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CCN-Week-04

Computer Networks

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CCN-Week-04

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  1. Computer Communication & Networks Lecture # 04 Physical Layer: Signals & Digital Transmission Nadeem Majeed Choudhary nadeem.majeed@uettaxila.edu.pk

  2. Physical Layer Topics to Cover Signals Digital Transmission Analog Transmission Multiplexing Transmission Media

  3. Analog & Digital Data • Data can be analog or digital. The term analog data refers to information that is continuous; digital data refers to information that has discrete states. Analog data take on continuous values. Digital data take on discrete values.

  4. Note To be transmitted, data must be transformed to electromagnetic signals.

  5. Note Signals can be analog or digital. Analog signals can have an infinite number of values in a range; digital signals can have only a limited number of values.

  6. Analog Vs Digital

  7. Analog Signals

  8. Sine Wave

  9. Cont’ • Three parameters to describe a sine wave • Peak amplitude • Frequency and time period • Phase

  10. Note The bandwidth of a composite signal is the difference between the highest and the lowest frequencies contained in that signal.

  11. Bandwidth

  12. Digital Signals

  13. Digital Signals • In addition to being represented by an analog signal, information can also be represented by a digital signal. For example, a 1 can be encoded as a positive voltage and a 0 as zero voltage. A digital signal can have more than two levels. In this case, we can send more than 1 bit for each level.

  14. Digital Signal

  15. Bit Rate & Bit Interval (contd.)

  16. Bit Interval and Bit Rate Example A digital signal has a bit rate of 2000 bps. What is the duration of each bit (bit interval) Solution The bit interval is the inverse of the bit rate. Bit interval = 1/ 2000 s = 0.000500 s = 0.000500 x 106ms = 500 ms

  17. Note The bit rate and the bandwidth are proportional to each other.

  18. Analog Vs Digital

  19. Analog versus digital signals

  20. Low Pass & Band Pass

  21. Data Rate Limits

  22. Data Rate Limits • A very important consideration in data communications is how fast we can send data, in bits per second, over a channel. Data rate depends on three factors: 1. The bandwidth available 2. The level of the signals we use 3. The quality of the channel (the level of noise)

  23. Noiseless Channel: Nyquist Bit Rate • Defines theoretical maximum bit rate for Noiseless Channel: • Bit Rate=2 X Bandwidth X log2L

  24. Example Consider a noiseless channel with a bandwidth of 3000 Hz transmitting a signal with two signal levels. The maximum bit rate can be calculated as BitRate = 2  3000  log2 2 = 6000 bps

  25. Example 8 Consider the same noiseless channel, transmitting a signal with four signal levels (for each level, we send two bits). The maximum bit rate can be calculated as: Bit Rate = 2 x 3000 x log2 4 = 12,000 bps

  26. Note Increasing the levels of a signal may reduce the reliability of the system.

  27. Noisy Channel: Shannon Capacity • Defines theoretical maximum bit rate for Noisy Channel: • Capacity=Bandwidth X log2(1+SNR)

  28. Example Consider an extremely noisy channel in which the value of the signal-to-noise ratio is almost zero. In other words, the noise is so strong that the signal is faint. For this channel the capacity is calculated as C = B log2 (1 + SNR) = B log2 (1 + 0)= B log2 (1) = B  0 = 0

  29. Example We can calculate the theoretical highest bit rate of a regular telephone line. A telephone line normally has a bandwidth of 3000. The signal-to-noise ratio is usually 3162. For this channel the capacity is calculated as C = B log2 (1 + SNR) = 3000 log2 (1 + 3162) = 3000 log2 (3163) C = 3000  11.62 = 34,860 bps

  30. Example We have a channel with a 1 MHz bandwidth. The SNR for this channel is 63; what is the appropriate bit rate and signal level? Solution First, we use the Shannon formula to find our upper limit. C = B log2 (1 + SNR) = 106 log2 (1 + 63) = 106 log2 (64) = 6 Mbps Then we use the Nyquist formula to find the number of signal levels. 6 Mbps = 2  1 MHz  log2L L = 8

  31. Note The Shannon capacity gives us the upper limit; the Nyquist formula tells us how many signal levels we need.

  32. Transmission Impairments

  33. Transmission Impairments • Signals travel through transmission media, which are not perfect. The imperfection causes signal impairment. This means that the signal at the beginning of the medium is not the same as the signal at the end of the medium. What is sent is not what is received. Three causes of impairment areattenuation, distortion, andnoise.

  34. Transmission Impairments

  35. Decibel • Used to signal gained or lost strength • dB = 10 log P2/P1 (Power) • dB Voltage = 20 log (V1/V2) • dB Current = 20 log (I1/I2) The dB is not an absolute quantity, it is always a RATIO of two quantities.  The unit can be used to express power gain (P2>P1), or power loss (P2<P1) -- in the latter case the result will be a negative number.

  36. Example • Suppose a signal travels through transmission medium and its power is reduced to one half…. Calculate attenuation loss?

  37. attenuation distortion noise Signal Distortion

  38. Performance • One important issue in networking is the performance of the network—how good is it?

  39. Performance • Bandwidth • Throughput • Latency (Delay) • Bandwidth-Delay Product

  40. Throughput

  41. Latency • Latency = propagation time + transmission time + queuing time + processing time

  42. Propagation Time

  43. Note The bandwidth-delay product defines the number of bits that can fill the link.

  44. Physical Layer Topics to Cover Signals Digital Transmission Analog Transmission Multiplexing Transmission Media

  45. Analog To Digital Conversion

  46. SamplingPulse Code ModulationSampling Rate: Nyquist Theorem

  47. PCM

  48. Quantization & Encoding Samples

  49. Note According to the Nyquist theorem, the sampling rate must be at least 2 times the highest frequency contained in the signal.

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