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Fundamentals of Telecommunication ICT- BVF- 4.1 Hassan Mesfer ICT-TE-7

Fundamentals of Telecommunication ICT- BVF- 4.1 Hassan Mesfer ICT-TE-7. TTC Riyadh, ICT–BVF–4.1. 04/10/2014. 1. Lecture 2. Signal Transmission. TTC Riyadh, ICT–BVF–4.1. 04/10/2014. 2. Transmission Terminology (1). Transmitter Generates message signal to be transmitted Receiver

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Fundamentals of Telecommunication ICT- BVF- 4.1 Hassan Mesfer ICT-TE-7

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  1. Fundamentals of Telecommunication • ICT- BVF- 4.1 • Hassan Mesfer ICT-TE-7 TTC Riyadh, ICT–BVF–4.1 04/10/2014 1

  2. Lecture 2 Signal Transmission TTC Riyadh, ICT–BVF–4.1 04/10/2014 2

  3. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 3

  4. Transmission Terminology (2) • 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 4

  5. Transmission Terminology (3) TTC Riyadh, ICT–BVF–4.1 04/10/2014 5

  6. Transmission Terminology (4) • 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 6

  7. Transmission Terminology (5) TTC Riyadh, ICT–BVF–4.1 04/10/2014 7

  8. Signals • 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 8

  9. Analog & Digital Signals TTC Riyadh, ICT–BVF–4.1 04/10/2014 9

  10. Periodic Signals TTC Riyadh, ICT–BVF–4.1 04/10/2014 10

  11. Sine Wave The general sine wave can be written: s(t) = A sin(2ft +) 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 11

  12. Varying Sine Waves

  13. 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) TTC Riyadh, ICT–BVF–4.1 04/10/2014 13

  14. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 14

  15. Fourier representation of periodic signals Fourier series: an, bn are Fourier coefficients , n = 0,1,2, ... , n = 1,2, ... 1 1 0 0 t t Periodic signal Component sine waves - harmonics TTC Riyadh, ICT–BVF–4.1 04/10/2014 15

  16. Fourier representation of periodic signals Adding sinusoidal and cosinusoidal components f of the same frequencies from the previous Fourier expression, furier series can be also written in this form: ; 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 Fn - is called spectrum of signal f(t) - is called amplitude spectrum, and it is an even function of frequency  - is called phase spectrum, and it is an odd function of frequency TTC Riyadh, ICT–BVF–4.1 04/10/2014 16

  17. Addition of FrequencyComponents(T=1/f)

  18. Fourier representation of aperiodic signals Fourier Transform: Fourier Transform Pair • - 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 18

  19. Frequency DomainRepresentations Periodic signal in time domain – In frequency domain is discrete Aperiodic signal in time domain – In frequency domain is continuous TTC Riyadh, ICT–BVF–4.1 04/10/2014 19

  20. Signal with DC Component

  21. System Transfer Function (1) • Communication systemas a „black box“ with an external • Input signal x(t) and • Output signal y(t) • Black box • x(t) y(t) • System usuallywouldbe a two-portnetworkdrivenby • Applied voltageorcurrent x(t) attheinputport • Producinganothervoltageorcurrent y(t) attheoutputport • Output waveforms y(t) maylookquite different frominput • Causedbyenergystorageelementsandotherinternaleffects • Regardlessofwhat’s in the box • System ischaracterizedbyrelationshipbetweeninputandoutput s TTC Riyadh, ICT–BVF–4.1 04/10/2014 21

  22. System Transfer Function (2) H(f) is a complexfunction, itcanbewrittenas: • |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) TTC Riyadh, ICT–BVF–4.1 04/10/2014 22

  23. System Transfer Function (3) • Nowlet x(t) beanysignalwithspectrum X(f), appliedattheinputofthesystemwith a transferfunction H(f) x(t) y(t) X(f) Y(f) • The spectrum Y(f) oftheoutputsignal y(t) will be: Y(f) = H(f)X(f). . . . . . (1) • The outputspectrum Y(f) equalstheinputspectrum X(f) multipliedbythetransferfunction H(f). • The correspondingamplitudeandphasespectraoftheoutputsignal y(t) are: |Y(f)| = |H(f)||X(f)| ; arg Y(f) = arg H(f) + arg X(f) H(f) TTC Riyadh, ICT–BVF–4.1 04/10/2014 23

  24. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 24

  25. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 25

  26. Acoustic Spectrum TTC Riyadh, ICT–BVF–4.1 04/10/2014 26

  27. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 27

  28. Conversion of Voice Input into Analog Signal Sound frequencies with varying volume converted into electromagnetic frequencies with varying voltage TTC Riyadh, ICT–BVF–4.1 04/10/2014 28

  29. Conversion of PC Input into Digital Signal • Binary digital data from computer terminals • Two dc components • Bandwidth depends on data rate TTC Riyadh, ICT–BVF–4.1 04/10/2014 29

  30. Analog Signals Carrying Analog and Digital Data TTC Riyadh, ICT–BVF–4.1 04/10/2014 30

  31. Digital Signals Carrying Analog and Digital Data TTC Riyadh, ICT–BVF–4.1 04/10/2014 31

  32. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 32

  33. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 33

  34. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 34

  35. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 35

  36. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 36

  37. Transmission Impairments (2) 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 37

  38. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 38

  39. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 39

  40. 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‘sconstant - 1.38 x 10-23 J/K T – temperature, in kelvins (absolute temperature) Find N0assumingroomtemperature T = 17 0 C Result: N = -204 dBW/Hz TTC Riyadh, ICT–BVF–4.1 04/10/2014 40

  41. Noise (4) • Thermal noise is assumed to be independent of frequency – white noise • Thermal noise in a bandwidth of B can be expressed as N = kTB or in decibel-watts N = 10logk + 10logT + 10logB = -228,6 dBW + 10logT + 10logB k - Boltzmann‘sconstant 0 1.38 x 10-23 J/K T – temperature, in kelvins (absolute temperature) Example: Given an receiverwithnoisetemperatureof 294 K and a 10 MHz bandwidth, find thermal noiseatreceiver‘soutput Result: N = -133,9 dBW TTC Riyadh, ICT–BVF–4.1 04/10/2014 41

  42. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 42

  43. 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?

  44. Data Rate andBandwidth • To answer the questioin consider this figure:

  45. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 45

  46. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 46

  47. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 47

  48. 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 TTC Riyadh, ICT–BVF–4.1 04/10/2014 48

  49. Asynchronous and Synchronous Transmission • Timing problems require a mechanism to synchronize the transmitter and receiver • Two solutions • Asynchronous • Synchronous TTC Riyadh, ICT–BVF–4.1 04/10/2014 49

  50. Asynchronous Transmission (1) • Data transmitted one character at a time • 5 to 8 bits • Timing only needs maintaining within each character • Resynchronize with each character TTC Riyadh, ICT–BVF–4.1 04/10/2014 50

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