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Data and Computer Communications

Data and Computer Communications. Data Transmission. Transmission Terminology. Data transmission occurs between a transmitter & receiver via some medium Guided medium eg. twisted pair, coaxial cable, optical fiber Unguided / wireless medium eg. air, water, vacuum. Transmission Terminology.

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Data and Computer Communications

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  1. Data and Computer Communications Data Transmission

  2. TransmissionTerminology • Data transmission occurs between a transmitter & receiver via some medium • Guided medium • eg. twisted pair, coaxial cable, optical fiber • Unguided / wireless medium • eg. air, water, vacuum

  3. TransmissionTerminology • Direct link • no intermediate devices • Point-to-point • direct link • only 2 devices share link • Multi-point • more than two devices share the link

  4. TransmissionTerminology • Simplex • one direction • eg. television • Half duplex • either direction, but only one way at a time • eg. police radio • Full duplex • both directions at the same time • eg. telephone

  5. Frequency, Spectrum and Bandwidth • Time domain concepts • Analog signal • Varies in a smooth way over time • Digital signal • Maintains a constant level then changes to another constant level • Periodic signal • Pattern repeated over time • Aperiodic signal • Pattern not repeated over time

  6. Analogue & Digital Signals

  7. PeriodicSignals

  8. Sine Wave • Peak amplitude (A) • Maximum strength of signal • Volts • Frequency (f) • Rate of change of signal • Hertz (Hz) or cycles per second • Period = time for one repetition (T) • T = 1/f • Phase () • Relative position in time

  9. Varying Sine Wavess(t) = A sin(2ft +)

  10. Wavelength () • is distance occupied by one cycle • between two points of corresponding phase in two consecutive cycles • assuming signal velocity v have  = vT • or equivalently f = v • especially when v=c • c = 3*108 ms-1 (speed of light in free space)

  11. Frequency Domain Concepts • Signals are made up of many frequencies • Components are sine waves • Fourier analysis can show that any signal is made up of component sine waves • Can plot frequency domain functions

  12. Addition of FrequencyComponents(T=1/f) • c is sum of f & 3f p p p p p

  13. FrequencyDomainRepresentations • Freq. domain func. of Fig 3.4c • Freq. domain func. of single square pulse p p p < <

  14. Spectrum & Bandwidth • Spectrum • Range of frequencies contained in signal • Absolute bandwidth • Width of spectrum • Effective bandwidth • Often just bandwidth • Narrow band of frequencies containing most energy • DC Component • Component of zero frequency

  15. Figure 3.7 (a) & (b)

  16. Bit time = T / 2

  17. Data Rate and Bandwidth • Any transmission system has a limited band of frequencies • This limits the data rate that can be carried • Square have infinite components and hence bandwidth • But most energy in first few components • Limited bandwidth increases distortion • Have a direct relationship between data rate & bandwidth

  18. Data Rate Calculation • Case 1 • Bandwidth 4MHz,use the sine wave ofFig. 3-7 (a) • 4MHz = 5f – f  f = 1MHz, • the period of fundamental frequency 1/f = 10-6 = 1us. One wave takes two data bits • Data rate = 2 Mbps • Case 2 • Bandwidth 8MHz,use the sine wave ofFig. 3-7 (a) • 8MHz = 5f – f  f = 2MHz • Data rate = 4 Mbps • Case 3 • Bandwidth 4MHz,use the sine wave ofFig. 3-4 (c) • 4MHz = 3f – f  f = 2MHz Data rate = 4 Mbps

  19. Data Rate vs. Bandwidth • Bandwidth ↑ • Data rate ↑ (compare case 1 & 2) • Same signal quality • Same bandwidth • Higher signal quality  lower data rate • Compare case 1 & 3 • Same data rate • Bandwidth ↑ better signal quality • Compare case 2 & 3

  20. Analog and Digital Data Transmission • Data • Entities that convey meaning • Signals & signaling • Electric or electromagnetic representations of data, physically propagates along medium • Transmission • Communication of data by propagation and processing of signals

  21. Acoustic Spectrum (Analog)

  22. Audio Signals • Freq. range 20Hz-20kHz (speech 100Hz-7kHz) • Easily converted into electromagnetic signals • Varying volume converted to varying voltage • Can limit frequency range for voice channel to 300-3400Hz

  23. Video Signals • USA - 483 lines per frame, at frames per sec • have 525 lines but 42 lost during vertical retrace • 525 lines x 30 scans = 15750 lines per sec • 63.5s per line • 11s for retrace, so 52.5 s per video line • Max frequency if line alternates black and white • 70% of 483 is subjective resolution – 338. • 4/3 ratio – 450 lines • Horizontal resolution is about 450 lines giving 225 cycles of wave in 52.5 s • Max frequency of 4.2MHz

