Chapter 3. Effect of Noise on Analog Communication Systems

1. Chapter 3. Effect of Noise on Analog Communication Systems Essentials of Communication Systems Engineering

2. Sources of noise • External • Atmospheric • Industrial • Extraterrestrial • Solar noise • Cosmic noise • Internal

3. Atmospheric • Atmospheric noise also known as static • It is caused by naturally occurring disturbances in the earth’s atmosphere SOURCES • lightening discharges, • thunderstorms and other natural electric disturbances.

4. Nature and Form • It comes in the form of amplitude modulated impulses. • Such impulse processes are random and spread over the whole of the RF spectrum used for broadcasting. • It consists of spurious radio signals with many frequency components.

5. It is propagated in the same way as ordinary radio waves of the same frequency. • Any radio station will therefore receive static from thunderstorms both local and distant. • It affects radio more than it affects television. The reason, field strength is inversely proportional to frequency.

6. At 30MHz and above atmospheric noise is less severe for two reasons: • Higher frequencies are limited to line of sight propagation • Very little of this noise is generated in the VHF range and above.

7. Industrial • Noise made by man easily outstrips any other between the frequencies of 1 to 600 MHz. • This includes such things as car and aircraft ignition, electric motors, switching equipment, leakage from high voltage lines etc.

8. Extraterrestrial Solar noise • This is the noise that originates from the sun. • The sun radiates a broad spectrum of frequencies, including those, which are used for broadcasting.

9. The sun is an active star and is constantly changing • It undergoes cycles of peak activity from which electrical disturbances erupt. • The cycle is about 11 years long.

10. Cosmic noise • Distant stars also radiate noise in much the same way as the sun. • The noise received from them is called black body noise. • Noise also comes from distant galaxies in much the same way as they come from the milky way.

11. Extraterrestrial noise is observable at frequencies in the range from about 8MHz to 1.43GHz. Apart from man made noise it is strongest component over the range of 20 to 120MHz. Not much of it below 20MHz penetrates below the ionosphere

12. Internal Noise This is the noise generated by any of the active or passive devices found in the receiver. This type of noise is random and difficult to treat on an individual basis but can be described statistically. Random noise power is proportional to the bandwidth over which it is measured.

13. Noise is a general term which is used to describe an unwanted signal which affects a wanted signal. These unwanted signals arise from a variety of sources which may be considered in one of two main categories:- • Interference, usually from a human source (man made) • Naturally occurring random noise Interference Interference arises for example, from other communication systems (cross talk), 50 Hz supplies (hum) and harmonics, switched mode power supplies, thyristor circuits, ignition (car spark plugs) motors … etc. 1. Introduction

14. Natural Noise Naturally occurring external noise sources include atmosphere disturbance (e.g. electric storms, lighting, ionospheric effect etc), so called ‘Sky Noise’ or Cosmic noise which includes noise from galaxy, solar noise and ‘hot spot’ due to oxygen and water vapour resonance in the earth’s atmosphere. 1. Introduction (Cont’d)

15. This type of noise is generated by all resistances (e.g. a resistor, semiconductor, the resistance of a resonant circuit, i.e. the real part of the impedance, cable etc). 2. Thermal Noise (Johnson Noise) Experimental results (by Johnson) and theoretical studies (by Nyquist) give the mean square noise voltage as Where k = Boltzmann’s constant = 1.38 x 10-23 Joules per K T = absolute temperature B = bandwidth noise measured in (Hz) R = resistance (ohms)

16. The law relating noise power, N, to the temperature and bandwidth is N = k TB watts Thermal noise is often referred to as ‘white noise’ because it has a uniform ‘spectral density’. 2. Thermal Noise (Johnson Noise) (Cont’d)

17. Shot noise was originally used to describe noise due to random fluctuations in electron emission from cathodes in vacuum tubes (called shot noise by analogy with lead shot). • Shot noise also occurs in semiconductors due to the liberation of charge carriers. • For pn junctions the mean square shot noise current is Where is the direct current as the pn junction (amps) is the reverse saturation current (amps) is the electron charge = 1.6 x 10-19 coulombs B is the effective noise bandwidth (Hz) • Shot noise is found to have a uniform spectral density as for thermal noise 3. Shot Noise

