fundamentals of telecommunication ict- bvf- 4.1 hassan mesfer ict-te-7

Fundamentals of Telecommunication

ICT- BVF- 4.1

Hassan Mesfer ICT-TE-7

Fundamentals of Telecommunication

ICT- BVF- 4.1

Hassan Mesfer ICT-TE-7

20/04/23 1TTC Riyadh, ICT–BVF–4.1

Lecture 2

Signal Transmission


Transmission Terminology (1)

• Transmitter• Generates message signal to be transmitted

• Receiver• Converts received signal into a form that can be handled by the

destination device.

• Medium• Guided medium• e.g. twisted pair, optical fiber

• Unguided medium• e.g. air, water, vacuum



• Direct link• No intermediate devices (other than: amplifiers or repeaters)

• Point-to-point• Direct link • Only two devices share link

• Multi-point• More than two devices share the link



• Simplex or unidirectional transmission– Signals are transmitte only in one direction

• e.g. television, radiobroadcasting

• Half duplex transmission• Either direction, but only one way at a time

• e.g. police radio

• Full duplex transmission– Both directions at the same time

• e.g. telephone


• Means by which data are propagated

• Physical representation of data

• Time domain concepts– Viewed as function of time, an electromagnetic signal can be

analog or digital– Analog signal

• Signal intensity various in a smooth way over time

– Digital signal• Signal intensity maintains a constant level then changes to another

constant level

– Periodic signal• Pattern repeated over time

• The simplest type of signal (sinusoidal form is fundamental )

– Aperiodic signal• Pattern not repeated over time

Signals


Analog & Digital Signals


Periodic Signals


Sine WaveThe general sine wave can be written:

s(t) = A sin(2ft +)

Can be represented by three parameters:

• Peak Amplitude (A)– maximum strength of signal– volts

• Frequency (f)– Rate of change of signal or repeats– Hertz (Hz) or cycles per second– Period T = time for one repetition– T = 1/f

• Phase ()– Relative position in time


Varying Sine Waves

Wavelength

• Distance occupied by one cycle

• Distance between two points of corresponding phase in

two consecutive cycles

• Assuming signal velocity v = vT f = v

– c = 3*108 ms-1 (speed of light in free space)


Frequency Domain Concepts

• Signal usually made up of many frequencies

• Components are sine waves

• Can be shown (Fourier analysis) that any signal is made

up of component sine waves

• Can plot frequency domain functions

• For periodic signals – Fourier series

• For aperiodic signals – Fourier transform


Fourier representation of periodic signals

1

0

1

0

t tPeriodic signal Component sine waves -

harmonics

f ta

a n f t b n f tn nn

( ) cos sin

00 0

122 2


Fourier series:

aT

f t n f t dtnT

T

22

0 2

2

0

0

0

/

/

cos

bT

f t n f t dtn

T

T

22

00

2

2

0

sin/

/

, n = 0,1,2, ...

an, bn are Fourier coefficients

, n = 1,2, ...

Fourier representation of periodic signals


n

tfnjn

n

tfnjnn eFejba

atf 00 220

2

1

2

f ta

C n tn nn

00

12cos C a b arctg

b

an n n nn

n

2 2 ;

Adding sinusoidal and cosinusoidal components f of the same frequencies from the previous Fourier expression, furier series can be also written in this form:

;

F a jbn n n 1

2

Fourier series can also be expressed in the following form, known as Complex form:

; n=0,1,2, . . .

Fn - are fourier coefficients, which are complex quantities. as such Fn can be writen in the polar coordinate as

F F en nj n

Fn - is called amplitude spectrum, and it is an even function of frequency

- is called phase spectrum, and it is an odd function of frequency

Fn - is called spectrum of signal f(t)

Addition of FrequencyComponents(T=1/f)

Fourier representation of aperiodic signals


Fourier Transform Pair

Fourier Transform:

- S(f) is a continuous function of frequency f and it is called the spectrum of the signal s(t)

- S(f) is a complex function , so we can write S(f) in the polar coordinate as:

S(f) =

|S(f)| – is called amplitude spectrum density

– is called phase spectrum density

- Is an even function

arg S(-f) = - arg S(f) - is an odd function

Frequency DomainRepresentations

Periodic signal in time domain – In frequency domain is discrete

Aperiodic signal in time domain – In frequency domain is continuous


Signal with DC Component

• Communication system as a „black box“ with an external Input signal x(t) and Output signal y(t)

Black box

x(t) y(t)

• System usually would be a two-port network driven by Applied voltage or current x(t) at the input port Producing another voltage or current y(t) at the output port

• Output waveforms y(t) may look quite different from input Caused by energy storage elements and other internal effects

• Regardless of what’s in the box System is characterized by relationship between input and output

s

System Transfer Function (1)


H(f) is a complex function, it can be written as:


• |H(f)| - is called amplitude response of the system Shows the impact of the system on aplitudes (gain or attenuation) of the input signal. H(f) is an even function, i.e. |H(-f)| = |H(f)|

• Ɵ(f) or arg H(f) – is calle phase response of the system Represents the impact of the system on phase (delay) of each component of the signal Ɵ(f) is an odd function, i.e. Ɵ(-f) = - Ɵ(f)

)()()( fjefHfH


• Now let x(t) be any signal with spectrum X(f), applied at the input of the system with a transfer function H(f)

x(t) y(t)

X(f) Y(f)

• The spectrum Y(f) of the output signal y(t) will be:

Y(f) = H(f)X(f) . . . . . . (1)

• The output spectrum Y(f) equals the input spectrum X(f) multiplied by the transfer function H(f).

