JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY KAKINADA KAKINADA – 533 001 , ANDHRA PRADESH

GATE Coaching Classes as per the Direction of Ministry of Education GOVERNMENT OF ANDHRA PRADESH

Analog Communication 26-05-2020 to 06-07-2020

Prof. Ch. Srinivasa Rao Dept. of ECE, JNTUK-UCE Vizianagaram Analog Communication-Day 7, 01-06-2020

Presentation Outline Noise: • Noise and its types • Thermal Noise • Parameters of Noise • Noise in Baseband Communication systems • Gaussian process and NB Noise • Problems

02-06-2020 Prof.Ch.Srinivasa Rao, JNTUK UCEV 2 Learning Outcomes

• At the end of this Session, Student will be able to: • LO 1 : Fundamental aspects of Noise • LO 2 : Different Noise types and its Paraneters • LO 3 : Gaussian Process and ND Noise

02-06-2020 Prof.Ch.Srinivasa Rao, JNTUK UCEV 3 Noise

Definitions of Noise:

• Noise is unwanted signal that affects wanted signal. • Noise can broadly be defined as any unknown signal that affects the recovery of the desired signal. • Noise is an unwanted signal, which interferes with the original message signal and corrupts the parameters of the message signal. This alteration in the communication process, leads to the message getting altered. It most likely enters at the channel or the receiver. Effect of noise

• Degrades system performance (Analog and digital) • Receiver cannot distinguish signal from noise • Efficiency of communication system reduces

Most common examples of noise are:

• Hiss sound in radio receivers • Buzz sound amidst of telephone conversations • Flicker in television receivers, Noise Sources

External Internal Noise Noise

Atmospheric Industrial Extraterrestrial

Solar Noise Cosmic Noise External Noise : • It is due to Man- made and natural resources • Sources over which we have no control such as thunders, snow fall, lightning etc. • Examples are Motors, generators, atmospheric sources.

Internal Noise: • It is due to random movement of electrons in electronic circuits • Major sources are resistors, diodes, transistors etc. • Thermal noise or Johnson noise and shot noise are examples. Atmospheric Noise Or Static Noise: • Caused by lighting discharges in thunderstorms • The electrical impulses are random in nature and spread over most of the RF spectrum used in broadcasting • Atmospheric Noise consists of false radio signals and distributed over wide range of frequencies • Atmospheric noise is less severe about above 30 MHz

Industrial Noise: The noise is effective in industrial and densely populated area • Automobile and aircraft ignition • Leakage from high voltage line • Heavy electric machine • Fluorescent light etc. • The noises are observable at frequencies in range of 1MHz to 600 MHz Extraterrestrial Noise or Space Noise: Caused by radiation of RF noise by sun and distant stars

• Solar Noise: Sun is large body at a very high temperature over 6000 0C on the surface and radiates over a very broad frequency spectrum which includes the frequencies we use for communication. • Cosmic Noise: Distant stars are also suns and have high temperatures, the radiate RF noise in the same manner as our sun. • The noise received is called thermal (or black body) noise and is distributed uniformly over the entire sky. • This noise is observable at frequencies in the range of 8MHz to 1.43 GHz. Types of noise

Thermal agitation noise (White Noise, Johnson noise, Electrical noise, Thermal Noise Johnson–Nyquist noise) is unavoidable, and generated by Resistors.

Shot Noise Poisson Noise is due to the random movement of electrons and holes

Noise Noise temperature is an equivalent temperature that produces that amount temperature of noise power 푇푒=푇(퐹−1)

Flicker Noise Pink noise/low frequency noise is inversely proportional to frequency, the noise effect will reduce for higher frequencies

It exists if the time taken by the electrons to travel from emitter to collector Transit-time noise in a transistor is more, it increases with frequency and quickly dominates other sources of noise

Concept to be remembered:

X(t) h(t) Y(t)

If Input signal x(t) is passed through some system h(t),then output spectral density may expressed 2 푠표 푓 = 푠푖 푓 |퐻 푓 | Where 푠표 푓 =output power spectral density 푠푖 푓 =input power spectral density H(f)=Fourier transform of the system A White noise is having one sided PSD is passed through a low pass filter whose transfer function is specified as H(f)=2푒−푗푓 The resulting is passed through low pass filter whose cut off frequency is B Hz.Find output noise power