18. Active devices, integrated circuit, diodes, transistors etc also exhibits a low frequency noise, which is frequency dependent (i.e. non uniform) known as flicker noise or ‘one – over – f’ noise. 4. Low Frequency or Flicker Noise 5. Excess Resistor Noise Thermal noise in resistors does not vary with frequency, as previously noted, by many resistors also generates as additional frequency dependent noise referred to as excess noise. 6. Burst Noise or Popcorn Noise Some semiconductors also produce burst or popcorn noise with a spectral density which is proportional to

19. 7. General Comments For frequencies below a few KHz (low frequency systems), flicker and popcorn noise are the most significant, but these may be ignored at higher frequencies where ‘white’ noise predominates.

20. The signal to noise ratio is given by 11. Signal to Noise The signal to noise in dB is expressed by for S and N measured in mW. 12. Noise Factor- Noise Figure Consider the network shown below,

21. 12. Noise Factor- Noise Figure (Cont’d) • The amount of noise added by the network is embodied in the Noise Factor F, which is defined by • Noise factor F = • F equals to 1 for noiseless network and in general F > 1. The noise figure in the noise factor quoted in dB • i.e. Noise Figure F dB = 10 log10 F F ≥ 0 dB • The noise figure / factor is the measure of how much a network degrades the (S/N)IN, the lower the value of F, the better the network.

22. 14. Noise Temperature

23. 19. System Noise Temperature

24. Additive 21. Additive White Gaussian Noise Noise is usually additive in that it adds to the information bearing signal. A model of the received signal with additive noise is shown below White White noise = = Constant Gaussian We generally assume that noise voltage amplitudes have a Gaussian or Normal distribution.

25. Introduction • Angle modulation systems and FM can provide a high degree of noise immunity • This noise immunity is obtained at the price of sacrificing channel bandwidth • Bandwidth requirements of angle modulation systems are considerably higher than that of amplitude modulation systems • This chapter deals with the followings: • Effect of noise on amplitude modulation systems • Effect of noise on angle modulation systems • Carrier-phase estimation using a phase-locked loop (PLL) • Analyze the effects of transmission loss and noise on analog communication systems

26. EFFECT OF NOISE ON AMPLITUDE-MODULATION SYSTEMS • Effect of Noise on a Baseband System • Effect of Noise on DSB-SC AM • Effect of Noise on SSB-AM • Effect of Noise on Conventional AM

27. Effect of Noise on a Baseband System • Since baseband systems serve as a basis for comparison of various modulation systems, we begin with a noise analysis of a baseband system. • In this case, there is no carrier demodulation to be performed. • The receiver consists only of an ideal lowpass filter with the bandwidth W. • The noise power at the output of the receiver, for a white noise input, is • If we denote the received power by PR, the baseband SNR is given by (6.1.2)

28. White process (Section 5.3.2) • White process is processes in which all frequency components appear with equal power, i.e., the power spectral density (PSD), Sx(f), is a constant for all frequencies. • the PSD of thermal noise, Sn(f), is usually given as (where k is Boltzrnann's constant and T is the temperature) • The value kTis usually denoted by N0, Then

29. Effect of Noise on DSB-SC AM • Transmitted signal : • The received signal at the output of the receiver noise-limiting filter : Sum of this signal and filtered noise • Recall from Section 5.3.3 and 2.7 that a filtered noise process can be expressed in terms of its in-phase and quadrature components as (where nc(t) is in-phase component and ns(t) is quadrature component)

30. Effect of Noise on DSB-SC AM • Received signal (Adding the filtered noise to the modulated signal) • Demodulate the received signal by first multiplying r(t) by a locally generated sinusoid cos(2fct + ), where  is the phase of the sinusoid. • Then passing the product signal through an ideal lowpass filter having a bandwidth W.

31. Effect of Noise on DSB-SC AM • The multiplication of r(t) with cos(2fct + ) yields • The lowpass filter rejects the double frequency components and passes only the lowpass components.