  24. Digital Data • As generated by computers etc. • Has two dc components • Bandwidth depends on data rate

  25. Analog Signals

  26. Digital Signals

  27. Advantages & Disadvantages of Digital Signals • Cheaper • Less susceptible to noise • But greater attenuation • Digital now preferred choice

  28. Transmission Impairments • Signal received may differ from signal transmitted causing: • Analog - degradation of signal quality • Digital - bit errors • Most significant impairments are • Attenuation and attenuation distortion • Delay distortion • Noise

  29. Attenuation • Where signal strength falls off with distance • Depends on medium • Received signal strength must be: • Strong enough to be detected • Sufficiently higher than noise to receive without error • So increase strength using amplifiers/repeaters • Is also an increasing function of frequency • So equalize attenuation across band of frequencies used • E.g. using loading coils or amplifiers • N_f = -10 log_10(P_f/P_1000)

  30. Delay Distortion • Only occurs in guided media • Propagation velocity varies with frequency • Hence various frequency components arrive at different times • Particularly critical for digital data • Since parts of one bit spill over into others • Causing inter-symbol interference

  31. Noise • additional signals inserted between transmitter and receiver • thermal • due to thermal agitation of electrons • uniformly distributed over frequency • white noise N= kTB, k = Boltzman’s constant (1.38*10^-21), T – temperature, B - Bandwidth In decibel watts – take log • intermodulation • signals that are the sum and difference of original frequencies sharing a medium

  32. Noise • Given a receiver with an effective noise temperature of 294K and a 10-MHz bandwidth, the thermal noise level at the receiver output is N = 228.6 + 10log(294) + 10log(107) • intermodulation • signals that are the sum and difference of original frequencies sharing a medium

  33. EXAMPLE 3.1 Room temperature is usually specified as T = 17°C, or 290 K. At this temperature, the thermal noise power density is N0 = (1.38 * 10-23) * 290 = 4 * 10-21 W/Hz = - 204 dBW/Hz where dBW is the decibel-watt, defined in Appendix 3A.

  34. EXAMPLE 3.2 Given a receiver with an effective noise temperature of 294 K • and a 10-MHz bandwidth, the thermal noise level at the receiver’s output is • N = - 228.6 dBW + 10 log(294) + 10 log 107 • = - 228.6 + 24.7 + 70 • = - 133.9 dBW

  35. Noise • 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 • A minor annoyance for analog signals • But a major source of error in digital data • A noise spike could corrupt many bits

  36. Channel Capacity • Max possible data rate on comms channel • Is a function of • Data rate - in bits per second • Bandwidth - in cycles per second or Hertz • Noise - on comms link • Error rate - of corrupted bits • Limitations due to physical properties • Want most efficient use of capacity

  37. Nyquist Bandwidth • Consider noise free channels • If rate of signal transmission is 2B then can carry signal with frequencies no greater than B • i.e. given bandwidth B, highest signal rate is 2B • For binary signals, 2B bps needs bandwidth B Hz • Can increase rate by using M signal levels • Nyquist Formula is: C = 2B log2M • So increase rate by increasing signals • At cost of receiver complexity • Limited by noise & other impairments

  38. EXAMPLE 3.3 Consider a voice channel being used, via modem, to transmit digital data. Assume a bandwidth of 3100 Hz. Then the Nyquist capacity, C, of the channel is 2B = 6200 bps. For M = 8, a value used with some modems, C becomes 18,600 bps for a bandwidth of 3100 Hz.

  39. Shannon Capacity Formula • Consider relation of data rate, noise & error rate • Faster data rate shortens each bit so bursts of noise affect more bits • Given noise level, higher rates mean higher errors • Shannon developed formula relating these to signal to noise ratio (in decibels) • SNRdb=10 log10 (signal/noise) • Capacity C=B log2(1+SNR) • Theoretical maximumcapacity • Gets lower in practice

  40. Problem Suppose the spectrum is between 3Mhz and 4 MHz and SNR_DB = 24. Calculate channel capacity using Shannon and Nyquist.

  41. B = 4 MHz - 3 MHz = 1 MHz • SNRdB = 24 dB = 10 log10SNR • SNR = 251 • Using Shannon’s formula, • C = 106 * log2(1 + 251) = 106 * 8 = 8 Mbps • This is a theoretical limit and, as we have said, is unlikely to be reached. But assume we can achieve the limit. Based on Nyquist’s formula, how many signal- ing levels are required? We have • C = 2B log2 M • 8 * 106 = 2 * (10^6)* log2 M • 4 = log2 M • M = 16

  42. Summary • Looked at data transmission issues • Frequency, spectrum & bandwidth • Analog vs digital signals • Transmission impairments

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