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Lecture 7: Noise in Communication Systems

This lecture covers various types of noise, such as additive white Gaussian noise (AWGN) and signal-to-noise ratio (SNR), along with examples and modulation techniques.

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Lecture 7: Noise in Communication Systems

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  1. Lecture 7: Noise to ASK, FSK and PSK 2ndsemester 1438-1439

  2. Outline - Several types of noise. - Additive white Gaussian noise (AWGN). - Signal to noise ratio (SNR).

  3. Noise • As signal is transmitted through a channel, undesired signal in the form of noise gets mixed up with the signal, along with the distortion introduced by the transmission media. • Noise is any unwanted energy tending to interfere with the signal to be transmitted.

  4. Noise The noise either be: • External Noise: This is noise originating from outside the communication system • Internal Noise: This is noise originating from within the communication system.

  5. Some Examples of Noise • Thermal Noise: This noise is due to the random and rapid movement of electrons in any resistive component. Electrons “bump” with each other. • Impulse noise: is irregular pulses or noise spikes of short duration

  6. Some Examples of Noise • Cross talk is a result of bunching several conductors together in a single cable. Signal carrying wires generate electromagnetic radiation, which is induced on other conductors because of close proximity of the conductors.

  7. Signal-to-Noise Ratio • In the study of noise, it is not important to know the absolute value of noise. • Even if the power of the noise is very small, it may have a significant effect if the power of the signal is also small. • What is important is a comparison between noise and the signal. • The signal-to-noise ratio (SNR) is the ratio of signal power to noise power.

  8. Signal-to-Noise Ratio SNR = Ps / Pn

  9. Signal-to-Noise Ratio • Ideally, SNR = ∞ (when Pn= 0). In practice, SNR should be high as possible. • A high SNR ratio means a good-quality signal. • A low SNR ratio means a low-quality signal. • The SNR is normally expressed in decibels, that is: SNR = 10 log10 (Ps / Pn) dB

  10. Figure 3.30 Two cases of SNR: a high SNR and a low SNR

  11. Example • The power of a signal is 10 mW and the power of the noise is 1 μW; what are the values of SNR and SNRdB SNR = 10 × 10-3 / 10-6 = 10,000 SNRdB = 10 log10 (10 × 10-3 / 10-6) = 10 log10 (10,000) = 40 dB

  12. Additive White Gaussian Noise (AWGN) - Additive white Gaussian noise (AWGN): Is a basic noise model used in Information theory to mimic the effect of many random processes that occur in nature.

  13. OOK Modulator with noise Apply a OOK for a random digital signal using the following carrier 3 sin (70πt) , SNRdb = 5 2 sin (2π20t), SNRdb = 10 4 sin (50πt), SNRdb = 15

  14. SNR =10 SNR =20

  15. FSK Modulator with noise Implement a BFSK modulation that use the following carriers: 1- fc1 = 2π40 and fc2 = 2π10 SNRdb = 10 2- fc1 = 100π and fc2 = 50π , SNRdb = 20 3- fc1 = 90π and fc2 = 30π SNRdb = 25

  16. SNR =10 SNR = 25

  17. PSK Modulator Implement a BPSK modulation that use the following carriers: 1- f = 2π7 Hz SNRdb = 10 2- f = 2π4 Hz SNRdb = 23 3- f = 2π 5 Hz SNRdb = 18

  18. SNR =5 SNR =20

  19. Any Questions ?

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