32. Effect of Noise on DSB-SC AM • In Chapter 3, the effect of a phase difference between the received carrier and a locally generated carrier at the receiver is a drop equal to cos2() in the received signal power. • Phase-locked loop (Section 6.4) • The effect of a phase-locked loop is to generate phase of the received carrier at the receiver. • If a phase-locked loop is employed, then  = 0and the demodulator is called a coherent or synchronous demodulator. • In our analysis in this section, we assume that we are employing a coherent demodulator. • With this assumption, we assume that  = 0

33. Effect of Noise on DSB-SC AM • Therefore, at the receiver output, the message signal and the noise components are additive and we are able to define a meaningful SNR. The message signal power is given by • power PMis the content of the message signal • The noise power is given by • The power content of n(t) can be found by noting that it is the result of passing nw(t) through a filter with bandwidth Bc.

34. Effect of Noise on DSB-SC AM • Therefore, the power spectral density of n(t) is given by • The noise power is • Now we can find the output SNR as • In this case, the received signal power, given by Eq. (3.2.2), is PR= Ac2PM /2.

35. Effect of Noise on DSB-SC AM • The output SNR for DSB-SC AM may be expressed as • which is identical to baseband SNR which is given by Equation (6.1.2). • In DSB-SC AM, the output SNR is the same as the SNR for a baseband system  DSB-SC AM does not provide any SNR improvement over a simple baseband communication system

36. Effect of Noise on SSB AM • SSB modulated signal : • Input to the demodulator • Assumption : Demodulation with an ideal phase reference. • Hence, the output of the lowpass filter is the in-phase component (with a coefficient of ½) of the preceding signal.

37. Effect of Noise on SSB AM • Parallel to our discussion of DSB, we have • The signal-to-noise ratio in an SSB system is equivalent to that of a DSB system.

38. Effect of Noise on Conventional AM • DSB AM signal : • Received signal at the input to the demodulator • a is the modulation index • mn(t) is normalized so that its minimum value is -1 • If a synchronous demodulator is employed, the situation is basically similar to the DSB case, except that we have 1 + amn(t) instead of m(t). • After mixing and lowpass filtering

39. Effect of Noise on Conventional AM • Received signal power • Assumed that the message process is zero mean. • Now we can derive the output SNR as • denotes the modulation efficiency • Since , the SNR in conventional AM is always smaller than the SNR in a baseband system.

40. Effect of Noise on Conventional AM • In practical applications, the modulation index a is in the range of 0.8-0.9. • Power content of the normalized message process depends on the message source. • Speech signals : Large dynamic range, PMis about 0.1. • The overall loss in SNR, when compared to a baseband system, is a factor of 0.075 or equivalent to a loss of 11 dB. • The reason for this loss is that a large part of the transmitter power is used to send the carrier component of the modulated signal and not the desired signal. • To analyze the envelope-detector performance in the presence of noise, we must use certain approximations. • This is a result of the nonlinear structure of an envelope detector, which makes an exact analysis difficult.

41. Effect of Noise on Conventional AM • In this case, the demodulator detects the envelope of the received signal and the noise process. • The input to the envelope detector is • Therefore, the envelope of r ( t ) is given by • Now we assume that the signal component in r ( t ) is much stronger than the noise component. Then • Therefore, we have a high probability that

42. Effect of Noise on Conventional AM • After removing the DC component, we obtain • which is basically the same as y(t) for the synchronous demodulation without the ½ coefficient. • This coefficient, of course, has no effect on the final SNR. • So we conclude that, under the assumption of high SNR at the receiver input, the performance of synchronous and envelope demodulators is the same. • However, if the preceding assumption is not true, that is, if we assume that, at the receiver input, the noise power is much stronger than the signal power,Then

43. Effect of Noise on Conventional AM • (a) : is small compared with the other components • (b) : ;the envelope of the noise process • Use the approximation , where

44. Effect of Noise on Conventional AM • Then • We observe that, at the demodulator output, the signal and the noise components are no longer additive. • In fact, the signal component is multiplied by noise and is no longer distinguishable. • In this case, no meaningful SNR can be defined. • We say that this system is operating below the threshold. • The subject of threshold and its effect on the performance of a communication system will be covered in more detail when we discuss the noise performance in angle modulation.