• The corresponding amplitude and phase spectra of the output signal y(t) are:

|Y(f)| = |H(f)||X(f)| ; arg Y(f) = arg H(f) + arg X(f)


H(f)


Spectrum & Bandwidth

• Spectrum– Range of frequencies contained in signal (f to 3f, previous

example)

• Absolute bandwidth– Width of spectrum (3f – f = 2f, previous example periodic signal)– Aperiodic signals have infinite bandwidth

• Effective bandwidth– Narrow band of frequencies containing most of the energy– Often just bandwidth

• DC or constant component – Component of zero frequency– No DC component, average amplitude of the signal is zero


Analog and Digital Data

• Data, messages – Entities that convey meaning

• Analog data– Continuous values within some interval

• e.g. sound (speech, music), video

– Frequency range (of hearing) 20Hz-20kHz– Speech bandwidth 100Hz to 7kHz– Telephone bandwidth (voice channel) 300Hz to 3400Hz– Video bandwidth 4MHz

• Digital data– Discrete values, taken from a certain set (alphabet, numerical

system)– e.g. text, integers


Acoustic Spectrum


Data and Signals

• Digital signals for digital data (baseband transmission)

• Analog signals for analog data (baseband and bandpass

transmission)

• Can use analog signal to carry digital data

– Modem (modulation demodulation)

• Can use digital signal to carry analog data

– Compact Disc audio


Conversion of Voice Input into Analog Signal

Sound frequencies with varying volume converted into electromagnetic frequencies with varying voltage


Conversion of PC Input into Digital Signal

• Binary digital data from computer terminals• Two dc components• Bandwidth depends on data rate


Analog Signals Carrying Analog and Digital Data


Digital Signals Carrying Analog and Digital Data


Analog Transmission

• Analog signal transmitted without regard to content

• May be analog data (e.g. voice) or digital data (e.g. binary)

• Attenuated over distance

• Use amplifiers to boost signal for longer distances

• Also amplifies noise (accumulative feature)

• With amplifiers cascaded, longer distance, more distorted

• For analog data (e.g. voice) a bit distortion is tolerated

• For digital data, cascade amplifiers introduce errors


Digital Transmission

• Concerned with content (1 or 0)

• Transmission only over a limited distance

• Integrity destroyed by noise, attenuation etc.

• For greater distance repeaters used

• Repeater receives signal– Extracts bit pattern

– Retransmits (regenerates pulses)

– Attenuation is overcome

– Noise is not amplified

• The same technique may be used for – Analog signals carrying digital data

– Repeater recovers digital data from analog signal

– Generates new clean analog signal

– Noise is not cumulative


Advantages of Digital Transmission

• Which is the preferred technology of transmission?

• Answer of telecommunication industry and customers – Digital

• The most important reasons:– Digital technology

• Low cost LSI/VLSI technology

– Data integrity• Longer distances over lower quality lines

– Capacity utilization• High bandwidth links economical• High degree of multiplexing easier with digital techniques

– Security & Privacy• Encryption

• Integration– Can treat analog and digital data similarly


Disadvantages of Digital Transmission

• Digital signals need infinite frequencies for perfect transmission

• Greater attenuation– Pulses become rounded and smaller– Leads to loss of information

Attenuation of Digital Signals


Transmission Impairments (1)

• Signal received may differ from signal transmitted

• Analog – degradation (signal shape) of signal quality

• Digital - bit errors

• Caused by– Attenuation and attenuation distortion– Delay distortion– Noise


Attenuation:

• Signal strength falls off with distance

• Depends on medium

• Received signal strength:– must be enough to be detected– must be sufficiently higher than noise to be received without

error

• Attenuation is an increasing function of frequency

Delay Distortion

• Only in guided media

• Propagation velocity varies with frequency

Transmission Impairments (2)


Noise (1)

• Additional signals inserted between transmitter and receiver

• Divideds into four categories:– Thermal; Intermodulation; Crosstalk; Impulse

• Thermal– Due to thermal agitation of electrons

– Uniformly distributed

– White noise

• Intermodulation– Signals that are the sum and difference of original

frequencies sharing a medium


Noise (2)

• Crosstalk– A signal from one line is picked up by another

• Impulse– Irregular pulses or spikes

– e.g. External electromagnetic interference

– Short duration

– High amplitude


Noise (3)

• Amount of thermal noise in a bandwidth of 1 Hz in any device or conductor is:

N0 = KT (W/Hz)

