Electrical Communications Systems 0909.331.01 Spring 2005

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Electrical Communications Systems0909.331.01
Spring 2005
Lecture 12bApril 27, 2005

• Shreekanth Mandayam
• ECE Department
• Rowan University
• http//engineering.rowan.edu/shreek/spring05/ecom
  ms/

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Plan

• Performance of Comm. Systems corrupted by Noise
• Performance Measures Digital and Analog
• Thermal (Johnson) Noise
• Amplitude Recall Random Variables lab1.ppt
• Power Spectral Density
• Autocorrelation function
• Wiener-Khintchine Theorem
• Bit Error Rates (BERs) for Digital Comm. Sys.
• General Procedure
• M-ary PSK and M-ary QAM
• Output SNR for Analog Comm. Sys.
• AM, DSB-SC, SSB and FM

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ECOMMS Topics
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Performance of Communications Systems Corrupted
by Noise
Analog Output SNR
Digital Bit Error Rate (BER)
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Noise

• A random, unwanted fluctuation in signal
  amplitude
• Thermal (Johnson) Noise
• Amplitude vs. time Gaussian PDF Model
• See Lab1 Pre-lab Lecture lab1.ppt
• We also want to know how much noise power there
  is per Hz why?

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Why?
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Power Spectral Density (PSD)

• Normalized power of a waveform in the frequency
  domain
• Used for measuring signal/noise power
  loss/transfer in communications system blocks

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Autocorrelation Function

• Measure of
• similarity of a waveform observed at times t
  seconds apart
• how rapidly a random waveform fluctuates with time

Matlab Demo autocorr.m
Wiener-Khintchine Theorem
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Thermal (Johnson) Noise
Matlab script psd_noise.m
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Digital Communications System
Noisy Receiver Model

Sample Hold
Threshold
Modulated Signal s(t)
Processing
S

Noise w(t)
Digital Output
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Symbol Error in M-ary PSK Systems
Matlab script dignoise.m
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Symbol Error in M-ary QAM Systems
Matlab script dignoise.m
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Analog Communications Systems
Baseband Model
Baseband Output (Signal Noise)

Message Signal m(t)
LPF
S

Noise n(t)
Noisy Receiver Model
Output (Signal Noise)

Modulated Signal s(t)
Demodulator
BPF
S

Noise n(t)
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Output SNR in Analog Comm. Systems
Matlab script analognoise.m
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Summary