Andrew S.; Wetherall, David J. (2011): Computer Networks. 5th edition. Boston: Pearson Prentice Hall.


171

communication networksmidas1.e-technik.tu-ilmenau.de/~webkn/webdaten/lehre... · 2019-11-07 ·...

Documents