N0 - noise power density in watts per 1 Hz bandwidth

k - Boltzmann‘s constant - 1.38 x 10-23 J/K

T – temperature, in kelvins (absolute temperature)

Find N0 assuming room temperature T = 17 0 C

Result: N = -204 dBW/Hz


Noise (4)

• Thermal noise is assumed to be independent of frequency – white noise

• Thermal noise in a bandwidth of B can be expressed asN = kTB

or in decibel-watts

N = 10logk + 10logT + 10logB

= -228,6 dBW + 10logT + 10logB

k - Boltzmann‘s constant 0 1.38 x 10-23 J/K

T – temperature, in kelvins (absolute temperature)

Example: Given an receiver with noise temperature of 294 K and a 10 MHz bandwidth, find thermal noise at receiver‘s output

Result: N = -133,9 dBW


Channel Capacity

Four concepts related to one another:

• Data rate– In bits per second– Rate at which data can be transmitted

• Bandwidth of the signal– In cycles per second or Hertz– Depends on the type of the signal– Constrained by the transmitter and nature of the transmission

medium

• Noise– Average level of noise over the communication path

• Error rate– Rate at which errors occur– Reception of 1 when 0 is transmitted and vice versa


Data Rate and Bandwidth• Any transmission system has a limited band of frequencies

• This limits the data rate that can be carried

Example:

• Consider the waveform of the binary stream 01010…

• Positive pulse represent binary 0, negative pulse binary 1

• Duration of each pulse is 1/(2f), data rate is 2f bits/s

• What are the important frequency components of this signal?

Data Rate andBandwidth

• To answer the questioin consider this figure:

Nyquist Bandwidth (1)

• Channel noise free

• Given bandwidth B, highest signal rate is 2B

• Given binary signal, data rate supported by B Hz is 2B bit/s

• Doubling the bandwidth doubles the data rate

• Data rate can be increased by using M signal levels

C = 2B log2M


Nyquist Bandwidth (2)

Example: Voice channel is used to transmit digital data

• What is the capacity C of the channel?

• Solution: Assume a bandwidth of 3100 Hz and binary signal

• C = 2B = 6200 bit/s

• If we use signal with 8 voltage levels, what will be the capacity C ?

• Result: 18.600 bit/s


Shannon Capacity Formula (1)• Consider the relationship among data rate, noise and error rate

• Faster data rate shortens each bit so burst of noise affects more bits– At given noise level, high data rate means higher error rate

• The key parameter is signal to noise ratio S/N or SNR (in decibels)

• SNRdb=10 log10 (signal power/noise power)– Amount in decibels intended signal exceeds noise level

– High S/N means high-quality signal, less intermediate repeaters

– Very important in digital transmission, upper limit bound for data rate

• Shannon’s result: theoretical maximum channel capacity

C = B log2(1+SNR)

• This is error free capacity


Shannon Capacity Formula (2)Example: Nyquist and Shannon capacity

• Bandwidth of a channel is between 3 MHz and 4 MHz and S/N = 24 dB. What is channel capacity?

Solution:

B = 4 MHz - 3 MHz = 1 MHz

S/N = 24 dB = 10 log10 (S/N)

S/N = 251

Using Shannon’s formula:

C = B log2(1+SNR) = 106 x log2(1+251) = 106 x 8 = 8 Mbit/s

Based on Nyquist’s formula, how many signal levels are required?

C = 2B log2M = 8 x 106 = 2 x 106 x log2M

log2M = 4 > M = 16


• Timing problems require a mechanism to synchronize the

transmitter and receiver

• Two solutions– Asynchronous

– Synchronous

Asynchronous and Synchronous Transmission


• Data transmitted one character at a time– 5 to 8 bits

• Timing only needs maintaining within each character

• Resynchronize with each character

Asynchronous Transmission (1)


• Interval between characters is not uniform (length of stop

element)

• In idle state, receiver looks for transition 1 to 0

• Then samples next seven intervals (char length)

• Then looks for next 1 to 0 for next character

• Simple

• Cheap

• Overhead of 2 or 3 bits per char (~20%)

• Good for data with large gaps (keyboard)



Bit Level

• Block of data transmitted without start or stop bits

• Clocks must be synchronized

• Can use separate clock line between transmitter and receiver– Transmitter or receiver pulses the line regularly with one short

pulse per bit time– Good over short distances– Subject to impairments

• Embed clock signal in data– Manchester encoding– Carrier frequency (analog)

Synchronous Transmission (1)


Block Level

• Need to indicate start and end of block

• Use preamble and postamble– e.g. series of SYN (hex 16) characters– e.g. block of 11111111 patterns ending in 11111110

• More efficient (lower overhead) than async


A typical frame format for synchronous transmission


• For sizable blocks of data synchronous transmission is far more

efficient than asynchronous

• Control, information, preamble, postamble are typically less

than 100 bits

• Asynchronous transmission requires 20% or more overhead



fundamentals of telecommunication ict- bvf- 4.1 hassan mesfer ict-te-7

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