Scribd
Upload
131 views16 pages

Analog Communicationlecture 16

The document discusses bandpass random processes and additive white Gaussian noise. It defines noise as unwanted interference that obscures information signals. Thermal noise is modeled as additive Gaussian noise. Additive white Gaussian noise has a constant power spectral density across all frequencies of interest, resulting in its autocorrelation being an impulse function and its average power being infinite. Bandpass random processes are examined by considering the system response to an impulse input.

Uploaded by

ali_rehman87
Copyright
© Attribution Non-Commercial (BY-NC)
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
131 views16 pages

Analog Communicationlecture 16

The document discusses bandpass random processes and additive white Gaussian noise. It defines noise as unwanted interference that obscures information signals. Thermal noise is modeled as additive Gaussian noise. Additive white Gaussian noise has a constant power spectral density across all frequencies of interest, resulting in its autocorrelation being an impulse function and its average power being infinite. Bandpass random processes are examined by considering the system response to an impulse input.

Uploaded by

ali_rehman87
Copyright
© Attribution Non-Commercial (BY-NC)
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
You are on page 1/ 16

Bandpass Random Process

Lecture 16
EEE 352 Analog Communication Systems
Mansoor Khan
Electrical Engineering Dept.
CIIT Islamabad Campus
Noise

• Noise refers to unwanted interference that tends to


obscure the information bearing signal

• Noise can be classified into two categories:

– Man-made Noise introduced by switching transients and simultaneous


presence of neighboring signals

– Natural Noise produced by the atmosphere and heating up of electrical


components. The latter is referred to as the Thermal noise
Additive Gaussian Noise
• Thermal noise is difficult to be eliminated and often modeled by the
Gaussian probability density function

• Additive Gaussian Noise: refers to the following model for


introduction of noise in the signal

• Given that the noise n is a Gaussian RV and a is the dc component,


which is constant, the pdf of z is given by
Additive Gaussian Noise
Distribution
• The normalized or standardized Gaussian density
function of a zero-mean process is obtained by
assuming unit variance.
Additive White Gaussian Noise
• The primary spectral characteristic of thermal noise is that its power
spectral density is the same for all frequencies of interest in most
communication systems

• Power spectral density Sn(w )

S n w 
N
2
• Autocorrelation function of white noise is

Rn    F S n w    
1 N
2
• The average power Pn of white noise is infinite

N
Pn   df  

2
Bandpass Random Processes
Bandpass Random Processes (cont)

• Consider the system response to an input  t   


Bandpass Random Processes (cont)

• dsada
Bandpass Random Processes (cont)
Bandpass Random Processes (cont)
Example
Example (cont)
Problem 11.1-7

You might also like