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Electrical Communications Systems ECE.09.433
Noise I Dr. Shreek Mandayam Electrical & Computer Engineering Rowan University
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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
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ECOMMS: Topics
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Performance of Communications Systems Corrupted by Noise
Digital Bit Error Rate (BER) Analog Output SNR
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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? 2. Demodulation 1. Modulation 3. Demodulation f |W(f)| Bandpass
fc -fc 1. Modulation 2. Demodulation f |W(f)| Baseband f |W(f)| Bandpass fIF -fIF 3. Demodulation
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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 Rx(t) t (time delay) Slowly fluctuating signal rapidly Matlab Demo: autocorr.m Wiener-Khintchine Theorem Rw(t) Pw(f) F
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Thermal (Johnson) Noise
0.5 1 1.5 2 2.5 3 x 10 12 -21 PSD of thermal noise frequency, Hz PSD, W/Hz Matlab script: psd_noise.m
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Summary
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