Solution: If Input signal x(t) is passed through some system h(t),then output spectral density may expressed 2 푠표 푓 = 푠푖 푓 |퐻 푓 | Where 푠표 푓 =output power spectral density 푠푖 푓 =input power spectral density H(f)=Fourier transform of the system

|퐻 푓 |2= |2푒−푗푓|2=4| 푒−푗2푓| since | 푒−푗2푓|=1 Given that White noise is having one sided PSD (푠푖 푓 )=푁0 Therefore 2 푠표 푓 = 푠푖 푓 |퐻 푓 | = 푁04 =4 푁0 1.A white noise of having 2 sided power spectral density 4 KW/Hz is passed through a low pass filter Whose cutoff frequency is 2 KHz. Find output noise power Method 2: Solution:

Method 1: 푁 Given 0 = 4 KW/Hz 2 푡ℎ푎푡 𝑖푚푝푙𝑖푒푠 푁0=8 KW/Hz Bandwidth=2 Khz power = 푁0B= 8 KW/Hz x 2 Khz=16Kw

So Output noise power 푁0 = 퐴푟푒푎 표푓 푆0 푓 = 4KHz x 4 KW/Hz =16푊 푁 A white noise of having 2 sided PSD of 0 푤푎푡푡푠/ℎ푧 is passed through a Low 2 pass filter whose cut frequency (푓푐) is W Hz. Find output white noise power ? Solution:

So Output noise power 푁0 = 퐴푟푒푎 표푓 푆0 푓 푁 = 2W x 0 = 푊 푁 2 0

Signal to Noise Ratio (SNR or S/N) SNR is the ratio of the signal power to noise power. The higher the value of SNR the greater will be the quality of the received output.

Signal P표푤푒푟 Ps Vs SNR = = = 20 log10( ) Noise Power Pn Vn

Average Power of modulating Signal Input SNR = (SNR) 퐼 = Average Power of Noise Signal at input

Average Power of demodulated Signal Output SNR = (SNR) = 푂 Average Power of Noise Signal at output

Average Power of modulated Signal Channel SNR = (SNR) = 푐 Average Power of Noise in message bandwidth Figure of Merit

• For the purpose of comparing different continuous wave modulation systems, we normalize the receiver performance by dividing the output signal to noise ration by the channel signal to noise ratio.

• The higher the value of the figure of merit, the better will the noise performance of the receiver be.

• The figure of merit may equal one, be less than one, or be greater than one, depending on the type of modulation used.

(SNR) Figure of Merit = o (SNR)I Noise Temperature

It calculates an equivalent temperature (Te) that would yield the same noise power at the output via additional thermal noise.

It is important to realize that the noise temperature of a component describes the additional noise that the component inserts onto a signal before it is amplified, as shown in the figure below.

Noise temperature is an equivalent temperature that produces that amount of noise power

푇푒=푇(퐹−1) Noise Factor

• Noise temperature is an equivalent temperature that produces that amount of noise power 푇푒=푇(퐹−1)

for calculating total noise factor of several cascaded amplifiers

퐹1,퐹2,−− & 퐺1,퐺2, 푒푡푐 푎푟푒 Noise figure and gains of different stages in cascade. Note that noise figure is mainly dominated by first two stages. GATE 2007, 1 Mark

The transfer function of RC low pass filter with a 3-dB bandwidth of 8 kHz is given by 1 H(w)= 푤 1+푗 푤0 Where 푤0=2휋(8000) 푁 Given 0 = 10−9 2 The output noise power is 2 푠표 푓 = 푠푖 푓 |퐻 푓 | Solution:

Rayleigh Distribution: Uniform Distribution:

References

❑Communication Systems by Simon Haykin, Wiley, 2nd Edition. ❑Principle of Communication System by Taub ,Schilling & Saha, TMH. ❑Modern digital and Analog Communications system by BP Lathi, Ding and Gupta, Oxford. ❑Electronic Communication Systems by Kennedy and Davis, TMH. ❑Communication Systems Analog and Digital by Singh and Sapre, TMH

Prof.Ch.Srinivasa Rao, JNTUK UCEV 61 02-06-2020 Prof.Ch.Srinivasa Rao, JNTUK UCEV 62